Development of a nomogram for predicting in-hospital mortality of patients with exacerbation of chronic obstructive pulmonary disease.

PubMed

Sakamoto, Yukiyo; Yamauchi, Yasuhiro; Yasunaga, Hideo; Takeshima, Hideyuki; Hasegawa, Wakae; Jo, Taisuke; Sasabuchi, Yusuke; Matsui, Hiroki; Fushimi, Kiyohide; Nagase, Takahide

2017-01-01

Patients with chronic obstructive pulmonary disease (COPD) often experience exacerbations of their disease, sometimes requiring hospital admission and being associated with increased mortality. Although previous studies have reported mortality from exacerbations of COPD, there is limited information about prediction of individual in-hospital mortality. We therefore aimed to use data from a nationwide inpatient database in Japan to generate a nomogram for predicting in-hospital mortality from patients' characteristics on admission. We retrospectively collected data on patients with COPD who had been admitted for exacerbations and been discharged between July 1, 2010 and March 31, 2013. We performed multivariable logistic regression analysis to examine factors associated with in-hospital mortality and thereafter used these factors to develop a nomogram for predicting in-hospital prognosis. The study comprised 3,064 eligible patients. In-hospital death occurred in 209 patients (6.8%). Higher mortality was associated with older age, being male, lower body mass index, disturbance of consciousness, severe dyspnea, history of mechanical ventilation, pneumonia, and having no asthma on admission. We developed a nomogram based on these variables to predict in-hospital mortality. The concordance index of the nomogram was 0.775. Internal validation was performed by a bootstrap method with 50 resamples, and calibration plots were found to be well fitted to predict in-hospital mortality. We developed a nomogram for predicting in-hospital mortality of exacerbations of COPD. This nomogram could help clinicians to predict risk of in-hospital mortality in individual patients with COPD exacerbation.

Cerebrospinal Fluid Cortisol Mediates Brain-Derived Neurotrophic Factor Relationships to Mortality after Severe TBI: A Prospective Cohort Study

PubMed Central

Munoz, Miranda J.; Kumar, Raj G.; Oh, Byung-Mo; Conley, Yvette P.; Wang, Zhensheng; Failla, Michelle D.; Wagner, Amy K.

2017-01-01

Distinct regulatory signaling mechanisms exist between cortisol and brain derived neurotrophic factor (BDNF) that may influence secondary injury cascades associated with traumatic brain injury (TBI) and predict outcome. We investigated concurrent CSF BDNF and cortisol relationships in 117 patients sampled days 0–6 after severe TBI while accounting for BDNF genetics and age. We also determined associations between CSF BDNF and cortisol with 6-month mortality. BDNF variants, rs6265 and rs7124442, were used to create a gene risk score (GRS) in reference to previously published hypothesized risk for mortality in “younger patients” (<48 years) and hypothesized BDNF production/secretion capacity with these variants. Group based trajectory analysis (TRAJ) was used to create two cortisol groups (high and low trajectories). A Bayesian estimation approach informed the mediation models. Results show CSF BDNF predicted patient cortisol TRAJ group (P = 0.001). Also, GRS moderated BDNF associations with cortisol TRAJ group. Additionally, cortisol TRAJ predicted 6-month mortality (P = 0.001). In a mediation analysis, BDNF predicted mortality, with cortisol acting as the mediator (P = 0.011), yielding a mediation percentage of 29.92%. Mediation effects increased to 45.45% among younger patients. A BDNF*GRS interaction predicted mortality in younger patients (P = 0.004). Thus, we conclude 6-month mortality after severe TBI can be predicted through a mediation model with CSF cortisol and BDNF, suggesting a regulatory role for cortisol with BDNF's contribution to TBI pathophysiology and mortality, particularly among younger individuals with severe TBI. Based on the literature, cortisol modulated BDNF effects on mortality after TBI may be related to known hormone and neurotrophin relationships to neurological injury severity and autonomic nervous system imbalance. PMID:28337122

Regression trees for predicting mortality in patients with cardiovascular disease: What improvement is achieved by using ensemble-based methods?

PubMed Central

Austin, Peter C; Lee, Douglas S; Steyerberg, Ewout W; Tu, Jack V

2012-01-01

In biomedical research, the logistic regression model is the most commonly used method for predicting the probability of a binary outcome. While many clinical researchers have expressed an enthusiasm for regression trees, this method may have limited accuracy for predicting health outcomes. We aimed to evaluate the improvement that is achieved by using ensemble-based methods, including bootstrap aggregation (bagging) of regression trees, random forests, and boosted regression trees. We analyzed 30-day mortality in two large cohorts of patients hospitalized with either acute myocardial infarction (N = 16,230) or congestive heart failure (N = 15,848) in two distinct eras (1999–2001 and 2004–2005). We found that both the in-sample and out-of-sample prediction of ensemble methods offered substantial improvement in predicting cardiovascular mortality compared to conventional regression trees. However, conventional logistic regression models that incorporated restricted cubic smoothing splines had even better performance. We conclude that ensemble methods from the data mining and machine learning literature increase the predictive performance of regression trees, but may not lead to clear advantages over conventional logistic regression models for predicting short-term mortality in population-based samples of subjects with cardiovascular disease. PMID:22777999

Assessing predicted age-specific breast cancer mortality rates in 27 European countries by 2020.

PubMed

Clèries, R; Rooney, R M; Vilardell, M; Espinàs, J A; Dyba, T; Borras, J M

2018-03-01

We assessed differences in predicted breast cancer (BC) mortality rates, across Europe, by 2020, taking into account changes in the time trends of BC mortality rates during the period 2000-2010. BC mortality data, for 27 European Union (EU) countries, were extracted from the World Health Organization mortality database. First, we compared BC mortality data between time periods 2000-2004 and 2006-2010 through standardized mortality ratios (SMRs) and carrying out a graphical assessment of the age-specific rates. Second, making use of the base period 2006-2012, we predicted BC mortality rates by 2020. Finally, making use of the SMRs and the predicted data, we identified a clustering of countries, assessing differences in the time trends between the areas defined in this clustering. The clustering approach identified two clusters of countries: the first cluster were countries where BC predicted mortality rates, in 2020, might slightly increase among women aged 69 and older compared with 2010 [Greece (SMR 1.01), Croatia (SMR 1.02), Latvia (SMR 1.15), Poland (SMR 1.14), Estonia (SMR 1.16), Bulgaria (SMR 1.13), Lithuania (SMR 1.03), Romania (SMR 1.13) and Slovakia (SMR 1.06)]. The second cluster was those countries where BC mortality rates level off or decrease in all age groups (remaining countries). However, BC mortality rates between these clusters might diminish and converge to similar figures by 2020. For the year 2020, our predictions have shown a converging pattern of BC mortality rates between European regions. Reducing disparities, in access to screening and treatment, could have a substantial effect in countries where a non-decreasing trend in age-specific BC mortality rates has been predicted.

Predicting outcome of status epilepticus.

PubMed

Leitinger, M; Kalss, G; Rohracher, A; Pilz, G; Novak, H; Höfler, J; Deak, I; Kuchukhidze, G; Dobesberger, J; Wakonig, A; Trinka, E

2015-08-01

Status epilepticus (SE) is a frequent neurological emergency complicated by high mortality and often poor functional outcome in survivors. The aim of this study was to review available clinical scores to predict outcome. Literature review. PubMed Search terms were "score", "outcome", and "status epilepticus" (April 9th 2015). Publications with abstracts available in English, no other language restrictions, or any restrictions concerning investigated patients were included. Two scores were identified: "Status Epilepticus Severity Score--STESS" and "Epidemiology based Mortality score in SE--EMSE". A comprehensive comparison of test parameters concerning performance, options, and limitations was performed. Epidemiology based Mortality score in SE allows detailed individualization of risk factors and is significantly superior to STESS in a retrospective explorative study. In particular, EMSE is very good at detection of good and bad outcome, whereas STESS detecting bad outcome is limited by a ceiling effect and uncertainty of correct cutoff value. Epidemiology based Mortality score in SE can be adapted to different regions in the world and to advances in medicine, as new data emerge. In addition, we designed a reporting standard for status epilepticus to enhance acquisition and communication of outcome relevant data. A data acquisition sheet used from patient admission in emergency room, from the EEG lab to intensive care unit, is provided for optimized data collection. Status Epilepticus Severity Score is easy to perform and predicts bad outcome, but has a low predictive value for good outcomes. Epidemiology based Mortality score in SE is superior to STESS in predicting good or bad outcome but needs marginally more time to perform. Epidemiology based Mortality score in SE may prove very useful for risk stratification in interventional studies and is recommended for individual outcome prediction. Prospective validation in different cohorts is needed for EMSE, whereas STESS needs further validation in cohorts with a wider range of etiologies. This article is part of a Special Issue entitled "Status Epilepticus". Copyright © 2015. Published by Elsevier Inc.

Hypoalbuminemia, Low Base Excess Values, and Tachypnea Predict 28-Day Mortality in Severe Sepsis and Septic Shock Patients in the Emergency Department.

PubMed

Seo, Min Ho; Choa, Minhong; You, Je Sung; Lee, Hye Sun; Hong, Jung Hwa; Park, Yoo Seok; Chung, Sung Phil; Park, Incheol

2016-11-01

The objective of this study was to develop a new nomogram that can predict 28-day mortality in severe sepsis and/or septic shock patients using a combination of several biomarkers that are inexpensive and readily available in most emergency departments, with and without scoring systems. We enrolled 561 patients who were admitted to an emergency department (ED) and received early goal-directed therapy for severe sepsis or septic shock. We collected demographic data, initial vital signs, and laboratory data sampled at the time of ED admission. Patients were randomly assigned to a training set or validation set. For the training set, we generated models using independent variables associated with 28-day mortality by multivariate analysis, and developed a new nomogram for the prediction of 28-day mortality. Thereafter, the diagnostic accuracy of the nomogram was tested using the validation set. The prediction model that included albumin, base excess, and respiratory rate demonstrated the largest area under the receiver operating characteristic curve (AUC) value of 0.8173 [95% confidence interval (CI), 0.7605-0.8741]. The logistic analysis revealed that a conventional scoring system was not associated with 28-day mortality. In the validation set, the discrimination of a newly developed nomogram was also good, with an AUC value of 0.7537 (95% CI, 0.6563-0.8512). Our new nomogram is valuable in predicting the 28-day mortality of patients with severe sepsis and/or septic shock in the emergency department. Moreover, our readily available nomogram is superior to conventional scoring systems in predicting mortality.

A way forward for fire-caused tree mortality prediction: Modeling a physiological consequence of fire

Treesearch

Kathleen L. Kavanaugh; Matthew B. Dickinson; Anthony S. Bova

2010-01-01

Current operational methods for predicting tree mortality from fire injury are regression-based models that only indirectly consider underlying causes and, thus, have limited generality. A better understanding of the physiological consequences of tree heating and injury are needed to develop biophysical process models that can make predictions under changing or novel...

An injury mortality prediction based on the anatomic injury scale

PubMed Central

Wang, Muding; Wu, Dan; Qiu, Wusi; Wang, Weimi; Zeng, Yunji; Shen, Yi

2017-01-01

Abstract To determine whether the injury mortality prediction (IMP) statistically outperforms the trauma mortality prediction model (TMPM) as a predictor of mortality. The TMPM is currently the best trauma score method, which is based on the anatomic injury. Its ability of mortality prediction is superior to the injury severity score (ISS) and to the new injury severity score (NISS). However, despite its statistical significance, the predictive power of TMPM needs to be further improved. Retrospective cohort study is based on the data of 1,148,359 injured patients in the National Trauma Data Bank hospitalized from 2010 to 2011. Sixty percent of the data was used to derive an empiric measure of severity of different Abbreviated Injury Scale predot codes by taking the weighted average death probabilities of trauma patients. Twenty percent of the data was used to create computing method of the IMP model. The remaining 20% of the data was used to evaluate the statistical performance of IMP and then be compared with the TMPM and the single worst injury by examining area under the receiver operating characteristic curve (ROC), the Hosmer–Lemeshow (HL) statistic, and the Akaike information criterion. IMP exhibits significantly both better discrimination (ROC-IMP, 0.903 [0.899–0.907] and ROC-TMPM, 0.890 [0.886–0.895]) and calibration (HL-IMP, 9.9 [4.4–14.7] and HL-TMPM, 197 [143–248]) compared with TMPM. All models show slight changes after the extension of age, gender, and mechanism of injury, but the extended IMP still dominated TMPM in every performance. The IMP has slight improvement in discrimination and calibration compared with the TMPM and can accurately predict mortality. Therefore, we consider it as a new feasible scoring method in trauma research. PMID:28858124

Commonly used severity scores are not good predictors of mortality in sepsis from severe leptospirosis: a series of ten patients.

PubMed

Velissaris, Dimitrios; Karanikolas, Menelaos; Flaris, Nikolaos; Fligou, Fotini; Marangos, Markos; Filos, Kriton S

2012-01-01

Introduction. Severe leptospirosis, also known as Weil's disease, can cause multiorgan failure with high mortality. Scoring systems for disease severity have not been validated for leptospirosis, and there is no documented method to predict mortality. Methods. This is a case series on 10 patients admitted to ICU for multiorgan failure from severe leptospirosis. Data were collected retrospectively, with approval from the Institution Ethics Committee. Results. Ten patients with severe leptospirosis were admitted in the Patras University Hospital ICU in a four-year period. Although, based on SOFA scores, predicted mortality was over 80%, seven of 10 patients survived and were discharged from the hospital in good condition. There was no association between SAPS II or SOFA scores and mortality, but survivors had significantly lower APACHE II scores compared to nonsurvivors. Conclusion. Commonly used severity scores do not seem to be useful in predicting mortality in severe leptospirosis. Early ICU admission and resuscitation based on a goal-directed therapy protocol are recommended and may reduce mortality. However, this study is limited by retrospective data collection and small sample size. Data from large prospective studies are needed to validate our findings.

Early Seizure Frequency and Aetiology Predict Long-Term Medical Outcome in Childhood-Onset Epilepsy

ERIC Educational Resources Information Center

Sillanpaa, Matti; Schmidt, Dieter

2009-01-01

In clinical practice, it is important to predict as soon as possible after diagnosis and starting treatment, which children are destined to develop medically intractable seizures and be at risk of increased mortality. In this study, we determined factors predictive of long-term seizure and mortality outcome in a population-based cohort of 102…

Classification of Airflow Limitation Based on z-Score Underestimates Mortality in Patients with Chronic Obstructive Pulmonary Disease.

PubMed

Tejero, Elena; Prats, Eva; Casitas, Raquel; Galera, Raúl; Pardo, Paloma; Gavilán, Adelaida; Martínez-Cerón, Elisabet; Cubillos-Zapata, Carolina; Del Peso, Luis; García-Río, Francisco

2017-08-01

Global Lung Function Initiative recommends reporting lung function measures as z-score, and a classification of airflow limitation (AL) based on this parameter has recently been proposed. To evaluate the prognostic capacity of the AL classifications based on z-score or percentage predicted of FEV 1 in patients with chronic obstructive pulmonary disease (COPD). A cohort of 2,614 patients with COPD recruited outside the hospital setting was examined after a mean (± SD) of 57 ± 13 months of follow-up, totaling 10,322 person-years. All-cause mortality was analyzed, evaluating the predictive capacity of several AL staging systems. Based on Global Initiative for Chronic Obstructive Lung Disease guidelines, 461 patients (17.6%) had mild, 1,452 (55.5%) moderate, 590 (22.6%) severe, and 111 (4.2%) very severe AL. According to z-score classification, 66.3% of patients remained with the same severity, whereas 23.7% worsened and 10.0% improved. Unlike other staging systems, patients with severe AL according to z-score had higher mortality than those with very severe AL (increase of risk by 5.2 and 3.9 times compared with mild AL, respectively). The predictive capacity for 5-year survival was slightly higher for FEV 1 expressed as percentage of predicted than as z-score (area under the curve: 0.714-0.760 vs. 0.649-0.708, respectively). A severity-dependent relationship between AL grades by z-score and mortality was only detected in patients younger than age 60 years. In patients with COPD, the AL classification based on z-score predicts worse mortality than those based on percentage of predicted. It is possible that the z-score underestimates AL severity in patients older than 60 years of age with severe functional impairment.

DNA methylation-based measures of biological age: meta-analysis predicting time to death.

PubMed

Chen, Brian H; Marioni, Riccardo E; Colicino, Elena; Peters, Marjolein J; Ward-Caviness, Cavin K; Tsai, Pei-Chien; Roetker, Nicholas S; Just, Allan C; Demerath, Ellen W; Guan, Weihua; Bressler, Jan; Fornage, Myriam; Studenski, Stephanie; Vandiver, Amy R; Moore, Ann Zenobia; Tanaka, Toshiko; Kiel, Douglas P; Liang, Liming; Vokonas, Pantel; Schwartz, Joel; Lunetta, Kathryn L; Murabito, Joanne M; Bandinelli, Stefania; Hernandez, Dena G; Melzer, David; Nalls, Michael; Pilling, Luke C; Price, Timothy R; Singleton, Andrew B; Gieger, Christian; Holle, Rolf; Kretschmer, Anja; Kronenberg, Florian; Kunze, Sonja; Linseisen, Jakob; Meisinger, Christine; Rathmann, Wolfgang; Waldenberger, Melanie; Visscher, Peter M; Shah, Sonia; Wray, Naomi R; McRae, Allan F; Franco, Oscar H; Hofman, Albert; Uitterlinden, André G; Absher, Devin; Assimes, Themistocles; Levine, Morgan E; Lu, Ake T; Tsao, Philip S; Hou, Lifang; Manson, JoAnn E; Carty, Cara L; LaCroix, Andrea Z; Reiner, Alexander P; Spector, Tim D; Feinberg, Andrew P; Levy, Daniel; Baccarelli, Andrea; van Meurs, Joyce; Bell, Jordana T; Peters, Annette; Deary, Ian J; Pankow, James S; Ferrucci, Luigi; Horvath, Steve

2016-09-28

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10 -9 ) , independent of chronological age, even after adjusting for additional risk factors (p<5.4x10 -4 ) , and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5x10 -43 ). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality.

The mortality risk score and the ADG score: two points-based scoring systems for the Johns Hopkins aggregated diagnosis groups to predict mortality in a general adult population cohort in Ontario, Canada.

PubMed

Austin, Peter C; Walraven, Carl van

2011-10-01

Logistic regression models that incorporated age, sex, and indicator variables for the Johns Hopkins' Aggregated Diagnosis Groups (ADGs) categories have been shown to accurately predict all-cause mortality in adults. To develop 2 different point-scoring systems using the ADGs. The Mortality Risk Score (MRS) collapses age, sex, and the ADGs to a single summary score that predicts the annual risk of all-cause death in adults. The ADG Score derives weights for the individual ADG diagnosis groups. : Retrospective cohort constructed using population-based administrative data. All 10,498,413 residents of Ontario, Canada, between the age of 20 and 100 years who were alive on their birthday in 2007, participated in this study. Participants were randomly divided into derivation and validation samples. : Death within 1 year. In the derivation cohort, the MRS ranged from -21 to 139 (median value 29, IQR 17 to 44). In the validation group, a logistic regression model with the MRS as the sole predictor significantly predicted the risk of 1-year mortality with a c-statistic of 0.917. A regression model with age, sex, and the ADG Score has similar performance. Both methods accurately predicted the risk of 1-year mortality across the 20 vigintiles of risk. The MRS combined values for a person's age, sex, and the John Hopkins ADGs to accurately predict 1-year mortality in adults. The ADG Score is a weighted score representing the presence or absence of the 32 ADG diagnosis groups. These scores will facilitate health services researchers conducting risk adjustment using administrative health care databases.

Frailty and the prediction of dependence and mortality in low- and middle-income countries: a 10/66 population-based cohort study.

PubMed

At, Jotheeswaran; Bryce, Renata; Prina, Matthew; Acosta, Daisy; Ferri, Cleusa P; Guerra, Mariella; Huang, Yueqin; Rodriguez, Juan J Llibre; Salas, Aquiles; Sosa, Ana Luisa; Williams, Joseph D; Dewey, Michael E; Acosta, Isaac; Liu, Zhaorui; Beard, John; Prince, Martin

2015-06-10

In countries with high incomes, frailty indicators predict adverse outcomes in older people, despite a lack of consensus on definition or measurement. We tested the predictive validity of physical and multidimensional frailty phenotypes in settings in Latin America, India, and China. Population-based cohort studies were conducted in catchment area sites in Cuba, Dominican Republic, Venezuela, Mexico, Peru, India, and China. Seven frailty indicators, namely gait speed, self-reported exhaustion, weight loss, low energy expenditure, undernutrition, cognitive, and sensory impairment were assessed to estimate frailty phenotypes. Mortality and onset of dependence were ascertained after a median of 3.9 years. Overall, 13,924 older people were assessed at baseline, with 47,438 person-years follow-up for mortality and 30,689 for dependence. Both frailty phenotypes predicted the onset of dependence and mortality, even adjusting for chronic diseases and disability, with little heterogeneity of effect among sites. However, population attributable fractions (PAF) summarising etiologic force were highest for the aggregate effect of the individual indicators, as opposed to either the number of indicators or the dichotomised frailty phenotypes. The aggregate of all seven indicators provided the best overall prediction (weighted mean PAF 41.8 % for dependence and 38.3 % for mortality). While weight loss, underactivity, slow walking speed, and cognitive impairment predicted both outcomes, whereas undernutrition predicted only mortality and sensory impairment only dependence. Exhaustion predicted neither outcome. Simply assessed frailty indicators identify older people at risk of dependence and mortality, beyond information provided by chronic disease diagnoses and disability. Frailty is likely to be multidimensional. A better understanding of the construct and pathways to adverse outcomes could inform multidimensional assessment and intervention to prevent or manage dependence in frail older people, with potential to add life to years, and years to life.

Predicting long-term forest development following hemlock mortality

Treesearch

Jennifer C. Jenkins; Charles D. Canham; Paul K. Barten

2000-01-01

The hemlock woolly adelgid (Adelges tsugae Annand.), an introduced pest specializing on eastern hemlock (Tsuga canadensis (L.) Carr.), threatens to cause widespread hemlock mortality in New England forests. In this study, we used a stem-based model of forest dynamics (SORTIE) to predict forest development in a northeastern forest...

Mortality risk prediction in burn injury: Comparison of logistic regression with machine learning approaches.

PubMed

Stylianou, Neophytos; Akbarov, Artur; Kontopantelis, Evangelos; Buchan, Iain; Dunn, Ken W

2015-08-01

Predicting mortality from burn injury has traditionally employed logistic regression models. Alternative machine learning methods have been introduced in some areas of clinical prediction as the necessary software and computational facilities have become accessible. Here we compare logistic regression and machine learning predictions of mortality from burn. An established logistic mortality model was compared to machine learning methods (artificial neural network, support vector machine, random forests and naïve Bayes) using a population-based (England & Wales) case-cohort registry. Predictive evaluation used: area under the receiver operating characteristic curve; sensitivity; specificity; positive predictive value and Youden's index. All methods had comparable discriminatory abilities, similar sensitivities, specificities and positive predictive values. Although some machine learning methods performed marginally better than logistic regression the differences were seldom statistically significant and clinically insubstantial. Random forests were marginally better for high positive predictive value and reasonable sensitivity. Neural networks yielded slightly better prediction overall. Logistic regression gives an optimal mix of performance and interpretability. The established logistic regression model of burn mortality performs well against more complex alternatives. Clinical prediction with a small set of strong, stable, independent predictors is unlikely to gain much from machine learning outside specialist research contexts. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Predicting mortality with biomarkers: a population-based prospective cohort study for elderly Costa Ricans

PubMed Central

2012-01-01

Background Little is known about adult health and mortality relationships outside high-income nations, partly because few datasets have contained biomarker data in representative populations. Our objective is to determine the prognostic value of biomarkers with respect to total and cardiovascular mortality in an elderly population of a middle-income country, as well as the extent to which they mediate the effects of age and sex on mortality. Methods This is a prospective population-based study in a nationally representative sample of elderly Costa Ricans. Baseline interviews occurred mostly in 2005 and mortality follow-up went through December 2010. Sample size after excluding observations with missing values: 2,313 individuals and 564 deaths. Main outcome: prospective death rate ratios for 22 baseline biomarkers, which were estimated with hazard regression models. Results Biomarkers significantly predict future death above and beyond demographic and self-reported health conditions. The studied biomarkers account for almost half of the effect of age on mortality. However, the sex gap in mortality became several times wider after controlling for biomarkers. The most powerful predictors were simple physical tests: handgrip strength, pulmonary peak flow, and walking speed. Three blood tests also predicted prospective mortality: C-reactive protein (CRP), glycated hemoglobin (HbA1c), and dehydroepiandrosterone sulfate (DHEAS). Strikingly, high blood pressure (BP) and high total cholesterol showed little or no predictive power. Anthropometric measures also failed to show significant mortality effects. Conclusions This study adds to the growing evidence that blood markers for CRP, HbA1c, and DHEAS, along with organ-specific functional reserve indicators (handgrip, walking speed, and pulmonary peak flow), are valuable tools for identifying vulnerable elderly. The results also highlight the need to better understand an anomaly noted previously in other settings: despite the continued medical focus on drugs for BP and cholesterol, high levels of BP and cholesterol have little predictive value of mortality in this elderly population. PMID:22694922

Validating the Malheur model for predicting ponderosa pine post-fire mortality using 24 fires in the Pacific Northwest, USA

Treesearch

Walter G. Thies; Douglas J. Westlind

2012-01-01

Fires, whether intentionally or accidentally set, commonly occur in western interior forests of the US. Following fire, managers need the ability to predict mortality of individual trees based on easily observed characteristics. Previously, a two-factor model using crown scorch and bole scorch proportions was developed with data from 3415 trees for predicting the...

A risk tertiles model for predicting mortality in patients with acute respiratory distress syndrome: age, plateau pressure, and P(aO(2))/F(IO(2)) at ARDS onset can predict mortality.

PubMed

Villar, Jesús; Pérez-Méndez, Lina; Basaldúa, Santiago; Blanco, Jesús; Aguilar, Gerardo; Toral, Darío; Zavala, Elizabeth; Romera, Miguel A; González-Díaz, Gumersindo; Nogal, Frutos Del; Santos-Bouza, Antonio; Ramos, Luís; Macías, Santiago; Kacmarek, Robert M

2011-04-01

Predicting mortality has become a necessary step for selecting patients for clinical trials and defining outcomes. We examined whether stratification by tertiles of respiratory and ventilatory variables at the onset of acute respiratory distress syndrome (ARDS) identifies patients with different risks of death in the intensive care unit. We performed a secondary analysis of data from 220 patients included in 2 multicenter prospective independent trials of ARDS patients mechanically ventilated with a lung-protective strategy. Using demographic, pulmonary, and ventilation data collected at ARDS onset, we derived and validated a simple prediction model based on a population-based stratification of variable values into low, middle, and high tertiles. The derivation cohort included 170 patients (all from one trial) and the validation cohort included 50 patients (all from a second trial). Tertile distribution for age, plateau airway pressure (P(plat)), and P(aO(2))/F(IO(2)) at ARDS onset identified subgroups with different mortalities, particularly for the highest-risk tertiles: age (> 62 years), P(plat) (> 29 cm H(2)O), and P(aO(2))/F(IO(2)) (< 112 mm Hg). Risk was defined by the number of coexisting high-risk tertiles: patients with no high-risk tertiles had a mortality of 12%, whereas patients with 3 high-risk tertiles had 90% mortality (P < .001). A prediction model based on tertiles of patient age, P(plat), and P(aO(2))/F(IO(2)) at the time the patient meets ARDS criteria identifies patients with the lowest and highest risk of intensive care unit death.

Determinants and development of a web-based child mortality prediction model in resource-limited settings: A data mining approach.

PubMed

Tesfaye, Brook; Atique, Suleman; Elias, Noah; Dibaba, Legesse; Shabbir, Syed-Abdul; Kebede, Mihiretu

2017-03-01

Improving child health and reducing child mortality rate are key health priorities in developing countries. This study aimed to identify determinant sand develop, a web-based child mortality prediction model in Ethiopian local language using classification data mining algorithm. Decision tree (using J48 algorithm) and rule induction (using PART algorithm) techniques were applied on 11,654 records of Ethiopian demographic and health survey data. Waikato Environment for Knowledge Analysis (WEKA) for windows version 3.6.8 was used to develop optimal models. 8157 (70%) records were randomly allocated to training group for model building while; the remaining 3496 (30%) records were allocated as the test group for model validation. The validation of the model was assessed using accuracy, sensitivity, specificity and area under Receiver Operating Characteristics (ROC) curve. Using Statistical Package for Social Sciences (SPSS) version 20.0; logistic regressions and Odds Ratio (OR) with 95% Confidence Interval (CI) was used to identify determinants of child mortality. The child mortality rate was 72 deaths per 1000 live births. Breast-feeding (AOR= 1.46, (95% CI [1.22. 1.75]), maternal education (AOR= 1.40, 95% CI [1.11, 1.81]), family planning (AOR= 1.21, [1.08, 1.43]), preceding birth interval (AOR= 4.90, [2.94, 8.15]), presence of diarrhea (AOR= 1.54, 95% CI [1.32, 1.66]), father's education (AOR= 1.4, 95% CI [1.04, 1.78]), low birth weight (AOR= 1.2, 95% CI [0.98, 1.51]) and, age of the mother at first birth (AOR= 1.42, [1.01-1.89]) were found to be determinants for child mortality. The J48 model had better performance, accuracy (94.3%), sensitivity (93.8%), specificity (94.3%), Positive Predictive Value (PPV) (92.2%), Negative Predictive Value (NPV) (94.5%) and, the area under ROC (94.8%). Subsequent to developing an optimal prediction model, we relied on this model to develop a web-based application system for child mortality prediction. In this study, nearly accurate results were obtained by employing decision tree and rule induction techniques. Determinants are identified and a web-based child mortality prediction model in Ethiopian local language is developed. Thus, the result obtained could support child health intervention programs in Ethiopia where trained human resource for health is limited. Advanced classification algorithms need to be tested to come up with optimal models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Derivation and validation of in-hospital mortality prediction models in ischaemic stroke patients using administrative data.

PubMed

Lee, Jason; Morishima, Toshitaka; Kunisawa, Susumu; Sasaki, Noriko; Otsubo, Tetsuya; Ikai, Hiroshi; Imanaka, Yuichi

2013-01-01

Stroke and other cerebrovascular diseases are a major cause of death and disability. Predicting in-hospital mortality in ischaemic stroke patients can help to identify high-risk patients and guide treatment approaches. Chart reviews provide important clinical information for mortality prediction, but are laborious and limiting in sample sizes. Administrative data allow for large-scale multi-institutional analyses but lack the necessary clinical information for outcome research. However, administrative claims data in Japan has seen the recent inclusion of patient consciousness and disability information, which may allow more accurate mortality prediction using administrative data alone. The aim of this study was to derive and validate models to predict in-hospital mortality in patients admitted for ischaemic stroke using administrative data. The sample consisted of 21,445 patients from 176 Japanese hospitals, who were randomly divided into derivation and validation subgroups. Multivariable logistic regression models were developed using 7- and 30-day and overall in-hospital mortality as dependent variables. Independent variables included patient age, sex, comorbidities upon admission, Japan Coma Scale (JCS) score, Barthel Index score, modified Rankin Scale (mRS) score, and admissions after hours and on weekends/public holidays. Models were developed in the derivation subgroup, and coefficients from these models were applied to the validation subgroup. Predictive ability was analysed using C-statistics; calibration was evaluated with Hosmer-Lemeshow χ(2) tests. All three models showed predictive abilities similar or surpassing that of chart review-based models. The C-statistics were highest in the 7-day in-hospital mortality prediction model, at 0.906 and 0.901 in the derivation and validation subgroups, respectively. For the 30-day in-hospital mortality prediction models, the C-statistics for the derivation and validation subgroups were 0.893 and 0.872, respectively; in overall in-hospital mortality prediction these values were 0.883 and 0.876. In this study, we have derived and validated in-hospital mortality prediction models for three different time spans using a large population of ischaemic stroke patients in a multi-institutional analysis. The recent inclusion of JCS, Barthel Index, and mRS scores in Japanese administrative data has allowed the prediction of in-hospital mortality with accuracy comparable to that of chart review analyses. The models developed using administrative data had consistently high predictive abilities for all models in both the derivation and validation subgroups. These results have implications in the role of administrative data in future mortality prediction analyses. Copyright © 2013 S. Karger AG, Basel.

Clinical utility of EMSE and STESS in predicting hospital mortality for status epilepticus.

PubMed

Zhang, Yu; Chen, Deng; Xu, Da; Tan, Ge; Liu, Ling

2018-05-25

To explore the applicability of the epidemiology-based mortality score in status epilepticus (EMSE) and the status epilepticus severity score (STESS) in predicting hospital mortality in patients with status epilepticus (SE) in western China. Furthermore, we sought to compare the abilities of the two scales to predict mortality from convulsive status epilepticus (CSE) and non-convulsive status epilepticus (NCSE). Patients with epilepsy (n = 253) were recruited from the West China Hospital of Sichuan University from January 2012 to January 2016. The EMSE and STESS for all patients were calculated immediately after admission. The main outcome was in-hospital death. The predicted values were analysed using SPSS 22.0 receiver operating characteristic (ROC) curves. Of the 253 patients with SE who were included in the study, 39 (15.4%) died in the hospital. Using STESS ≥4 points to predict SE mortality, the area under the ROC curve (AUC) was 0.724 (P < 0.05). Using EMSE ≥79 points, the AUC was 0.776 (P < 0.05). To predict mortality in NCSE, STESS ≥2 points was used and resulted in an AUC of 0.632 (P > 0.05), while EMSE ≥90 points gave an AUC of 0.666 (P > 0.05). The hospital mortality rate from SE in this study was 15.4%. Those with STESS ≥4 points or EMSE ≥79 points had higher rates of SE mortality. Both STESS and EMSE are less useful predicting in-hospital mortality in NCSE compared to CSE. Furthermore, the EMSE has some advantages over the STESS. Copyright © 2018 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

The New York risk score for in-hospital and 30-day mortality for coronary artery bypass graft surgery.

PubMed

Hannan, Edward L; Farrell, Louise Szypulski; Wechsler, Andrew; Jordan, Desmond; Lahey, Stephen J; Culliford, Alfred T; Gold, Jeffrey P; Higgins, Robert S D; Smith, Craig R

2013-01-01

Simplified risk scores for coronary artery bypass graft surgery are frequently in lieu of more complicated statistical models and are valuable for informed consent and choice of intervention. Previous risk scores have been based on in-hospital mortality, but a substantial number of patients die within 30 days of the procedure. These deaths should also be accounted for, so we have developed a risk score based on in-hospital and 30-day mortality. New York's Cardiac Surgery Reporting System was used to develop an in-hospital and 30-day logistic regression model for patients undergoing coronary artery bypass graft surgery in 2009, and this model was converted into a simple linear risk score that provides estimated in-hospital and 30-day mortality rates for different values of the score. The accuracy of the risk score in predicting mortality was tested. This score was also validated by applying it to 2008 New York coronary artery bypass graft data. Subsequent analyses evaluated the ability of the risk score to predict complications and length of stay. The overall in-hospital and 30-day mortality rate for the 10,148 patients in the study was 1.79%. There are seven risk factors comprising the score, with risk factor scores ranging from 1 to 5, and the highest possible total score is 23. The score accurately predicted mortality in 2009 as well as in 2008, and was strongly correlated with complications and length of stay. The risk score is a simple way of estimating short-term mortality that accurately predicts mortality in the year the model was developed as well as in the previous year. Perioperative complications and length of stay are also well predicted by the risk score. Copyright © 2013 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

DNA methylation-based measures of biological age: meta-analysis predicting time to death

PubMed Central

Chen, Brian H.; Marioni, Riccardo E.; Colicino, Elena; Peters, Marjolein J.; Ward-Caviness, Cavin K.; Tsai, Pei-Chien; Roetker, Nicholas S.; Just, Allan C.; Demerath, Ellen W.; Guan, Weihua; Bressler, Jan; Fornage, Myriam; Studenski, Stephanie; Vandiver, Amy R.; Moore, Ann Zenobia; Tanaka, Toshiko; Kiel, Douglas P.; Liang, Liming; Vokonas, Pantel; Schwartz, Joel; Lunetta, Kathryn L.; Murabito, Joanne M.; Bandinelli, Stefania; Hernandez, Dena G.; Melzer, David; Nalls, Michael; Pilling, Luke C.; Price, Timothy R.; Singleton, Andrew B.; Gieger, Christian; Holle, Rolf; Kretschmer, Anja; Kronenberg, Florian; Kunze, Sonja; Linseisen, Jakob; Meisinger, Christine; Rathmann, Wolfgang; Waldenberger, Melanie; Visscher, Peter M.; Shah, Sonia; Wray, Naomi R.; McRae, Allan F.; Franco, Oscar H.; Hofman, Albert; Uitterlinden, André G.; Absher, Devin; Assimes, Themistocles; Levine, Morgan E.; Lu, Ake T.; Tsao, Philip S.; Hou, Lifang; Manson, JoAnn E.; Carty, Cara L.; LaCroix, Andrea Z.; Reiner, Alexander P.; Spector, Tim D.; Feinberg, Andrew P.; Levy, Daniel; Baccarelli, Andrea; van Meurs, Joyce; Bell, Jordana T.; Peters, Annette; Deary, Ian J.; Pankow, James S.; Ferrucci, Luigi; Horvath, Steve

2016-01-01

Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10−9), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10−4), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10−43). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality. PMID:27690265

A comparison of base deficit and vital signs in the early assessment of patients with penetrating trauma in a high burden setting.

PubMed

Dunham, Mark Peter; Sartorius, Benn; Laing, Grant Llewellyn; Bruce, John Lambert; Clarke, Damian Luiz

2017-09-01

An assessment of physiological status is a key step in the early assessment of trauma patients with implications for triage, investigation and management. This has traditionally been done using vital signs. Previous work from large European trauma datasets has suggested that base deficit (BD) predicts clinically important outcomes better than vital signs (VS). A BD derived classification of haemorrhagic shock appeared superior to one based on VS derived from ATLS criteria in a population of predominantly blunt trauma patients. The initial aim of this study was to see if this observation would be reproduced in penetrating trauma patients. The power of each individual variable (BD, heart rate (HR), systolic blood pressure (SBP), shock index(SI) (HR/SBP) and Glasgow Coma Score (GCS)) to predict mortality was then also compared. A retrospective analysis of adult trauma patients presenting to the Pietermaritzburg Metropolitan Trauma Service was performed. Patients were classified into four "shock" groups using VS or BD and the outcomes compared. Receiver Operator Characteristic (ROC) curves were then generated to compare the predictive power for mortality of each individual variable. 1863 patients were identified. The overall mortality rate was 2.1%. When classified by BD, HR rose and SBP fell as the "shock class" increased but not to the degree suggested by the ATLS classification. The BD classification of haemorrhagic shock appeared to predict mortality better than that based on the ATLS criteria. Mortality increased from 0.2% (Class 1) to 19.7% (Class 4) based on the 4 level BD classification. Mortality increased from 0.3% (Class 1) to 12.6% (Class 4) when classified based by VS. Area under the receiver operator characteristic (AUROC) curve analysis of the individual variables demonstrated that BD predicted mortality significantly better than HR, GCS, SBP and SI. AUROC curve (95% Confidence Interval (CI)) for BD was 0.90 (0.85-0.95) compared to HR 0.67(0.56-0.77), GCS 0.70(0.62-0.79), SBP 0.75(0.65-0.85) and SI 0.77(0.68-0.86). BD appears superior to vital signs in the immediate physiological assessment of penetrating trauma patients. The use of BD to assess physiological status may help refine their early triage, investigation and management. Copyright © 2017 Elsevier Ltd. All rights reserved.

Prediction using patient comparison vs. modeling: a case study for mortality prediction.

PubMed

Hoogendoorn, Mark; El Hassouni, Ali; Mok, Kwongyen; Ghassemi, Marzyeh; Szolovits, Peter

2016-08-01

Information in Electronic Medical Records (EMRs) can be used to generate accurate predictions for the occurrence of a variety of health states, which can contribute to more pro-active interventions. The very nature of EMRs does make the application of off-the-shelf machine learning techniques difficult. In this paper, we study two approaches to making predictions that have hardly been compared in the past: (1) extracting high-level (temporal) features from EMRs and building a predictive model, and (2) defining a patient similarity metric and predicting based on the outcome observed for similar patients. We analyze and compare both approaches on the MIMIC-II ICU dataset to predict patient mortality and find that the patient similarity approach does not scale well and results in a less accurate model (AUC of 0.68) compared to the modeling approach (0.84). We also show that mortality can be predicted within a median of 72 hours.

Performance of International Classification of Diseases-based injury severity measures used to predict in-hospital mortality: A systematic review and meta-analysis.

PubMed

Gagné, Mathieu; Moore, Lynne; Beaudoin, Claudia; Batomen Kuimi, Brice Lionel; Sirois, Marie-Josée

2016-03-01

The International Classification of Diseases (ICD) is the main classification system used for population-based injury surveillance activities but does not contain information on injury severity. ICD-based injury severity measures can be empirically derived or mapped, but no single approach has been formally recommended. This study aimed to compare the performance of ICD-based injury severity measures to predict in-hospital mortality among injury-related admissions. A systematic review and a meta-analysis were conducted. MEDLINE, EMBASE, and Global Health databases were searched from their inception through September 2014. Observational studies that assessed the performance of ICD-based injury severity measures to predict in-hospital mortality and reported discriminative ability using the area under a receiver operating characteristic curve (AUC) were included. Metrics of model performance were extracted. Pooled AUC were estimated under random-effects models. Twenty-two eligible studies reported 72 assessments of discrimination on ICD-based injury severity measures. Reported AUC ranged from 0.681 to 0.958. Of the 72 assessments, 46 showed excellent (0.80 ≤ AUC < 0.90) and 6 outstanding (AUC ≥ 0.90) discriminative ability. Pooled AUC for ICD-based Injury Severity Score (ICISS) based on the product of traditional survival proportions was significantly higher than measures based on ICD mapped to Abbreviated Injury Scale (AIS) scores (0.863 vs. 0.825 for ICDMAP-ISS [p = 0.005] and ICDMAP-NISS [p = 0.016]). Similar results were observed when studies were stratified by the type of data used (trauma registry or hospital discharge) or the provenance of survival proportions (internally or externally derived). However, among studies published after 2003 the Trauma Mortality Prediction Model based on ICD-9 codes (TMPM-9) demonstrated superior discriminative ability than ICISS using the product of traditional survival proportions (0.850 vs. 0.802, p = 0.002). Models generally showed poor calibration. ICISS using the product of traditional survival proportions and TMPM-9 predict mortality more accurately than those mapped to AIS codes and should be preferred for describing injury severity when ICD is used to record injury diagnoses. Systematic review and meta-analysis, level III.

Predicting exposure-response associations of ambient particulate matter with mortality in 73 Chinese cities.

PubMed

Madaniyazi, Lina; Guo, Yuming; Chen, Renjie; Kan, Haidong; Tong, Shilu

2016-01-01

Estimating the burden of mortality associated with particulates requires knowledge of exposure-response associations. However, the evidence on exposure-response associations is limited in many cities, especially in developing countries. In this study, we predicted associations of particulates smaller than 10 μm in aerodynamic diameter (PM10) with mortality in 73 Chinese cities. The meta-regression model was used to test and quantify which city-specific characteristics contributed significantly to the heterogeneity of PM10-mortality associations for 16 Chinese cities. Then, those city-specific characteristics with statistically significant regression coefficients were treated as independent variables to build multivariate meta-regression models. The model with the best fitness was used to predict PM10-mortality associations in 73 Chinese cities in 2010. Mean temperature, PM10 concentration and green space per capita could best explain the heterogeneity in PM10-mortality associations. Based on city-specific characteristics, we were able to develop multivariate meta-regression models to predict associations between air pollutants and health outcomes reasonably well. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought?

Treesearch

Nate McDowell; William T. Pockman; Craig D. Allen; David D. Breshears; Neil Cobb; Thomas Kolb; Jennifer Plaut; John Sperry; Adam West; David G. Williams; Enrico A. Yepez

2008-01-01

Severe droughts have been associated with regional-scale forest mortality worldwide. Climate change is expected to exacerbate regional mortality events; however, prediction remains difficult because the physiological mechanisms underlying drought survival and mortality are poorly understood. We developed a hydraulically based theory considering carbon balance and...

[Value of sepsis single-disease manage system in predicting mortality in patients with sepsis].

PubMed

Chen, J; Wang, L H; Ouyang, B; Chen, M Y; Wu, J F; Liu, Y J; Liu, Z M; Guan, X D

2018-04-03

Objective: To observe the effect of sepsis single-disease manage system on the improvement of sepsis treatment and the value in predicting mortality in patients with sepsis. Methods: A retrospective study was conducted. Patients with sepsis admitted to the Department of Surgical Intensive Care Unit of Sun Yat-Sen University First Affiliated Hospital from September 22, 2013 to May 5, 2015 were enrolled in this study. Sepsis single-disease manage system (Rui Xin clinical data manage system, China data, China) was used to monitor 25 clinical quality parameters, consisting of timeliness, normalization and outcome parameters. Based on whether these quality parameters could be completed or not, the clinical practice was evaluated by the system. The unachieved quality parameter was defined as suspicious parameters, and these suspicious parameters were used to predict mortality of patients with receiver operating characteristic curve (ROC). Results: A total of 1 220 patients with sepsis were enrolled, included 805 males and 415 females. The mean age was (59±17) years, and acute physiology and chronic health evaluation (APACHE Ⅱ) scores was 19±8. The area under ROC curve of total suspicious numbers for predicting 28-day mortality was 0.70; when the suspicious parameters number was more than 6, the sensitivity was 68.0% and the specificity was 61.0% for predicting 28-day mortality. In addition, the area under ROC curve of outcome suspicious number for predicting 28-day mortality was 0.89; when the suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 78.0% for predicting 28-day mortality. Moreover, the area under ROC curve of total suspicious number for predicting 90-day mortality was 0.73; when the total suspicious parameters number was more than 7, the sensitivity was 60.0% and the specificity was 74.0% for predicting 90-day mortality. Finally, the area under ROC curve of outcome suspicious numbers for predicting 90-day mortality was 0.92; when suspicious outcome parameters numbers was more than 1, the sensitivity was 88.0% and the specificity was 81.0% for predicting 90-day mortality. Conclusion: The single center study suggests that this sepsis single-disease manage system could be used to monitor the completion of clinical practice for intensivist in managing sepsis, and the number of quality parameters failed to complete could be used to predict the mortality of the patients.

Association between Long-Term Exposure to Particulate Matter Air Pollution and Mortality in a South Korean National Cohort: Comparison across Different Exposure Assessment Approaches

PubMed Central

Kim, Sun-Young; Kim, Ho

2017-01-01

Increasing numbers of cohort studies have reported that long-term exposure to ambient particulate matter is associated with mortality. However, there has been little evidence from Asian countries. We aimed to explore the association between long-term exposure to particulate matter with a diameter ≤10 µm (PM10) and mortality in South Korea, using a nationwide population-based cohort and an improved exposure assessment (EA) incorporating time-varying concentrations and residential addresses (EA1). We also compared the association across different EA approaches. We used information from 275,337 people who underwent health screening from 2002 to 2006 and who had follow-up data for 12 years in the National Health Insurance Service-National Sample Cohort. Individual exposures were computed as 5-year averages using predicted residential district-specific annual-average PM10 concentrations for 2002–2006. We estimated hazard ratios (HRs) of non-accidental and five cause-specific mortalities per 10 µg/m3 increase in PM10 using the Cox proportional hazards model. Then, we compared the association of EA1 with three other approaches based on time-varying concentrations and/or addresses: predictions in each year and addresses at baseline (EA2); predictions at baseline and addresses in each year (EA3); and predictions and addresses at baseline (EA4). We found a marginal association between long-term PM10 and non-accidental mortality. The HRs of five cause-specific mortalities were mostly higher than that of non-accidental mortality, but statistically insignificant. In the comparison between EA approaches, the HRs of EA1 were similar to those of EA2 but higher than EA3 and EA4. Our findings confirmed the association between long-term exposure to PM10 and mortality based on a population-representative cohort in South Korea, and suggested the importance of assessing individual exposure incorporating air pollution changes over time. PMID:28946613

Infant Maltreatment-Related Mortality in Alaska: Correcting the Count and Using Birth Certificates to Predict Mortality

ERIC Educational Resources Information Center

Parrish, Jared W.; Gessner, Bradford D.

2010-01-01

Objectives: To accurately count the number of infant maltreatment-related fatalities and to use information from the birth certificates to predict infant maltreatment-related deaths. Methods: A population-based retrospective cohort study of infants born in Alaska for the years 1992 through 2005 was conducted. Risk factor variables were ascertained…

Accuracy and Calibration of Computational Approaches for Inpatient Mortality Predictive Modeling.

PubMed

Nakas, Christos T; Schütz, Narayan; Werners, Marcus; Leichtle, Alexander B

2016-01-01

Electronic Health Record (EHR) data can be a key resource for decision-making support in clinical practice in the "big data" era. The complete database from early 2012 to late 2015 involving hospital admissions to Inselspital Bern, the largest Swiss University Hospital, was used in this study, involving over 100,000 admissions. Age, sex, and initial laboratory test results were the features/variables of interest for each admission, the outcome being inpatient mortality. Computational decision support systems were utilized for the calculation of the risk of inpatient mortality. We assessed the recently proposed Acute Laboratory Risk of Mortality Score (ALaRMS) model, and further built generalized linear models, generalized estimating equations, artificial neural networks, and decision tree systems for the predictive modeling of the risk of inpatient mortality. The Area Under the ROC Curve (AUC) for ALaRMS marginally corresponded to the anticipated accuracy (AUC = 0.858). Penalized logistic regression methodology provided a better result (AUC = 0.872). Decision tree and neural network-based methodology provided even higher predictive performance (up to AUC = 0.912 and 0.906, respectively). Additionally, decision tree-based methods can efficiently handle Electronic Health Record (EHR) data that have a significant amount of missing records (in up to >50% of the studied features) eliminating the need for imputation in order to have complete data. In conclusion, we show that statistical learning methodology can provide superior predictive performance in comparison to existing methods and can also be production ready. Statistical modeling procedures provided unbiased, well-calibrated models that can be efficient decision support tools for predicting inpatient mortality and assigning preventive measures.

Should predictive scores based on vital signs be used in the same way as those based on laboratory data? A hypothesis generating retrospective evaluation of in-hospital mortality by four different scoring systems.

PubMed

Kellett, John; Murray, Alan

2016-05-01

few studies have compared the discrimination of predictive scores of in-hospital mortality that used vital signs with those using laboratory results in different patient populations. a hypothesis generating retrospective observational cohort study. A score that only used vital signs was compared with three other scores that used laboratory changes in 44,985 medical and 20,432 surgical patients. the discrimination of the score based only on vital signs was highest for the prediction of in-hospital death within 24h. In contrast the, albeit lower, discrimination of scores based only on laboratory data remained constant for the prediction of death up to 30 days after hospital admission. Moreover, the discrimination of scores based only on laboratory data was higher in surgical than in medical patients. in acutely ill medical patients a vital sign based score appears to predict mortality within 24h better than scores using laboratory data. This may be because in acutely ill patients vital sign changes indicate how well a patient is responding to a current insult. In contrast, for patients without acute illness laboratory data may be a more valuable indication of the patient's capacity to respond to insults in the future. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Tree mortality predicted from drought-induced vascular damage

USGS Publications Warehouse

Anderegg, William R.L.; Flint, Alan L.; Huang, Cho-ying; Flint, Lorraine E.; Berry, Joseph A.; Davis, Frank W.; Sperry, John S.; Field, Christopher B.

2015-01-01

The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality1, 2, 3. Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality4, 5. Here we assess the causes of tree mortality, using field measurements of branch hydraulic conductivity during ongoing mortality in Populus tremuloides in the southwestern United States and a detailed plant hydraulics model. We identify a lethal plant water stress threshold that corresponds with a loss of vascular transport capacity from air entry into the xylem. We then use this hydraulic-based threshold to simulate forest dieback during historical drought, and compare predictions against three independent mortality data sets. The hydraulic threshold predicted with 75% accuracy regional patterns of tree mortality as found in field plots and mortality maps derived from Landsat imagery. In a high-emissions scenario, climate models project that drought stress will exceed the observed mortality threshold in the southwestern United States by the 2050s. Our approach provides a powerful and tractable way of incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.

A European benchmarking system to evaluate in-hospital mortality rates in acute coronary syndrome: the EURHOBOP project.

PubMed

Dégano, Irene R; Subirana, Isaac; Torre, Marina; Grau, María; Vila, Joan; Fusco, Danilo; Kirchberger, Inge; Ferrières, Jean; Malmivaara, Antti; Azevedo, Ana; Meisinger, Christa; Bongard, Vanina; Farmakis, Dimitros; Davoli, Marina; Häkkinen, Unto; Araújo, Carla; Lekakis, John; Elosua, Roberto; Marrugat, Jaume

2015-03-01

Hospital performance models in acute myocardial infarction (AMI) are useful to assess patient management. While models are available for individual countries, mainly US, cross-European performance models are lacking. Thus, we aimed to develop a system to benchmark European hospitals in AMI and percutaneous coronary intervention (PCI), based on predicted in-hospital mortality. We used the EURopean HOspital Benchmarking by Outcomes in ACS Processes (EURHOBOP) cohort to develop the models, which included 11,631 AMI patients and 8276 acute coronary syndrome (ACS) patients who underwent PCI. Models were validated with a cohort of 55,955 European ACS patients. Multilevel logistic regression was used to predict in-hospital mortality in European hospitals for AMI and PCI. Administrative and clinical models were constructed with patient- and hospital-level covariates, as well as hospital- and country-based random effects. Internal cross-validation and external validation showed good discrimination at the patient level and good calibration at the hospital level, based on the C-index (0.736-0.819) and the concordance correlation coefficient (55.4%-80.3%). Mortality ratios (MRs) showed excellent concordance between administrative and clinical models (97.5% for AMI and 91.6% for PCI). Exclusion of transfers and hospital stays ≤1day did not affect in-hospital mortality prediction in sensitivity analyses, as shown by MR concordance (80.9%-85.4%). Models were used to develop a benchmarking system to compare in-hospital mortality rates of European hospitals with similar characteristics. The developed system, based on the EURHOBOP models, is a simple and reliable tool to compare in-hospital mortality rates between European hospitals in AMI and PCI. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Long-Term Post-CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions.

PubMed

Carr, Brendan M; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C; Zhu, Wei; Shroyer, A Laurie

2016-01-01

Clinical risk models are commonly used to predict short-term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long-term mortality. The added value of long-term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long-term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Long-term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c-index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Mortality rates were 3%, 9%, and 17% at one-, three-, and five years, respectively (median follow-up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long-term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Long-term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long-term mortality risk can be accurately assessed and subgroups of higher-risk patients can be identified for enhanced follow-up care. More research appears warranted to refine long-term CABG clinical risk models. © 2015 The Authors. Journal of Cardiac Surgery Published by Wiley Periodicals, Inc.

Long‐Term Post‐CABG Survival: Performance of Clinical Risk Models Versus Actuarial Predictions

PubMed Central

Carr, Brendan M.; Romeiser, Jamie; Ruan, Joyce; Gupta, Sandeep; Seifert, Frank C.; Zhu, Wei

2015-01-01

Abstract Background/aim Clinical risk models are commonly used to predict short‐term coronary artery bypass grafting (CABG) mortality but are less commonly used to predict long‐term mortality. The added value of long‐term mortality clinical risk models over traditional actuarial models has not been evaluated. To address this, the predictive performance of a long‐term clinical risk model was compared with that of an actuarial model to identify the clinical variable(s) most responsible for any differences observed. Methods Long‐term mortality for 1028 CABG patients was estimated using the Hannan New York State clinical risk model and an actuarial model (based on age, gender, and race/ethnicity). Vital status was assessed using the Social Security Death Index. Observed/expected (O/E) ratios were calculated, and the models' predictive performances were compared using a nested c‐index approach. Linear regression analyses identified the subgroup of risk factors driving the differences observed. Results Mortality rates were 3%, 9%, and 17% at one‐, three‐, and five years, respectively (median follow‐up: five years). The clinical risk model provided more accurate predictions. Greater divergence between model estimates occurred with increasing long‐term mortality risk, with baseline renal dysfunction identified as a particularly important driver of these differences. Conclusions Long‐term mortality clinical risk models provide enhanced predictive power compared to actuarial models. Using the Hannan risk model, a patient's long‐term mortality risk can be accurately assessed and subgroups of higher‐risk patients can be identified for enhanced follow‐up care. More research appears warranted to refine long‐term CABG clinical risk models. doi: 10.1111/jocs.12665 (J Card Surg 2016;31:23–30) PMID:26543019

The New York State risk score for predicting in-hospital/30-day mortality following percutaneous coronary intervention.

PubMed

Hannan, Edward L; Farrell, Louise Szypulski; Walford, Gary; Jacobs, Alice K; Berger, Peter B; Holmes, David R; Stamato, Nicholas J; Sharma, Samin; King, Spencer B

2013-06-01

This study sought to develop a percutaneous coronary intervention (PCI) risk score for in-hospital/30-day mortality. Risk scores are simplified linear scores that provide clinicians with quick estimates of patients' short-term mortality rates for informed consent and to determine the appropriate intervention. Earlier PCI risk scores were based on in-hospital mortality. However, for PCI, a substantial percentage of patients die within 30 days of the procedure after discharge. New York's Percutaneous Coronary Interventions Reporting System was used to develop an in-hospital/30-day logistic regression model for patients undergoing PCI in 2010, and this model was converted into a simple linear risk score that estimates mortality rates. The score was validated by applying it to 2009 New York PCI data. Subsequent analyses evaluated the ability of the score to predict complications and length of stay. A total of 54,223 patients were used to develop the risk score. There are 11 risk factors that make up the score, with risk factor scores ranging from 1 to 9, and the highest total score is 34. The score was validated based on patients undergoing PCI in the previous year, and accurately predicted mortality for all patients as well as patients who recently suffered a myocardial infarction (MI). The PCI risk score developed here enables clinicians to estimate in-hospital/30-day mortality very quickly and quite accurately. It accurately predicts mortality for patients undergoing PCI in the previous year and for MI patients, and is also moderately related to perioperative complications and length of stay. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Pediatric trauma BIG score: predicting mortality in children after military and civilian trauma.

PubMed

Borgman, Matthew A; Maegele, Marc; Wade, Charles E; Blackbourne, Lorne H; Spinella, Philip C

2011-04-01

To develop a validated mortality prediction score for children with traumatic injuries. We identified all children (<18 years of age) in the US military established Joint Theater Trauma Registry from 2002 to 2009 who were admitted to combat-support hospitals with traumatic injuries in Iraq and Afghanistan. We identified factors associated with mortality using univariate and then multivariate regression modeling. The developed mortality prediction score was then validated on a data set of pediatric patients (≤ 18 years of age) from the German Trauma Registry, 2002-2007. Admission base deficit, international normalized ratio, and Glasgow Coma Scale were independently associated with mortality in 707 patients from the derivation set and 1101 patients in the validation set. These variables were combined into the pediatric "BIG" score (base deficit + [2.5 × international normalized ratio] + [15 - Glasgow Coma Scale), which were each calculated to have an area under the curve of 0.89 (95% confidence interval: 0.83-0.95) and 0.89 (95% confidence interval: 0.87-0.92) on the derivation and validation sets, respectively. The pediatric trauma BIG score is a simple method that can be performed rapidly on admission to evaluate severity of illness and predict mortality in children with traumatic injuries. The score has been shown to be accurate in both penetrating-injury and blunt-injury populations and may have significant utility in comparing severity of injury in future pediatric trauma research and quality-assurance studies. In addition, this score may be used to determine inclusion criteria on admission for prospective studies when accurately estimating the mortality for sample size calculation is required.

Melanoma-specific mortality and competing mortality in patients with non-metastatic malignant melanoma: a population-based analysis.

PubMed

Shen, Weidong; Sakamoto, Naoko; Yang, Limin

2016-07-07

The objectives of this study were to evaluate and model the probability of melanoma-specific death and competing causes of death for patients with melanoma by competing risk analysis, and to build competing risk nomograms to provide individualized and accurate predictive tools. Melanoma data were obtained from the Surveillance Epidemiology and End Results program. All patients diagnosed with primary non-metastatic melanoma during the years 2004-2007 were potentially eligible for inclusion. The cumulative incidence function (CIF) was used to describe the probability of melanoma mortality and competing risk mortality. We used Gray's test to compare differences in CIF between groups. The proportional subdistribution hazard approach by Fine and Gray was used to model CIF. We built competing risk nomograms based on the models that we developed. The 5-year cumulative incidence of melanoma death was 7.1 %, and the cumulative incidence of other causes of death was 7.4 %. We identified that variables associated with an elevated probability of melanoma-specific mortality included older age, male sex, thick melanoma, ulcerated cancer, and positive lymph nodes. The nomograms were well calibrated. C-indexes were 0.85 and 0.83 for nomograms predicting the probability of melanoma mortality and competing risk mortality, which suggests good discriminative ability. This large study cohort enabled us to build a reliable competing risk model and nomogram for predicting melanoma prognosis. Model performance proved to be good. This individualized predictive tool can be used in clinical practice to help treatment-related decision making.

Surrogate endpoints for cancer screening trials: general principles and an illustration using the UK Flexible Sigmoidoscopy Screening Trial.

PubMed

Cuzick, Jack; Cafferty, Fay H; Edwards, Robert; Møller, Henrik; Duffy, Stephen W

2007-01-01

Cancer screening is aimed primarily at reducing deaths. Thus, site-specific cancer mortality is the appropriate endpoint for evaluating screening interventions. However, it is also the most demanding endpoint, requiring follow-up and a large numbers of patients order to have adequate power. Therefore, it is highly desirable to have surrogate endpoints that can reliably predict mortality reductions many years earlier. We here review a range of surrogate markers in terms of their potential advantages and pitfalls, and argue that a measure which weights incident cancers according to their predicted mortality has many advantages over other measures and should be used more routinely. Application to the UK Flexible Sigmoidoscopy Screening Trial data suggests that predicted colorectal cancer mortality, based on stage-specific incidence, is a more powerful endpoint than actual mortality and could advance the analysis time by about three years. Total colorectal cancer incidence as a surrogate endpoint provides little advance in the analysis time over actual mortality. The approach requires reliable prognostic data, (e.g. stage), for both the study cohort and a representative sample of the whole population. The routine collection of such data should be a priority for cancer registries. Surrogate endpoints should not replace a long-term analysis based directly on mortality, but can provide reliable early indicators which can be useful both for monitoring ongoing screening programmes and for making policy decisions.

Pediatric Heart Donor Assessment Tool (PH-DAT): A novel donor risk scoring system to predict 1-year mortality in pediatric heart transplantation.

PubMed

Zafar, Farhan; Jaquiss, Robert D; Almond, Christopher S; Lorts, Angela; Chin, Clifford; Rizwan, Raheel; Bryant, Roosevelt; Tweddell, James S; Morales, David L S

2018-03-01

In this study we sought to quantify hazards associated with various donor factors into a cumulative risk scoring system (the Pediatric Heart Donor Assessment Tool, or PH-DAT) to predict 1-year mortality after pediatric heart transplantation (PHT). PHT data with complete donor information (5,732) were randomly divided into a derivation cohort and a validation cohort (3:1). From the derivation cohort, donor-specific variables associated with 1-year mortality (exploratory p-value < 0.2) were incorporated into a multivariate logistic regression model. Scores were assigned to independent predictors (p < 0.05) based on relative odds ratios (ORs). The final model had an acceptable predictive value (c-statistic = 0.62). The significant 5 variables (ischemic time, stroke as the cause of death, donor-to-recipient height ratio, donor left ventricular ejection fraction, glomerular filtration rate) were used for the scoring system. The validation cohort demonstrated a strong correlation between the observed and expected rates of 1-year mortality (r = 0.87). The risk of 1-year mortality increases by 11% (OR 1.11 [1.08 to 1.14]; p < 0.001) in the derivation cohort and 9% (OR 1.09 [1.04 to 1.14]; p = 0.001) in the validation cohort with an increase of 1-point in score. Mortality risk increased 5 times from the lowest to the highest donor score in this cohort. Based on this model, a donor score range of 10 to 28 predicted 1-year recipient mortality of 11% to 31%. This novel pediatric-specific, donor risk scoring system appears capable of predicting post-transplant mortality. Although the PH-DAT may benefit organ allocation and assessment of recipient risk while controlling for donor risk, prospective validation of this model is warranted. Copyright © 2018 International Society for the Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

A Three-Step Approach To Model Tree Mortality in the State of Georgia

Treesearch

Qingmin Meng; Chris J. Cieszewski; Roger C. Lowe; Michal Zasada

2005-01-01

Tree mortality is one of the most complex phenomena of forest growth and yield. Many types of factors affect tree mortality, which is considered difficult to predict. This study presents a new systematic approach to simulate tree mortality based on the integration of statistical models and geographical information systems. This method begins with variable preselection...

Validation of a new mortality risk prediction model for people 65 years and older in northwest Russia: The Crystal risk score.

PubMed

Turusheva, Anna; Frolova, Elena; Bert, Vaes; Hegendoerfer, Eralda; Degryse, Jean-Marie

2017-07-01

Prediction models help to make decisions about further management in clinical practice. This study aims to develop a mortality risk score based on previously identified risk predictors and to perform internal and external validations. In a population-based prospective cohort study of 611 community-dwelling individuals aged 65+ in St. Petersburg (Russia), all-cause mortality risks over 2.5 years follow-up were determined based on the results obtained from anthropometry, medical history, physical performance tests, spirometry and laboratory tests. C-statistic, risk reclassification analysis, integrated discrimination improvement analysis, decision curves analysis, internal validation and external validation were performed. Older adults were at higher risk for mortality [HR (95%CI)=4.54 (3.73-5.52)] when two or more of the following components were present: poor physical performance, low muscle mass, poor lung function, and anemia. If anemia was combined with high C-reactive protein (CRP) and high B-type natriuretic peptide (BNP) was added the HR (95%CI) was slightly higher (5.81 (4.73-7.14)) even after adjusting for age, sex and comorbidities. Our models were validated in an external population of adults 80+. The extended model had a better predictive capacity for cardiovascular mortality [HR (95%CI)=5.05 (2.23-11.44)] compared to the baseline model [HR (95%CI)=2.17 (1.18-4.00)] in the external population. We developed and validated a new risk prediction score that may be used to identify older adults at higher risk for mortality in Russia. Additional studies need to determine which targeted interventions improve the outcomes of these at-risk individuals. Copyright © 2017 Elsevier B.V. All rights reserved.

Linking livestock snow disaster mortality and environmental stressors in the Qinghai-Tibetan Plateau: Quantification based on generalized additive models.

PubMed

Li, Yijia; Ye, Tao; Liu, Weihang; Gao, Yu

2018-06-01

Livestock snow disaster occurs widely in Central-to-Eastern Asian temperate and alpine grasslands. The effects of snow disaster on livestock involve a complex interaction between precipitation, vegetation, livestock, and herder communities. Quantifying the relationship among livestock mortality, snow hazard intensity, and seasonal environmental stressors is of great importance for snow disaster early warning, risk assessments, and adaptation strategies. Using a wide-spatial extent, long-time series, and event-based livestock snow disaster dataset, this study quantified those relationships and established a quantitative model of livestock mortality for prediction purpose for the Qinghai-Tibet Plateau region. Estimations using generalized additive models (GAMs) were shown to accurately predict livestock mortality and mortality rate due to snow disaster, with adjusted-R 2 up to 0.794 and 0.666, respectively. These results showed that a longer snow disaster duration, lower temperatures during the disaster, and a drier summer with less vegetation all contribute significantly and non-linearly to higher mortality (rate), after controlling for elevation and socioeconomic conditions. These results can be readily applied to risk assessment and risk-based adaptation actions. Copyright © 2017 Elsevier B.V. All rights reserved.

Prediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus - A population-based retrospective cohort study.

PubMed

Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen

2017-06-01

This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell"'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models. Copyright © 2017 Elsevier Inc. All rights reserved.

A web-based tool to predict acute kidney injury in patients with ST-elevation myocardial infarction: Development, internal validation and comparison.

PubMed

Zambetti, Benjamin R; Thomas, Fridtjof; Hwang, Inyong; Brown, Allen C; Chumpia, Mason; Ellis, Robert T; Naik, Darshan; Khouzam, Rami N; Ibebuogu, Uzoma N; Reed, Guy L

2017-01-01

In ST-elevation myocardial infarction (STEMI), acute kidney injury (AKI) may increase subsequent morbidity and mortality. Still, it remains difficult to predict AKI risk in these patients. We sought to 1) determine the frequency and clinical outcomes of AKI and, 2) develop, validate and compare a web-based tool for predicting AKI. In a racially diverse series of 1144 consecutive STEMI patients, Stage 1 or greater AKI occurred in 12.9% and was severe (Stage 2-3) in 2.9%. AKI was associated with increased mortality (5.7-fold, unadjusted) and hospital stay (2.5-fold). AKI was associated with systolic dysfunction, increased left ventricular end-diastolic pressures, hypotension and intra-aortic balloon counterpulsation. A computational algorithm (UT-AKI) was derived and internally validated. It showed higher sensitivity and improved overall prediction for AKI (area under the curve 0.76) vs. other published indices. Higher UT-AKI scores were associated with more severe AKI, longer hospital stay and greater hospital mortality. In a large, racially diverse cohort of STEMI patients, Stage 1 or greater AKI was relatively common and was associated with significant morbidity and mortality. A web-accessible, internally validated tool was developed with improved overall value for predicting AKI. By identifying patients at increased risk, this tool may help physicians tailor post-procedural diagnostic and therapeutic strategies after STEMI to reduce AKI and its associated morbidity and mortality.

What weather variables are important in predicting heat-related mortality? A new application of statistical learning methods

PubMed Central

Zhang, Kai; Li, Yun; Schwartz, Joel D.; O'Neill, Marie S.

2014-01-01

Hot weather increases risk of mortality. Previous studies used different sets of weather variables to characterize heat stress, resulting in variation in heat-mortality- associations depending on the metric used. We employed a statistical learning method – random forests – to examine which of various weather variables had the greatest impact on heat-related mortality. We compiled a summertime daily weather and mortality counts dataset from four U.S. cities (Chicago, IL; Detroit, MI; Philadelphia, PA; and Phoenix, AZ) from 1998 to 2006. A variety of weather variables were ranked in predicting deviation from typical daily all-cause and cause-specific death counts. Ranks of weather variables varied with city and health outcome. Apparent temperature appeared to be the most important predictor of heat-related mortality for all-cause mortality. Absolute humidity was, on average, most frequently selected one of the top variables for all-cause mortality and seven cause-specific mortality categories. Our analysis affirms that apparent temperature is a reasonable variable for activating heat alerts and warnings, which are commonly based on predictions of total mortality in next few days. Additionally, absolute humidity should be included in future heat-health studies. Finally, random forests can be used to guide choice of weather variables in heat epidemiology studies. PMID:24834832

Prediction of delayed mortality of fire-damaged ponderosa pine following prescribed fires in eastern Oregon, USA.

Treesearch

Walter G. Thies; Douglas J. Westlina; Mark Loewen; Greg Brenner

2006-01-01

Prescribed burning is a management tool used to reduce fuel loads in western interior forests. Following a burn, managers need the ability to predict the mortality of individual trees based on easily observed characteristics. A study was established in six stands of mixed-age ponderosa pine (Pinus ponderosa Dougl. ex Laws.) with scattered western...

Pleural cancer mortality in Spain: time-trends and updating of predictions up to 2020.

PubMed

López-Abente, Gonzalo; García-Gómez, Montserrat; Menéndez-Navarro, Alfredo; Fernández-Navarro, Pablo; Ramis, Rebeca; García-Pérez, Javier; Cervantes, Marta; Ferreras, Eva; Jiménez-Muñoz, María; Pastor-Barriuso, Roberto

2013-11-06

A total of 2,514,346 metric tons (Mt) of asbestos were imported into Spain from 1906 until the ban on asbestos in 2002. Our objective was to study pleural cancer mortality trends as an indicator of mesothelioma mortality and update mortality predictions for the periods 2011-2015 and 2016-2020 in Spain. Log-linear Poisson models were fitted to study the effect of age, period of death and birth cohort (APC) on mortality trends. Change points in cohort- and period-effect curvatures were assessed using segmented regression. Fractional power-link APC models were used to predict mortality until 2020. In addition, an alternative model based on national asbestos consumption figures was also used to perform long-term predictions. Pleural cancer deaths increased across the study period, rising from 491 in 1976-1980 to 1,249 in 2006-2010. Predictions for the five-year period 2016-2020 indicated a total of 1,319 pleural cancer deaths (264 deaths/year). Forecasts up to 2020 indicated that this increase would continue, though the age-adjusted rates showed a levelling-off in male mortality from 2001 to 2005, corresponding to the lower risk in post-1960 generations. Among women, rates were lower and the mortality trend was also different, indicating that occupational exposure was possibly the single factor having most influence on pleural cancer mortality. The cancer mortality-related consequences of human exposure to asbestos are set to persist and remain in evidence until the last surviving members of the exposed cohorts have disappeared. It can thus be assumed that occupationally-related deaths due to pleural mesothelioma will continue to occur in Spain until at least 2040.

Prediction of mesothelioma and lung cancer in a cohort of asbestos exposed workers.

PubMed

Gasparrini, Antonio; Pizzo, Anna Maria; Gorini, Giuseppe; Seniori Costantini, Adele; Silvestri, Stefano; Ciapini, Cesare; Innocenti, Andrea; Berry, Geoffrey

2008-01-01

Several papers have reported state-wide projections of mesothelioma deaths, but few have computed these predictions in selected exposed groups. To predict the future deaths attributable to asbestos in a cohort of railway rolling stock workers. The future mortality of the 1,146 living workers has been computed in term of individual probability of dying for three different risks: baseline mortality, lung cancer excess, mesothelioma mortality. Lung cancer mortality attributable to asbestos was calculated assuming the excess risk as stable or with a decrease after a period of time since first exposure. Mesothelioma mortality was based on cumulative exposure and time since first exposure, with the inclusion of a term for clearance of asbestos fibres from the lung. The most likely range of the number of deaths attributable to asbestos in the period 2005-2050 was 15-30 for excess of lung cancer, and 23-35 for mesothelioma. This study provides predictions of asbestos-related mortality even in a selected cohort of exposed subjects, using previous knowledge about exposure-response relationship. The inclusion of individual information in the projection model helps reduce misclassification and improves the results. The method could be extended in other selected cohorts.

Research frontiers for improving our understanding of drought‐induced tree and forest mortality

USGS Publications Warehouse

Hartmann, Henrik; Moura, Catarina; Anderegg, William R. L.; Ruehr, Nadine; Salmon, Yann; Allen, Craig D.; Arndt, Stefan K.; Breshears, David D.; Davi, Hendrik; Galbraith, David; Ruthrof, Katinka X.; Wunder, Jan; Adams, Henry D.; Bloemen, Jasper; Cailleret, Maxime; Cobb, Richard; Gessler, Arthur; Grams, Thorsten E. E.; Jansen, Steven; Kautz, Markus; Lloret, Francisco; O’Brien, Michael

2018-01-01

Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die‐off events have severe consequences for ecosystem services, biophysical and biogeochemical land–atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global monitoring network of forest mortality. In light of recent and anticipated large forest die‐off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought‐induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.

A Comparison of Systemic Inflammation-Based Prognostic Scores in Patients on Regular Hemodialysis

PubMed Central

Kato, Akihiko; Tsuji, Takayuki; Sakao, Yukitoshi; Ohashi, Naro; Yasuda, Hideo; Fujimoto, Taiki; Takita, Takako; Furuhashi, Mitsuyoshi; Kumagai, Hiromichi

2013-01-01

Background/Aims Systemic inflammation-based prognostic scores have prognostic power in patients with cancer, independently of tumor stage and site. Although inflammatory status is associated with mortality in hemodialysis (HD) patients, it remains to be determined as to whether these composite scores are useful in predicting clinical outcomes. Methods We calculated the 6 prognostic scores [Glasgow prognostic score (GPS), modified GPS (mGPS), neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), prognostic index (PI) and prognostic nutritional index (PNI), which have been established as a useful scoring system in cancer patients. We enrolled 339 patients on regular HD (age: 64 ± 13 years; time on HD: 129 ± 114 months; males/females = 253/85) and followed them for 42 months. The area under the receiver-operating characteristics curve was used to determine which scoring system was more predictive of mortality. Results Elevated GPS, mGPS, NLR, PLR, PI and PNI were all associated with total mortality, independent of covariates. If GPS was raised, mGPS, NLR, PLR and PI were also predictive of all-cause mortality and/or hospitalization. GPS and PNI were associated with poor nutritional status. Using overall mortality as an endpoint, the area under the curve (AUC) was significant for a GPS of 0.701 (95% CI: 0.637-0.765; p < 0.01) and for a PNI of 0.616 (95% CI: 0.553-0.768; p = 0.01). However, AUC for hypoalbuminemia (<3.5 g/dl) was comparable to that of GPS (0.695, 95% CI: 0.632-0.759; p < 0.01). Conclusion GPS, based on serum albumin and highly sensitive C-reactive protein, has the most prognostic power for mortality prediction among the prognostic scores in HD patients. However, as the determination of serum albumin reflects mortality similarly to GPS, other composite combinations are needed to provide additional clinical utility beyond that of albumin alone in HD patients. PMID:24403910

C-Reactive Protein and Prediction of 1-Year Mortality in Prevalent Hemodialysis Patients

PubMed Central

Bazeley, Jonathan; Bieber, Brian; Li, Yun; Morgenstern, Hal; de Sequera, Patricia; Combe, Christian; Yamamoto, Hiroyasu; Gallagher, Martin; Port, Friedrich K.

2011-01-01

Summary Background and objectives Measurement of C-reactive protein (CRP) levels remains uncommon in North America, although it is now routine in many countries. Using Dialysis Outcomes and Practice Patterns Study data, our primary aim was to evaluate the value of CRP for predicting mortality when measured along with other common inflammatory biomarkers. Design, setting, participants, & measurements We studied 5061 prevalent hemodialysis patients from 2005 to 2008 in 140 facilities routinely measuring CRP in 10 countries. The association of CRP with mortality was evaluated using Cox regression. Prediction of 1-year mortality was assessed in logistic regression models with differing adjustment variables. Results Median baseline CRP was lower in Japan (1.0 mg/L) than other countries (6.0 mg/L). CRP was positively, monotonically associated with mortality. No threshold below which mortality rate leveled off was identified. In prediction models, CRP performance was comparable with albumin and exceeded ferritin and white blood cell (WBC) count based on measures of model discrimination (c-statistics, net reclassification improvement [NRI]) and global model fit (generalized R2). The primary analysis included age, gender, diabetes, catheter use, and the four inflammatory markers (omitting one at a time). Specifying NRI ≥5% as appropriate reclassification of predicted mortality risk, NRI for CRP was 12.8% compared with 10.3% for albumin, 0.8% for ferritin, and <0.1% for WBC. Conclusions These findings demonstrate the value of measuring CRP in addition to standard inflammatory biomarkers to improve mortality prediction in hemodialysis patients. Future studies are indicated to identify interventions that lower CRP and to identify whether they improve clinical outcomes. PMID:21868617

External validation of Vascular Study Group of New England risk predictive model of mortality after elective abdominal aorta aneurysm repair in the Vascular Quality Initiative and comparison against established models.

PubMed

Eslami, Mohammad H; Rybin, Denis V; Doros, Gheorghe; Siracuse, Jeffrey J; Farber, Alik

2018-01-01

The purpose of this study is to externally validate a recently reported Vascular Study Group of New England (VSGNE) risk predictive model of postoperative mortality after elective abdominal aortic aneurysm (AAA) repair and to compare its predictive ability across different patients' risk categories and against the established risk predictive models using the Vascular Quality Initiative (VQI) AAA sample. The VQI AAA database (2010-2015) was queried for patients who underwent elective AAA repair. The VSGNE cases were excluded from the VQI sample. The external validation of a recently published VSGNE AAA risk predictive model, which includes only preoperative variables (age, gender, history of coronary artery disease, chronic obstructive pulmonary disease, cerebrovascular disease, creatinine levels, and aneurysm size) and planned type of repair, was performed using the VQI elective AAA repair sample. The predictive value of the model was assessed via the C-statistic. Hosmer-Lemeshow method was used to assess calibration and goodness of fit. This model was then compared with the Medicare, Vascular Governance Northwest model, and Glasgow Aneurysm Score for predicting mortality in VQI sample. The Vuong test was performed to compare the model fit between the models. Model discrimination was assessed in different risk group VQI quintiles. Data from 4431 cases from the VSGNE sample with the overall mortality rate of 1.4% was used to develop the model. The internally validated VSGNE model showed a very high discriminating ability in predicting mortality (C = 0.822) and good model fit (Hosmer-Lemeshow P = .309) among the VSGNE elective AAA repair sample. External validation on 16,989 VQI cases with an overall 0.9% mortality rate showed very robust predictive ability of mortality (C = 0.802). Vuong tests yielded a significant fit difference favoring the VSGNE over then Medicare model (C = 0.780), Vascular Governance Northwest (0.774), and Glasgow Aneurysm Score (0.639). Across the 5 risk quintiles, the VSGNE model predicted observed mortality significantly with great accuracy. This simple VSGNE AAA risk predictive model showed very high discriminative ability in predicting mortality after elective AAA repair among a large external independent sample of AAA cases performed by a diverse array of physicians nationwide. The risk score based on this simple VSGNE model can reliably stratify patients according to their risk of mortality after elective AAA repair better than other established models. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Spatial variations in mortality in pelagic early life stages of a marine fish (Gadus morhua)

NASA Astrophysics Data System (ADS)

Langangen, Øystein; Stige, Leif C.; Yaragina, Natalia A.; Ottersen, Geir; Vikebø, Frode B.; Stenseth, Nils Chr.

2014-09-01

Mortality of pelagic eggs and larvae of marine fish is often assumed to be constant both in space and time due to lacking information. This may, however, be a gross oversimplification, as early life stages are likely to experience large variations in mortality both in time and space. In this paper we develop a method for estimating the spatial variability in mortality of eggs and larvae. The method relies on survey data and physical-biological particle-drift models to predict the drift of ichthyoplankton. Furthermore, the method was used to estimate the spatially resolved mortality field in the egg and larval stages of Barents Sea cod (Gadus morhua). We analyzed data from the Barents Sea for the period between 1959 and 1993 when there are two surveys available: a spring and a summer survey. An individual-based physical-biological particle-drift model, tailored to the egg and larval stages of Barents Sea cod, was used to predict the drift trajectories from the observed stage-specific distributions in spring to the time of observation in the summer, a drift time of approximately 45 days. We interpreted the spatial patterns in the differences between the predicted and observed abundance distributions in summer as reflecting the spatial patterns in mortality over the drift period. Using the estimated mortality fields, we show that the spatial variations in mortality might have a significant impact on survival to later life stages and we suggest that there may be trade-offs between increased early survival in off shore regions and reduced probability of ending up in the favorable nursing grounds in the Barents Sea. In addition, we show that accounting for the estimated mortality field, improves the correlation between a simulated recruitment index and observation-based indices of juvenile abundance.

Use of the Hardman index in predicting mortality in endovascular repair of ruptured abdominal aortic aneurysms.

PubMed

Conroy, Daniel M; Altaf, Nishath; Goode, Steve D; Braithwaite, Bruce D; MacSweeney, Shane T; Richards, Toby

2011-12-01

The Hardman index is a predictor of 30-day mortality after open ruptured abdominal aneurysm repair through the use of preoperative patient factors. The aim of this study was to assess the Hardman index in patients undergoing endovascular repair of ruptured aortic aneurysms. A retrospective analysis of 95 patients undergoing emergency endovascular repairs of computed tomography-confirmed ruptured aneurysms from 1994 to 2008 in a university hospital was performed. All relevant patient variables, calculations of the Hardman index, and the incidence of 30-day mortality were collected in these patients. Correlation of the relationship between each variable and the overall score with the incidence of 30-day mortality was undertaken. The 24-hour mortality was 16% and 30-day mortality 36%. Increasing scores on the Hardman index showed an increasing mortality rate. Thirty-day mortality in patients with a score of 0 to 2 was 30.5%, and in those with a score of ≥3 was 69.2% (P = .01, risk ratio = 2.26, 95% confidence interval = 0.98 to 5.17). This is lower than predicted in both patient groups based on Hardman index score. Loss of consciousness was the only statistically significant independent predictor of 30-day mortality with a risk ratio of 3.16 (95% confidence interval = 2.00-4.97, P < .001). These data suggest that the Hardman index can predict an increased risk of 30-day mortality from endovascular repairs of ruptured aortic aneurysms. However, mortality from endovascular repair is much lower than would be predicted in open repair and it therefore cannot be used clinically as a tool for exclusion from intervention.

Does Mode of Transport Confer a Mortality Benefit in Trauma Patients? Characteristics and Outcomes at an Ontario Lead Trauma Hospital.

PubMed

Buchanan, Ian M; Coates, Angela; Sne, Niv

2016-09-01

Evidence-based guidelines regarding the optimal mode of transport for trauma patients from scene to trauma centre are lacking. The purpose of this study was to investigate the relationship between trauma patient outcomes and mode of transport at a single Ontario Level I Trauma Centre, and specifically to investigate if the mode of transport confers a mortality benefit. A historical, observational cohort study was undertaken to compare rotor-wing and ground transported patients. Captured data included demographics, injury severity, temporal and mortality variables. TRISS-L analysis was performed to examine mortality outcomes. 387 rotor-wing transport and 2,759 ground transport patients were analyzed over an 18-year period. Rotor-wing patients were younger, had a higher Injury Severity Score, and had longer prehospital transport times. Mechanism of injury was similarly distributed between groups. After controlling for heterogeneity with TRISS-L analysis, the mortality of rotor-wing patients was found to be lower than predicted mortality, whereas the converse was found with ground patients. Rotor-wing and ground transported trauma patients represent heterogeneous populations. Accounting for these differences, rotor-wing patients were found to outperform their predicted mortality, whereas ground patients underperformed predictions.

Simultaneous Prediction of New Morbidity, Mortality, and Survival Without New Morbidity From Pediatric Intensive Care: A New Paradigm for Outcomes Assessment.

PubMed

Pollack, Murray M; Holubkov, Richard; Funai, Tomohiko; Berger, John T; Clark, Amy E; Meert, Kathleen; Berg, Robert A; Carcillo, Joseph; Wessel, David L; Moler, Frank; Dalton, Heidi; Newth, Christopher J L; Shanley, Thomas; Harrison, Rick E; Doctor, Allan; Jenkins, Tammara L; Tamburro, Robert; Dean, J Michael

2015-08-01

Assessments of care including quality assessments adjusted for physiological status should include the development of new morbidities as well as mortalities. We hypothesized that morbidity, like mortality, is associated with physiological dysfunction and could be predicted simultaneously with mortality. Prospective cohort study from December 4, 2011, to April 7, 2013. General and cardiac/cardiovascular PICUs at seven sites. Randomly selected PICU patients from their first PICU admission. None. Among 10,078 admissions, the unadjusted morbidity rates (measured with the Functional Status Scale and defined as an increase of ≥ 3 from preillness to hospital discharge) were 4.6% (site range, 2.6-7.7%) and unadjusted mortality rates were 2.7% (site range, 1.3-5.0%). Morbidity and mortality were significantly (p < 0.001) associated with physiological instability (measured with the Pediatric Risk of Mortality III score) in dichotomous (survival and death) and trichotomous (survival without new morbidity, survival with new morbidity, and death) models without covariate adjustments. Morbidity risk increased with increasing Pediatric Risk of Mortality III scores and then decreased at the highest Pediatric Risk of Mortality III values as potential morbidities became mortalities. The trichotomous model with covariate adjustments included age, admission source, diagnostic factors, baseline Functional Status Scale, and the Pediatric Risk of Mortality III score. The three-level goodness-of-fit test indicated satisfactory performance for the derivation and validation sets (p > 0.20). Predictive ability assessed with the volume under the surface was 0.50 ± 0.019 (derivation) and 0.50 ± 0.034 (validation) (vs chance performance = 0.17). Site-level standardized morbidity ratios were more variable than standardized mortality ratios. New morbidities were associated with physiological status and can be modeled simultaneously with mortality. Trichotomous outcome models including both morbidity and mortality based on physiological status are suitable for research studies and quality and other outcome assessments. This approach may be applicable to other assessments presently based only on mortality.

Derivation of data-driven triggers for palliative care consultation in critically ill patients.

PubMed

Hua, May S; Ma, Xiaoyue; Li, Guohua; Wunsch, Hannah

2018-04-30

To examine the ability of existing triggers for intensive care unit (ICU) palliative care consultation to predict 6-month mortality, and derive new triggers for consultation based on risk factors for 6-month mortality. Retrospective cohort study of NY state residents who received intensive care, 2008-2013. We examined sensitivity and specificity of existing triggers for predicting 6-month mortality and used logistic regression to generate patient subgroups at high-risk for 6-month mortality as potential novel triggers for ICU palliative care consultation. Of 1,019,849 patients, 195,847 (19.2%) died within 6 months of admission. Existing triggers were specific but not sensitive for predicting 6-month mortality, (sensitivity 0.3%-11.1%, specificity 96.5-99.9% for individual triggers). Using logistic regression, patient subgroups with the highest predicted probability of 6-month mortality were older patients admitted with sepsis (age 70-79 probability 49.7%, [49.5-50.0]) or cancer (non-metastatic cancer, age 70-79 probability 51.5%, [51.1-51.9]; metastatic cancer, age 70-79 probability 60.3%, [59.9-60.6]). Sensitivity and specificity of novel triggers ranged from 0.05% to 9.2% and 98.6% to 99.9%, respectively. Existing triggers for palliative care consultation are specific, but insensitive for 6-month mortality. Using a data-driven approach to derive novel triggers may identify subgroups of patients at high-risk of 6-month mortality. Copyright © 2018 Elsevier Inc. All rights reserved.

[Risk Prediction Using Routine Data: Development and Validation of Multivariable Models Predicting 30- and 90-day Mortality after Surgical Treatment of Colorectal Cancer].

PubMed

Crispin, Alexander; Strahwald, Brigitte; Cheney, Catherine; Mansmann, Ulrich

2018-06-04

Quality control, benchmarking, and pay for performance (P4P) require valid indicators and statistical models allowing adjustment for differences in risk profiles of the patient populations of the respective institutions. Using hospital remuneration data for measuring quality and modelling patient risks has been criticized by clinicians. Here we explore the potential of prediction models for 30- and 90-day mortality after colorectal cancer surgery based on routine data. Full census of a major statutory health insurer. Surgical departments throughout the Federal Republic of Germany. 4283 and 4124 insurants with major surgery for treatment of colorectal cancer during 2013 and 2014, respectively. Age, sex, primary and secondary diagnoses as well as tumor locations as recorded in the hospital remuneration data according to §301 SGB V. 30- and 90-day mortality. Elixhauser comorbidities, Charlson conditions, and Charlson scores were generated from the ICD-10 diagnoses. Multivariable prediction models were developed using a penalized logistic regression approach (logistic ridge regression) in a derivation set (patients treated in 2013). Calibration and discrimination of the models were assessed in an internal validation sample (patients treated in 2014) using calibration curves, Brier scores, receiver operating characteristic curves (ROC curves) and the areas under the ROC curves (AUC). 30- and 90-day mortality rates in the learning-sample were 5.7 and 8.4%, respectively. The corresponding values in the validation sample were 5.9% and once more 8.4%. Models based on Elixhauser comorbidities exhibited the highest discriminatory power with AUC values of 0.804 (95% CI: 0.776 -0.832) and 0.805 (95% CI: 0.782-0.828) for 30- and 90-day mortality. The Brier scores for these models were 0.050 (95% CI: 0.044-0.056) and 0.067 (95% CI: 0.060-0.074) and similar to the models based on Charlson conditions. Regardless of the model, low predicted probabilities were well calibrated, while higher predicted values tended to be overestimates. The reasonable results regarding discrimination and calibration notwithstanding, models based on hospital remuneration data may not be helpful for P4P. Routine data do not offer information regarding a wide range of quality indicators more useful than mortality. As an alternative, models based on clinical registries may allow a wider, more valid perspective. © Georg Thieme Verlag KG Stuttgart · New York.

Simultaneous Prediction of New Morbidity, Mortality, and Survival without New Morbidity from Pediatric Intensive Care: A New Paradigm for Outcomes Assessment

PubMed Central

Pollack, Murray M.; Holubkov, Richard; Funai, Tomohiko; Berger, John T.; Clark, Amy E.; Meert, Kathleen; Berg, Robert A.; Carcillo, Joseph; Wessel, David L.; Moler, Frank; Dalton, Heidi; Newth, Christopher J. L.; Shanley, Thomas; Harrison, Rick E.; Doctor, Allan; Jenkins, Tammara L.; Tamburro, Robert; Dean, J. Michael

2015-01-01

Objective Assessments of care including quality assessments adjusted for physiological status should include the development of new morbidities as well as mortalities. We hypothesized that morbidity, like mortality, is associated with physiological dysfunction and could be predicted simultaneously with mortality. Design Prospective cohort study from December 4, 2011 to April 7, 2013. Setting and Patients General and cardiac/cardiovascular pediatric intensive care units at 7 sites. Measurements and Main Results Among 10,078 admissions, the unadjusted morbidity rates (measured with the Functional Status Scale (FSS), and defined as an increase of ≥ 3 from pre-illness to hospital discharge) were 4.6% (site range 2.6% to 7.7%) and unadjusted mortality rates were 2.7% (site range 1.3% – 5.0%). Morbidity and mortality were significantly (p<0.001) associated with physiological instability (measured with the PRISM III score) in dichotomous (survival, death) and trichotomous (survival without new morbidity, survival with new morbidity, death) models without covariate adjustments. Morbidity risk increased with increasing PRISM III scores and then decreased at the highest PRISM III values as potential morbidities became mortalities. The trichotomous model with covariate adjustments included age, admission source, diagnostic factors, baseline FSS and the PRISM III score. The three-level goodness of fit test indicated satisfactory performance for the derivation and validation sets (p>0.20). Predictive ability assessed with the volume under the surface (VUS) was 0.50 ± 0.019 (derivation) and 0.50 ± 0.034 (validation) (versus chance performance = 0.17). Site-level standardized morbidity ratios were more variable than standardized mortality ratios. Conclusions New morbidities were associated with physiological status and can be modeled simultaneously with mortality. Trichotomous outcome models including both morbidity and mortality based on physiological status are suitable for research studies, and quality and other outcome assessments. This approach may be applicable to other assessments presently based only on mortality. PMID:25985385

Tree injury and mortality in fires: developing process-based models

Treesearch

Bret W. Butler; Matthew B. Dickinson

2010-01-01

Wildland fire managers are often required to predict tree injury and mortality when planning a prescribed burn or when considering wildfire management options; and, currently, statistical models based on post-fire observations are the only tools available for this purpose. Implicit in the derivation of statistical models is the assumption that they are strictly...

Which AIS based scoring system is the best predictor of outcome in orthopaedic blunt trauma patients?

PubMed

Harwood, Paul J; Giannoudis, Peter V; Probst, Christian; Van Griensven, Martijn; Krettek, Christian; Pape, Hans-Christoph

2006-02-01

Abbreviated Injury Scale (AIS)-based systems-the Injury Severity Score (ISS), New Injury Severity Score (NISS), and AISmax-are used to assess trauma patients. The merits of each in predicting outcome are controversial. A large prospective database was used to assess their predictive capacity using receiver operator characteristic curves. In all, 10,062 adult, blunt-trauma patients met the inclusion criteria. All systems were significant outcome predictors for sepsis, multiple organ failure (MOF), length of hospital stay, length of intensive care unit (ICU) admission and mortality (p < 0.0001). NISS was a significantly better predictor than the ISS for mortality (p < 0.0001). NISS was equivalent to the AISmax for mortality prediction and superior in patients with orthopaedic injuries. NISS was significantly better for sepsis, MOF, ICU stay, and total hospital stay (p < 0.0001). NISS is superior or equivalent to the ISS and AISmax for prediction of all investigated outcomes in a population of blunt trauma patients. As NISS is easier to calculate, its use is recommended to stratify patients for clinical and research purposes.

Effective use of outcomes data in cardiovascular surgery

NASA Astrophysics Data System (ADS)

Yasnoff, William A.; Page, U. S.

1994-12-01

We have established the Merged Cardiac Registry (MCR) containing over 100,000 cardiovascular surgery cases from 47 sites in the U.S. and Europe. MCR outcomes data are used by the contributors for clinical quality improvement. A tool for prospective prediction of mortality and stroke for coronary artery bypass graft surgery (83% of the cases), known as RiskMaster, has been developed using a Bayesian model based on 40,819 patients who had their surgery from 1988-92, and tested on 4,244 patients from 1993. In patients with mortality risks of 10% or less (92% of cases), the average risk prediction is identical to the actual 30- day mortality (p > 0.37), while risk is overestimated in higher risk patients. The receiver operating characteristic curve area for mortality prediction is 0.76 +/- 0.02. The RiskMaster prediction tool is now available online or as a standalone software package. MCR data also shows that average mortality risk is identical for a given body surface area regardless of gender. Outcomes data measure the benefits of health care, and are therefore an essential element in cost/benefit analysis. We believe their cost is justified by their use for the rational assessment of treatment alternatives.

Clostridium difficile Associated Risk of Death Score (CARDS): A novel severity score to predict mortality among hospitalized patients with Clostridium difficile infection

PubMed Central

Kassam, Zain; Fabersunne, Camila Cribb; Smith, Mark B.; Alm, Eric J.; Kaplan, Gilaad G.; Nguyen, Geoffrey C.; Ananthakrishnan, Ashwin N.

2016-01-01

Background Clostridium difficile infection (CDI) is public health threat and associated with significant mortality. However, there is a paucity of objectively derived CDI severity scoring systems to predict mortality. Aims To develop a novel CDI risk score to predict mortality entitled: Clostridium difficile Associated Risk of Death Score (CARDS). Methods We obtained data from the United States 2011 Nationwide Inpatient Sample (NIS) database. All CDI-associated hospitalizations were identified using discharge codes (ICD-9-CM, 008.45). Multivariate logistic regression was utilized to identify independent predictors of mortality. CARDS was calculated by assigning a numeric weight to each parameter based on their odds ratio in the final logistic model. Predictive properties of model discrimination were assessed using the c-statistic and validated in an independent sample using the 2010 NIS database. Results We identified 77,776 hospitalizations, yielding an estimate of 374,747 cases with an associated diagnosis of CDI in the United States, 8% of whom died in the hospital. The 8 severity score predictors were identified on multivariate analysis: age, cardiopulmonary disease, malignancy, diabetes, inflammatory bowel disease, acute renal failure, liver disease and ICU admission, with weights ranging from −1 (for diabetes) to 5 (for ICU admission). The overall risk score in the cohort ranged from 0 to 18. Mortality increased significantly as CARDS increased. CDI-associated mortality was 1.2% with a CARDS of 0 compared to 100% with CARDS of 18. The model performed equally well in our validation cohort. Conclusion CARDS is a promising simple severity score to predict mortality among those hospitalized with CDI. PMID:26849527

Neighborhood Differences in Post-Stroke Mortality

PubMed Central

Osypuk, Theresa L.; Ehntholt, Amy; Moon, J. Robin; Gilsanz, Paola; Glymour, M. Maria

2017-01-01

Background Post-stroke mortality is higher among residents of disadvantaged neighborhoods, but it is not known whether neighborhood inequalities are specific to stroke survival or similar to mortality patterns in the general population. We hypothesized that neighborhood disadvantage would predict higher post-stroke mortality and neighborhood effects would be relatively larger for stroke patients than for individuals with no history of stroke. Methods and Results Health and Retirement Study participants aged 50+ without stroke at baseline (n=15,560) were followed up to 12 years for incident stroke (1,715 events over 159,286 person-years) and mortality (5,325 deaths). Baseline neighborhood characteristics included objective measures based on census tracts (family income, poverty, deprivation, residential stability, and percent white, black or foreign-born) and self-reported neighborhood social ties. Using Cox proportional hazard models, we compared neighborhood mortality effects for people with versus without a history of stroke. Most neighborhood variables predicted mortality for both stroke patients and the general population in demographic-adjusted models. Neighborhood percent white predicted lower mortality for stroke survivors (HR=0.75 for neighborhoods in highest 25th percentile vs. below, 95 % CI: 0.62, 0.91) more strongly than for stroke-free adults (HR=0.92 (0.83, 1.02); p=0.04 for stroke-by-neighborhood interaction). No other neighborhood characteristic had different effects for people with versus without stroke. Neighborhood-mortality associations emerged within three months after stroke, when associations were often stronger than among stroke-free individuals. Conclusions Neighborhood characteristics predict post-stroke mortality, but most effects are similar for individuals without stroke. Eliminating disparities in stroke survival may require addressing pathways that are not specific to traditional post-stroke care. PMID:28228449

Stem mortality in surface fires: Part II, experimental methods for characterizing the thermal response of tree stems to heating by fires

Treesearch

D. M. Jimenez; B. W. Butler; J. Reardon

2003-01-01

Current methods for predicting fire-induced plant mortality in shrubs and trees are largely empirical. These methods are not readily linked to duff burning, soil heating, and surface fire behavior models. In response to the need for a physics-based model of this process, a detailed model for predicting the temperature distribution through a tree stem as a function of...

Prediction of Mortality in Patients with Isolated Traumatic Subarachnoid Hemorrhage Using a Decision Tree Classifier: A Retrospective Analysis Based on a Trauma Registry System.

PubMed

Rau, Cheng-Shyuan; Wu, Shao-Chun; Chien, Peng-Chen; Kuo, Pao-Jen; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2017-11-22

Background: In contrast to patients with traumatic subarachnoid hemorrhage (tSAH) in the presence of other types of intracranial hemorrhage, the prognosis of patients with isolated tSAH is good. The incidence of mortality in these patients ranges from 0-2.5%. However, few data or predictive models are available for the identification of patients with a high mortality risk. In this study, we aimed to construct a model for mortality prediction using a decision tree (DT) algorithm, along with data obtained from a population-based trauma registry, in a Level 1 trauma center. Methods: Five hundred and forty-five patients with isolated tSAH, including 533 patients who survived and 12 who died, between January 2009 and December 2016, were allocated to training ( n = 377) or test ( n = 168) sets. Using the data on demographics and injury characteristics, as well as laboratory data of the patients, classification and regression tree (CART) analysis was performed based on the Gini impurity index, using the rpart function in the rpart package in R. Results: In this established DT model, three nodes (head Abbreviated Injury Scale (AIS) score ≤4, creatinine (Cr) <1.4 mg/dL, and age <76 years) were identified as important determinative variables in the prediction of mortality. Of the patients with isolated tSAH, 60% of those with a head AIS >4 died, as did the 57% of those with an AIS score ≤4, but Cr ≥1.4 and age ≥76 years. All patients who did not meet the above-mentioned criteria survived. With all the variables in the model, the DT achieved an accuracy of 97.9% (sensitivity of 90.9% and specificity of 98.1%) and 97.7% (sensitivity of 100% and specificity of 97.7%), for the training set and test set, respectively. Conclusions: The study established a DT model with three nodes (head AIS score ≤4, Cr <1.4, and age <76 years) to predict fatal outcomes in patients with isolated tSAH. The proposed decision-making algorithm may help identify patients with a high risk of mortality.

Long-term forecasting and comparison of mortality in the Evaluation of the Xience Everolimus Eluting Stent vs. Coronary Artery Bypass Surgery for Effectiveness of Left Main Revascularization (EXCEL) trial: prospective validation of the SYNTAX Score II.

PubMed

Campos, Carlos M; van Klaveren, David; Farooq, Vasim; Simonton, Charles A; Kappetein, Arie-Pieter; Sabik, Joseph F; Steyerberg, Ewout W; Stone, Gregg W; Serruys, Patrick W

2015-05-21

To prospectively validate the SYNTAX Score II and forecast the outcomes of the randomized Evaluation of the Xience Everolimus-Eluting Stent Versus Coronary Artery Bypass Surgery for Effectiveness of Left Main Revascularization (EXCEL) Trial. Evaluation of the Xience Everolimus Eluting Stent vs. Coronary Artery Bypass Surgery for Effectiveness of Left Main Revascularization is a prospective, randomized multicenter trial designed to establish the efficacy and safety of percutaneous coronary intervention (PCI) with the everolimus-eluting stent compared with coronary artery bypass graft (CABG) surgery in subjects with unprotected left-main coronary artery (ULMCA) disease and low-intermediate anatomical SYNTAX scores (<33). After completion of patient recruitment in EXCEL, the SYNTAX Score II was prospectively applied to predict 4-year mortality in the CABG and PCI arms. The 95% prediction intervals (PIs) for mortality were computed using simulation with bootstrap resampling (10 000 times). For the entire study cohort, the 4-year predicted mortalities were 8.5 and 10.5% in the PCI and CABG arms, respectively [odds ratios (OR) 0.79; 95% PI 0.43-1.50). In subjects with low (≤22) anatomical SYNTAX scores, the predicted OR was 0.69 (95% PI 0.34-1.45); in intermediate anatomical SYNTAX scores (23-32), the predicted OR was 0.93 (95% PI 0.53-1.62). Based on 4-year mortality predictions in EXCEL, clinical characteristics shifted long-term mortality predictions either in favour of PCI (older age, male gender and COPD) or CABG (younger age, lower creatinine clearance, female gender, reduced left ventricular ejection fraction). The SYNTAX Score II indicates at least an equipoise for long-term mortality between CABG and PCI in subjects with ULMCA disease up to an intermediate anatomical complexity. Both anatomical and clinical characteristics had a clear impact on long-term mortality predictions and decision making between CABG and PCI. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

Comparison of the Mini-Nutritional Assessment short and long form and serum albumin as prognostic indicators of hip fracture outcomes.

PubMed

Helminen, Heli; Luukkaala, Tiina; Saarnio, Juha; Nuotio, Maria

2017-04-01

Malnutrition is common among older hip fracture patients and associated with adverse outcomes. We examined Mini Nutritional Assessment short (MNA-SF) and long form (MNA-LF) and serum albumin as prognostic indicators of mobility, living arrangements and mortality after hip fracture. Population-based prospective data were collected on 594 hip fracture patients aged 65 and over. MNA-SF, MNA-LF and serum albumin were assessed on admission. Outcomes were poorer mobility; transfer to more assisted living accommodation and mortality one month, four months and one year post fracture. Logistic regression analyses for mobility and living arrangements with odds ratios (OR) and Cox proportional hazards model for mortality with hazard ratios (HR) and 95% confidence intervals (CI) were used, adjusted for age, gender, ASA grade and fracture type. All measures predicted mortality at all time-points. Risk of malnutrition and malnutrition measured by MNA-LF predicted mobility and living arrangements within four months of hip fracture. At one year, risk of malnutrition predicted mobility and malnutrition predicted living arrangements, when measured by MNA-LF. Malnutrition, but not risk thereof, measured by MNA-SF predicted living arrangements at all time-points. None of the measures predicted one-month mobility. All measures were strong indicators of short- and long-term mortality after hip fracture. MNA-LF was superior in predicting mobility and living arrangements, particularly at four months. All measures were relatively poor in predicting short-term outcomes of mobility and living arrangements. Copyright © 2017 Elsevier Ltd. All rights reserved.

Using Forecast and Observed Weather Data to Assess Performance of Forecast Products in Identifying Heat Waves and Estimating Heat Wave Effects on Mortality

PubMed Central

Chen, Yeh-Hsin; Schwartz, Joel D.; Rood, Richard B.; O’Neill, Marie S.

2014-01-01

Background: Heat wave and health warning systems are activated based on forecasts of health-threatening hot weather. Objective: We estimated heat–mortality associations based on forecast and observed weather data in Detroit, Michigan, and compared the accuracy of forecast products for predicting heat waves. Methods: We derived and compared apparent temperature (AT) and heat wave days (with heat waves defined as ≥ 2 days of daily mean AT ≥ 95th percentile of warm-season average) from weather observations and six different forecast products. We used Poisson regression with and without adjustment for ozone and/or PM10 (particulate matter with aerodynamic diameter ≤ 10 μm) to estimate and compare associations of daily all-cause mortality with observed and predicted AT and heat wave days. Results: The 1-day-ahead forecast of a local operational product, Revised Digital Forecast, had about half the number of false positives compared with all other forecasts. On average, controlling for heat waves, days with observed AT = 25.3°C were associated with 3.5% higher mortality (95% CI: –1.6, 8.8%) than days with AT = 8.5°C. Observed heat wave days were associated with 6.2% higher mortality (95% CI: –0.4, 13.2%) than non–heat wave days. The accuracy of predictions varied, but associations between mortality and forecast heat generally tended to overestimate heat effects, whereas associations with forecast heat waves tended to underestimate heat wave effects, relative to associations based on observed weather metrics. Conclusions: Our findings suggest that incorporating knowledge of local conditions may improve the accuracy of predictions used to activate heat wave and health warning systems. Citation: Zhang K, Chen YH, Schwartz JD, Rood RB, O’Neill MS. 2014. Using forecast and observed weather data to assess performance of forecast products in identifying heat waves and estimating heat wave effects on mortality. Environ Health Perspect 122:912–918; http://dx.doi.org/10.1289/ehp.1306858 PMID:24833618

Non-linear feature extraction from HRV signal for mortality prediction of ICU cardiovascular patient.

PubMed

Karimi Moridani, Mohammad; Setarehdan, Seyed Kamaledin; Motie Nasrabadi, Ali; Hajinasrollah, Esmaeil

2016-01-01

Intensive care unit (ICU) patients are at risk of in-ICU morbidities and mortality, making specific systems for identifying at-risk patients a necessity for improving clinical care. This study presents a new method for predicting in-hospital mortality using heart rate variability (HRV) collected from the times of a patient's ICU stay. In this paper, a HRV time series processing based method is proposed for mortality prediction of ICU cardiovascular patients. HRV signals were obtained measuring R-R time intervals. A novel method, named return map, is then developed that reveals useful information from the HRV time series. This study also proposed several features that can be extracted from the return map, including the angle between two vectors, the area of triangles formed by successive points, shortest distance to 45° line and their various combinations. Finally, a thresholding technique is proposed to extract the risk period and to predict mortality. The data used to evaluate the proposed algorithm obtained from 80 cardiovascular ICU patients, from the first 48 h of the first ICU stay of 40 males and 40 females. This study showed that the angle feature has on average a sensitivity of 87.5% (with 12 false alarms), the area feature has on average a sensitivity of 89.58% (with 10 false alarms), the shortest distance feature has on average a sensitivity of 85.42% (with 14 false alarms) and, finally, the combined feature has on average a sensitivity of 92.71% (with seven false alarms). The results showed that the last half an hour before the patient's death is very informative for diagnosing the patient's condition and to save his/her life. These results confirm that it is possible to predict mortality based on the features introduced in this paper, relying on the variations of the HRV dynamic characteristics.

Change in Leukocyte Telomere Length Predicts Mortality in Patients with Stable Coronary Heart Disease from the Heart and Soul Study.

PubMed

Goglin, Sarah E; Farzaneh-Far, Ramin; Epel, Elissa S; Lin, Jue; Blackburn, Elizabeth H; Whooley, Mary A

2016-01-01

Short telomere length independently predicts mortality in patients with coronary heart disease. Whether 5-year change in telomere length predicts subsequent mortality in patients with coronary heart disease has not been evaluated. In a prospective cohort study of 608 individuals with stable coronary artery disease, we measured leukocyte telomere length at baseline and after five years of follow-up. We divided the sample into tertiles of telomere change: shortened, maintained or lengthened. We used Cox survival models to evaluate 5-year change in telomere length as a predictor of mortality. During an average of 4.2 years follow-up, there were 149 deaths. Change in telomere length was inversely predictive of all-cause mortality. Using the continuous variable of telomere length change, each standard deviation (325 base pair) greater increase in telomere length was associated with a 24% reduction in mortality (HR 0.76, 95% CI 0.61-0.94; p = 0.01), adjusted for age, sex, waist to hip ratio, exercise capacity, LV ejection fraction, serum creatinine, and year 5 telomere length. Mortality occurred in 39% (79/203) of patients who experienced telomere shortening, 22% (45/203) of patients whose telomere length was maintained, and 12% (25/202) of patients who experienced telomere lengthening (p<0.001). As compared with patients whose telomere length was maintained, those who experienced telomere lengthening were 56% less likely to die (HR 0.44, 95% CI, 0.23-0.87). In patients with coronary heart disease, an increase in leukocyte telomere length over 5 years is associated with decreased mortality.

The derivation and validation of a simple model for predicting in-hospital mortality of acutely admitted patients to internal medicine wards.

PubMed

Sakhnini, Ali; Saliba, Walid; Schwartz, Naama; Bisharat, Naiel

2017-06-01

Limited information is available about clinical predictors of in-hospital mortality in acute unselected medical admissions. Such information could assist medical decision-making.To develop a clinical model for predicting in-hospital mortality in unselected acute medical admissions and to test the impact of secondary conditions on hospital mortality.This is an analysis of the medical records of patients admitted to internal medicine wards at one university-affiliated hospital. Data obtained from the years 2013 to 2014 were used as a derivation dataset for creating a prediction model, while data from 2015 was used as a validation dataset to test the performance of the model. For each admission, a set of clinical and epidemiological variables was obtained. The main diagnosis at hospitalization was recorded, and all additional or secondary conditions that coexisted at hospital admission or that developed during hospital stay were considered secondary conditions.The derivation and validation datasets included 7268 and 7843 patients, respectively. The in-hospital mortality rate averaged 7.2%. The following variables entered the final model; age, body mass index, mean arterial pressure on admission, prior admission within 3 months, background morbidity of heart failure and active malignancy, and chronic use of statins and antiplatelet agents. The c-statistic (ROC-AUC) of the prediction model was 80.5% without adjustment for main or secondary conditions, 84.5%, with adjustment for the main diagnosis, and 89.5% with adjustment for the main diagnosis and secondary conditions. The accuracy of the predictive model reached 81% on the validation dataset.A prediction model based on clinical data with adjustment for secondary conditions exhibited a high degree of prediction accuracy. We provide a proof of concept that there is an added value for incorporating secondary conditions while predicting probabilities of in-hospital mortality. Further improvement of the model performance and validation in other cohorts are needed to aid hospitalists in predicting health outcomes.

[Evaluation of the capacity of the APR-DRG classification system to predict hospital mortality].

PubMed

De Marco, Maria Francesca; Lorenzoni, Luca; Addari, Piero; Nante, Nicola

2002-01-01

Inpatient mortality has increasingly been used as an hospital outcome measure. Comparing mortality rates across hospitals requires adjustment for patient risks before making inferences about quality of care based on patient outcomes. Therefore it is essential to dispose of well performing severity measures. The aim of this study is to evaluate the ability of the All Patient Refined DRG system to predict inpatient mortality for congestive heart failure, myocardial infarction, pneumonia and ischemic stroke. Administrative records were used in this analysis. We used two statistics methods to assess the ability of the APR-DRG to predict mortality: the area under the receiver operating characteristics curve (referred to as the c-statistic) and the Hosmer-Lemeshow test. The database for the study included 19,212 discharges for stroke, pneumonia, myocardial infarction and congestive heart failure from fifteen hospital participating in the Italian APR-DRG Project. A multivariate analysis was performed to predict mortality for each condition in study using age, sex and APR-DRG risk mortality subclass as independent variables. Inpatient mortality rate ranges from 9.7% (pneumonia) to 16.7% (stroke). Model discrimination, calculated using the c-statistic, was 0.91 for myocardial infarction, 0.68 for stroke, 0.78 for pneumonia and 0.71 for congestive heart failure. The model calibration assessed using the Hosmer-Leme-show test was quite good. The performance of the APR-DRG scheme when used on Italian hospital activity records is similar to that reported in literature and it seems to improve by adding age and sex to the model. The APR-DRG system does not completely capture the effects of these variables. In some cases, the better performance might be due to the inclusion of specific complications in the risk-of-mortality subclass assignment.

Predictors of in-hospital mortality amongst octogenarians undergoing emergency general surgery: a retrospective cohort study.

PubMed

Wilson, Iain; Paul Barrett, Michael; Sinha, Ashish; Chan, Shirley

2014-11-01

Elderly patients are often judged to be fit for emergency surgery based on age alone. This study identified risk factors predictive of in-hospital mortality amongst octogenarians undergoing emergency general surgery. A retrospective review of octogenarians undergoing emergency general surgery over 3 years was performed. Parametric survival analysis using Cox multivariate regression model was used to identify risk factors predictive of in-hospital mortality. Hazard ratios (HR) and corresponding 95% confidence interval were calculated. Seventy-three patients with a median age of 84 years were identified. Twenty-eight (38%) patients died post-operatively. Multivariate analysis identified ASA grade (ASA 5 HR 23.4 95% CI 2.38-230, p = 0.007) and chronic obstructive pulmonary disease (COPD) (HR 3.35 95% CI 1.15-9.69, p = 0.026) to be the only significant predictors of in-hospital mortality. Identification of high risk surgical patients should be based on physiological fitness for surgery rather than chronological age. Crown Copyright © 2014. Published by Elsevier Ltd. All rights reserved.

Comparing observed and predicted mortality among ICUs using different prognostic systems: why do performance assessments differ?

PubMed

Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

2015-02-01

To compare ICU performance using standardized mortality ratios generated by the Acute Physiology and Chronic Health Evaluation IVa and a National Quality Forum-endorsed methodology and examine potential reasons for model-based standardized mortality ratio differences. Retrospective analysis of day 1 hospital mortality predictions at the ICU level using Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models on the same patient cohort. Forty-seven ICUs at 36 U.S. hospitals from January 2008 to May 2013. Eighty-nine thousand three hundred fifty-three consecutive unselected ICU admissions. None. We assessed standardized mortality ratios for each ICU using data for patients eligible for Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum predictions in order to compare unit-level model performance, differences in ICU rankings, and how case-mix adjustment might explain standardized mortality ratio differences. Hospital mortality was 11.5%. Overall standardized mortality ratio was 0.89 using Acute Physiology and Chronic Health Evaluation IVa and 1.07 using National Quality Forum, the latter having a widely dispersed and multimodal standardized mortality ratio distribution. Model exclusion criteria eliminated mortality predictions for 10.6% of patients for Acute Physiology and Chronic Health Evaluation IVa and 27.9% for National Quality Forum. The two models agreed on the significance and direction of standardized mortality ratio only 45% of the time. Four ICUs had standardized mortality ratios significantly less than 1.0 using Acute Physiology and Chronic Health Evaluation IVa, but significantly greater than 1.0 using National Quality Forum. Two ICUs had standardized mortality ratios exceeding 1.75 using National Quality Forum, but nonsignificant performance using Acute Physiology and Chronic Health Evaluation IVa. Stratification by patient and institutional characteristics indicated that units caring for more severely ill patients and those with a higher percentage of patients on mechanical ventilation had the most discordant standardized mortality ratios between the two predictive models. Acute Physiology and Chronic Health Evaluation IVa and National Quality Forum models yield different ICU performance assessments due to differences in case-mix adjustment. Given the growing role of outcomes in driving prospective payment patient referral and public reporting, performance should be assessed by models with fewer exclusions, superior accuracy, and better case-mix adjustment.

Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

PubMed

Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

2018-05-01

Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

Use of admission serum lactate and sodium levels to predict mortality in necrotizing soft-tissue infections.

PubMed

Yaghoubian, Arezou; de Virgilio, Christian; Dauphine, Christine; Lewis, Roger J; Lin, Matthew

2007-09-01

Simple admission laboratory values can be used to classify patients with necrotizing soft-tissue infection (NSTI) into high and low mortality risk groups. Chart review. Public teaching hospital. All patients with NSTI from 1997 through 2006. Variables analyzed included medical history, admission vital signs, laboratory values, and microbiologic findings. Data analyses included univariate and classification and regression tree analyses. Mortality. One hundred twenty-four patients were identified with NSTI. The overall mortality rate was 21 of 124 (17%). On univariate analysis, factors associated with mortality included a history of cancer (P = .03), intravenous drug abuse (P < .001), low systolic blood pressure on admission (P = .03), base deficit (P = .009), and elevated white blood cell count (P = .06). On exploratory classification and regression tree analysis, admission serum lactate and sodium levels were predictors of mortality, with a sensitivity of 100%, specificity of 28%, positive predictive value of 23%, and negative predictive value of 100%. A serum lactate level greater than or equal to 54.1 mg/dL (6 mmol/L) alone was associated with a 32% mortality, whereas a serum sodium level greater than or equal to 135 mEq/L combined with a lactate level less than 54.1 mg/dL was associated with a mortality of 0%. Mortality for NSTIs remains high. A simple model, using admission serum lactate and serum sodium levels, may help identify patients at greatest risk for death.

Comparative Longterm Mortality Trends in Cancer vs. Ischemic Heart Disease in Puerto Rico.

PubMed

Torres, David; Pericchi, Luis R; Mattei, Hernando; Zevallos, Juan C

2017-06-01

Although contemporary mortality data are important for health assessment and planning purposes, their availability lag several years. Statistical projection techniques can be employed to obtain current estimates. This study aimed to assess annual trends of mortality in Puerto Rico due to cancer and Ischemic Heart Disease (IHD), and to predict shorterm and longterm cancer and IHD mortality figures. Age-adjusted mortality per 100,000 population projections with a 50% interval probability were calculated utilizing a Bayesian statistical approach of Age-Period-Cohort dynamic model. Multiple cause-of-death annual files for years 1994-2010 for Puerto Rico were used to calculate shortterm (2011-2012) predictions. Longterm (2013-2022) predictions were based on quinquennial data. We also calculated gender differences in rates (men-women) for each study period. Mortality rates for women were similar for cancer and IHD in the 1994-1998 period, but changed substantially in the projected 2018-2022 period. Cancer mortality rates declined gradually overtime, and the gender difference remained constant throughout the historical and projected trends. A consistent declining trend for IHD historical annual mortality rate was observed for both genders, with a substantial changepoint around 2004-2005 for men. The initial gender difference of 33% (80/100,00 vs. 60/100,000) in mortality rates observed between cancer and IHD in the 1994-1998 period increased to 300% (60/100,000 vs. 20/100,000) for the 2018-2022 period. The APC projection model accurately projects shortterm and longterm mortality trends for cancer and IHD in this population: The steady historical and projected cancer mortality rates contrasts with the substantial decline in IHD mortality rates, especially in men.

Differences in open versus laparoscopic gastric bypass mortality risk using the Obesity Surgery Mortality Risk Score (OS-MRS).

PubMed

Brolin, Robert E; Cody, Ronald P; Marcella, Stephen W

2015-01-01

The Obesity Surgery Mortality Risk Score (OS-MRS) was developed to ascertain preoperative mortality risk of patients having bariatric surgery. To date there has not been a comparison between open and laparoscopic operations using the OS-MRS. To determine whether there are differences in mortality risk between open and laparoscopic Roux-en-Y Gastric Bypass (RYGB) using the OS-MRS. Three university-affiliated hospitals. The 90-day mortality of 2467 consecutive patients who had primary open (1574) or laparoscopic (893) RYGB performed by one surgeon was determined. Univariate and multivariate analysis using 5 OS-MRS risk factors including body mass index (BMI) gender, age>45, presence of hypertension and preoperative deep vein thrombosis (DVT) risk was performed in each group. Each patient was placed in 1 of 3 OS-MRS risk classes based on the number of risks: A (0-1), B (2-3), and C (4-5). Preoperative BMI and DVT risk factors were significantly greater in the open group (OG). Preoperative age was significantly greater in the laparoscopic group (LG). There were significantly more class B and C patients in LG. Ninety-day mortality rates for OG and LG patients were 1.0% and .9%, respectively. Pulmonary embolism was the most common cause of death. All deaths in LG occurred during first 4 years of that experience. Mortality rate by class was A = .1%; B = 1.5%; C = 2.3%. The difference in mortality between class B and C patients was not significant. Univariate analysis in the OG indicated that BMI, age, gender, and DVT risk were significant predictors of mortality. In the LG only BMI and DVT were significant predictors of death. Presence of hypertension was not a significant predictor in either group. Multivariate analysis excluding hypertension found that age was predictive of mortality in the OG while BMI (P = .057) and gender (P = .065) approached statistical significance. Conversely, only BMI was predictive of mortality in the LG with age approaching significance (P = .058). In multivariate analysis DVT risk was not predictive of mortality in either group. There are significant differences in the predictive value of the OS-MRS between open and laparoscopic RYGB. Although laparoscopic patients were significantly older versus the open patients, age was not predictive of mortality after laparoscopic RYGB. BMI trended toward increased mortality risk in both groups. Changes in technique and protocol likely contributed toward no mortality during the last 6 years of our laparoscopic experience. Copyright © 2015 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

An experimental demonstration of stem damage as a predictor of fire-caused mortality for ponderosa pine

USGS Publications Warehouse

van Mantgem, P.; Schwartz, M.

2004-01-01

We subjected 159 small ponderosa pine (Pinus ponderosa Dougl. ex P. & C. Laws.) to treatments designed to test the relative importance of stem damage as a predictor of postfire mortality. The treatments consisted of a group with the basal bark artificially thinned, a second group with fuels removed from the base of the stem, and an untreated control. Following prescribed burning, crown scorch severity was equivalent among the groups. Postfire mortality was significantly less frequent in the fuels removal group than in the bark removal and control groups. No model of mortality for the fuels removal group was possible, because dead trees constituted <4% of subject trees. Mortality in the bark removal group was best predicted by crown scorch and stem scorch severity, whereas death in the control group was predicted by crown scorch severity and bark thickness. The relative lack of mortality in the fuels removal group and the increased sensitivity to stem damage in the bark removal group suggest that stem damage is a critical determinant of postfire mortality for small ponderosa pine.

Predictive power of the grace score in population with diabetes.

PubMed

Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

2017-12-01

Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Red blood cell distribution width as a risk factor for inhospital mortality in obstetric patients admitted to an intensive care unit: a single centre retrospective cohort study.

PubMed

Chu, Yufeng; Yuan, Zhongshang; Meng, Mei; Zhou, Haiyan; Wang, Chunting; Yang, Gong; Ren, Hongsheng

2017-06-21

Red blood cell distribution width (RDW) has been shown to predict mortality in critically ill patients. To our knowledge, whether or not RDW is associated with clinical outcomes of obstetric patients requiring critical care has not been evaluated. This was a single centre, retrospective, observational study of obstetric patients admitted to the intensive care unit (ICU). Patients were excluded from the analysis if they had known haematological diseases or recently underwent blood transfusion. Patients who died or were discharged from the ICU within 24 hours of admission were also excluded. Patient clinical characteristics at ICU admission were retrieved from the medical charts. Multiple logistic regression was used to estimate OR and 95% CI for inhospital mortality associated with RDW. The receiver operating characteristic curve was used to examine the performance of RDW, alone or in combination with the Acute Physiology and Chronic Health Evaluation II score (APACHE II), in predicting inhospital mortality. A total of 376 patients were included in the study. The hospital mortality rate was 5.32%. A significant association was found between baseline RDW levels and hospital mortality (OR per per cent increase in RDW, 1.31; 95% CI 1.15 to 1.49). Further adjustment for haematocrit and other potential confounders did not appreciably alter the result (p<0.001). The area under the curve (AUC) for inhospital mortality based on RDW was similar to that based on the APACHE II score (0.752 vs 0.766). A combination of these two factors resulted in substantial improvement in risk prediction, with an AUC value of 0.872 (p<0.001). The study suggests that RDW is an independent predictor for inhospital mortality among ICU admitted obstetric patients. Combining RDW and APACHE II score could significantly improve inhospital prognostic prediction among these critically ill obstetric patients. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Mortality Prediction Model of Septic Shock Patients Based on Routinely Recorded Data

PubMed Central

Carrara, Marta; Baselli, Giuseppe; Ferrario, Manuela

2015-01-01

We studied the problem of mortality prediction in two datasets, the first composed of 23 septic shock patients and the second composed of 73 septic subjects selected from the public database MIMIC-II. For each patient we derived hemodynamic variables, laboratory results, and clinical information of the first 48 hours after shock onset and we performed univariate and multivariate analyses to predict mortality in the following 7 days. The results show interesting features that individually identify significant differences between survivors and nonsurvivors and features which gain importance only when considered together with the others in a multivariate regression model. This preliminary study on two small septic shock populations represents a novel contribution towards new personalized models for an integration of multiparameter patient information to improve critical care management of shock patients. PMID:26557154

Derivation and Internal Validation of a Clinical Prediction Tool for 30-Day Mortality in Lower Gastrointestinal Bleeding.

PubMed

Sengupta, Neil; Tapper, Elliot B

2017-05-01

There are limited data to predict which patients with lower gastrointestinal bleeding are at risk for adverse outcomes. We aimed to develop a clinical tool based on admission variables to predict 30-day mortality in lower gastrointestinal bleeding. We used a validated machine learning algorithm to identify adult patients hospitalized with lower gastrointestinal bleeding at an academic medical center between 2008 and 2015. The cohort was split randomly into derivation and validation cohorts. In the derivation cohort, we used multiple logistic regression on all candidate admission variables to create a prediction model for 30-day mortality, using area under the receiving operator characteristic curve and misclassification rate to estimate prediction accuracy. Regression coefficients were used to derive an integer score, and mortality risk associated with point totals was assessed. In the derivation cohort (n = 4044), 8 variables were most associated with 30-day mortality: age, dementia, metastatic cancer, chronic kidney disease, chronic pulmonary disease, anticoagulant use, admission hematocrit, and albumin. The model yielded a misclassification rate of 0.06 and area under the curve of 0.81. The integer score ranged from -10 to 26 in the derivation cohort, with a misclassification rate of 0.11 and area under the curve of 0.74. In the validation cohort (n = 2060), the score had an area under the curve of 0.72 with a misclassification rate of 0.12. After dividing the score into 4 quartiles of risk, 30-day mortality in the derivation and validation sets was 3.6% and 4.4% in quartile 1, 4.9% and 7.3% in quartile 2, 9.9% and 9.1% in quartile 3, and 24% and 26% in quartile 4, respectively. A clinical tool can be used to predict 30-day mortality in patients hospitalized with lower gastrointestinal bleeding. Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting risk of coronary events and all-cause mortality: role of B-type natriuretic peptide above traditional risk factors and coronary artery calcium scoring in the general population: the Heinz Nixdorf Recall Study.

PubMed

Kara, Kaffer; Mahabadi, Amir A; Berg, Marie H; Lehmann, Nils; Möhlenkamp, Stefan; Kälsch, Hagen; Bauer, Marcus; Moebus, Susanne; Dragano, Nico; Jöckel, Karl-Heinz; Neumann, Till; Erbel, Raimund

2014-09-01

Several biomarkers including B-type natriuretic peptide (BNP) have been suggested to improve prediction of coronary events and all-cause mortality. Moreover, coronary artery calcium (CAC) as marker of subclinical atherosclerosis is a strong predictor for cardiovascular mortality and morbidity. We aimed to evaluate the predictive ability of BNP and CAC for all-cause mortality and coronary events above traditional cardiovascular risk factors (TRF) in the general population. We followed 3782 participants of the population-based Heinz Nixdorf Recall cohort study without coronary artery disease at baseline for 7.3 ± 1.3 years. Associations of BNP and CAC with incident coronary events and all-cause mortality were assessed using Cox regression, Harrell's c, and time-dependent integrated discrimination improvement (IDI(t), increase in explained variance). Subjects with high BNP levels had increased frequency of coronary events and death (coronary events/mortality: 14.1/28.2% for BNP ≥100 pg/ml vs. 2.7/5.5% for BNP < 100 pg/ml, respectively). Subjects with a BNP ≥100 pg/ml had increased incidence of hard endpoints sustaining adjustment for CAC and TRF (for coronary events: hazard ratio (HR) (95% confidence interval (CI)) 3.41(1.78-6.53); for all-cause mortality: HR 3.35(2.15-5.23)). Adding BNP to TRF and CAC increased measures of predictive ability: coronary events (Harrell's c, for coronary events, 0.775-0.784, p = 0.09; for all-cause mortality 0.733-0.740, p = 0.04; and IDI(t) (95% CI), for coronary events: 2.79% (0.33-5.65%) and for all-cause mortality 1.78% (0.73-3.10%). Elevated levels of BNP are associated with excess incident coronary events and all-cause mortality rates, with BNP and CAC significantly and complementary improving prediction of risk in the general population above TRF. © The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

Cognition and mortality in older people: the Sydney Memory and Ageing Study.

PubMed

Connors, Michael H; Sachdev, Perminder S; Kochan, Nicole A; Xu, Jing; Draper, Brian; Brodaty, Henry

2015-11-01

Both cognitive ability and cognitive decline have been shown to predict mortality in older people. As dementia, a major form of cognitive decline, has an established association with shorter survival, it is unclear the extent to which cognitive ability and cognitive decline predict mortality in the absence of dementia. To determine whether cognitive ability and decline in cognitive ability predict mortality in older individuals without dementia. The Sydney Memory and Ageing Study is an observational population-based cohort study. Participants completed detailed neuropsychological assessments and medical examinations to assess for risk factors such as depression, obesity, hypertension, diabetes, hypercholesterolaemia, smoking and physical activity. Participants were regularly assessed at 2-year intervals over 8 years. A community sample in Sydney, Australia. One thousand and thirty-seven elderly people without dementia. Overall, 236 (22.8%) participants died within 8 years. Both cognitive ability at baseline and decline in cognitive ability over 2 years predicted mortality. Decline in cognitive ability, but not baseline cognitive ability, was a significant predictor of mortality when depression and other medical risk factors were controlled for. These relationships also held when excluding incident cases of dementia. The findings indicate that decline in cognition is a robust predictor of mortality in older people without dementia at a population level. This relationship is not accounted for by co-morbid depression or other established biomedical risk factors. © The Author 2015. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Reducing patient mortality, length of stay and readmissions through machine learning-based sepsis prediction in the emergency department, intensive care unit and hospital floor units

PubMed Central

McCoy, Andrea

2017-01-01

Introduction Sepsis management is a challenge for hospitals nationwide, as severe sepsis carries high mortality rates and costs the US healthcare system billions of dollars each year. It has been shown that early intervention for patients with severe sepsis and septic shock is associated with higher rates of survival. The Cape Regional Medical Center (CRMC) aimed to improve sepsis-related patient outcomes through a revised sepsis management approach. Methods In collaboration with Dascena, CRMC formed a quality improvement team to implement a machine learning-based sepsis prediction algorithm to identify patients with sepsis earlier. Previously, CRMC assessed all patients for sepsis using twice-daily systemic inflammatory response syndrome screenings, but desired improvements. The quality improvement team worked to implement a machine learning-based algorithm, collect and incorporate feedback, and tailor the system to current hospital workflow. Results Relative to the pre-implementation period, the post-implementation period sepsis-related in-hospital mortality rate decreased by 60.24%, sepsis-related hospital length of stay decreased by 9.55% and sepsis-related 30-day readmission rate decreased by 50.14%. Conclusion The machine learning-based sepsis prediction algorithm improved patient outcomes at CRMC. PMID:29450295

Cystatin C-based glomerular filtration rate associates more closely with mortality than creatinine-based or combined glomerular filtration rate equations in unselected patients.

PubMed

Helmersson-Karlqvist, Johanna; Ärnlöv, Johan; Larsson, Anders

2016-10-01

Decreased glomerular filtration rate (GFR) is an important cardiovascular risk factor, but estimated GFR (eGFR) may differ depending on whether it is based on creatinine or cystatin C. A combined creatinine/cystatin C equation has recently been shown to best estimate GFR; however, the benefits of using the combined equation for risk prediction in routine clinical care have been less studied. This study compares mortality risk prediction by eGFR using the combined creatinine/cystatin C equation (CKD-EPI), a sole creatinine equation (CKD-EPI) and a sole cystatin C equation (CAPA), respectively, using assays that are traceable to international calibrators. All patients analysed for both creatinine and cystatin C from the same blood sample tube (n = 13,054) during 2005-2007 in Uppsala University Hospital Laboratory were divided into eGFR risk categories>60, 30-60 and <30 mL/min/1.73 m(2) by each eGFR equation. During follow-up (median 4.6 years), 4398 participants died, of which 1396 deaths were due to cardiovascular causes. Reduced eGFR was significantly associated with death as assessed by all eGFR equations. The net reclassification improvement (NRI) for the combination equation compared with the sole creatinine equation was 0.10 (p < 0.001) for all-cause mortality and 0.08 (p < 0.001) for cardiovascular mortality, indicating improved reclassification. In contrast, NRI for the combination equation, compared with the sole cystatin C equation, was -0.06 (p < 0.001) for all-cause mortality and -0.02 (p = 0.032) for cardiovascular mortality, indicating a worsened reclassification. In routine clinical care, cystatin C-based eGFR was more closely associated with mortality compared with both creatinine-based eGFR and creatinine/cystatin C-based eGFR. © The European Society of Cardiology 2016.

Challenges associated with projecting urbanization-induced heat-related mortality.

PubMed

Hondula, David M; Georgescu, Matei; Balling, Robert C

2014-08-15

Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables. Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983-2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (-95%) to an increase of 339 deaths per year (+359%). Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making. Copyright © 2014 Elsevier B.V. All rights reserved.

Prognostic capability of different liver disease scoring systems for prediction of early mortality after transjugular intrahepatic portosystemic shunt creation.

PubMed

Gaba, Ron C; Couture, Patrick M; Bui, James T; Knuttinen, M Grace; Walzer, Natasha M; Kallwitz, Eric R; Berkes, Jamie L; Cotler, Scott J

2013-03-01

To compare the performance of various liver disease scoring systems in predicting early mortality after transjugular intrahepatic portosystemic shunt (TIPS) creation. In this single-institution retrospective study, eight scoring systems were used to grade liver disease in 211 patients (male-to-female ratio = 131:80; mean age, 54 y) before TIPS creation from 1999-2011. Scoring systems included bilirubin level, Child-Pugh (CP) score, Model for End-Stage Liver Disease (MELD) and Model for End-Stage Liver Disease sodium (MELD-Na) score, Emory score, prognostic index (PI), Acute Physiology and Chronic Health Evaluation (APACHE) 2 score, and Bonn TIPS early mortality (BOTEM) score. Medical record review was used to identify 30-day and 90-day clinical outcomes. The relationship of scoring parameters with mortality outcomes was assessed with multivariate analysis, and the relative ability of systems to predict mortality after TIPS creation was evaluated by comparing area under receiver operating characteristic (AUROC) curves. TIPS were successfully created for variceal hemorrhage (n = 121), ascites (n = 72), hepatic hydrothorax (n = 15), and portal vein thrombosis (n = 3). All scoring systems had a significant association with 30-day and 90-day mortality (P<.050 in each case) on multivariate analysis. Based on 30-day and 90-day AUROC, MELD (0.878, 0.816) and MELD-Na (0.863, 0.823) scores had the best capability to predict early mortality compared with bilirubin (0.786, 0.749), CP (0.822, 0.771), Emory (0.786, 0.681), PI (0.854, 0.760), APACHE 2 (0.836, 0.735), and BOTEM (0.798, 0.698), with statistical superiority over bilirubin, Emory, and BOTEM scores. Several liver disease scoring systems have prognostic value for early mortality after TIPS creation. MELD and MELD-Na scores most effectively predict survival after TIPS creation. Copyright © 2013. Published by Elsevier Inc.

The Surgical Mortality Probability Model: derivation and validation of a simple risk prediction rule for noncardiac surgery.

PubMed

Glance, Laurent G; Lustik, Stewart J; Hannan, Edward L; Osler, Turner M; Mukamel, Dana B; Qian, Feng; Dick, Andrew W

2012-04-01

To develop a 30-day mortality risk index for noncardiac surgery that can be used to communicate risk information to patients and guide clinical management at the "point-of-care," and that can be used by surgeons and hospitals to internally audit their quality of care. Clinicians rely on the Revised Cardiac Risk Index to quantify the risk of cardiac complications in patients undergoing noncardiac surgery. Because mortality from noncardiac causes accounts for many perioperative deaths, there is also a need for a simple bedside risk index to predict 30-day all-cause mortality after noncardiac surgery. Retrospective cohort study of 298,772 patients undergoing noncardiac surgery during 2005 to 2007 using the American College of Surgeons National Surgical Quality Improvement Program database. The 9-point S-MPM (Surgical Mortality Probability Model) 30-day mortality risk index was derived empirically and includes three risk factors: ASA (American Society of Anesthesiologists) physical status, emergency status, and surgery risk class. Patients with ASA physical status I, II, III, IV or V were assigned either 0, 2, 4, 5, or 6 points, respectively; intermediate- or high-risk procedures were assigned 1 or 2 points, respectively; and emergency procedures were assigned 1 point. Patients with risk scores less than 5 had a predicted risk of mortality less than 0.50%, whereas patients with a risk score of 5 to 6 had a risk of mortality between 1.5% and 4.0%. Patients with a risk score greater than 6 had risk of mortality more than 10%. S-MPM exhibited excellent discrimination (C statistic, 0.897) and acceptable calibration (Hosmer-Lemeshow statistic 13.0, P = 0.023) in the validation data set. Thirty-day mortality after noncardiac surgery can be accurately predicted using a simple and accurate risk score based on information readily available at the bedside. This risk index may play a useful role in facilitating shared decision making, developing and implementing risk-reduction strategies, and guiding quality improvement efforts.

Mortality, morbidity and refractoriness prediction in status epilepticus: Comparison of STESS and EMSE scores.

PubMed

Giovannini, Giada; Monti, Giulia; Tondelli, Manuela; Marudi, Andrea; Valzania, Franco; Leitinger, Markus; Trinka, Eugen; Meletti, Stefano

2017-03-01

Status epilepticus (SE) is a neurological emergency, characterized by high short-term morbidity and mortality. We evaluated and compared two scores that have been developed to evaluate status epilepticus prognosis: STESS (Status Epilepticus Severity Score) and EMSE (Epidemiology based Mortality score in Status Epilepticus). A prospective observational study was performed on consecutive patients with SE admitted between September 2013 and August 2015. Demographics, clinical variables, STESS-3 and -4, and EMSE-64 scores were calculated for each patient at baseline. SE drug response, 30-day mortality and morbidity were the outcomes measure. 162 episodes of SE were observed: 69% had a STESS ≥3; 34% had a STESS ≥4; 51% patients had an EMSE ≥64. The 30-days mortality was 31.5%: EMSE-64 showed greater negative predictive value (NPV) (97.5%), positive predictive value (PPV) (59.8%) and accuracy in the prediction of death than STESS-3 and STESS-4 (p<0.001). At 30 days, the clinical condition had deteriorated in 59% of the cases: EMSE-64 showed greater NPV (71.3%), PPV (87.8%) and accuracy than STESS-3 and STESS-4 (p<0.001) in the prediction of this outcome. In 23% of all cases, status epilepticus proved refractory to non-anaesthetic treatment. All three scales showed a high NPV (EMSE-64: 87.3%; STESS-4: 89.4%; STESS-3: 87.5%) but a low PPV (EMSE-64: 40.9%; STESS-4: 52.9%; STESS-3: 32%) for the prediction of refractoriness to first and second line drugs. This means that accuracy for the prediction of refractoriness was equally poor for all scales. EMSE-64 appears superior to STESS-3 and STESS-4 in the prediction of 30-days mortality and morbidity. All scales showed poor accuracy in the prediction of response to first and second line antiepileptic drugs. At present, there are no reliable scores capable of predicting treatment responsiveness. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Reducing mortality risk by targeting specific air pollution sources: Suva, Fiji.

PubMed

Isley, C F; Nelson, P F; Taylor, M P; Stelcer, E; Atanacio, A J; Cohen, D D; Mani, F S; Maata, M

2018-01-15

Health implications of air pollution vary dependent upon pollutant sources. This work determines the value, in terms of reduced mortality, of reducing ambient particulate matter (PM 2.5 : effective aerodynamic diameter 2.5μm or less) concentration due to different emission sources. Suva, a Pacific Island city with substantial input from combustion sources, is used as a case-study. Elemental concentration was determined, by ion beam analysis, for PM 2.5 samples from Suva, spanning one year. Sources of PM 2.5 have been quantified by positive matrix factorisation. A review of recent literature has been carried out to delineate the mortality risk associated with these sources. Risk factors have then been applied for Suva, to calculate the possible mortality reduction that may be achieved through reduction in pollutant levels. Higher risk ratios for black carbon and sulphur resulted in mortality predictions for PM 2.5 from fossil fuel combustion, road vehicle emissions and waste burning that surpass predictions for these sources based on health risk of PM 2.5 mass alone. Predicted mortality for Suva from fossil fuel smoke exceeds the national toll from road accidents in Fiji. The greatest benefit for Suva, in terms of reduced mortality, is likely to be accomplished by reducing emissions from fossil fuel combustion (diesel), vehicles and waste burning. Copyright © 2017. Published by Elsevier B.V.

What is the best predictor of mortality in perforated peptic ulcer disease? A population-based, multivariable regression analysis including three clinical scoring systems.

PubMed

Thorsen, Kenneth; Søreide, Jon Arne; Søreide, Kjetil

2014-07-01

Mortality rates in perforated peptic ulcer (PPU) have remained unchanged. The aim of this study was to compare known clinical factors and three scoring systems (American Society of Anesthesiologists (ASA), Boey and peptic ulcer perforation (PULP)) in the ability to predict mortality in PPU. This is a consecutive, observational cohort study of patients surgically treated for perforated peptic ulcer over a decade (January 2001 through December 2010). Primary outcome was 30-day mortality. A total of 172 patients were included, of whom 28 (16 %) died within 30 days. Among the factors associated with mortality, the PULP score had an odds ratio (OR) of 18.6 and the ASA score had an OR of 11.6, both with an area under the curve (AUC) of 0.79. The Boey score had an OR of 5.0 and an AUC of 0.75. Hypoalbuminaemia alone (≤37 g/l) achieved an OR of 8.7 and an AUC of 0.78. In multivariable regression, mortality was best predicted by a combination of increasing age, presence of active cancer and delay from admission to surgery of >24 h, together with hypoalbuminaemia, hyperbilirubinaemia and increased creatinine values, for a model AUC of 0.89. Six clinical factors predicted 30-day mortality better than available risk scores. Hypoalbuminaemia was the strongest single predictor of mortality and may be included for improved risk estimation.

Longitudinal modelling of theory-based depressive vulnerabilities, depression trajectories and poor outcomes post-ACS.

PubMed

Keegan, Conor; Conroy, Ronán; Doyle, Frank

2016-02-01

Depression is associated with increased mortality in patients with acute coronary syndrome (ACS). However, little is known about the theoretical causes of depression trajectories post-ACS, and whether these trajectories predict subsequent morbidity/mortality. We tested a longitudinal model of depressive vulnerabilities, trajectories and mortality. A prospective observational study of 374 ACS patients was conducted. Participants completed questionnaires on theoretical vulnerabilities (interpersonal life events, reinforcing events, cognitive distortions, and Type D personality) during hospitalisation and depression at baseline and 3, 6 and 12 months post-hospitalisation. Latent class analysis determined trajectories of depression. Path analysis was used to test relationships among vulnerabilities, depression trajectories and outcomes (combination of 1-year morbidity and 7-year mortality). Vulnerabilities independently predicted persistent and subthreshold depression trajectory categories, with effect sizes significantly highest for persistent depression. Both subthreshold and persistent depression trajectories were significant predictors of morbidity/mortality (e.g. persistent depression OR=2.4, 95% CI=1.8-3.1, relative to never depressed). Causality cannot be inferred from these associations. We had no measures of history of depression or treatments, which may affect associations. Theoretical vulnerabilities predicted depression trajectories, which in turn predicted increased morbidity/mortality, demonstrating for the first time a potential longitudinal chain of events post-ACS. This longitudinal model has important practical implications as clinicians can use vulnerability measures to identify those at most risk of poor outcomes. Copyright © 2015. Published by Elsevier B.V.

Psychological Language on Twitter Predicts County-Level Heart Disease Mortality

PubMed Central

Eichstaedt, Johannes C.; Schwartz, Hansen Andrew; Kern, Margaret L.; Park, Gregory; Labarthe, Darwin R.; Merchant, Raina M.; Jha, Sneha; Agrawal, Megha; Dziurzynski, Lukasz A.; Sap, Maarten; Weeg, Christopher; Larson, Emily E.; Ungar, Lyle H.; Seligman, Martin E. P.

2015-01-01

Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions—especially anger—emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level. PMID:25605707

Psychological language on Twitter predicts county-level heart disease mortality.

PubMed

Eichstaedt, Johannes C; Schwartz, Hansen Andrew; Kern, Margaret L; Park, Gregory; Labarthe, Darwin R; Merchant, Raina M; Jha, Sneha; Agrawal, Megha; Dziurzynski, Lukasz A; Sap, Maarten; Weeg, Christopher; Larson, Emily E; Ungar, Lyle H; Seligman, Martin E P

2015-02-01

Hostility and chronic stress are known risk factors for heart disease, but they are costly to assess on a large scale. We used language expressed on Twitter to characterize community-level psychological correlates of age-adjusted mortality from atherosclerotic heart disease (AHD). Language patterns reflecting negative social relationships, disengagement, and negative emotions-especially anger-emerged as risk factors; positive emotions and psychological engagement emerged as protective factors. Most correlations remained significant after controlling for income and education. A cross-sectional regression model based only on Twitter language predicted AHD mortality significantly better than did a model that combined 10 common demographic, socioeconomic, and health risk factors, including smoking, diabetes, hypertension, and obesity. Capturing community psychological characteristics through social media is feasible, and these characteristics are strong markers of cardiovascular mortality at the community level. © The Author(s) 2014.

A comparison of pre ICU admission SIRS, EWS and q SOFA scores for predicting mortality and length of stay in ICU.

PubMed

Siddiqui, Shahla; Chua, Maureen; Kumaresh, Venkatesan; Choo, Robin

2017-10-01

The 2015 sepsis definitions suggest using the quick SOFA score for risk stratification of sepsis patients among other changes in sepsis definition. Our aim was to validate the q sofa score for diagnosing sepsis and comparing it to traditional scores of pre ICU admission sepsis outcome prediction such as EWS and SIRS in our setting in order to predict mortality and length of stay. This was a retrospective cohort study. We retrospectively calculated the q sofa, SIRS and EWS scores of all ICU patients admitted with the diagnosis of sepsis at our center in 2015. This was analysed using STATA 12. Logistic regression and ROC curves were used for analysis in addition to descriptive analysis. 58 patients were included in the study. Based on our one year results we have shown that although q SOFA is more sensitive in predicting LOS in ICU of sepsis patients, the EWS score is more sensitive and specific in predicting mortality in the ICU of such patients when compared to q SOFA and SIRS scores. In conclusion, we find that in our setting, EWS is better than SIRS and q SOFA for predicting mortality and perhaps length of stay as well. The q Sofa score remains validated for diagnosis of sepsis. Copyright © 2017 Elsevier Inc. All rights reserved.

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

PubMed

Jafari, Seyed Ali; Jahandideh, Sepideh; Jahandideh, Mina; Asadabadi, Ebrahim Barzegari

2015-01-01

Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of road traffic death rate will be helpful in its management. Based on this fact, we used an artificial neural network model optimised through Genetic algorithm to predict mortality. In this study, a five-fold cross-validation procedure on a data set containing total of 178 countries was used to verify the performance of models. The best-fit model was selected according to the root mean square errors (RMSE). Genetic algorithm, as a powerful model which has not been introduced in prediction of mortality to this extent in previous studies, showed high performance. The lowest RMSE obtained was 0.0808. Such satisfactory results could be attributed to the use of Genetic algorithm as a powerful optimiser which selects the best input feature set to be fed into the neural networks. Seven factors have been known as the most effective factors on the road traffic mortality rate by high accuracy. The gained results displayed that our model is very promising and may play a useful role in developing a better method for assessing the influence of road traffic mortality risk factors.

NT-proBNP Predicts All-Cause Mortality in a Population of Insurance Applicants, Follow-up Analysis and Further Observations.

PubMed

Fulks, Michael; Kaufman, Valerie; Clark, Michael; Stout, Robert L

2017-01-01

- Further refine the independent value of NT-proBNP, accounting for the impact of other test results, in predicting all-cause mortality for individual life insurance applicants with and without heart disease. - Using the Social Security Death Master File and multivariate analysis, relative mortality was determined for 245,322 life insurance applicants ages 50 to 89 tested for NT-proBNP (almost all based on age and policy amount) along with other laboratory tests and measurement of blood pressure and BMI. - NT-proBNP values ≤75 pg/mL included the majority of applicants denying heart disease and had the lowest risk, while values >500 pg/mL for females and >300 pg/mL for males had very high relative risk. Those admitting to heart disease had a higher mortality risk for each band of NT-proBNP relative to those denying heart disease but had a similar and equally predictive risk curve. - NT-proBNP is a strong independent predictor of all-cause mortality in the absence or presence of known heart disease but the range of values associated with increased risk varies by sex.

One-hour glucose value as a long-term predictor of cardiovascular morbidity and mortality: the Malmö Preventive Project.

PubMed

Nielsen, Mette L; Pareek, Manan; Leósdóttir, Margrét; Eriksson, Karl-Fredrik; Nilsson, Peter M; Olsen, Michael H

2018-03-01

To examine the predictive capability of a 1-h vs 2-h postload glucose value for cardiovascular morbidity and mortality. Prospective, population-based cohort study (Malmö Preventive Project) with subject inclusion 1974-1992. 4934 men without known diabetes and cardiovascular disease, who had blood glucose (BG) measured at 0, 20, 40, 60, 90 and 120 min during an OGTT (30 g glucose per m 2 body surface area), were followed for 27 years. Data on cardiovascular events and death were obtained through national and local registries. Predictive capabilities of fasting BG (FBG) and glucose values obtained during OGTT alone and added to a clinical prediction model comprising traditional cardiovascular risk factors were assessed using Harrell's concordance index (C-index) and integrated discrimination improvement (IDI). Median age was 48 (25th-75th percentile: 48-49) years and mean FBG 4.6 ± 0.6 mmol/L. FBG and 2-h postload BG did not independently predict cardiovascular events or death. Conversely, 1-h postload BG predicted cardiovascular morbidity and mortality and remained an independent predictor of cardiovascular death (HR: 1.09, 95% CI: 1.01-1.17, P  = 0.02) and all-cause mortality (HR: 1.10, 95% CI: 1.05-1.16, P  < 0.0001) after adjusting for various traditional risk factors. Clinical risk factors with added 1-h postload BG performed better than clinical risk factors alone, in predicting cardiovascular death (likelihood-ratio test, P  = 0.02) and all-cause mortality (likelihood-ratio test, P  = 0.0001; significant IDI, P  = 0.0003). Among men without known diabetes, addition of 1-h BG, but not FBG or 2-h BG, to clinical risk factors provided incremental prognostic yield for prediction of cardiovascular death and all-cause mortality. © 2018 European Society of Endocrinology.

Reaction Time and Established Risk Factors for Total and Cardiovascular Disease Mortality: Comparison of Effect Estimates in the Follow-Up of a Large, UK-Wide, General-Population Based Survey

ERIC Educational Resources Information Center

Roberts, Beverly A.; Der, Geoff; Deary, Ian J.; Batty, G. David

2009-01-01

Higher cognitive function is associated with faster choice reaction time (CRT), and both are associated with a reduced risk of mortality from all-causes and cardiovascular disease (CVD). However, comparison of the predictive capacity of CRT, an emerging risk factor, with that for established "classic" risk factors for mortality, such as…

Risk-adjusted performance evaluation in three academic thoracic surgery units using the Eurolung risk models.

PubMed

Pompili, Cecilia; Shargall, Yaron; Decaluwe, Herbert; Moons, Johnny; Chari, Madhu; Brunelli, Alessandro

2018-01-03

The objective of this study was to evaluate the performance of 3 thoracic surgery centres using the Eurolung risk models for morbidity and mortality. This was a retrospective analysis performed on data collected from 3 academic centres (2014-2016). Seven hundred and twenty-one patients in Centre 1, 857 patients in Centre 2 and 433 patients in Centre 3 who underwent anatomical lung resections were analysed. The Eurolung1 and Eurolung2 models were used to predict risk-adjusted cardiopulmonary morbidity and 30-day mortality rates. Observed and risk-adjusted outcomes were compared within each centre. The observed morbidity of Centre 1 was in line with the predicted morbidity (observed 21.1% vs predicted 22.7%, P = 0.31). Centre 2 performed better than expected (observed morbidity 20.2% vs predicted 26.7%, P < 0.001), whereas the observed morbidity of Centre 3 was higher than the predicted morbidity (observed 41.1% vs predicted 24.3%, P < 0.001). Centre 1 had higher observed mortality when compared with the predicted mortality (3.6% vs 2.1%, P = 0.005), whereas Centre 2 had an observed mortality rate significantly lower than the predicted mortality rate (1.2% vs 2.5%, P = 0.013). Centre 3 had an observed mortality rate in line with the predicted mortality rate (observed 1.4% vs predicted 2.4%, P = 0.17). The observed mortality rates in the patients with major complications were 30.8% in Centre 1 (versus predicted mortality rate 3.8%, P < 0.001), 8.2% in Centre 2 (versus predicted mortality rate 4.1%, P = 0.030) and 9.0% in Centre 3 (versus predicted mortality rate 3.5%, P = 0.014). The Eurolung models were successfully used as risk-adjusting instruments to internally audit the outcomes of 3 different centres, showing their applicability for future quality improvement initiatives. © The Author(s) 2018. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.

A Prognostic Model for One-year Mortality in Patients Requiring Prolonged Mechanical Ventilation

PubMed Central

Carson, Shannon S.; Garrett, Joanne; Hanson, Laura C.; Lanier, Joyce; Govert, Joe; Brake, Mary C.; Landucci, Dante L.; Cox, Christopher E.; Carey, Timothy S.

2009-01-01

Objective A measure that identifies patients who are at high risk of mortality after prolonged ventilation will help physicians communicate prognosis to patients or surrogate decision-makers. Our objective was to develop and validate a prognostic model for 1-year mortality in patients ventilated for 21 days or more. Design Prospective cohort study. Setting University-based tertiary care hospital Patients 300 consecutive medical, surgical, and trauma patients requiring mechanical ventilation for at least 21 days were prospectively enrolled. Measurements and Main Results Predictive variables were measured on day 21 of ventilation for the first 200 patients and entered into logistic regression models with 1-year and 3-month mortality as outcomes. Final models were validated using data from 100 subsequent patients. One-year mortality was 51% in the development set and 58% in the validation set. Independent predictors of mortality included requirement for vasopressors, hemodialysis, platelet count ≤150 ×109/L, and age ≥50. Areas under the ROC curve for the development model and validation model were 0.82 (se 0.03) and 0.82 (se 0.05) respectively. The model had sensitivity of 0.42 (se 0.12) and specificity of 0.99 (se 0.01) for identifying patients who had ≥90% risk of death at 1 year. Observed mortality was highly consistent with both 3- and 12-month predicted mortality. These four predictive variables can be used in a simple prognostic score that clearly identifies low risk patients (no risk factors, 15% mortality) and high risk patients (3 or 4 risk factors, 97% mortality). Conclusions Simple clinical variables measured on day 21 of mechanical ventilation can identify patients at highest and lowest risk of death from prolonged ventilation. PMID:18552692

PREDICTIVE MODELING OF LIGHT-INDUCED MORTALITY OF ENTEROCOCCI FAECALIS IN RECREATIONAL WATERS

EPA Science Inventory

One approach to predictive modeling of biological contamination of recreational waters involves the application of process-based approaches that consider microbial sources, hydrodynamic transport, and microbial fate. This presentation focuses on one important fate process, light-...

Medium-term survival after primary angioplasty for myocardial infarction complicated by cardiogenic shock after the age of 75 years.

PubMed

Samadi, A; Le Feuvre, C; Allali, Y; Collet, J-P; Barthélémy, O; Beygui, F; Helft, G; Montalescot, G; Metzger, J-P

2008-03-01

To assess mortality in people > or =75 years of age 6 months after myocardial infarction complicated by cardiogenic shock and treated by angioplasty with complete revascularisation and optimal anti-thrombotic treatment; to compare results to those of younger patients with or without shock and to analyse predictive factors for death. The study is based on 1011 consecutive patients with myocardial infarction admitted for primary angioplasty, subdivided into four groups by age and the presence or absence of cardiogenic shock: group 1 (<75 years of age without shock, n=733), group 2 (<75 years of age with shock, n=49), group 3 (> or =75 years of age without shock, n=208) and group 4 (> or =75 years of age with shock, n=20). These four patient groups were compared for mortality rates and predictive factors for in-hospital and 6 month mortality. In-hospital mortality in groups 1 to 4 was 1.7%, 30.6%, 9.1%, and 70% (p<0.0001) respectively and 6-month mortality was 3.1%, 40%, 16% and 78% (P<0.0001). By univariate analysis renal failure was a predictive factor for death at 6 months in patients without cardiogenic shock (groups 1 and 3), and left ventricular function in patients in group 2. No predictive factors were found in group 4 patients. The independent predictive factors for death at 6 months were: age >75 years of age (P<0.0003), cardiogenic shock (P<0.0001), triple vessel lesions (P<0.01) and creatinine clearance (P=0.004). Mortality after angioplasty remains high in people > or =75 years with cardiogenic shock despite all the advances in the management of myocardial infarction. These disappointing results should encourage us to assess the role of surgical revascularisation and circulatory assistance.

Predictive models for mortality after ruptured aortic aneurysm repair do not predict futility and are not useful for clinical decision making.

PubMed

Thompson, Patrick C; Dalman, Ronald L; Harris, E John; Chandra, Venita; Lee, Jason T; Mell, Matthew W

2016-12-01

The clinical decision-making utility of scoring algorithms for predicting mortality after ruptured abdominal aortic aneurysms (rAAAs) remains unknown. We sought to determine the clinical utility of the algorithms compared with our clinical decision making and outcomes for management of rAAA during a 10-year period. Patients admitted with a diagnosis rAAA at a large university hospital were identified from 2005 to 2014. The Glasgow Aneurysm Score, Hardman Index, Vancouver Score, Edinburgh Ruptured Aneurysm Score, University of Washington Ruptured Aneurysm Score, Vascular Study Group of New England rAAA Risk Score, and the Artificial Neural Network Score were analyzed for accuracy in predicting mortality. Among patients quantified into the highest-risk group (predicted mortality >80%-85%), we compared the predicted with the actual outcome to determine how well these scores predicted futility. The cohort comprised 64 patients. Of those, 24 (38%) underwent open repair, 36 (56%) underwent endovascular repair, and 4 (6%) received only comfort care. Overall mortality was 30% (open repair, 26%; endovascular repair, 24%; no repair, 100%). As assessed by the scoring systems, 5% to 35% of patients were categorized as high-mortality risk. Intersystem agreement was poor, with κ values ranging from 0.06 to 0.79. Actual mortality was lower than the predicted mortality (50%-70% vs 78%-100%) for all scoring systems, with each scoring system overestimating mortality by 10% to 50%. Mortality rates for patients not designated into the high-risk cohort were dramatically lower, ranging from 7% to 29%. Futility, defined as 100% mortality, was predicted in five of 63 patients with the Hardman Index and in two of 63 of the University of Washington score. Of these, surgery was not offered to one of five and one of two patients, respectively. If one of these two models were used to withhold operative intervention, the mortality of these patients would have been 100%. The actual mortality for these patients was 60% and 50%, respectively. Clinical algorithms for predicting mortality after rAAA were not useful for predicting futility. Most patients with rAAA were not classified in the highest-risk group by the clinical decision models. Among patients identified as highest risk, predicted mortality was overestimated compared with actual mortality. The data from this study support the limited value to surgeons of the currently published algorithms. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Simplified Mortality Score for the Intensive Care Unit (SMS-ICU): protocol for the development and validation of a bedside clinical prediction rule.

PubMed

Granholm, Anders; Perner, Anders; Krag, Mette; Hjortrup, Peter Buhl; Haase, Nicolai; Holst, Lars Broksø; Marker, Søren; Collet, Marie Oxenbøll; Jensen, Aksel Karl Georg; Møller, Morten Hylander

2017-03-09

Mortality prediction scores are widely used in intensive care units (ICUs) and in research, but their predictive value deteriorates as scores age. Existing mortality prediction scores are imprecise and complex, which increases the risk of missing data and decreases the applicability bedside in daily clinical practice. We propose the development and validation of a new, simple and updated clinical prediction rule: the Simplified Mortality Score for use in the Intensive Care Unit (SMS-ICU). During the first phase of the study, we will develop and internally validate a clinical prediction rule that predicts 90-day mortality on ICU admission. The development sample will comprise 4247 adult critically ill patients acutely admitted to the ICU, enrolled in 5 contemporary high-quality ICU studies/trials. The score will be developed using binary logistic regression analysis with backward stepwise elimination of candidate variables, and subsequently be converted into a point-based clinical prediction rule. The general performance, discrimination and calibration of the score will be evaluated, and the score will be internally validated using bootstrapping. During the second phase of the study, the score will be externally validated in a fully independent sample consisting of 3350 patients included in the ongoing Stress Ulcer Prophylaxis in the Intensive Care Unit trial. We will compare the performance of the SMS-ICU to that of existing scores. We will use data from patients enrolled in studies/trials already approved by the relevant ethical committees and this study requires no further permissions. The results will be reported in accordance with the Transparent Reporting of multivariate prediction models for Individual Prognosis Or Diagnosis (TRIPOD) statement, and submitted to a peer-reviewed journal. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Predicting post-fire tree mortality for 14 conifers in the Pacific Northwest, USA: Model evaluation, development, and thresholds

Treesearch

Lindsay M. Grayson; Robert A. Progar; Sharon M. Hood

2017-01-01

Fire is a driving force in the North American landscape and predicting post-fire tree mortality is vital to land management. Post-fire tree mortality can have substantial economic and social impacts, and natural resource managers need reliable predictive methods to anticipate potential mortality following fire events. Current fire mortality models are limited to a few...

Chemotherapy effectiveness and mortality prediction in surgically treated osteosarcoma dogs: A validation study.

PubMed

Schmidt, A F; Nielen, M; Withrow, S J; Selmic, L E; Burton, J H; Klungel, O H; Groenwold, R H H; Kirpensteijn, J

2016-03-01

Canine osteosarcoma is the most common bone cancer, and an important cause of mortality and morbidity, in large purebred dogs. Previously we constructed two multivariable models to predict a dog's 5-month or 1-year mortality risk after surgical treatment for osteosarcoma. According to the 5-month model, dogs with a relatively low risk of 5-month mortality benefited most from additional chemotherapy treatment. In the present study, we externally validated these results using an independent cohort study of 794 dogs. External performance of our prediction models showed some disagreement between observed and predicted risk, mean difference: -0.11 (95% confidence interval [95% CI]-0.29; 0.08) for 5-month risk and 0.25 (95%CI 0.10; 0.40) for 1-year mortality risk. After updating the intercept, agreement improved: -0.0004 (95%CI-0.16; 0.16) and -0.002 (95%CI-0.15; 0.15). The chemotherapy by predicted mortality risk interaction (P-value=0.01) showed that the chemotherapy compared to no chemotherapy effectiveness was modified by 5-month mortality risk: dogs with a relatively lower risk of mortality benefited most from additional chemotherapy. Chemotherapy effectiveness on 1-year mortality was not significantly modified by predicted risk (P-value=0.28). In conclusion, this external validation study confirmed that our multivariable risk prediction models can predict a patient's mortality risk and that dogs with a relatively lower risk of 5-month mortality seem to benefit most from chemotherapy. Copyright © 2016 Elsevier B.V. All rights reserved.

Usual gait speed independently predicts mortality in very old people: a population-based study.

PubMed

Toots, Annika; Rosendahl, Erik; Lundin-Olsson, Lillemor; Nordström, Peter; Gustafson, Yngve; Littbrand, Håkan

2013-07-01

In older people, usual gait speed has been shown to independently predict mortality; however, less is known about whether usual gait speed is as informative in very old populations, in which prevalence of multimorbidity and disability is high. The aim of this study was to investigate if usual gait speed can independently predict all-cause mortality in very old people, and whether the prediction is influenced by dementia disorder, dependency in activities of daily living (ADL), or use of walking aids in the gait speed test. Prospective cohort study. Population-based study in northern Sweden and Finland (the Umeå 85+/GERDA Study). A total of 772 participants with a mean age of 89.6 years, 70% women, 33% with dementia disorders, 54% with ADL dependency, and 39% living in residential care facilities. Usual gait speed assessed over 2.4 meters and mortality followed-up for 5 years. The mean ± SD gait speed was 0.52 ± 0.21 m/s for the 620 (80%) participants able to complete the gait speed test. Cox proportional hazard regression analyses adjusted for potential confounders were performed. Compared with the fastest gait speed group (≥ 0.64 m/s), the hazard ratio for mortality was for the following groups: unable = 2.27 (P < .001), ≤ 0.36 m/s = 1.97 (P = .001), 0.37 to 0.49 m/s = 1.99 (P < .001), 0.50 to 0.63 m/s = 1.11 (P = .604). No interaction effects were found between gait speed and age, sex, dementia disorder, dependency in ADLs, or use of walking aids. Among people aged 85 or older, including people dependent in ADLs and with dementia disorders, usual gait speed was an independent predictor of 5-year all-cause mortality. Inability to complete the gait test or gait speeds slower than 0.5 m/s appears to be associated with higher mortality risk. Gait speed might be a useful clinical indicator of health status among very old people. Copyright © 2013 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.

A new drought tipping point for conifer mortality

NASA Astrophysics Data System (ADS)

Kolb, Thomas E.

2015-03-01

(Huang et al 2015 Environ. Res. Lett. 10 024011) present a method for predicting mortality of ponderosa pine (Pinus ponderosa) and pinyon pine (Pinus edulis) in the Southwestern US during severe drought based on the relationship between the standardized precipitation-evapotranspiration index (SPEI) and annual tree ring growth. Ring growth was zero when SPEI for September to July was -1.64. The threshold SPEI of -1.64 was successful in distinguishing areas with high tree mortality during recent severe drought from areas with low mortality, and is proposed to be a tipping point of drought severity leading to tree mortality. Below, I discuss this work in more detail.

Prediction of Postoperative Mortality in Liver Transplantation in the Era of MELD-Based Liver Allocation: A Multivariate Analysis

PubMed Central

Schultze, Daniel; Hillebrand, Norbert; Hinz, Ulf; Büchler, Markus W.; Schemmer, Peter

2014-01-01

Background and Aims Liver transplantation is the only curative treatment for end-stage liver disease. While waiting list mortality can be predicted by the MELD-score, reliable scoring systems for the postoperative period do not exist. This study's objective was to identify risk factors that contribute to postoperative mortality. Methods Between December 2006 and March 2011, 429 patients underwent liver transplantation in our department. Risk factors for postoperative mortality in 266 consecutive liver transplantations were identified using univariate and multivariate analyses. Patients who were <18 years, HU-listings, and split-, living related, combined or re-transplantations were excluded from the analysis. The correlation between number of risk factors and mortality was analyzed. Results A labMELD ≥20, female sex, coronary heart disease, donor risk index >1.5 and donor Na+>145 mmol/L were identified to be independent predictive factors for postoperative mortality. With increasing number of these risk-factors, postoperative 90-day and 1-year mortality increased (0–1: 0 and 0%; 2: 2.9 and 17.4%; 3: 5.6 and 16.8%; 4: 22.2 and 33.3%; 5–6: 60.9 and 66.2%). Conclusions In this analysis, a simple score was derived that adequately identified patients at risk after liver transplantation. Opening a discussion on the inclusion of these parameters in the process of organ allocation may be a worthwhile venture. PMID:24905210

Predictors of mortality in patients with emphysema and severe airflow obstruction.

PubMed

Martinez, Fernando J; Foster, Gregory; Curtis, Jeffrey L; Criner, Gerard; Weinmann, Gail; Fishman, Alfred; DeCamp, Malcolm M; Benditt, Joshua; Sciurba, Frank; Make, Barry; Mohsenifar, Zab; Diaz, Philip; Hoffman, Eric; Wise, Robert

2006-06-15

Limited data exist describing risk factors for mortality in patients having predominantly emphysema. A total of 609 patients with severe emphysema (ages 40-83 yr; 64.2% male) randomized to the medical therapy arm of the National Emphysema Treatment Trial formed the study group. Cox proportional hazards regression analysis was used to investigate risk factors for all-cause mortality. Risk factors examined included demographics, body mass index, physiologic data, quality of life, dyspnea, oxygen utilization, hemoglobin, smoking history, quantitative emphysema markers on computed tomography, and a modification of a recently described multifunctional index (modified BODE). Overall, high mortality was seen in this cohort (12.7 deaths per 100 person-years; 292 total deaths). In multivariate analyses, increasing age (p=0.001), oxygen utilization (p=0.04), lower total lung capacity % predicted (p=0.05), higher residual volume % predicted (p=0.04), lower maximal cardiopulmonary exercise testing workload (p=0.002), greater proportion of emphysema in the lower lung zone versus the upper lung zone (p=0.005), and lower upper-to-lower-lung perfusion ratio (p=0.007), and modified BODE (p=0.02) were predictive of mortality. FEV1 was a significant predictor of mortality in univariate analysis (p=0.005), but not in multivariate analysis (p=0.21). Although patients with advanced emphysema experience significant mortality, subgroups based on age, oxygen utilization, physiologic measures, exercise capacity, and emphysema distribution identify those at increased risk of death.

An evaluation of climate/mortality relationships in large U.S. cities and the possible impacts of a climate change.

PubMed Central

Kalkstein, L S; Greene, J S

1997-01-01

A new air mass-based synoptic procedure is used to evaluate climate/mortality relationships as they presently exist and to estimate how a predicted global warming might alter these values. Forty-four large U.S. cities with metropolitan areas exceeding 1 million in population are analyzed. Sharp increases in mortality are noted in summer for most cities in the East and Midwest when two particular air masses are present. A very warm air mass of maritime origin is most important in the eastern United States, which when present can increase daily mortality by as many as 30 deaths in large cities. A hot, dry air mass is important in many cities, and, although rare in the East, can increase daily mortality by up to 50 deaths. Cities in the South and Southwest show lesser weather/mortality relationships in summer. During winter, air mass-induced increases in mortality are considerably less than in summer. Although daily winter mortality is usually higher than summer, the causes of death that are responsible for most winter mortality do not vary much with temperature. Using models that estimate climate change for the years 2020 and 2050, it is estimated that summer mortality will increase dramatically and winter mortality will decrease slightly, even if people acclimatize to the increased warmth. Thus, a sizable net increase in weather-related mortality is estimated if the climate warms as the models predict. PMID:9074886

Machine Learning Algorithm Predicts Cardiac Resynchronization Therapy Outcomes: Lessons From the COMPANION Trial.

PubMed

Kalscheur, Matthew M; Kipp, Ryan T; Tattersall, Matthew C; Mei, Chaoqun; Buhr, Kevin A; DeMets, David L; Field, Michael E; Eckhardt, Lee L; Page, C David

2018-01-01

Cardiac resynchronization therapy (CRT) reduces morbidity and mortality in heart failure patients with reduced left ventricular function and intraventricular conduction delay. However, individual outcomes vary significantly. This study sought to use a machine learning algorithm to develop a model to predict outcomes after CRT. Models were developed with machine learning algorithms to predict all-cause mortality or heart failure hospitalization at 12 months post-CRT in the COMPANION trial (Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure). The best performing model was developed with the random forest algorithm. The ability of this model to predict all-cause mortality or heart failure hospitalization and all-cause mortality alone was compared with discrimination obtained using a combination of bundle branch block morphology and QRS duration. In the 595 patients with CRT-defibrillator in the COMPANION trial, 105 deaths occurred (median follow-up, 15.7 months). The survival difference across subgroups differentiated by bundle branch block morphology and QRS duration did not reach significance ( P =0.08). The random forest model produced quartiles of patients with an 8-fold difference in survival between those with the highest and lowest predicted probability for events (hazard ratio, 7.96; P <0.0001). The model also discriminated the risk of the composite end point of all-cause mortality or heart failure hospitalization better than subgroups based on bundle branch block morphology and QRS duration. In the COMPANION trial, a machine learning algorithm produced a model that predicted clinical outcomes after CRT. Applied before device implant, this model may better differentiate outcomes over current clinical discriminators and improve shared decision-making with patients. © 2018 American Heart Association, Inc.

From vital signs to clinical outcomes for patients with sepsis: a machine learning basis for a clinical decision support system

PubMed Central

Gultepe, Eren; Green, Jeffrey P; Nguyen, Hien; Adams, Jason; Albertson, Timothy; Tagkopoulos, Ilias

2014-01-01

Objective To develop a decision support system to identify patients at high risk for hyperlactatemia based upon routinely measured vital signs and laboratory studies. Materials and methods Electronic health records of 741 adult patients at the University of California Davis Health System who met at least two systemic inflammatory response syndrome criteria were used to associate patients’ vital signs, white blood cell count (WBC), with sepsis occurrence and mortality. Generative and discriminative classification (naïve Bayes, support vector machines, Gaussian mixture models, hidden Markov models) were used to integrate heterogeneous patient data and form a predictive tool for the inference of lactate level and mortality risk. Results An accuracy of 0.99 and discriminability of 1.00 area under the receiver operating characteristic curve (AUC) for lactate level prediction was obtained when the vital signs and WBC measurements were analysed in a 24 h time bin. An accuracy of 0.73 and discriminability of 0.73 AUC for mortality prediction in patients with sepsis was achieved with only three features: median of lactate levels, mean arterial pressure, and median absolute deviation of the respiratory rate. Discussion This study introduces a new scheme for the prediction of lactate levels and mortality risk from patient vital signs and WBC. Accurate prediction of both these variables can drive the appropriate response by clinical staff and thus may have important implications for patient health and treatment outcome. Conclusions Effective predictions of lactate levels and mortality risk can be provided with a few clinical variables when the temporal aspect and variability of patient data are considered. PMID:23959843

Aortic valve replacement with or without coronary artery bypass graft surgery: the risk of surgery in patients > or =80 years old.

PubMed

Maslow, Andrew; Casey, Paula; Poppas, Athena; Schwartz, Carl; Singh, Arun

2010-02-01

The purpose of this study was to evaluate the outcomes for elderly (> or =80 years) patients undergoing aortic valve replacement (AVR) with or without coronary artery bypass graft surgery (AVR/CABG). The authors hypothesized that the mortalities of AVR and AVR/CABG are lower than that predicted by published risk scores. A retrospective analysis of data from a single-hospital database. Single tertiary care, private practice. Consecutive patients undergoing AVR or AVR/CABG. Two hundred sixty-one elderly (> or =80 years) patients undergoing isolated AVR (145) or AVR/CABG (116) were evaluated. The majority (94.6%) underwent AVR for aortic valve stenosis. Outcomes were recorded and compared between the 2 surgical procedures with predicted mortalities based on published risk assessment scoring systems. The overall short-term mortality for the elderly group was 6.1% (AVR 5.5% and AVR/CABG 6.9%). The median long-term survival was 6.8 years. There were no significant differences in either morbidity or mortality between the AVR and AVR/CABG groups. Although predicted mortalities were similar for each surgical procedure, they overestimated observed outcome by up to 4-fold. Short- and long-term mortality was low for this group of elderly patients undergoing AVR or AVR/CABG and not significantly different between the 2 surgical groups. Predicted outcomes were worse than that observed, consistent with the hypothesis, and supportive of a more aggressive surgical treatment for aortic valve disease in the elderly patient. Copyright 2010 Elsevier Inc. All rights reserved.

The Peptic Ulcer Perforation (PULP) score: a predictor of mortality following peptic ulcer perforation. A cohort study.

PubMed

Møller, M H; Engebjerg, M C; Adamsen, S; Bendix, J; Thomsen, R W

2012-05-01

Accurate and early identification of high-risk surgical patients with perforated peptic ulcer (PPU) is important for triage and risk stratification. The objective of the present study was to develop a new and improved clinical rule to predict mortality in patients following surgical treatment for PPU. nationwide cohort study based on prospectively collected data. thirty-five hospitals in Denmark. a total of 2668 patients surgically treated for gastric or duodenal PPU between 1 February 2003 and 31 August 2009. 30-day mortality. We derived a new clinical prediction rule for 30-day mortality and evaluated and compared its prognostic performance with the American Society of Anaesthesiologists (ASA) and Boey scores. A total of 708 patients (27%) died within 30 days of surgery. The Peptic Ulcer Perforation (PULP) score - comprised eight variables with an adjusted odds ratio of more than 1.28: 1) age > 65 years, 2) active malignant disease or AIDS, 3) liver cirrhosis, 4) steroid use, 5) time from perforation to admission > 24 h, 6) pre-operative shock, 7) serum creatinine > 130 μM, and 8) the four levels of the ASA score (from 2 to 5). The score predicted mortality well (area under receiver operating characteristics curve (AUC) 0.83). It performed considerably better than the Boey score (AUC 0.70) and better than the ASA score alone (AUC 0.78). The PULP score accurately predicts 30-day mortality in patients operated for PPU and can assist in risk stratification and triage. © 2011 The Authors Acta Anaesthesiologica Scandinavica © 2011 The Acta Anaesthesiologica Scandinavica Foundation.

Remotely sensed predictors of conifer tree mortality during severe drought

NASA Astrophysics Data System (ADS)

Brodrick, P. G.; Asner, G. P.

2017-11-01

Widespread, drought-induced forest mortality has been documented on every forested continent over the last two decades, yet early pre-mortality indicators of tree death remain poorly understood. Remotely sensed physiological-based measures offer a means for large-scale analysis to understand and predict drought-induced mortality. Here, we use laser-guided imaging spectroscopy from multiple years of aerial surveys to assess the impact of sustained canopy water loss on tree mortality. We analyze both gross canopy mortality in 2016 and the change in mortality between 2015 and 2016 in millions of sampled conifer forest locations throughout the Sierra Nevada mountains in California. On average, sustained water loss and gross mortality are strongly related, and year-to-year water loss within the drought indicates subsequent mortality. Both relationships are consistent after controlling for location and tree community composition, suggesting that these metrics may serve as indicators of mortality during a drought.

Decoy receptor 3, a novel inflammatory marker, and mortality in hemodialysis patients.

PubMed

Hung, Szu-Chun; Hsu, Ta-Wei; Lin, Yao-Ping; Tarng, Der-Cherng

2012-08-01

Inflammation is closely associated with cardiovascular disease, the leading cause of mortality in patients with CKD. Serum decoy receptor 3 (DcR3) is a member of the TNF receptor superfamily. CKD patients have higher levels of DcR3 than the general population, but whether DcR3 predicts mortality in CKD patients on hemodialysis has not been explored. DcR3 levels were measured in 316 prevalent hemodialysis patients who were followed up from November 1, 2004, to June 30, 2009, for cardiovascular and all-cause mortality. The baseline DcR3 concentration showed a strong positive correlation with inflammatory markers including high-sensitivity C-reactive protein, IL-6, intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1). During a follow-up period of 54 months, 90 patients died (34 cardiovascular deaths). Kaplan-Meier survival analysis showed higher cardiovascular and all-cause mortality in patients with higher DcR3 levels. The hazard ratios (95% confidence intervals) of the highest versus lowest tertiles of DcR3 were 2.8 (1.1-7.3; P for trend=0.04) for cardiovascular mortality and 2.1 (1.1-3.7; P for trend=0.02) for all-cause mortality, respectively. Based on the minimal increase in the area under the receiver operating characteristic curve from 0.79 to 0.80, the addition of DcR3 to established risk factors including VCAM-1, albumin, and IL-6 does not improve the prediction of mortality. Higher DcR3 levels strongly correlate with inflammation and independently predict cardiovascular and all-cause mortality in CKD patients on hemodialysis.

Short and Long-Term Outcomes After Surgical Procedures Lasting for More Than Six Hours.

PubMed

Cornellà, Natalia; Sancho, Joan; Sitges-Serra, Antonio

2017-08-23

Long-term all-cause mortality and dependency after complex surgical procedures have not been assessed in the framework of value-based medicine. The aim of this study was to investigate the postoperative and long-term outcomes after surgical procedures lasting for more than six hours. Retrospective cohort study of patients undergoing a first elective complex surgical procedure between 2004 and 2013. Heart and transplant surgery was excluded. Mortality and dependency from the healthcare system were selected as outcome variables. Gender, age, ASA, creatinine, albumin kinetics, complications, benign vs malignant underlying condition, number of drugs at discharge, and admission and length of stay in the ICU were recorded as predictive variables. Some 620 adult patients were included in the study. Postoperative, <1year and <5years cumulative mortality was 6.8%, 17.6% and 45%, respectively. Of patients discharged from hospital after surgery, 76% remained dependent on the healthcare system. In multivariate analysis for postoperative, <1year and <5years mortality, postoperative albumin concentration, ASA score and an ICU stay >7days, were the most significant independent predictive variables. Prolonged surgery carries a significant short and long-term mortality and disability. These data may contribute to more informed decisions taken concerning major surgery in the framework of value-based medicine.

Herd factors associated with dairy cow mortality.

PubMed

McConnel, C; Lombard, J; Wagner, B; Kopral, C; Garry, F

2015-08-01

Summary studies of dairy cow removal indicate increasing levels of mortality over the past several decades. This poses a serious problem for the US dairy industry. The objective of this project was to evaluate associations between facilities, herd management practices, disease occurrence and death rates on US dairy operations through an analysis of the National Animal Health Monitoring System's Dairy 2007 survey. The survey included farms in 17 states that represented 79.5% of US dairy operations and 82.5% of the US dairy cow population. During the first phase of the study operations were randomly selected from a sampling list maintained by the National Agricultural Statistics Service. Only farms that participated in phase I and had 30 or more dairy cows were eligible to participate in phase II. In total, 459 farms had complete data for all selected variables and were included in this analysis. Univariable associations between dairy cow mortality and 162 a priori identified operation-level management practices or characteristics were evaluated. Sixty of the 162 management factors explored in the univariate analysis met initial screening criteria and were further evaluated in a multivariable model exploring more complex relationships. The final weighted, negative binomial regression model included six variables. Based on the incidence rate ratio, this model predicted 32.0% less mortality for operations that vaccinated heifers for at least one of the following: bovine viral diarrhea, infectious bovine rhinotracheitis, parainfluenza 3, bovine respiratory syncytial virus, Haemophilus somnus, leptospirosis, Salmonella, Escherichia coli or clostridia. The final multivariable model also predicted a 27.0% increase in mortality for operations from which a bulk tank milk sample tested ELISA positive for bovine leukosis virus. Additionally, an 18.0% higher mortality was predicted for operations that used necropsies to determine the cause of death for some proportion of dead dairy cows. The final model also predicted that increased proportions of dairy cows with clinical mastitis and infertility problems were associated with increased mortality. Finally, an increase in mortality was predicted to be associated with an increase in the proportion of lame or injured permanently removed dairy cows. In general terms, this model identified that mortality was associated with reproductive problems, non-infectious postpartum disease, infectious disease and infectious disease prevention, and information derived from postmortem evaluations. Ultimately, addressing excessive mortality levels requires a concerted effort that recognizes and appropriately manages the numerous and diverse underlying risks.

A comparison of administrative and physiologic predictive models in determining risk adjusted mortality rates in critically ill patients.

PubMed

Enfield, Kyle B; Schafer, Katherine; Zlupko, Mike; Herasevich, Vitaly; Novicoff, Wendy M; Gajic, Ognjen; Hoke, Tracey R; Truwit, Jonathon D

2012-01-01

Hospitals are increasingly compared based on clinical outcomes adjusted for severity of illness. Multiple methods exist to adjust for differences between patients. The challenge for consumers of this information, both the public and healthcare providers, is interpreting differences in risk adjustment models particularly when models differ in their use of administrative and physiologic data. We set to examine how administrative and physiologic models compare to each when applied to critically ill patients. We prospectively abstracted variables for a physiologic and administrative model of mortality from two intensive care units in the United States. Predicted mortality was compared through the Pearsons Product coefficient and Bland-Altman analysis. A subgroup of patients admitted directly from the emergency department was analyzed to remove potential confounding changes in condition prior to ICU admission. We included 556 patients from two academic medical centers in this analysis. The administrative model and physiologic models predicted mortalities for the combined cohort were 15.3% (95% CI 13.7%, 16.8%) and 24.6% (95% CI 22.7%, 26.5%) (t-test p-value<0.001). The r(2) for these models was 0.297. The Bland-Atlman plot suggests that at low predicted mortality there was good agreement; however, as mortality increased the models diverged. Similar results were found when analyzing a subgroup of patients admitted directly from the emergency department. When comparing the two hospitals, there was a statistical difference when using the administrative model but not the physiologic model. Unexplained mortality, defined as those patients who died who had a predicted mortality less than 10%, was a rare event by either model. In conclusion, while it has been shown that administrative models provide estimates of mortality that are similar to physiologic models in non-critically ill patients with pneumonia, our results suggest this finding can not be applied globally to patients admitted to intensive care units. As patients and providers increasingly use publicly reported information in making health care decisions and referrals, it is critical that the provided information be understood. Our results suggest that severity of illness may influence the mortality index in administrative models. We suggest that when interpreting "report cards" or metrics, health care providers determine how the risk adjustment was made and compares to other risk adjustment models.

Cancer mortality in Brazil

PubMed Central

Barbosa, Isabelle R.; de Souza, Dyego L.B.; Bernal, María M.; Costa, Íris do C.C.

2015-01-01

Abstract Cancer is currently in the spotlight due to their heavy responsibility as main cause of death in both developed and developing countries. Analysis of the epidemiological situation is required as a support tool for the planning of public health measures for the most vulnerable groups. We analyzed cancer mortality trends in Brazil and geographic regions in the period 1996 to 2010 and calculate mortality predictions for the period 2011 to 2030. This is an epidemiological, demographic-based study that utilized information from the Mortality Information System on all deaths due to cancer in Brazil. Mortality trends were analyzed by the Joinpoint regression, and Nordpred was utilized for the calculation of predictions. Stability was verified for the female (annual percentage change [APC] = 0.4%) and male (APC = 0.5%) sexes. The North and Northeast regions present significant increasing trends for mortality in both sexes. Until 2030, female mortality trends will not present considerable variations, but there will be a decrease in mortality trends for the male sex. There will be increases in mortality rates until 2030 for the North and Northeast regions, whereas reductions will be verified for the remaining geographic regions. This variation will be explained by the demographic structure of regions until 2030. There are pronounced regional and sex differences in cancer mortality in Brazil, and these discrepancies will continue to increase until the year 2030, when the Northeast region will present the highest cancer mortality rates in Brazil. PMID:25906105

Risk of fetal mortality after exposure to Listeria monocytogenes based on dose-response data from pregnant guinea pigs and primates.

PubMed

Williams, Denita; Castleman, Jennifer; Lee, Chi-Ching; Mote, Beth; Smith, Mary Alice

2009-11-01

One-third of the annual cases of listeriosis in the United States occur during pregnancy and can lead to miscarriage or stillbirth, premature delivery, or infection of the newborn. Previous risk assessments completed by the Food and Drug Administration/the Food Safety Inspection Service of the U.S. Department of Agriculture/the Centers for Disease Control and Prevention (FDA/USDA/CDC) and Food and Agricultural Organization/the World Health Organization (FAO/WHO) were based on dose-response data from mice. Recent animal studies using nonhuman primates and guinea pigs have both estimated LD(50)s of approximately 10(7) Listeria monocytogenes colony forming units (cfu). The FAO/WHO estimated a human LD(50) of 1.9 x 10(6) cfu based on data from a pregnant woman consuming contaminated soft cheese. We reevaluated risk based on dose-response curves from pregnant rhesus monkeys and guinea pigs. Using standard risk assessment methodology including hazard identification, exposure assessment, hazard characterization, and risk characterization, risk was calculated based on the new dose-response information. To compare models, we looked at mortality rate per serving at predicted doses ranging from 10(-4) to 10(12) L. monocytogenes cfu. Based on a serving of 10(6) L. monocytogenes cfu, the primate model predicts a death rate of 5.9 x 10(-1) compared to the FDA/USDA/CDC (fig. IV-12) predicted rate of 1.3 x 10(-7). Based on the guinea pig and primate models, the mortality rate calculated by the FDA/USDA/CDC is underestimated for this susceptible population.

Using claims data to examine mortality trends following hospitalization for heart attack in Medicare.

PubMed

Ash, Arlene S; Posner, Michael A; Speckman, Jeanne; Franco, Shakira; Yacht, Andrew C; Bramwell, Lindsey

2003-10-01

To see if changes in the demographics and illness burden of Medicare patients hospitalized for acute myocardial infarction (AMI) from 1995 through 1999 can explain an observed rise (from 32 percent to 34 percent) in one-year mortality over that period. Utilization data from the Centers for Medicare and Medicaid Services (CMS) fee-for-service claims (MedPAR, Outpatient, and Carrier Standard Analytic Files); patient demographics and date of death from CMS Denominator and Vital Status files. For over 1.5 million AMI discharges in 1995-1999 we retain diagnoses from one year prior, and during, the case-defining admission. We fit logistic regression models to predict one-year mortality for the 1995 cases and apply them to 1996-1999 files. The CORE model uses age, sex, and original reason for Medicare entitlement to predict mortality. Three other models use the CORE variables plus morbidity indicators from well-known morbidity classification methods (Charlson, DCG, and AHRQ's CCS). Regressions were used as is--without pruning to eliminate clinical or statistical anomalies. Each model references the same diagnoses--those recorded during the pre- and index admission periods. We compare each model's ability to predict mortality and use each to calculate risk-adjusted mortality in 1996-1999. The comprehensive morbidity classifications (DCG and CCS) led to more accurate predictions than the Charlson, which dominated the CORE model (validated C-statistics: 0.81, 0.82, 0.74, and 0.66, respectively). Using the CORE model for risk adjustment reduced, but did not eliminate, the mortality increase. In contrast, adjustment using any of the morbidity models produced essentially flat graphs. Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends.

Using Claims Data to Examine Mortality Trends Following Hospitalization for Heart Attack in Medicare

PubMed Central

Ash, Arlene S; Posner, Michael A; Speckman, Jeanne; Franco, Shakira; Yacht, Andrew C; Bramwell, Lindsey

2003-01-01

Objective To see if changes in the demographics and illness burden of Medicare patients hospitalized for acute myocardial infarction (AMI) from 1995 through 1999 can explain an observed rise (from 32 percent to 34 percent) in one-year mortality over that period. Data Sources Utilization data from the Centers for Medicare and Medicaid Services (CMS) fee-for-service claims (MedPAR, Outpatient, and Carrier Standard Analytic Files); patient demographics and date of death from CMS Denominator and Vital Status files. For over 1.5 million AMI discharges in 1995–1999 we retain diagnoses from one year prior, and during, the case-defining admission. Study Design We fit logistic regression models to predict one-year mortality for the 1995 cases and apply them to 1996–1999 files. The CORE model uses age, sex, and original reason for Medicare entitlement to predict mortality. Three other models use the CORE variables plus morbidity indicators from well-known morbidity classification methods (Charlson, DCG, and AHRQ's CCS). Regressions were used as is—without pruning to eliminate clinical or statistical anomalies. Each model references the same diagnoses—those recorded during the pre- and index admission periods. We compare each model's ability to predict mortality and use each to calculate risk-adjusted mortality in 1996–1999. Principal Findings The comprehensive morbidity classifications (DCG and CCS) led to more accurate predictions than the Charlson, which dominated the CORE model (validated C-statistics: 0.81, 0.82, 0.74, and 0.66, respectively). Using the CORE model for risk adjustment reduced, but did not eliminate, the mortality increase. In contrast, adjustment using any of the morbidity models produced essentially flat graphs. Conclusions Prediction models based on claims-derived demographics and morbidity profiles can be extremely accurate. While one-year post-AMI mortality in Medicare may not be worsening, outcomes appear not to have continued to improve as they had in the prior decade. Rich morbidity information is available in claims data, especially when longitudinally tracked across multiple settings of care, and is important in setting performance targets and evaluating trends. PMID:14596389

Does the emergency surgery score accurately predict outcomes in emergent laparotomies?

PubMed

Peponis, Thomas; Bohnen, Jordan D; Sangji, Naveen F; Nandan, Anirudh R; Han, Kelsey; Lee, Jarone; Yeh, D Dante; de Moya, Marc A; Velmahos, George C; Chang, David C; Kaafarani, Haytham M A

2017-08-01

The emergency surgery score is a mortality-risk calculator for emergency general operation patients. We sought to examine whether the emergency surgery score predicts 30-day morbidity and mortality in a high-risk group of patients undergoing emergent laparotomy. Using the 2011-2012 American College of Surgeons National Surgical Quality Improvement Program database, we identified all patients who underwent emergent laparotomy using (1) the American College of Surgeons National Surgical Quality Improvement Program definition of "emergent," and (2) all Current Procedural Terminology codes denoting a laparotomy, excluding aortic aneurysm rupture. Multivariable logistic regression analyses were performed to measure the correlation (c-statistic) between the emergency surgery score and (1) 30-day mortality, and (2) 30-day morbidity after emergent laparotomy. As sensitivity analyses, the correlation between the emergency surgery score and 30-day mortality was also evaluated in prespecified subgroups based on Current Procedural Terminology codes. A total of 26,410 emergent laparotomy patients were included. Thirty-day mortality and morbidity were 10.2% and 43.8%, respectively. The emergency surgery score correlated well with mortality (c-statistic = 0.84); scores of 1, 11, and 22 correlated with mortalities of 0.4%, 39%, and 100%, respectively. Similarly, the emergency surgery score correlated well with morbidity (c-statistic = 0.74); scores of 0, 7, and 11 correlated with complication rates of 13%, 58%, and 79%, respectively. The morbidity rates plateaued for scores higher than 11. Sensitivity analyses demonstrated that the emergency surgery score effectively predicts mortality in patients undergoing emergent (1) splenic, (2) gastroduodenal, (3) intestinal, (4) hepatobiliary, or (5) incarcerated ventral hernia operation. The emergency surgery score accurately predicts outcomes in all types of emergent laparotomy patients and may prove valuable as a bedside decision-making tool for patient and family counseling, as well as for adequate risk-adjustment in emergent laparotomy quality benchmarking efforts. Copyright © 2017 Elsevier Inc. All rights reserved.

Epidemiology and Long-term Clinical and Biologic Risk Factors for Pneumonia in Community-Dwelling Older Americans

PubMed Central

Alvarez, Karina; Loehr, Laura; Folsom, Aaron R.; Newman, Anne B.; Weissfeld, Lisa A.; Wunderink, Richard G.; Kritchevsky, Stephen B.; Mukamal, Kenneth J.; London, Stephanie J.; Harris, Tamara B.; Bauer, Doug C.; Angus, Derek C.

2013-01-01

Background: Preventing pneumonia requires better understanding of incidence, mortality, and long-term clinical and biologic risk factors, particularly in younger individuals. Methods: This was a cohort study in three population-based cohorts of community-dwelling individuals. A derivation cohort (n = 16,260) was used to determine incidence and survival and develop a risk prediction model. The prediction model was validated in two cohorts (n = 8,495). The primary outcome was 10-year risk of pneumonia hospitalization. Results: The crude and age-adjusted incidences of pneumonia were 6.71 and 9.43 cases/1,000 person-years (10-year risk was 6.15%). The 30-day and 1-year mortality were 16.5% and 31.5%. Although age was the most important risk factor (range of crude incidence rates, 1.69-39.13 cases/1,000 person-years for each 5-year increment from 45-85 years), 38% of pneumonia cases occurred in adults < 65 years of age. The 30-day and 1-year mortality were 12.5% and 25.7% in those < 65 years of age. Although most comorbidities were associated with higher risk of pneumonia, reduced lung function was the most important risk factor (relative risk = 6.61 for severe reduction based on FEV1 by spirometry). A clinical risk prediction model based on age, smoking, and lung function predicted 10-year risk (area under curve [AUC] = 0.77 and Hosmer-Lemeshow [HL] C statistic = 0.12). Model discrimination and calibration were similar in the internal validation cohort (AUC = 0.77; HL C statistic, 0.65) but lower in the external validation cohort (AUC = 0.62; HL C statistic, 0.45). The model also calibrated well in blacks and younger adults. C-reactive protein and IL-6 were associated with higher pneumonia risk but did not improve model performance. Conclusions: Pneumonia hospitalization is common and associated with high mortality, even in younger healthy adults. Long-term risk of pneumonia can be predicted in community-dwelling adults with a simple clinical risk prediction model. PMID:23744106

Event-rate and delta inflation when evaluating mortality as a primary outcome from randomized controlled trials of nutritional interventions during critical illness: a systematic review.

PubMed

Summers, Matthew J; Chapple, Lee-anne S; McClave, Stephen A; Deane, Adam M

2016-04-01

There is a lack of high-quality evidence that proves that nutritional interventions during critical illness reduce mortality. We evaluated whether power calculations for randomized controlled trials (RCTs) of nutritional interventions that used mortality as the primary outcome were realistic, and whether overestimation was systematic in the studies identified to determine whether this was due to overestimates of event rate or delta. A systematic review of the literature between 2005 and 2015 was performed to identify RCTs of nutritional interventions administered to critically ill adults that had mortality as the primary outcome. Predicted event rate (predicted mortality during the control), predicted mortality during intervention, predicted delta (predicted difference between mortality during the control and intervention), actual event rate (observed mortality during control), observed mortality during intervention, and actual delta (difference between observed mortality during the control and intervention) were recorded. The event-rate gap (predicted event rate minus observed event rate), the delta gap (predicted delta minus observed delta), and the predicted number needed to treat were calculated. Data are shown as median (range). Fourteen articles were extracted, with power calculations provided for 10 studies. The predicted event rate was 29.9% (20.0–52.4%), and the predicted delta was 7.9% (3.0–20.0%). If the study hypothesis was proven correct then, on the basis of the power calculations, the number needed to treat would have been 12.7 (5.0–33.3) patients. The actual event rate was 25.3% (6.1–50.0%), the observed mortality during the intervention was 24.4% (6.3–39.7%), and the actual delta was 0.5% (−10.2–10.3%), such that the event-rate gap was 2.6% (−3.9–23.7%) and delta gap was 7.5% (3.2–25.2%). Overestimates of delta occur frequently in RCTs of nutritional interventions in the critically ill that are powered to determine a mortality benefit. Delta inflation may explain the number of "negative" studies in this field of research.

The impact of future summer temperature on public health in Barcelona and Catalonia, Spain

NASA Astrophysics Data System (ADS)

Ostro, Bart; Barrera-Gómez, Jose; Ballester, Joan; Basagaña, Xavier; Sunyer, Jordi

2012-11-01

Several epidemiological studies have reported associations between increases in summer temperatures and risks of premature mortality. The quantitative implications of predicted future increases in summer temperature, however, have not been extensively characterized. We have quantified these effects for the four main cities in Catalonia, Spain (Barcelona, Tarragona, Lleida, Girona). We first used case-crossover analysis to estimate the association between temperature and mortality for each of these cities for the period 1983 to 2006. These exposure-response (ER) functions were then combined with local measures of current and projected changes in population, mortality and temperature for the years 2025 and 2050. Predicted daily mean temperatures were based on the A1B greenhouse gas emission, "business-as-usual" scenario simulations derived from the ENSEMBLES project. Several different ER functions were examined and significant associations between temperature and mortality were observed for all four cities. For these four cities, the age-specific piecewise linear model predicts 520 (95%CI 340, 720) additional annual deaths attributable to the change in temperature in 2025 relative to the average from the baseline period of 1960-1990. For 2050, the estimate increases to 1,610 deaths per year during the warm season. For Catalonia as a whole, the point estimates for those two years are 720 and 2,330 deaths per year, respectively, or about 2 and 3% of the warm season. In comparing these predicted impacts with current causes of mortality, they clearly represent significant burdens to public health in Catalonia.

The impact of future summer temperature on public health in Barcelona and Catalonia, Spain.

PubMed

Ostro, Bart; Barrera-Gómez, Jose; Ballester, Joan; Basagaña, Xavier; Sunyer, Jordi

2012-11-01

Several epidemiological studies have reported associations between increases in summer temperatures and risks of premature mortality. The quantitative implications of predicted future increases in summer temperature, however, have not been extensively characterized. We have quantified these effects for the four main cities in Catalonia, Spain (Barcelona, Tarragona, Lleida, Girona). We first used case-crossover analysis to estimate the association between temperature and mortality for each of these cities for the period 1983 to 2006. These exposure-response (ER) functions were then combined with local measures of current and projected changes in population, mortality and temperature for the years 2025 and 2050. Predicted daily mean temperatures were based on the A1B greenhouse gas emission, "business-as-usual" scenario simulations derived from the ENSEMBLES project. Several different ER functions were examined and significant associations between temperature and mortality were observed for all four cities. For these four cities, the age-specific piecewise linear model predicts 520 (95%CI  340, 720) additional annual deaths attributable to the change in temperature in 2025 relative to the average from the baseline period of 1960-1990. For 2050, the estimate increases to 1,610 deaths per year during the warm season. For Catalonia as a whole, the point estimates for those two years are 720 and 2,330 deaths per year, respectively, or about 2 and 3% of the warm season. In comparing these predicted impacts with current causes of mortality, they clearly represent significant burdens to public health in Catalonia.

[The safety of biologics : a risk-benefit assessment of treating rheumatoid arthritis with biologics based on registry data on mortality].

PubMed

Sander, O

2010-11-01

The aim of this study is a risk-benefit assessment of treating rheumatoid arthritis with biologics based on registry data on mortality.UK, Sweden and Spain have published evaluable data on mortality. A parallel control group was conducted in the UK. Sweden and Spain used an historical cohort for comparison.Central registries supported British and Swedish research by sending details on all deaths. The variety of possible confounders prevents direct comparisons of the registers and safe predictions for individual patients.The death rate in TNF-inhibitor-treated patients is higher than in the general population but lower than in the control groups with RA. Thus comorbidities are not balanced, the weighted mortality rate scaled down the difference between exposed patients and controls. When TNF-inhibitors are given for the usual indication, mortality is reduced compared to conventional therapy.

Evaluation of MELD score and Maddrey discriminant function for mortality prediction in patients with alcoholic hepatitis.

PubMed

Monsanto, Pedro; Almeida, Nuno; Lrias, Clotilde; Pina, Jos Eduardo; Sofia, Carlos

2013-01-01

Maddrey discriminant function (DF) is the traditional model for evaluating the severity and prognosis in alcoholic hepatitis (AH). However, MELD has also been used for this purpose. We aimed to determine the predictive parameters and compare the ability of Maddrey DF and MELD to predict short-term mortality in patients with AH. Retrospective study of 45 patients admitted in our department with AH between 2000 and 2010. Demographic, clinical and laboratory parameters were collected. MELD and Maddrey DF were calculated on admission. Short-term mortality was assessed at 30 and 90 days. Student t-test, χ2 test, univariate analysis, logistic regression and receiver operating characteristic curves were performed. Thirty-day and 90-day mortality was 27% and 42%, respectively. In multivariate analysis, Maddrey DF was the only independent predictor of mortality for these two periods. Receiver operating characteristic curves for Maddrey DF revealed an excellent discriminatory ability to predict 30-day and 90-day mortality for a Maddrey DF greater than 65 and 60, respectively. Discriminatory ability to predict 30-day and 90-day mortality for MELD was low. AH remains associated with a high short-term mortality. Maddrey DF is a more valuable model than MELD to predict short-term mortality in patients with AH.

Comparison of AIMS65, Glasgow–Blatchford score, and Rockall score in a European series of patients with upper gastrointestinal bleeding: performance when predicting in-hospital and delayed mortality

PubMed Central

Martínez-Cara, Juan G; Jiménez-Rosales, Rita; Úbeda-Muñoz, Margarita; de Hierro, Mercedes López; de Teresa, Javier

2015-01-01

Objective AIMS65 is a score designed to predict in-hospital mortality, length of stay, and costs of gastrointestinal bleeding. Our aims were to revalidate AIMS65 as predictor of inpatient mortality and to compare AIMS65’s performance with that of Glasgow–Blatchford (GBS) and Rockall scores (RS) with regard to mortality, and the secondary outcomes of a composite endpoint of severity, transfusion requirements, rebleeding, delayed (6-month) mortality, and length of stay. Methods The study included 309 patients. Clinical and biochemical data, transfusion requirements, endoscopic, surgical, or radiological treatments, and outcomes for 6 months after admission were collected. Clinical outcomes were in-hospital mortality, delayed mortality, rebleeding, composite endpoint, blood transfusions, and length of stay. Results In receiver-operating characteristic curve analyses, AIMS65, GBS, and RS were similar when predicting inpatient mortality (0.76 vs. 0.78 vs. 0.78). Regarding endoscopic intervention, AIMS65 and GBS were identical (0.62 vs. 0.62). AIMS65 was useless when predicting rebleeding compared to GBS or RS (0.56 vs. 0.70 vs. 0.71). GBS was better at predicting the need for transfusions. No patient with AIMS65 = 0, GBS ≤ 6, or RS ≤ 4 died. Considering the composite endpoint, an AIMS65 of 0 did not exclude high risk patients, but a GBS ≤ 1 or RS ≤ 2 did. The three scores were similar in predicting prolonged in-hospital stay. Delayed mortality was better predicted by AIMS65. Conclusion AIMS65 is comparable to GBS and RS in essential endpoints such as inpatient mortality, the need for endoscopic intervention and length of stay. GBS is a better score predicting rebleeding and the need for transfusion, but AIMS65 shows a better performance predicting delayed mortality. PMID:27403303

Predicting post-fire tree mortality for 12 western US conifers using the First-Order Fire Effects Model (FOFEM)

Treesearch

Sharon Hood; Duncan Lutes

2017-01-01

Accurate prediction of fire-caused tree mortality is critical for making sound land management decisions such as developing burning prescriptions and post-fire management guidelines. To improve efforts to predict post-fire tree mortality, we developed 3-year post-fire mortality models for 12 Western conifer species - white fir (Abies concolor [Gord. &...

Response of branch growth and mortality to silvicultural treatments in coastal Douglas-fir plantations: implications for predicting tree growth.

Treesearch

A.R. Weiskittel; D. Maguire; R.A. Monserud

2007-01-01

Static models of individual tree crown attributes such as height to crown base and maximum branch diameter profile have been developed for several commercially important species. Dynamic models of individual branch growth and mortality have received less attention, but have generally been developed retrospectively by dissecting felled trees; however, this approach is...

Using growth velocity to predict child mortality.

PubMed

Schwinger, Catherine; Fadnes, Lars T; Van den Broeck, Jan

2016-03-01

Growth assessment based on the WHO child growth velocity standards can potentially be used to predict adverse health outcomes. Nevertheless, there are very few studies on growth velocity to predict mortality. We aimed to determine the ability of various growth velocity measures to predict child death within 3 mo and to compare it with those of attained growth measures. Data from 5657 children <5 y old who were enrolled in a cohort study in the Democratic Republic of Congo were used. Children were measured up to 6 times in 3-mo intervals, and 246 (4.3%) children died during the study period. Generalized estimating equation (GEE) models informed the mortality risk within 3 mo for weight and length velocity z scores and 3-mo changes in midupper arm circumference (MUAC). We used receiver operating characteristic (ROC) curves to present balance in sensitivity and specificity to predict child death. GEE models showed that children had an exponential increase in the risk of dying with decreasing growth velocity in all 4 indexes (1.2- to 2.4-fold for every unit decrease). A length and weight velocity z score of <-3 was associated with an 11.8- and a 7.9-fold increase, respectively, in the RR of death in the subsequent 3-mo period (95% CIs: 3.9, 35.5, and 3.9, 16.2, respectively). Weight and length velocity z scores had better predictive abilities [area under the ROC curves (AUCs) of 0.67 and 0.69] than did weight-for-age (AUC: 0.57) and length-for-age (AUC: 0.52) z scores. Among wasted children (weight-for-height z score <-2), the AUC of weight velocity z scores was 0.87. Absolute MUAC performed best among the attained indexes (AUC: 0.63), but longitudinal assessment of MUAC-based indexes did not increase the predictive value. Although repeated growth measures are slightly more complex to implement, their superiority in mortality-predictive abilities suggests that these could be used more for identifying children at increased risk of death.

Meta-analysis reveals that hydraulic traits explain cross-species patterns of drought-induced tree mortality across the globe.

PubMed

Anderegg, William R L; Klein, Tamir; Bartlett, Megan; Sack, Lawren; Pellegrini, Adam F A; Choat, Brendan; Jansen, Steven

2016-05-03

Drought-induced tree mortality has been observed globally and is expected to increase under climate change scenarios, with large potential consequences for the terrestrial carbon sink. Predicting mortality across species is crucial for assessing the effects of climate extremes on forest community biodiversity, composition, and carbon sequestration. However, the physiological traits associated with elevated risk of mortality in diverse ecosystems remain unknown, although these traits could greatly improve understanding and prediction of tree mortality in forests. We performed a meta-analysis on species' mortality rates across 475 species from 33 studies around the globe to assess which traits determine a species' mortality risk. We found that species-specific mortality anomalies from community mortality rate in a given drought were associated with plant hydraulic traits. Across all species, mortality was best predicted by a low hydraulic safety margin-the difference between typical minimum xylem water potential and that causing xylem dysfunction-and xylem vulnerability to embolism. Angiosperms and gymnosperms experienced roughly equal mortality risks. Our results provide broad support for the hypothesis that hydraulic traits capture key mechanisms determining tree death and highlight that physiological traits can improve vegetation model prediction of tree mortality during climate extremes.

Data mining identifies Digit Symbol Substitution Test score and serum cystatin C as dominant predictors of mortality in older men and women.

PubMed

Swindell, William R; Cummings, Steven R; Sanders, Jason L; Caserotti, Paolo; Rosano, Caterina; Satterfield, Suzanne; Strotmeyer, Elsa S; Harris, Tamara B; Simonsick, Eleanor M; Cawthon, Peggy M

2012-08-01

Characterization of long-term health trajectory in older individuals is important for proactive health management. However, the relative prognostic value of information contained in clinical profiles of nonfrail older adults is often unclear. We screened 825 phenotypic and genetic measures evaluated during the Health, Aging, and Body Composition Study (Health ABC) baseline visit (3,067 men and women aged 70-79). Variables that best predicted mortality over 13 years of follow-up were identified using 10-fold cross-validation. Mortality was most strongly associated with low Digit Symbol Substitution Test (DSST) score (DSST<25; 21.9% of cohort; hazard ratio [HR]=1.87±0.06) and elevated serum cystatin C (≥1.30 mg/mL; 12.1% of cohort; HR=2.25±0.07). These variables predicted mortality better than 823 other measures, including baseline age and a 45-variable health deficit index. Given elevated cystatin C (≥1.30 mg/mL), mortality risk was further increased by high serum creatinine, high abdominal visceral fat density, and smoking history (2.52≤HR ≤3.73). Given a low DSST score (<25) combined with low-to-moderate cystatin C (<1.30 mg/mL), mortality risk was highest among those with elevated plasma resistin and smoking history (1.90≤HR≤2.02). DSST score and serum cystatin C warrant priority consideration for the evaluation of mortality risk in older individuals. Both variables, taken individually, predict mortality better than chronological age or a health deficit index in well-functioning older adults (ages 70-79). DSST score and serum cystatin C can thus provide evidence-based tools for geriatric assessment.

Effectiveness and cost of reducing particle-related mortality with particle filtration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fisk, W. J.; Chan, W. R.

This study evaluates the mortality-related benefits and costs of improvements in particle filtration in U.S. homes and commercial buildings based on models with empirical inputs. The models account for time spent in various environments as well as activity levels and associated breathing rates. The scenarios evaluated include improvements in filter efficiencies in both forced-air heating and cooling systems of homes and heating, ventilating, and air conditioning systems of workplaces as well as use of portable air cleaners in homes. The predicted reductions in mortality range from approximately 0.25 to 2.4 per 10 000 population. The largest reductions in mortality were frommore » interventions with continuously operating portable air cleaners in homes because, given our scenarios, these portable air cleaners with HEPA filters most reduced particle exposures. For some interventions, predicted annual mortality-related economic benefits exceed $1000 per person. Economic benefits always exceed costs with benefit-to-cost ratios ranging from approximately 3.9 to 133. In conclusion, restricting interventions to homes of the elderly further increases the mortality reductions per unit population and the benefit-to-cost ratios.« less

Predicting mortality rates: Comparison of an administrative predictive model (hospital standardized mortality ratio) with a physiological predictive model (Acute Physiology and Chronic Health Evaluation IV)--A cross-sectional study.

PubMed

Toua, Rene Elaine; de Kock, Jacques Erasmus; Welzel, Tyson

2016-02-01

Direct comparison of mortality rates has limited value because most deaths are due to the disease process. Predicting the risk of death accurately remains a challenge. A cross-sectional study compared the expected mortality rate as calculated with an administrative model to a physiological model, Acute Physiology and Chronic Health Evaluation IV. The combined cohort and stratified samples (<0.1, 0.1-0.5, or >0.5 predicted mortality) were considered. A total of 47,982 patients were scored from 1 July 2013 to 30 June 2014, and 46,061 records were included in the analysis. A moderate correlation was shown for the combined cohort (Pearson correlation index, 0.618; 95% confidence interval [CI], 0.380-0.779; R(2) = 0.38). A very good correlation for the less than 10% stratum (Pearson correlation index, 0.884; R(2) = 0.78; 95% CI, 0.79-0.937) and a moderate correlation for 0.1 to 0.5 predicted mortality rates (Pearson correlation index, 0.782; R(2) = 0.61; 95% CI, 0.623-0.879). There was no significant positive correlation for the greater than 50% predicted mortality stratum (Pearson correlation index, 0.087; R(2) = 0.007; 95% CI, -0.23 to 0.387). At less than 0.1, the models are interchangeable, but in spite of a moderate correlation, greater than 0.1 hospital standardized mortality ratio cannot be used to predict mortality. Copyright © 2015 Elsevier Inc. All rights reserved.

Predictive Values of the New Sarcopenia Index by the Foundation for the National Institutes of Health Sarcopenia Project for Mortality among Older Korean Adults.

PubMed

Moon, Joon Ho; Kim, Kyoung Min; Kim, Jung Hee; Moon, Jae Hoon; Choi, Sung Hee; Lim, Soo; Lim, Jae-Young; Kim, Ki Woong; Park, Kyong Soo; Jang, Hak Chul

2016-01-01

We evaluated the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project's recommended criteria for sarcopenia's association with mortality among older Korean adults. We conducted a community-based prospective cohort study which included 560 (285 men and 275 women) older Korean adults aged ≥65 years. Muscle mass (appendicular skeletal muscle mass-to-body mass index ratio (ASM/BMI)), handgrip strength, and walking velocity were evaluated in association with all-cause mortality during 6-year follow-up. Both the lowest quintile for each parameter (ethnic-specific cutoff) and FNIH-recommended values were used as cutoffs. Forty men (14.0%) and 21 women (7.6%) died during 6-year follow-up. The deceased subjects were older and had lower ASM, handgrip strength, and walking velocity. Sarcopenia defined by both low lean mass and weakness had a 4.13 (95% CI, 1.69-10.11) times higher risk of death, and sarcopenia defined by a combination of low lean mass, weakness, and slowness had a 9.56 (3.16-28.90) times higher risk of death after adjusting for covariates in men. However, these significant associations were not observed in women. In terms of cutoffs of each parameter, using the lowest quintile showed better predictive values in mortality than using the FNIH-recommended values. Moreover, new muscle mass index, ASM/BMI, provided better prognostic values than ASM/height2 in all associations. New sarcopenia definition by FNIH was better able to predict 6-year mortality among Korean men. Moreover, ethnic-specific cutoffs, the lowest quintile for each parameter, predicted the higher risk of mortality than the FNIH-recommended values.

Predictive Values of the New Sarcopenia Index by the Foundation for the National Institutes of Health Sarcopenia Project for Mortality among Older Korean Adults

PubMed Central

Kim, Jung Hee; Moon, Jae Hoon; Choi, Sung Hee; Lim, Soo; Lim, Jae-Young; Kim, Ki Woong; Park, Kyong Soo; Jang, Hak Chul

2016-01-01

Objective We evaluated the Foundation for the National Institutes of Health (FNIH) Sarcopenia Project’s recommended criteria for sarcopenia’s association with mortality among older Korean adults. Methods We conducted a community-based prospective cohort study which included 560 (285 men and 275 women) older Korean adults aged ≥65 years. Muscle mass (appendicular skeletal muscle mass-to-body mass index ratio (ASM/BMI)), handgrip strength, and walking velocity were evaluated in association with all-cause mortality during 6-year follow-up. Both the lowest quintile for each parameter (ethnic-specific cutoff) and FNIH-recommended values were used as cutoffs. Results Forty men (14.0%) and 21 women (7.6%) died during 6-year follow-up. The deceased subjects were older and had lower ASM, handgrip strength, and walking velocity. Sarcopenia defined by both low lean mass and weakness had a 4.13 (95% CI, 1.69–10.11) times higher risk of death, and sarcopenia defined by a combination of low lean mass, weakness, and slowness had a 9.56 (3.16–28.90) times higher risk of death after adjusting for covariates in men. However, these significant associations were not observed in women. In terms of cutoffs of each parameter, using the lowest quintile showed better predictive values in mortality than using the FNIH-recommended values. Moreover, new muscle mass index, ASM/BMI, provided better prognostic values than ASM/height2 in all associations. Conclusions New sarcopenia definition by FNIH was better able to predict 6-year mortality among Korean men. Moreover, ethnic-specific cutoffs, the lowest quintile for each parameter, predicted the higher risk of mortality than the FNIH-recommended values. PMID:27832145

Cancer incidence and mortality in Serbia 1999–2009

PubMed Central

2013-01-01

Background Despite the increase in cancer incidence in the last years in Serbia, no nation-wide, population-based cancer epidemiology data have been reported. In this study cancer incidence and mortality rates for Serbia are presented using nation-wide data from two population-based cancer registries. These rates are additionally compared to European and global cancer epidemiology estimates. Finally, predictions on Serbian cancer incidence and mortality rates are provided. Methods Cancer incidence and mortality was collected from the cancer registries of Central Serbia and Vojvodina from 1999 to 2009. Using age-specific regression models, we estimated time trends and predictions for cancer incidence and mortality for the following five years (2010–2014). The comparison of Serbian with European and global cancer incidence/mortality rates, adjusted to the world population (ASR-W) was performed using Serbian population-based data and estimates from GLOBOCAN 2008. Results Increasing trends in both overall cancer incidence and mortality rates were identified for Serbia. In men, lung cancer showed the highest incidence (ASR-W 2009: 70.8/100,000), followed by colorectal (ASR-W 2009: 39.9/100,000), prostate (ASR-W 2009: 29.1/100,000) and bladder cancer (ASR-W 2009: 16.2/100,000). Breast cancer was the most common form of cancer in women (ASR-W 2009: 70.8/100,000) followed by cervical (ASR-W 2009: 25.5/100,000), colorectal (ASR-W 2009: 21.1/100,000) and lung cancer (ASR-W 2009: 19.4/100,000). Prostate and colorectal cancers have been significantly increasing over the last years in men, while this was also observed for breast cancer incidence and lung cancer mortality in women. In 2008 Serbia had the highest mortality rate from breast cancer (ASR-W 2008: 22.7/100,000), among all European countries while incidence and mortality of cervical, lung and colorectal cancer were well above European estimates. Conclusion Cancer incidence and mortality in Serbia has been generally increasing over the past years. For a number of cancer sites, incidence and mortality is alarmingly higher than in the majority of European regions. For this increasing trend to be controlled, the management of risk factors that are present among the Serbian population is necessary. Additionally, prevention and early diagnosis are areas where significant improvements could still be made. PMID:23320890

Cancer incidence and mortality in Serbia 1999-2009.

PubMed

Mihajlović, Jovan; Pechlivanoglou, Petros; Miladinov-Mikov, Marica; Zivković, Snežana; Postma, Maarten J

2013-01-15

Despite the increase in cancer incidence in the last years in Serbia, no nation-wide, population-based cancer epidemiology data have been reported. In this study cancer incidence and mortality rates for Serbia are presented using nation-wide data from two population-based cancer registries. These rates are additionally compared to European and global cancer epidemiology estimates. Finally, predictions on Serbian cancer incidence and mortality rates are provided. Cancer incidence and mortality was collected from the cancer registries of Central Serbia and Vojvodina from 1999 to 2009. Using age-specific regression models, we estimated time trends and predictions for cancer incidence and mortality for the following five years (2010-2014). The comparison of Serbian with European and global cancer incidence/mortality rates, adjusted to the world population (ASR-W) was performed using Serbian population-based data and estimates from GLOBOCAN 2008. Increasing trends in both overall cancer incidence and mortality rates were identified for Serbia. In men, lung cancer showed the highest incidence (ASR-W 2009: 70.8/100,000), followed by colorectal (ASR-W 2009: 39.9/100,000), prostate (ASR-W 2009: 29.1/100,000) and bladder cancer (ASR-W 2009: 16.2/100,000). Breast cancer was the most common form of cancer in women (ASR-W 2009: 70.8/100,000) followed by cervical (ASR-W 2009: 25.5/100,000), colorectal (ASR-W 2009: 21.1/100,000) and lung cancer (ASR-W 2009: 19.4/100,000). Prostate and colorectal cancers have been significantly increasing over the last years in men, while this was also observed for breast cancer incidence and lung cancer mortality in women. In 2008 Serbia had the highest mortality rate from breast cancer (ASR-W 2008: 22.7/100,000), among all European countries while incidence and mortality of cervical, lung and colorectal cancer were well above European estimates. Cancer incidence and mortality in Serbia has been generally increasing over the past years. For a number of cancer sites, incidence and mortality is alarmingly higher than in the majority of European regions. For this increasing trend to be controlled, the management of risk factors that are present among the Serbian population is necessary. Additionally, prevention and early diagnosis are areas where significant improvements could still be made.

Modeling the shape and composition of the human body using dual energy X-ray absorptiometry images

PubMed Central

Shepherd, John A.; Fan, Bo; Schwartz, Ann V.; Cawthon, Peggy; Cummings, Steven R.; Kritchevsky, Stephen; Nevitt, Michael; Santanasto, Adam; Cootes, Timothy F.

2017-01-01

There is growing evidence that body shape and regional body composition are strong indicators of metabolic health. The purpose of this study was to develop statistical models that accurately describe holistic body shape, thickness, and leanness. We hypothesized that there are unique body shape features that are predictive of mortality beyond standard clinical measures. We developed algorithms to process whole-body dual-energy X-ray absorptiometry (DXA) scans into body thickness and leanness images. We performed statistical appearance modeling (SAM) and principal component analysis (PCA) to efficiently encode the variance of body shape, leanness, and thickness across sample of 400 older Americans from the Health ABC study. The sample included 200 cases and 200 controls based on 6-year mortality status, matched on sex, race and BMI. The final model contained 52 points outlining the torso, upper arms, thighs, and bony landmarks. Correlation analyses were performed on the PCA parameters to identify body shape features that vary across groups and with metabolic risk. Stepwise logistic regression was performed to identify sex and race, and predict mortality risk as a function of body shape parameters. These parameters are novel body composition features that uniquely identify body phenotypes of different groups and predict mortality risk. Three parameters from a SAM of body leanness and thickness accurately identified sex (training AUC = 0.99) and six accurately identified race (training AUC = 0.91) in the sample dataset. Three parameters from a SAM of only body thickness predicted mortality (training AUC = 0.66, validation AUC = 0.62). Further study is warranted to identify specific shape/composition features that predict other health outcomes. PMID:28423041

Comparison of Nutritional Risk Scores for Predicting Mortality in Japanese Chronic Hemodialysis Patients.

PubMed

Takahashi, Hiroshi; Inoue, Keiko; Shimizu, Kazue; Hiraga, Keiko; Takahashi, Erika; Otaki, Kaori; Yoshikawa, Taeko; Furuta, Kumiko; Tokunaga, Chika; Sakakibara, Tomoyo; Ito, Yasuhiko

2017-05-01

Protein energy wasting (PEW) is consistently associated with poor prognosis in hemodialysis (HD) patients. We compared the predictability of PEW as diagnosed by The International Society of Renal Nutrition and Metabolism criteria (PEW ISRNM ) and geriatric nutritional risk index (GNRI) for all-cause mortality in Japanese HD patients. As cut-off values for body mass index (BMI) for PEW have not been established in PEW ISRNM for Asian populations, these were also investigated. The nutritional status from 409 HD patients was evaluated according to ISRNM and GNRI criteria. To compare the predictability of mortality, C-index, net reclassification improvement (NRI) and integrated discrimination improvement were evaluated. During follow-up (median, 52 months; range, 7 months), 70 patients (17.1%) presented PEW according to ISRNM and 131 patients (32.1%) according to GNRI; in addition, 101 patients (24.7%) died. PEW ISRNM and GNRI were identified as independent predictors of death. Addition of PEW ISRNM and GNRI to a predictive model based on established risk factors improved NRI and integrated discrimination improvement. However, no differences were found between models including PEW ISRNM and GNRI. When lowering the criterion level of BMI per 1 kg/m 2 sequentially, PEW ISRNM at BMI <20 kg/m 2 maximized the hazard ratio for mortality. The model including PEW ISRNM at BMI <20 kg/m 2 improved NRI compared with the model including GNRI. PEW ISRNM and GNRI represent independent predictors of mortality, with comparable predictability. The diagnostic criterion of BMI in the ISRNM for Japanese population might be better at <20 kg/m 2 than at <23 kg/m 2 . Copyright © 2016 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Comparison of National Operative Mortality in Gastroenterological Surgery Using Web-based Prospective Data Entry Systems.

PubMed

Anazawa, Takayuki; Paruch, Jennifer L; Miyata, Hiroaki; Gotoh, Mitsukazu; Ko, Clifford Y; Cohen, Mark E; Hirahara, Norimichi; Zhou, Lynn; Konno, Hiroyuki; Wakabayashi, Go; Sugihara, Kenichi; Mori, Masaki

2015-12-01

International collaboration is important in healthcare quality evaluation; however, few international comparisons of general surgery outcomes have been accomplished. Furthermore, predictive model application for risk stratification has not been internationally evaluated. The National Clinical Database (NCD) in Japan was developed in collaboration with the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP), with a goal of creating a standardized surgery database for quality improvement. The study aimed to compare the consistency and impact of risk factors of 3 major gastroenterological surgical procedures in Japan and the United States (US) using web-based prospective data entry systems: right hemicolectomy (RH), low anterior resection (LAR), and pancreaticoduodenectomy (PD).Data from NCD and ACS-NSQIP, collected over 2 years, were examined. Logistic regression models were used for predicting 30-day mortality for both countries. Models were exchanged and evaluated to determine whether the models built for one population were accurate for the other population.We obtained data for 113,980 patients; 50,501 (Japan: 34,638; US: 15,863), 42,770 (Japan: 35,445; US: 7325), and 20,709 (Japan: 15,527; US: 5182) underwent RH, LAR, and, PD, respectively. Thirty-day mortality rates for RH were 0.76% (Japan) and 1.88% (US); rates for LAR were 0.43% versus 1.08%; and rates for PD were 1.35% versus 2.57%. Patient background, comorbidities, and practice style were different between Japan and the US. In the models, the odds ratio for each variable was similar between NCD and ACS-NSQIP. Local risk models could predict mortality using local data, but could not accurately predict mortality using data from other countries.We demonstrated the feasibility and efficacy of the international collaborative research between Japan and the US, but found that local risk models remain essential for quality improvement.

External validation of a multivariable claims-based rule for predicting in-hospital mortality and 30-day post-pulmonary embolism complications.

PubMed

Coleman, Craig I; Peacock, W Frank; Fermann, Gregory J; Crivera, Concetta; Weeda, Erin R; Hull, Michael; DuCharme, Mary; Becker, Laura; Schein, Jeff R

2016-10-22

Low-risk pulmonary embolism (PE) patients may be candidates for outpatient treatment or abbreviated hospital stay. There is a need for a claims-based prediction rule that payers/hospitals can use to risk stratify PE patients. We sought to validate the In-hospital Mortality for PulmonAry embolism using Claims daTa (IMPACT) prediction rule for in-hospital and 30-day outcomes. We used the Optum Research Database from 1/2008-3/2015 and included adults hospitalized for PE (415.1x in the primary position or secondary position when accompanied by a primary code for a PE complication) and having continuous medical and prescription coverage for ≥6-months prior and 3-months post-inclusion or until death. In-hospital and 30-day mortality and 30-day complications (recurrent venous thromboembolism, rehospitalization or death) were assessed and prognostic accuracies of IMPACT with 95 % confidence intervals (CIs) were calculated. In total, 47,531 PE patients were included. In-hospital and 30-day mortality occurred in 7.9 and 9.4 % of patients and 20.8 % experienced any complication within 30-days. Of the 19.5 % of patients classified as low-risk by IMPACT, 2.0 % died in-hospital, resulting in a sensitivity and specificity of 95.2 % (95 % CI, 94.4-95.8) and 20.7 % (95 % CI, 20.4-21.1). Only 1 additional low-risk patient died within 30-days of admission and 12.2 % experienced a complication, translating into a sensitivity and specificity of 95.9 % (95 % CI, 95.3-96.5) and 21.1 % (95 % CI, 20.7-21.5) for mortality and 88.5 % (95 % CI, 87.9-89.2) and 21.6 % (95 % CI, 21.2-22.0) for any complication. IMPACT had acceptable sensitivity for predicting in-hospital and 30-day mortality or complications and may be valuable for retrospective risk stratification of PE patients.

Basic arterial blood gas biomarkers as a predictor of mortality in tetralogy of Fallot patients.

PubMed

Bhardwaj, Vandana; Kapoor, Poonam Malhotra; Irpachi, Kalpana; Ladha, Suruchi; Chowdhury, Ujjwal Kumar

2017-01-01

Serum lactate and base deficit have been shown to be a predictor of morbidity and mortality in critically ill patients. Poor preoperative oxygenation appears to be one of the significant factors that affects early mortality in tetralogy of Fallot (TOF). There is little published literature evaluating the utility of serum lactate, base excess (BE), and oxygen partial pressure (PO 2 ) as simple, widely available, prognostic markers in patients undergoing surgical repair of TOF. This prospective, observational study was conducted in 150 TOF patients, undergoing elective intracardiac repair. PO 2 , BE, and lactate levels at three different time intervals were recorded. Arterial blood samples were collected after induction (T1), after cardiopulmonary bypass (T2), and 48 h (T3) after surgery in the Intensive Care Unit (ICU). To observe the changes in PO 2 , BE, and lactate levels over a period of time, repeated measures analysis was performed with Bonferroni method. The receiver operating characteristics (ROC) analysis was used to find area under curve (AUC) and cutoff values of various biomarkers for predicting mortality in ICU. The patients who could not survive showed significant elevated lactate levels at baseline (T1) and postoperatively (T2) as compared to patients who survived after surgery (P < 0.001). However, in nonsurvivors, the BE value decreased significantly in the postoperative period in comparison to survivors (-2.8 ± 4.27 vs. 5.04 ± 2.06) (P < 0.001). In nonsurvivors, there was a significant fall of PO 2 to a mean value of 59.86 ± 15.09 in ICU (T3), whereas those who survived had a PO 2 of 125.86 ± 95.09 (P < 0.001). The ROC curve analysis showed that lactate levels (T3) have highest mortality predictive value (AUC: 96.9%) as compared to BE (AUC: 94.5%) and PO 2 (AUC: 81.1%). Serum lactate and BE may be used as prognostic markers to predict mortality in patients undergoing TOF repair. The routine analysis of these simple, fast, widely available, and cost-effective biomarkers should be encouraged to predict prognosis of TOF patients.

Metabonomics Analysis of Plasma Reveals the Lactate to Cholesterol Ratio as an Independent Prognostic Factor of Short-Term Mortality in Acute Heart Failure

PubMed Central

Desmoulin, Franck; Galinier, Michel; Trouillet, Charlotte; Berry, Matthieu; Delmas, Clément; Turkieh, Annie; Massabuau, Pierre; Taegtmeyer, Heinrich; Smih, Fatima; Rouet, Philippe

2013-01-01

Objective Mortality in heart failure (AHF) remains high, especially during the first days of hospitalization. New prognostic biomarkers may help to optimize treatment. The aim of the study was to determine metabolites that have a high prognostic value. Methods We conducted a prospective study on a training cohort of AHF patients (n = 126) admitted in the cardiac intensive care unit and assessed survival at 30 days. Venous plasmas collected at admission were used for 1H NMR – based metabonomics analysis. Differences between plasma metabolite profiles allow determination of discriminating metabolites. A cohort of AHF patients was subsequently constituted (n = 74) to validate the findings. Results Lactate and cholesterol were the major discriminating metabolites predicting 30-day mortality. Mortality was increased in patients with high lactate and low total cholesterol concentrations at admission. Accuracies of lactate, cholesterol concentration and lactate to cholesterol (Lact/Chol) ratio to predict 30-day mortality were evaluated using ROC analysis. The Lact/Chol ratio provided the best accuracy with an AUC of 0.82 (P < 0.0001). The acute physiology and chronic health evaluation (APACHE) II scoring system provided an AUC of 0.76 for predicting 30-day mortality. APACHE II score, Cardiogenic shock (CS) state and Lact/Chol ratio ≥ 0.4 (cutoff value with 82% sensitivity and 64% specificity) were significant independent predictors of 30-day mortality with hazard ratios (HR) of 1.11, 4.77 and 3.59, respectively. In CS patients, the HR of 30-day mortality risk for plasma Lact/Chol ratio ≥ 0.4 was 3.26 compared to a Lact/Chol ratio of < 0.4 (P  =  0.018). The predictive power of the Lact/Chol ratio for 30-day mortality outcome was confirmed with the independent validation cohort. Conclusion This study identifies the plasma Lact/Chol ratio as a useful objective and simple parameter to evaluate short term prognostic and could be integrated into quantitative guidance for decision making in heart failure care. PMID:23573279

Anion gap as a prognostic tool for risk stratification in critically ill patients - a systematic review and meta-analysis.

PubMed

Glasmacher, Stella Andrea; Stones, William

2016-08-30

Lactate concentration is a robust predictor of mortality but in many low resource settings facilities for its analysis are not available. Anion gap (AG), calculated from clinical chemistry results, is a marker of metabolic acidosis and may be more easily obtained in such settings. In this systematic review and meta-analysis we investigated whether the AG predicts mortality in adult patients admitted to critical care settings. We searched Medline, Embase, Web of Science, Scopus, The Cochrane Library and regional electronic databases from inception until May 2016. Studies conducted in any clinical setting that related AG to in-hospital mortality, in-intensive care unit mortality, 31-day mortality or comparable outcome measures were eligible for inclusion. Methodological quality of included studies was assessed using the Quality in Prognostic Studies tool. Descriptive meta-analysis was performed and the I(2) test was used to quantify heterogeneity. Subgroup analysis was undertaken to identify potential sources of heterogeneity between studies. Nineteen studies reporting findings in 12,497 patients were included. Overall, quality of studies was poor and most studies were rated as being at moderate or high risk of attrition bias and confounding. There was substantial diversity between studies with regards to clinical setting, age and mortality rates of patient cohorts. High statistical heterogeneity was found in the meta-analyses of area under the ROC curve (I(2) = 99 %) and mean difference (I(2) = 97 %) for the observed AG. Three studies reported good discriminatory power of the AG to predict mortality and were responsible for a large proportion of statistical heterogeneity. The remaining 16 studies reported poor to moderate ability of the AG to predict mortality. Subgroup analysis suggested that intravenous fluids affect the ability of the AG to predict mortality. Based on the limited quality of available evidence, a single AG measurement cannot be recommended for risk stratification in critically ill patients. The probable influence of intravenous fluids on AG levels renders the AG an impractical tool in clinical practice. Future research should focus on increasing the availability of lactate monitoring in low resource settings. CRD42015015249 . Registered on 4th February 2015.

External validation of the CAPRA-S score to predict biochemical recurrence, metastasis and mortality after radical prostatectomy in a European cohort.

PubMed

Tilki, Derya; Mandel, Philipp; Schlomm, Thorsten; Chun, Felix K-H; Tennstedt, Pierre; Pehrke, Dirk; Haese, Alexander; Huland, Hartwig; Graefen, Markus; Salomon, Georg

2015-06-01

The CAPRA-S score predicts prostate cancer recurrence based on pathological information from radical prostatectomy. To our knowledge CAPRA-S has never been externally validated in a European cohort. We independently validated CAPRA-S in a single institution European database. The study cohort comprised 14,532 patients treated with radical prostatectomy between January 1992 and August 2012. Prediction of biochemical recurrence, metastasis and cancer specific mortality by CAPRA-S was assessed by Kaplan-Meier analysis and the c-index. CAPRA-S performance to predict biochemical recurrence was evaluated by calibration plot and decision curve analysis. Median followup was 50.8 months (IQR 25.0-96.0). Biochemical recurrence developed in 20.3% of men at a median of 21.2 months (IQR 7.7-44.9). When stratifying patients by CAPRA-S risk group, estimated 5-year biochemical recurrence-free survival was 91.4%, 70.4% and 29.3% in the low, intermediate and high risk groups, respectively. The CAPRA-S c-index to predict biochemical recurrence, metastasis and cancer specific mortality was 0.80, 0.85 and 0.88, respectively. Metastasis developed in 417 men and 196 men died of prostate cancer. The CAPRA-S score was accurate when applied in a European study cohort. It predicted biochemical recurrence, metastasis and cancer specific mortality after radical prostatectomy with a c-index of greater than 0.80. The score can be valuable in regard to decision making for adjuvant therapy. Copyright © 2015. Published by Elsevier Inc.

Which dogs with appendicular osteosarcoma benefit most from chemotherapy after surgery? Results from an individual patient data meta-analysis.

PubMed

Schmidt, A F; Groenwold, R H H; Amsellem, P; Bacon, N; Klungel, O H; Hoes, A W; de Boer, A; Kow, K; Maritato, K; Kirpensteijn, J; Nielen, M

2016-03-01

Osteosarcoma (OS) is a malignant tumor of mesenchymal origin that produces osteoid. Given that the prognosis can vary considerably between dogs, we aimed to explore whether treatment could be tailored towards patient subgroups, characterized by their predicted risk of mortality. For the current study, a subset of five nonrandomized studies (400 subjects of whom 88 were dead at 5 months follow-up) was used from a previously published 20 study individual patient data meta-analysis. Missing data was dependent on observed variables and was imputed to correct for this dependency. Based on a previously published multivariable prognostic model, the 5-month mortality risk was predicted. Subsequently, in surgically treated dogs, using a logistic regression model with a random intercept for a study indicator, we explored whether chemotherapy effectiveness depended on predicted 5-month mortality risk. After adjustment for potential confounders the main effect of any chemotherapy was 0.48 (odds ratio) (95%CI 0.30; 0.78). Testing for chemotherapy by predicted 5-month mortality risk interaction revealed that the effects of any chemotherapy decreased with increasing predicted risk; interaction OR 3.41 (1.07; 10.84). Results from individually comparing carboplatin, cisplatin, doxorubicin and doxorubicin combination therapy to no chemotherapy, were similar in magnitude and direction. These results indicate that the main treatment effects of chemotherapy do not necessarily apply to all patients. Copyright © 2015 Elsevier B.V. All rights reserved.

Predicting mortality among older adults hospitalized for community-acquired pneumonia: an enhanced confusion, urea, respiratory rate and blood pressure score compared with pneumonia severity index.

PubMed

Abisheganaden, John; Ding, Yew Yoong; Chong, Wai-Fung; Heng, Bee-Hoon; Lim, Tow Keang

2012-08-01

Pneumonia Severity Index (PSI) predicts mortality better than Confusion, Urea >7 mmol/L, Respiratory rate >30/min, low Blood pressure: diastolic blood pressure <60 mm Hg or systolic blood pressure <90 mm Hg, and age >65 years (CURB-65) for community-acquired pneumonia (CAP) but is more cumbersome. The objective was to determine whether CURB enhanced with a small number of additional variables can predict mortality with at least the same accuracy as PSI. Retrospective review of medical records and administrative data of adults aged 55 years or older hospitalized for CAP over 1 year from three hospitals. For 1052 hospital admissions of unique patients, 30-day mortality was 17.2%. PSI class and CURB-65 predicted 30-day mortality with area under curve (AUC) of 0.77 (95% confidence interval (CI): 0.73-0.80) and 0.70 (95% CI: 0.66-0.74) respectively. When age and three co-morbid conditions (metastatic cancer, solid tumours without metastases and stroke) were added to CURB, the AUC improved to 0.80 (95% CI: 0.77-0.83). Bootstrap validation obtained an AUC estimate of 0.78, indicating negligible overfitting of the model. Based on this model, a clinical score (enhanced CURB score) was developed that had possible values from 5 to 25. Its AUC was 0.79 (95% CI: 0.76-0.83) and remained similar to that of PSI class. An enhanced CURB score predicted 30-day mortality with at least the same accuracy as PSI class did among older adults hospitalized for CAP. External validation of this score in other populations is the next step to determine whether it can be used more widely. © 2012 The Authors. Respirology © 2012 Asian Pacific Society of Respirology.

Value of Excess Pressure Integral for Predicting 15-Year All-Cause and Cardiovascular Mortalities in End-Stage Renal Disease Patients.

PubMed

Huang, Jui-Tzu; Cheng, Hao-Min; Yu, Wen-Chung; Lin, Yao-Ping; Sung, Shih-Hsien; Wang, Jiun-Jr; Wu, Chung-Li; Chen, Chen-Huan

2017-11-29

The excess pressure integral (XSPI), derived from analysis of the arterial pressure curve, may be a significant predictor of cardiovascular events in high-risk patients. We comprehensively investigated the prognostic value of XSPI for predicting long-term mortality in end-stage renal disease patients undergoing regular hemodialysis. A total of 267 uremic patients (50.2% female; mean age 54.2±14.9 years) receiving regular hemodialysis for more than 6 months were enrolled. Cardiovascular parameters were obtained by echocardiography and applanation tonometry. Calibrated carotid arterial pressure waveforms were analyzed according to the wave-transmission and reservoir-wave theories. Multivariable Cox proportional hazard models were constructed to account for age, sex, diabetes mellitus, albumin, body mass index, and hemodialysis treatment adequacy. Incremental utility of the parameters to risk stratification was assessed by net reclassification improvement. During a median follow-up of 15.3 years, 124 deaths (46.4%) incurred. Baseline XSPI was significantly predictive of all-cause (hazard ratio per 1 SD 1.4, 95% confidence interval 1.15-1.70, P =0.0006) and cardiovascular mortalities (1.47, 1.18-1.84, P =0.0006) after accounting for the covariates. The addition of XSPI to the base prognostic model significantly improved prediction of both all-cause mortality (net reclassification improvement=0.1549, P =0.0012) and cardiovascular mortality (net reclassification improvement=0.1535, P =0.0033). XSPI was superior to carotid-pulse wave velocity, forward and backward wave amplitudes, and left ventricular ejection fraction in consideration of overall independent and incremental prognostics values. In end-stage renal disease patients undergoing regular hemodialysis, XSPI was significantly predictive of long-term mortality and demonstrated an incremental value to conventional prognostic factors. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Weight-based determination of fluid overload status and mortality in pediatric intensive care unit patients requiring continuous renal replacement therapy

PubMed Central

Selewski, David T.; Cornell, Timothy T.; Lombel, Rebecca M.; Blatt, Neal B.; Han, Yong Y.; Mottes, Theresa; Kommareddi, Mallika; Kershaw, David B.; Shanley, Thomas P.; Heung, Michael

2012-01-01

Purpose In pediatric intensive care unit (PICU) patients, fluid overload (FO) at initiation of continuous renal replacement therapy (CRRT) has been reported to be an independent risk factor for mortality. Previous studies have calculated FO based on daily fluid balance during ICU admission, which is labor intensive and error prone. We hypothesized that a weight-based definition of FO at CRRT initiation would correlate with the fluid balance method and prove predictive of outcome. Methods This is a retrospective single-center review of PICU patients requiring CRRT from July 2006 through February 2010 (n = 113). We compared the degree of FO at CRRT initiation using the standard fluid balance method versus methods based on patient weight changes assessed by both univariate and multivariate analyses. Results The degree of fluid overload at CRRT initiation was significantly greater in nonsurvivors, irrespective of which method was used. The univariate odds ratio for PICU mortality per 1% increase in FO was 1.056 [95% confidence interval (CI) 1.025, 1.087] by the fluid balance method, 1.044 (95% CI 1.019, 1.069) by the weight-based method using PICU admission weight, and 1.045 (95% CI 1.022, 1.07) by the weight-based method using hospital admission weight. On multivariate analyses, all three methods approached significance in predicting PICU survival. Conclusions Our findings suggest that weight-based definitions of FO are useful in defining FO at CRRT initiation and are associated with increased mortality in a broad PICU patient population. This study provides evidence for a more practical weight-based definition of FO that can be used at the bedside. PMID:21533569

Do commonly used frailty models predict mortality, loss of autonomy and mental decline in older adults in northwestern Russia? A prospective cohort study.

PubMed

Turusheva, Anna; Frolova, Elena; Korystina, Elena; Zelenukha, Dmitry; Tadjibaev, Pulodjon; Gurina, Natalia; Turkeshi, Eralda; Degryse, Jean-Marie

2016-05-09

Frailty prevalence differs across countries depending on the models used to assess it that are based on various conceptual and operational definitions. This study aims to assess the clinical validity of three frailty models among community-dwelling older adults in north-western Russia where there is a higher incidence of cardiovascular disease and lower life expectancy than in European countries. The Crystal study is a population-based prospective cohort study in Kolpino, St. Petersburg, Russia. A random sample of the population living in the district was stratified into two age groups: 65-75 (n = 305) and 75+ (n = 306) and had a baseline comprehensive health assessment followed by a second one after 33.4 +/-3 months. The total observation time was 47 +/-14.6 months. Frailty was assessed according to the models of Fried, Puts and Steverink-Slaets. Its association with mortality at 5 years follow-up as well as dependency, mental and physical decline at around 2.5 years follow up was explored by multivariable and time-to-event analyses. Mortality was predicted independently from age, sex and comorbidities only by the frail status of the Fried model in those over 75 years old [HR (95 % CI) = 2.50 (1.20-5.20)]. Mental decline was independently predicted only by pre-frail [OR (95 % CI) = 0.24 (0.10-0.55)] and frail [OR (95 % CI) = 0.196 (0.06-0.67)] status of Fried model in those 65-75 years old. The prediction of dependency and physical decline by pre-frail and frail status of any the three frailty models was not statistically significant in this cohort of older adults. None of the three frailty models was valid at predicting 5 years mortality and disability, mental and physical decline at 2.5 years in a cohort of older adults in north-west Russia. Frailty by the Fried model had only limited value for mortality in those 75 years old and mental decline in those 65-75 years old. Further research is needed to identify valid frailty markers for older adults in this population.

Comparison of the Mortality Probability Admission Model III, National Quality Forum, and Acute Physiology and Chronic Health Evaluation IV hospital mortality models: implications for national benchmarking*.

PubMed

Kramer, Andrew A; Higgins, Thomas L; Zimmerman, Jack E

2014-03-01

To examine the accuracy of the original Mortality Probability Admission Model III, ICU Outcomes Model/National Quality Forum modification of Mortality Probability Admission Model III, and Acute Physiology and Chronic Health Evaluation IVa models for comparing observed and risk-adjusted hospital mortality predictions. Retrospective paired analyses of day 1 hospital mortality predictions using three prognostic models. Fifty-five ICUs at 38 U.S. hospitals from January 2008 to December 2012. Among 174,001 intensive care admissions, 109,926 met model inclusion criteria and 55,304 had data for mortality prediction using all three models. None. We compared patient exclusions and the discrimination, calibration, and accuracy for each model. Acute Physiology and Chronic Health Evaluation IVa excluded 10.7% of all patients, ICU Outcomes Model/National Quality Forum 20.1%, and Mortality Probability Admission Model III 24.1%. Discrimination of Acute Physiology and Chronic Health Evaluation IVa was superior with area under receiver operating curve (0.88) compared with Mortality Probability Admission Model III (0.81) and ICU Outcomes Model/National Quality Forum (0.80). Acute Physiology and Chronic Health Evaluation IVa was better calibrated (lowest Hosmer-Lemeshow statistic). The accuracy of Acute Physiology and Chronic Health Evaluation IVa was superior (adjusted Brier score = 31.0%) to that for Mortality Probability Admission Model III (16.1%) and ICU Outcomes Model/National Quality Forum (17.8%). Compared with observed mortality, Acute Physiology and Chronic Health Evaluation IVa overpredicted mortality by 1.5% and Mortality Probability Admission Model III by 3.1%; ICU Outcomes Model/National Quality Forum underpredicted mortality by 1.2%. Calibration curves showed that Acute Physiology and Chronic Health Evaluation performed well over the entire risk range, unlike the Mortality Probability Admission Model and ICU Outcomes Model/National Quality Forum models. Acute Physiology and Chronic Health Evaluation IVa had better accuracy within patient subgroups and for specific admission diagnoses. Acute Physiology and Chronic Health Evaluation IVa offered the best discrimination and calibration on a large common dataset and excluded fewer patients than Mortality Probability Admission Model III or ICU Outcomes Model/National Quality Forum. The choice of ICU performance benchmarks should be based on a comparison of model accuracy using data for identical patients.

General outcomes and risk factors for minor and major amputations in Brazil.

PubMed

Leite, Jose O; Costa, Leandro O; Fonseca, Walter M; Souza, Debora U; Goncalves, Barbara C; Gomes, Gabriela B; Cruz, Lucas A; Nister, Nilder; Navarro, Tulio P; Bath, Jonathan; Dardik, Alan

2018-06-01

Objectives Major and minor amputations are associated with significant rates of mortality. However, little is known about the impact of unplanned redo-amputation during the same hospitalization on outcomes. The objectives of this study were to identify the risk factors associated with in-hospital mortality after both major and minor amputations as well as the results of unplanned redo-amputation on outcome. Methods Retrospective study of 342 consecutive patients who were treated with lower extremity amputation in Brazil between January 2013 and October 2014. Results The in-hospital mortality rate was higher in major compared to minor amputation (25.6% vs. 4.1%; p < 0.0001). Whereas chronic kidney disease, chronic obstructive pulmonary disease, and planned staged amputation predicted in-hospital mortality after major amputation, age, and congestive heart failure predicted mortality after minor amputation. The white blood cell count predicted in-hospital mortality following both major and minor amputation. However, postoperative infection predicted in-hospital mortality only following major amputation. Conclusions In-hospital mortality was high after major amputations. Unplanned redo-amputation was not a predictor of in-hospital mortality after major or minor amputation. Planned staged amputation was associated with reduced survival after major but not minor amputation. Postoperative infection predicted mortality after major amputation. Systemic diseases and postoperative white blood cell were associated with in-hospital mortality. This study suggests a possible link between a pro-inflammatory state and increased in-hospital mortality following amputation.

Automated Prediction of Early Blood Transfusion and Mortality in Trauma Patients

DTIC Science & Technology

2014-09-24

We hypothesized that analysis of pulse oximeter signals could predict blood transfusion and mortality as accurately as conventional vital signs(VSs...to 3-hour transfusion, MT, and mortality no differently from pulse oximeter signals alone. Pulse oximeter features collected in the first 15 minutes...time is an unrealized goal. We hypothesized that analysis of pulse oximeter signals could predict blood transfusion and mortality as accurately as

Automated identification and predictive tools to help identify high-risk heart failure patients: pilot evaluation.

PubMed

Evans, R Scott; Benuzillo, Jose; Horne, Benjamin D; Lloyd, James F; Bradshaw, Alejandra; Budge, Deborah; Rasmusson, Kismet D; Roberts, Colleen; Buckway, Jason; Geer, Norma; Garrett, Teresa; Lappé, Donald L

2016-09-01

Develop and evaluate an automated identification and predictive risk report for hospitalized heart failure (HF) patients. Dictated free-text reports from the previous 24 h were analyzed each day with natural language processing (NLP), to help improve the early identification of hospitalized patients with HF. A second application that uses an Intermountain Healthcare-developed predictive score to determine each HF patient's risk for 30-day hospital readmission and 30-day mortality was also developed. That information was included in an identification and predictive risk report, which was evaluated at a 354-bed hospital that treats high-risk HF patients. The addition of NLP-identified HF patients increased the identification score's sensitivity from 82.6% to 95.3% and its specificity from 82.7% to 97.5%, and the model's positive predictive value is 97.45%. Daily multidisciplinary discharge planning meetings are now based on the information provided by the HF identification and predictive report, and clinician's review of potential HF admissions takes less time compared to the previously used manual methodology (10 vs 40 min). An evaluation of the use of the HF predictive report identified a significant reduction in 30-day mortality and a significant increase in patient discharges to home care instead of to a specialized nursing facility. Using clinical decision support to help identify HF patients and automatically calculating their 30-day all-cause readmission and 30-day mortality risks, coupled with a multidisciplinary care process pathway, was found to be an effective process to improve HF patient identification, significantly reduce 30-day mortality, and significantly increase patient discharges to home care. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Enhancing the Value of Population-Based Risk Scores for Institutional-Level Use.

PubMed

Raza, Sajjad; Sabik, Joseph F; Rajeswaran, Jeevanantham; Idrees, Jay J; Trezzi, Matteo; Riaz, Haris; Javadikasgari, Hoda; Nowicki, Edward R; Svensson, Lars G; Blackstone, Eugene H

2016-07-01

We hypothesized that factors associated with an institution's residual risk unaccounted for by population-based models may be identifiable and used to enhance the value of population-based risk scores for quality improvement. From January 2000 to January 2010, 4,971 patients underwent aortic valve replacement (AVR), either isolated (n = 2,660) or with concomitant coronary artery bypass grafting (AVR+CABG; n = 2,311). Operative mortality and major morbidity and mortality predicted by The Society of Thoracic Surgeons (STS) risk models were compared with observed values. After adjusting for patients' STS score, additional and refined risk factors were sought to explain residual risk. Differences between STS model coefficients (risk-factor strength) and those specific to our institution were calculated. Observed operative mortality was less than predicted for AVR (1.6% [42 of 2,660] vs 2.8%, p < 0.0001) and AVR+CABG (2.6% [59 of 2,311] vs 4.9%, p < 0.0001). Observed major morbidity and mortality was also lower than predicted for isolated AVR (14.6% [389 of 2,660] vs 17.5%, p < 0.0001) and AVR+CABG (20.0% [462 of 2,311] vs 25.8%, p < 0.0001). Shorter height, higher bilirubin, and lower albumin were identified as additional institution-specific risk factors, and body surface area, creatinine, glomerular filtration rate, blood urea nitrogen, and heart failure across all levels of functional class were identified as refined risk-factor variables associated with residual risk. In many instances, risk-factor strength differed substantially from that of STS models. Scores derived from population-based models can be enhanced for institutional level use by adjusting for institution-specific additional and refined risk factors. Identifying these and measuring differences in institution-specific versus population-based risk-factor strength can identify areas to target for quality improvement initiatives. Copyright © 2016 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Biological age as a health index for mortality and major age-related disease incidence in Koreans: National Health Insurance Service – Health screening 11-year follow-up study

PubMed Central

Kang, Young Gon; Suh, Eunkyung; Lee, Jae-woo; Kim, Dong Wook; Cho, Kyung Hee; Bae, Chul-Young

2018-01-01

Purpose A comprehensive health index is needed to measure an individual’s overall health and aging status and predict the risk of death and age-related disease incidence, and evaluate the effect of a health management program. The purpose of this study is to demonstrate the validity of estimated biological age (BA) in relation to all-cause mortality and age-related disease incidence based on National Sample Cohort database. Patients and methods This study was based on National Sample Cohort database of the National Health Insurance Service – Eligibility database and the National Health Insurance Service – Medical and Health Examination database of the year 2002 through 2013. BA model was developed based on the National Health Insurance Service – National Sample Cohort (NHIS – NSC) database and Cox proportional hazard analysis was done for mortality and major age-related disease incidence. Results For every 1 year increase of the calculated BA and chronological age difference, the hazard ratio for mortality significantly increased by 1.6% (1.5% in men and 2.0% in women) and also for hypertension, diabetes mellitus, heart disease, stroke, and cancer incidence by 2.5%, 4.2%, 1.3%, 1.6%, and 0.4%, respectively (p<0.001). Conclusion Estimated BA by the developed BA model based on NHIS – NSC database is expected to be used not only as an index for assessing health and aging status and predicting mortality and major age-related disease incidence, but can also be applied to various health care fields. PMID:29593385

New equations for predicting postoperative risk in patients with hip fracture.

PubMed

Hirose, Jun; Ide, Junji; Irie, Hiroki; Kikukawa, Kenshi; Mizuta, Hiroshi

2009-12-01

Predicting the postoperative course of patients with hip fractures would be helpful for surgical planning and risk management. We therefore established equations to predict the morbidity and mortality rates in candidates for hip fracture surgery using the Estimation of Physiologic Ability and Surgical Stress (E-PASS) risk-scoring system. First we evaluated the correlation between the E-PASS scores and postoperative morbidity and mortality rates in all 722 patients surgically treated for hip fractures during the study period (Group A). Next we established equations to predict morbidity and mortality rates. We then applied these equations to all 633 patients with hip fractures treated at seven other hospitals (Group B) and compared the predicted and actual morbidity and mortality rates to assess the predictive ability of the E-PASS and Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) systems. The ratio of actual to predicted morbidity and mortality rates was closer to 1.0 with the E-PASS than the POSSUM system. Our data suggest the E-PASS scoring system is useful for defining postoperative risk and its underlying algorithm accurately predicts morbidity and mortality rates in patients with hip fractures before surgery. This information then can be used to manage their condition and potentially improve treatment outcomes. Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.

Rockall score in predicting outcomes of elderly patients with acute upper gastrointestinal bleeding

PubMed Central

Wang, Chang-Yuan; Qin, Jian; Wang, Jing; Sun, Chang-Yi; Cao, Tao; Zhu, Dan-Dan

2013-01-01

AIM: To validate the clinical Rockall score in predicting outcomes (rebleeding, surgery and mortality) in elderly patients with acute upper gastrointestinal bleeding (AUGIB). METHODS: A retrospective analysis was undertaken in 341 patients admitted to the emergency room and Intensive Care Unit of Xuanwu Hospital of Capital Medical University with non-variceal upper gastrointestinal bleeding. The Rockall scores were calculated, and the association between clinical Rockall scores and patient outcomes (rebleeding, surgery and mortality) was assessed. Based on the Rockall scores, patients were divided into three risk categories: low risk ≤ 3, moderate risk 3-4, high risk ≥ 4, and the percentages of rebleeding/death/surgery in each risk category were compared. The area under the receiver operating characteristic (ROC) curve was calculated to assess the validity of the Rockall system in predicting rebleeding, surgery and mortality of patients with AUGIB. RESULTS: A positive linear correlation between clinical Rockall scores and patient outcomes in terms of rebleeding, surgery and mortality was observed (r = 0.962, 0.955 and 0.946, respectively, P = 0.001). High clinical Rockall scores > 3 were associated with adverse outcomes (rebleeding, surgery and death). There was a significant correlation between high Rockall scores and the occurrence of rebleeding, surgery and mortality in the entire patient population (χ2 = 49.29, 23.10 and 27.64, respectively, P = 0.001). For rebleeding, the area under the ROC curve was 0.788 (95%CI: 0.726-0.849, P = 0.001); For surgery, the area under the ROC curve was 0.752 (95%CI: 0.679-0.825, P = 0.001) and for mortality, the area under the ROC curve was 0.787 (95%CI: 0.716-0.859, P = 0.001). CONCLUSION: The Rockall score is clinically useful, rapid and accurate in predicting rebleeding, surgery and mortality outcomes in elderly patients with AUGIB. PMID:23801840

Sepsis mortality prediction with the Quotient Basis Kernel.

PubMed

Ribas Ripoll, Vicent J; Vellido, Alfredo; Romero, Enrique; Ruiz-Rodríguez, Juan Carlos

2014-05-01

This paper presents an algorithm to assess the risk of death in patients with sepsis. Sepsis is a common clinical syndrome in the intensive care unit (ICU) that can lead to severe sepsis, a severe state of septic shock or multi-organ failure. The proposed algorithm may be implemented as part of a clinical decision support system that can be used in combination with the scores deployed in the ICU to improve the accuracy, sensitivity and specificity of mortality prediction for patients with sepsis. In this paper, we used the Simplified Acute Physiology Score (SAPS) for ICU patients and the Sequential Organ Failure Assessment (SOFA) to build our kernels and algorithms. In the proposed method, we embed the available data in a suitable feature space and use algorithms based on linear algebra, geometry and statistics for inference. We present a simplified version of the Fisher kernel (practical Fisher kernel for multinomial distributions), as well as a novel kernel that we named the Quotient Basis Kernel (QBK). These kernels are used as the basis for mortality prediction using soft-margin support vector machines. The two new kernels presented are compared against other generative kernels based on the Jensen-Shannon metric (centred, exponential and inverse) and other widely used kernels (linear, polynomial and Gaussian). Clinical relevance is also evaluated by comparing these results with logistic regression and the standard clinical prediction method based on the initial SAPS score. As described in this paper, we tested the new methods via cross-validation with a cohort of 400 test patients. The results obtained using our methods compare favourably with those obtained using alternative kernels (80.18% accuracy for the QBK) and the standard clinical prediction method, which are based on the basal SAPS score or logistic regression (71.32% and 71.55%, respectively). The QBK presented a sensitivity and specificity of 79.34% and 83.24%, which outperformed the other kernels analysed, logistic regression and the standard clinical prediction method based on the basal SAPS score. Several scoring systems for patients with sepsis have been introduced and developed over the last 30 years. They allow for the assessment of the severity of disease and provide an estimate of in-hospital mortality. Physiology-based scoring systems are applied to critically ill patients and have a number of advantages over diagnosis-based systems. Severity score systems are often used to stratify critically ill patients for possible inclusion in clinical trials. In this paper, we present an effective algorithm that combines both scoring methodologies for the assessment of death in patients with sepsis that can be used to improve the sensitivity and specificity of the currently available methods. Copyright © 2014 Elsevier B.V. All rights reserved.

Development and Validation of a Deep Neural Network Model for Prediction of Postoperative In-hospital Mortality.

PubMed

Lee, Christine K; Hofer, Ira; Gabel, Eilon; Baldi, Pierre; Cannesson, Maxime

2018-04-17

The authors tested the hypothesis that deep neural networks trained on intraoperative features can predict postoperative in-hospital mortality. The data used to train and validate the algorithm consists of 59,985 patients with 87 features extracted at the end of surgery. Feed-forward networks with a logistic output were trained using stochastic gradient descent with momentum. The deep neural networks were trained on 80% of the data, with 20% reserved for testing. The authors assessed improvement of the deep neural network by adding American Society of Anesthesiologists (ASA) Physical Status Classification and robustness of the deep neural network to a reduced feature set. The networks were then compared to ASA Physical Status, logistic regression, and other published clinical scores including the Surgical Apgar, Preoperative Score to Predict Postoperative Mortality, Risk Quantification Index, and the Risk Stratification Index. In-hospital mortality in the training and test sets were 0.81% and 0.73%. The deep neural network with a reduced feature set and ASA Physical Status classification had the highest area under the receiver operating characteristics curve, 0.91 (95% CI, 0.88 to 0.93). The highest logistic regression area under the curve was found with a reduced feature set and ASA Physical Status (0.90, 95% CI, 0.87 to 0.93). The Risk Stratification Index had the highest area under the receiver operating characteristics curve, at 0.97 (95% CI, 0.94 to 0.99). Deep neural networks can predict in-hospital mortality based on automatically extractable intraoperative data, but are not (yet) superior to existing methods.

Assessment of performance and utility of mortality prediction models in a single Indian mixed tertiary intensive care unit.

PubMed

Sathe, Prachee M; Bapat, Sharda N

2014-01-01

To assess the performance and utility of two mortality prediction models viz. Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in a single Indian mixed tertiary intensive care unit (ICU). Secondary objectives were bench-marking and setting a base line for research. In this observational cohort, data needed for calculation of both scores were prospectively collected for all consecutive admissions to 28-bedded ICU in the year 2011. After excluding readmissions, discharges within 24 h and age <18 years, the records of 1543 patients were analyzed using appropriate statistical methods. Both models overpredicted mortality in this cohort [standardized mortality ratio (SMR) 0.88 ± 0.05 and 0.95 ± 0.06 using APACHE II and SAPS II respectively]. Patterns of predicted mortality had strong association with true mortality (R (2) = 0.98 for APACHE II and R (2) = 0.99 for SAPS II). Both models performed poorly in formal Hosmer-Lemeshow goodness-of-fit testing (Chi-square = 12.8 (P = 0.03) for APACHE II, Chi-square = 26.6 (P = 0.001) for SAPS II) but showed good discrimination (area under receiver operating characteristic curve 0.86 ± 0.013 SE (P < 0.001) and 0.83 ± 0.013 SE (P < 0.001) for APACHE II and SAPS II, respectively). There were wide variations in SMRs calculated for subgroups based on International Classification of Disease, 10(th) edition (standard deviation ± 0.27 for APACHE II and 0.30 for SAPS II). Lack of fit of data to the models and wide variation in SMRs in subgroups put a limitation on utility of these models as tools for assessing quality of care and comparing performances of different units without customization. Considering comparable performance and simplicity of use, efforts should be made to adapt SAPS II.

Quantifying the global contribution of alcohol consumption to cardiomyopathy.

PubMed

Manthey, Jakob; Imtiaz, Sameer; Neufeld, Maria; Rylett, Margaret; Rehm, Jürgen

2017-05-25

The global impact of alcohol consumption on deaths due to cardiomyopathy (CM) has not been quantified to date, even though CM contains a subcategory for alcoholic CM with an effect of heavy drinking over time as the postulated underlying causal mechanism. In this feasibility study, a model to estimate the alcohol-attributable fraction (AAF) of CM deaths based on alcohol exposure measures is proposed. A two-step model was developed based on aggregate-level data from 95 countries, including the most populous (data from 2013 or last available year). First, the crude mortality rate of alcoholic CM per 1,000,000 adults was predicted using a negative binomial regression based on prevalence of alcohol use disorders (AUD) and adult alcohol per capita consumption (APC) (n = 52 countries). Second, the proportion of alcoholic CM among all CM deaths (i.e., AAF) was predicted using a fractional response probit regression with alcoholic CM crude mortality rate (from Step 1), AUD prevalence, APC per drinker, and Global Burden of Disease region as predictions. Additional models repeated these steps by sex and for the wider Global Burden of Disease study definition of CM. There were strong correlations (>0.9) between the crude mortality rate of alcoholic CM and the AAFs, supporting the modeling strategy. In the first step, the population-weighted mean crude mortality rate was estimated at 8.4 alcoholic CM deaths per 1,000,000 (95% CI: 7.4-9.3). In the second step, the global AAFs were estimated at 6.9% (95% CI: 5.4-8.4%). Sex-specific figures suggested a lower AAF among females (2.9%, 95% CI: 2.3-3.4%) as compared to males (8.9%, 95% CI: 7.0-10.7%). Larger deviations between observed and predicted AAFs were found in Eastern Europe and Central Asia. The model proposed promises to fill the gap to include AAFs for CM into comparative risk assessments in the future. These predictions likely will be underestimates because of the stigma involved in all fully alcohol-attributable conditions and subsequent problems in coding of alcoholic CM deaths.

Development of a Risk Prediction Model and Clinical Risk Score for Isolated Tricuspid Valve Surgery.

PubMed

LaPar, Damien J; Likosky, Donald S; Zhang, Min; Theurer, Patty; Fonner, C Edwin; Kern, John A; Bolling, Stephen F; Drake, Daniel H; Speir, Alan M; Rich, Jeffrey B; Kron, Irving L; Prager, Richard L; Ailawadi, Gorav

2018-02-01

While tricuspid valve (TV) operations remain associated with high mortality (∼8-10%), no robust prediction models exist to support clinical decision-making. We developed a preoperative clinical risk model with an easily calculable clinical risk score (CRS) to predict mortality and major morbidity after isolated TV surgery. Multi-state Society of Thoracic Surgeons database records were evaluated for 2,050 isolated TV repair and replacement operations for any etiology performed at 50 hospitals (2002-2014). Parsimonious preoperative risk prediction models were developed using multi-level mixed effects regression to estimate mortality and composite major morbidity risk. Model results were utilized to establish a novel CRS for patients undergoing TV operations. Models were evaluated for discrimination and calibration. Operative mortality and composite major morbidity rates were 9% and 42%, respectively. Final regression models performed well (both P<0.001, AUC = 0.74 and 0.76) and included preoperative factors: age, gender, stroke, hemodialysis, ejection fraction, lung disease, NYHA class, reoperation and urgent or emergency status (all P<0.05). A simple CRS from 0-10+ was highly associated (P<0.001) with incremental increases in predicted mortality and major morbidity. Predicted mortality risk ranged from 2%-34% across CRS categories, while predicted major morbidity risk ranged from 13%-71%. Mortality and major morbidity after isolated TV surgery can be predicted using preoperative patient data from the STS Adult Cardiac Database. A simple clinical risk score predicts mortality and major morbidity after isolated TV surgery. This score may facilitate perioperative counseling and identification of suitable patients for TV surgery. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Is Educational Attainment Associated with Increased Risk of Mortality in People with Dementia? A Population-based Study.

PubMed

Contador, Israel; Stern, Yaakov; Bermejo-Pareja, Felix; Sanchez-Ferro, Alvaro; Benito-Leon, Julian

2017-01-01

The association between higher education and increased mortality in Alzheimer's disease (AD) is controversial. Further it is unknown whether education predicts survival in all dementia subtypes. We assessed mortality rates and death causes of persons with dementia compared to participants without dementia. Participants derive from the Neurological Disorders in Central Spain, a prospective population- based cohort study of older adults. We compared 269 persons with dementia to 2944 participants without dementia. We carried out Cox regression models to predict the risk of mortality dependent on the educational attainment adjusting for covariates. Reasons of death were obtained from the National Population Register. During a median follow-up of 5.4 years, 400 individuals died (171 with dementia, 229 without dementia). Among the participants with dementia, those with higher educational attainment had an increased risk of death than those with lower education; the adjusted hazard ratio (HRa) was 1.40 (95% confidence interval [CI], 1.01 to 1.94). When the analysis was restricted to patients with AD the HRa increased to 1.51 (95% CI = 1.01-2.24). By contrast, educational attainment was not associated with increased mortality among participants without dementia (HRa = 0.92, 95% CI = 0.71-1.20, p = 0.55), whereas education did not influence mortality in QD. Our findings suggest that high educational attainment is associated with increased mortality risk in people with dementia. This observation implies that neuropathology is more advanced in patients with higher education at any level of clinical severity, leading these individuals to an earlier death after diagnosis. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Determinants of mortality in systemic sclerosis: a focused review.

PubMed

Poudel, Dilli Ram; Jayakumar, Divya; Danve, Abhijeet; Sehra, Shiv Tej; Derk, Chris T

2017-11-07

Scleroderma (systemic sclerosis) is an autoimmune rheumatic disorder that is characterized by fibrosis, vascular dysfunction, and autoantibody production that involves most visceral organs. It is characterized by a high morbidity and mortality rate, mainly due to disease-related complications. Epidemiological data describing mortality and survival in this population have been based on both population and observational studies. Multiple clinical and non-clinical factors have been found to predict higher likelihood of death among thepatients. Here, we do an extensive review of the available literature, utilizing the PubMed database, to describe scleroderma and non-scleroderma related determinants of mortality in this population. We found that even though the mortality among the general population has declined, scleroderma continues to carry a very high morbidity and mortality rate, however we have made some slow progress in improving the mortality among scleroderma patients over the last few decades.

Development and validation of a prognostic index for 4-year mortality in older adults.

PubMed

Lee, Sei J; Lindquist, Karla; Segal, Mark R; Covinsky, Kenneth E

2006-02-15

Both comorbid conditions and functional measures predict mortality in older adults, but few prognostic indexes combine both classes of predictors. Combining easily obtained measures into an accurate predictive model could be useful to clinicians advising patients, as well as policy makers and epidemiologists interested in risk adjustment. To develop and validate a prognostic index for 4-year mortality using information that can be obtained from patient report. Using the 1998 wave of the Health and Retirement Study (HRS), a population-based study of community-dwelling US adults older than 50 years, we developed the prognostic index from 11,701 individuals and validated the index with 8009. Individuals were asked about their demographic characteristics, whether they had specific diseases, and whether they had difficulty with a series of functional measures. We identified variables independently associated with mortality and weighted the variables to create a risk index. Death by December 31, 2002. The overall response rate was 81%. During the 4-year follow-up, there were 1361 deaths (12%) in the development cohort and 1072 deaths (13%) in the validation cohort. Twelve independent predictors of mortality were identified: 2 demographic variables (age: 60-64 years, 1 point; 65-69 years, 2 points; 70-74 years, 3 points; 75-79 years, 4 points; 80-84 years, 5 points, >85 years, 7 points and male sex, 2 points), 6 comorbid conditions (diabetes, 1 point; cancer, 2 points; lung disease, 2 points; heart failure, 2 points; current tobacco use, 2 points; and body mass index <25, 1 point), and difficulty with 4 functional variables (bathing, 2 points; walking several blocks, 2 points; managing money, 2 points, and pushing large objects, 1 point. Scores on the risk index were strongly associated with 4-year mortality in the validation cohort, with 0 to 5 points predicting a less than 4% risk, 6 to 9 points predicting a 15% risk, 10 to 13 points predicting a 42% risk, and 14 or more points predicting a 64% risk. The risk index showed excellent discrimination with a cstatistic of 0.84 in the development cohort and 0.82 in the validation cohort. This prognostic index, incorporating age, sex, self-reported comorbid conditions, and functional measures, accurately stratifies community-dwelling older adults into groups at varying risk of mortality.

Development and Validation of the Nursing Home Minimum Data Set 3.0 Mortality Risk Score (MRS3).

PubMed

Thomas, Kali S; Ogarek, Jessica A; Teno, Joan M; Gozalo, Pedro L; Mor, Vincent

2018-03-05

To develop a score to predict mortality using the Minimum Data Set 3.0 (MDS 3.0) that can be readily calculated from items collected during nursing home (NH) residents' admission assessments. We developed a training cohort of Medicare beneficiaries newly admitted to U.S. NHs during 2012 (N=1,426,815) and a testing cohort from 2013 (N=1,160,964). Data came from the MDS 3.0 assessments linked to the Medicare Beneficiary Summary File. Using the training dataset, we developed a composite MDS 3.0 Mortality Risk Score (MRS3) consisting of 17 clinical items and patients' age groups based on their relation to 30-day mortality. We assessed the calibration and discrimination of the MRS3 in predicting 30-day and 60-day mortality and compared its performance to the Charlson Comorbidity Index and the clinician's assessment of 6-month prognosis measured at admission. The 30-day and 60-day mortality rate for the testing population was 2.8% and 5.6%, respectively. Results from logistic regression models suggest that the MRS3 performed well in predicting death within 30 and 60 days (C-Statistics of 0.744 (95%CL = 0.741, 0.747) and 0.709 (95%CL=0.706, 0.711), respectively). The MRS3 was a superior predictor of mortality compared to the Charlson Comorbidity Index (C-statistics of 0.611 (95%CL=0.607, 0.615) and 0.608 (95%CL=0.605, 0.610)) and the clinicians' assessments of patients' 6-month prognoses (C-statistics of 0.543 (95%CL=0.542, 0.545) and 0.528 (95%CL=0.527, 0.529). The MRS3 is a good predictor of mortality and can be useful in guiding decision-making, informing plans of care, and adjusting for patients' risk of mortality.

Physical function and self-rated health status as predictors of mortality: results from longitudinal analysis in the ilSIRENTE study.

PubMed

Cesari, Matteo; Onder, Graziano; Zamboni, Valentina; Manini, Todd; Shorr, Ronald I; Russo, Andrea; Bernabei, Roberto; Pahor, Marco; Landi, Francesco

2008-12-22

Physical function measures have been shown to predict negative health-related events in older persons, including mortality. These markers of functioning may interact with the self-rated health (SRH) in the prediction of events. Aim of the present study is to compare the predictive value for mortality of measures of physical function and SRH status, and test their possible interactions. Data are from 335 older persons aged >or= 80 years (mean age 85.6 years) enrolled in the "Invecchiamento e Longevità nel Sirente" (ilSIRENTE) study. The predictive values for mortality of 4-meter walk test, Short Physical Performance Battery (SPPB), hand grip strength, Activities of Daily Living (ADL) scale, Instrumental ADL (IADL) scale, and a SRH scale were compared using proportional hazard models. Kaplan-Meier survival curves for mortality and Receiver Operating Characteristic (ROC) curve analyses were also computed to estimate the predictive value of the independent variables of interest for mortality (alone and in combination). During the 24-month follow-up (mean 1.8 years), 71 (21.2%) events occurred in the study sample. All the tested variables were able to significantly predict mortality. No significant interaction was reported between physical function measures and SRH. The SPPB score was the strongest predictor of overall mortality after adjustment for potential confounders (per SD increase; HR 0.64; 95%CI 0.48-0.86). A similar predictive value was showed by the SRH (per SD increase; HR 0.76; 95%CI 0.59-0.97). The chair stand test was the SPPB subtask showing the highest prognostic value. All the tested measures are able to predict mortality with different extents, but strongest results were obtained from the SPPB and the SRH. The chair stand test may be as useful as the complete SPPB in estimating the mortality risk.

Customization of a Severity of Illness Score Using Local Electronic Medical Record Data.

PubMed

Lee, Joon; Maslove, David M

2017-01-01

Severity of illness (SOI) scores are traditionally based on archival data collected from a wide range of clinical settings. Mortality prediction using SOI scores tends to underperform when applied to contemporary cases or those that differ from the case-mix of the original derivation cohorts. We investigated the use of local clinical data captured from hospital electronic medical records (EMRs) to improve the predictive performance of traditional severity of illness scoring. We conducted a retrospective analysis using data from the Multiparameter Intelligent Monitoring in Intensive Care II (MIMIC-II) database, which contains clinical data from the Beth Israel Deaconess Medical Center in Boston, Massachusetts. A total of 17 490 intensive care unit (ICU) admissions with complete data were included, from 4 different service types: medical ICU, surgical ICU, coronary care unit, and cardiac surgery recovery unit. We developed customized SOI scores trained on data from each service type, using the clinical variables employed in the Simplified Acute Physiology Score (SAPS). In-hospital, 30-day, and 2-year mortality predictions were compared with those obtained from using the original SAPS using the area under the receiver-operating characteristics curve (AUROC) as well as the area under the precision-recall curve (AUPRC). Test performance in different cohorts stratified by severity of organ injury was also evaluated. Most customized scores (30 of 39) significantly outperformed SAPS with respect to both AUROC and AUPRC. Enhancements over SAPS were greatest for patients undergoing cardiovascular surgery and for prediction of 2-year mortality. Custom models based on ICU-specific data provided better mortality prediction than traditional SAPS scoring using the same predictor variables. Our local data approach demonstrates the value of electronic data capture in the ICU, of secondary uses of EMR data, and of local customization of SOI scoring. © The Author(s) 2015.

Crohn's disease: increased mortality 10 years after diagnosis in a Europe‐wide population based cohort

PubMed Central

Wolters, F L; Russel, M G; Sijbrandij, J; Schouten, L J; Odes, S; Riis, L; Munkholm, P; Bodini, P; O'Morain, C; Mouzas, I A; Tsianos, E; Vermeire, S; Monteiro, E; Limonard, C; Vatn, M; Fornaciari, G; Pereira, S; Moum, B; Stockbrügger, R W

2006-01-01

Background No previous correlation between phenotype at diagnosis of Crohn's disease (CD) and mortality has been performed. We assessed the predictive value of phenotype at diagnosis on overall and disease related mortality in a European cohort of CD patients. Methods Overall and disease related mortality were recorded 10 years after diagnosis in a prospectively assembled, uniformly diagnosed European population based inception cohort of 380 CD patients diagnosed between 1991 and 1993. Standardised mortality ratios (SMRs) were calculated for geographic and phenotypic subgroups at diagnosis. Results Thirty seven deaths were observed in the entire cohort whereas 21.5 deaths were expected (SMR 1.85 (95% CI 1.30–2.55)). Mortality risk was significantly increased in both females (SMR 1.93 (95% CI 1.10–3.14)) and males (SMR 1.79 (95% CI 1.11–2.73)). Patients from northern European centres had a significant overall increased mortality risk (SMR 2.04 (95% CI 1.32–3.01)) whereas a tendency towards increased overall mortality risk was also observed in the south (SMR 1.55 (95% CI 0.80–2.70)). Mortality risk was increased in patients with colonic disease location and with inflammatory disease behaviour at diagnosis. Mortality risk was also increased in the age group above 40 years at diagnosis for both total and CD related causes. Excess mortality was mainly due to gastrointestinal causes that were related to CD. Conclusions This European multinational population based study revealed an increased overall mortality risk in CD patients 10 years after diagnosis, and age above 40 years at diagnosis was found to be the sole factor associated with increased mortality risk. PMID:16150857

Crohn's disease: increased mortality 10 years after diagnosis in a Europe-wide population based cohort.

PubMed

Wolters, F L; Russel, M G; Sijbrandij, J; Schouten, L J; Odes, S; Riis, L; Munkholm, P; Bodini, P; O'Morain, C; Mouzas, I A; Tsianos, E; Vermeire, S; Monteiro, E; Limonard, C; Vatn, M; Fornaciari, G; Pereira, S; Moum, B; Stockbrügger, R W

2006-04-01

No previous correlation between phenotype at diagnosis of Crohn's disease (CD) and mortality has been performed. We assessed the predictive value of phenotype at diagnosis on overall and disease related mortality in a European cohort of CD patients. Overall and disease related mortality were recorded 10 years after diagnosis in a prospectively assembled, uniformly diagnosed European population based inception cohort of 380 CD patients diagnosed between 1991 and 1993. Standardised mortality ratios (SMRs) were calculated for geographic and phenotypic subgroups at diagnosis. Thirty seven deaths were observed in the entire cohort whereas 21.5 deaths were expected (SMR 1.85 (95% CI 1.30-2.55)). Mortality risk was significantly increased in both females (SMR 1.93 (95% CI 1.10-3.14)) and males (SMR 1.79 (95% CI 1.11-2.73)). Patients from northern European centres had a significant overall increased mortality risk (SMR 2.04 (95% CI 1.32-3.01)) whereas a tendency towards increased overall mortality risk was also observed in the south (SMR 1.55 (95% CI 0.80-2.70)). Mortality risk was increased in patients with colonic disease location and with inflammatory disease behaviour at diagnosis. Mortality risk was also increased in the age group above 40 years at diagnosis for both total and CD related causes. Excess mortality was mainly due to gastrointestinal causes that were related to CD. This European multinational population based study revealed an increased overall mortality risk in CD patients 10 years after diagnosis, and age above 40 years at diagnosis was found to be the sole factor associated with increased mortality risk.

Probabilistic population projections with migration uncertainty

PubMed Central

Azose, Jonathan J.; Ševčíková, Hana; Raftery, Adrian E.

2016-01-01

We produce probabilistic projections of population for all countries based on probabilistic projections of fertility, mortality, and migration. We compare our projections to those from the United Nations’ Probabilistic Population Projections, which uses similar methods for fertility and mortality but deterministic migration projections. We find that uncertainty in migration projection is a substantial contributor to uncertainty in population projections for many countries. Prediction intervals for the populations of Northern America and Europe are over 70% wider, whereas prediction intervals for the populations of Africa, Asia, and the world as a whole are nearly unchanged. Out-of-sample validation shows that the model is reasonably well calibrated. PMID:27217571

How can mortality increase population size? A test of two mechanistic hypotheses.

PubMed

McIntire, Kristina M; Juliano, Steven A

2018-05-03

Overcompensation occurs when added mortality increases survival to the next life-cycle stage. Overcompensation can contribute to the Hydra Effect, wherein added mortality increases equilibrium population size. One hypothesis for overcompensation is that added mortality eases density-dependence, increasing survival to adulthood ("temporal separation of mortality and density dependence"). Mortality early in the life cycle is therefore predicted to cause overcompensation, whereas mortality later in the life cycle is not. Another hypothesis for overcompensation is that threat of mortality (e.g., from predation) causes behavioral changes that reduce overexploitation of resources, allowing resource recovery, and increasing production of adults ("prudent resource exploitation"). Behaviorally active predation cues alone are therefore predicted to cause overcompensation. We tested these predictions in two experiments with larvae of two species of Aedes. As predicted, early mortality yielded greater production of adults, and of adult females, and greater estimated rate of population increase than did later mortality. Addition of water-borne predation cues usually reduced browsing on surfaces in late-stage larvae, but contrary to prediction, resulted in neither significantly greater production of adult mosquitoes nor significantly greater estimated rate of increase. Thus we have strong evidence that timing of mortality contributes to overcompensation and the Hydra effect in mosquitoes. Evidence that predation cues alone can result in overcompensation via prudent resource exploitation is lacking. We expect the overcompensation in response to early mortality will be common in organisms with complex life cycles, density dependence among juveniles, and developmental control of populations. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Practical laboratory-based clinical decision tools and associations with short-term bleeding and mortality outcomes.

PubMed

Graves, Kevin G; Muhlestein, Joseph B; Lappé, Donald L; McCubrey, Raymond O; May, Heidi T; Knight, Stacey; Le, Viet T; Bair, Tami L; Anderson, Jeffrey L; Horne, Benjamin D

2018-07-01

The red cell distribution width (RDW) predicts mortality in numerous populations. The Intermountain Risk Scores (IMRS) predict patient outcomes using laboratory measurements including RDW. Whether the RDW or IMRS predicts in-hospital outcomes is unknown. The predictive abilities of RDW and two IMRS formulations (the complete blood count [CBC] risk score [CBC-RS] or full IMRS using CBC plus the basic metabolic profile) were studied among percutaneous coronary intervention patients at Intermountain (males: N = 6007, females: N = 2165). Primary endpoints were a composite bleeding outcome and in-hospital mortality. IMRS predicted the composite bleeding endpoint (females: χ 2  = 47.1, odds ratio [OR] = 1.13 per +1 score, p < 0.001; males: χ 2  = 108.7, OR = 1.13 per +1 score, p < 0.001) more strongly than RDW (females: χ 2  = 1.6, OR = 1.04 per +1%, p = 0.20; males: χ 2  = 11.2, OR = 1.09 per +1%, p < 0.001). For in-hospital mortality, RDW was predictive in females (χ 2  = 4.3, OR = 1.13 per +1%, p = 0.037) and males (χ 2  = 4.4, OR = 1.11 per +1%, p = 0.037), but IMRS was profoundly more predictive (females: χ 2  = 35.5, OR = 1.36 per +1 score, p < 0.001; males: χ 2  = 72.9, OR = 1.40 per+1 score, p < 0.001). CBC-RS was more predictive than RDW but not as powerful as IMRS. The IMRS, the CBC-RS, and RDW predict in-hospital outcomes. Risk score-directed personalization of in-hospital clinical care should be studied. Copyright © 2018 Elsevier B.V. All rights reserved.

Differential Effect of Modified Medical Research Council Dyspnea, COPD Assessment Test, and Clinical COPD Questionnaire for Symptoms Evaluation Within the New GOLD Staging and Mortality in COPD.

PubMed

Casanova, Ciro; Marin, Jose M; Martinez-Gonzalez, Cristina; de Lucas-Ramos, Pilar; Mir-Viladrich, Isabel; Cosio, Borja; Peces-Barba, German; Solanes-García, Ingrid; Agüero, Ramón; Feu-Collado, Nuria; Calle-Rubio, Miryam; Alfageme, Inmaculada; de Diego-Damia, Alfredo; Irigaray, Rosa; Marín, Margarita; Balcells, Eva; Llunell, Antonia; Galdiz, Juan Bautista; Golpe, Rafael; Lacarcel, Celia; Cabrera, Carlos; Marin, Alicia; Soriano, Joan B; Lopez-Campos, Jose Luis; Soler-Cataluña, Juan José; de-Torres, Juan P

2015-07-01

The modified Medical Research Council (mMRC) dyspnea, the COPD Assessment Test (CAT), and the Clinical COPD Questionnaire (CCQ) have been interchangeably proposed by GOLD (Global Initiative for Chronic Obstructive Lung Disease) for assessing symptoms in patients with COPD. However, there are no data on the prognostic value of these tools in terms of mortality. We endeavored to evaluate the prognostic value of the CAT and CCQ scores and compare them with mMRC dyspnea. We analyzed the ability of these tests to predict mortality in an observational cohort of 768 patients with COPD (82% men; FEV1, 60%) from the COPD History Assessment in Spain (CHAIN) study, a multicenter observational Spanish cohort, who were monitored annually for a mean follow-up time of 38 months. Subjects who died (n = 73; 9.5%) had higher CAT (14 vs 11, P = .022), CCQ (1.6 vs 1.3, P = .033), and mMRC dyspnea scores (2 vs 1, P < .001) than survivors. Receiver operating characteristic analysis showed that higher CAT, CCQ, and mMRC dyspnea scores were associated with higher mortality (area under the curve: 0.589, 0.588, and 0.649, respectively). CAT scores ≥ 17 and CCQ scores > 2.5 provided a similar sensitivity than mMRC dyspnea scores ≥ 2 to predict all-cause mortality. The CAT and the CCQ have similar ability for predicting all-cause mortality in patients with COPD, but were inferior to mMRC dyspnea scores. We suggest new thresholds for CAT and CCQ scores based on mortality risk that could be useful for the new GOLD grading classification. ClinicalTrials.gov; No.: NCT01122758; URL: www.clinicaltrials.gov.

Predicting Early Mortality After Hip Fracture Surgery: The Hip Fracture Estimator of Mortality Amsterdam.

PubMed

Karres, Julian; Kieviet, Noera; Eerenberg, Jan-Peter; Vrouenraets, Bart C

2018-01-01

Early mortality after hip fracture surgery is high and preoperative risk assessment for the individual patient is challenging. A risk model could identify patients in need of more intensive perioperative care, provide insight in the prognosis, and allow for risk adjustment in audits. This study aimed to develop and validate a risk prediction model for 30-day mortality after hip fracture surgery: the Hip fracture Estimator of Mortality Amsterdam (HEMA). Data on 1050 consecutive patients undergoing hip fracture surgery between 2004 and 2010 were retrospectively collected and randomly split into a development cohort (746 patients) and validation cohort (304 patients). Logistic regression analysis was performed in the development cohort to determine risk factors for the HEMA. Discrimination and calibration were assessed in both cohorts using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, and by stratification into low-, medium- and high-risk groups. Nine predictors for 30-day mortality were identified and used in the final model: age ≥85 years, in-hospital fracture, signs of malnutrition, myocardial infarction, congestive heart failure, current pneumonia, renal failure, malignancy, and serum urea >9 mmol/L. The HEMA showed good discrimination in the development cohort (AUC = 0.81) and the validation cohort (AUC = 0.79). The Hosmer-Lemeshow test indicated no lack of fit in either cohort (P > 0.05). The HEMA is based on preoperative variables and can be used to predict the risk of 30-day mortality after hip fracture surgery for the individual patient. Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence.

A composite score of protein-energy nutritional status predicts mortality in haemodialysis patients no better than its individual components.

PubMed

Mazairac, Albert H A; de Wit, G Ardine; Grooteman, Muriel P C; Penne, E Lars; van der Weerd, Neelke C; van den Dorpel, Marinus A; Nubé, Menso J; Lévesque, Renée; Ter Wee, Piet M; Bots, Michiel L; Blankestijn, Peter J

2011-06-01

Protein-energy wasting is tightly associated with mortality in haemodialysis patients. An expert panel of the International Society of Renal Nutrition and Metabolism (ISRNM) has published a consensus on the parameters that define protein-energy nutritional status and posed the question, 'which scoring system most effectively predicts outcome?' The aim of our study was therefore to develop a composite score of protein-energy nutritional status (cPENS) and to assess its prediction of all-cause mortality. We used the data of 560 haemodialysis patients participating in the CONvective TRAnsport STudy (CONTRAST). All participants were followed for occurrence of death. Internationally recommended nutritional targets were used as components of the cPENS, including the subjective global assessment (target score ≥ 6), albumin (≥ 4.0 g/dL), normalized protein nitrogen appearance (≥ 0.8 g/kg/day), cholesterol (≥ 100 mg/dL), creatinine (≥ 10 mg/dL) and BMI (> 23 kg/m(2)). A Cox regression model was used to analyse the relation between different cPENS variants and mortality. The median follow-up time was 1.4 years (max 4.2). One hundred and five patients (19%) died. A cPENS variant based on albumin, BMI, creatinine and the nPNA yielded the strongest relation with mortality (hazard ratio 0.63, 95% confidence interval 0.54-0.74, P < 0.001), after adjustments for confounders. Some of the individual parameters of the cPENS, notably albumin and creatinine, were related to mortality with similar strength and magnitude. In conclusion, albumin reflects mortality risk similarly to multiple nutritional parameters combined. This questions the clinical value of the proposed diagnostic criteria for protein-energy wasting.

Controlling for Frailty in Pharmacoepidemiologic Studies of Older Adults: Validation of an Existing Medicare Claims-based Algorithm.

PubMed

Cuthbertson, Carmen C; Kucharska-Newton, Anna; Faurot, Keturah R; Stürmer, Til; Jonsson Funk, Michele; Palta, Priya; Windham, B Gwen; Thai, Sydney; Lund, Jennifer L

2018-07-01

Frailty is a geriatric syndrome characterized by weakness and weight loss and is associated with adverse health outcomes. It is often an unmeasured confounder in pharmacoepidemiologic and comparative effectiveness studies using administrative claims data. Among the Atherosclerosis Risk in Communities (ARIC) Study Visit 5 participants (2011-2013; n = 3,146), we conducted a validation study to compare a Medicare claims-based algorithm of dependency in activities of daily living (or dependency) developed as a proxy for frailty with a reference standard measure of phenotypic frailty. We applied the algorithm to the ARIC participants' claims data to generate a predicted probability of dependency. Using the claims-based algorithm, we estimated the C-statistic for predicting phenotypic frailty. We further categorized participants by their predicted probability of dependency (<5%, 5% to <20%, and ≥20%) and estimated associations with difficulties in physical abilities, falls, and mortality. The claims-based algorithm showed good discrimination of phenotypic frailty (C-statistic = 0.71; 95% confidence interval [CI] = 0.67, 0.74). Participants classified with a high predicted probability of dependency (≥20%) had higher prevalence of falls and difficulty in physical ability, and a greater risk of 1-year all-cause mortality (hazard ratio = 5.7 [95% CI = 2.5, 13]) than participants classified with a low predicted probability (<5%). Sensitivity and specificity varied across predicted probability of dependency thresholds. The Medicare claims-based algorithm showed good discrimination of phenotypic frailty and high predictive ability with adverse health outcomes. This algorithm can be used in future Medicare claims analyses to reduce confounding by frailty and improve study validity.

Predictive Value of the Sequential Organ Failure Assessment Score for Mortality in a Contemporary Cardiac Intensive Care Unit Population.

PubMed

Jentzer, Jacob C; Bennett, Courtney; Wiley, Brandon M; Murphree, Dennis H; Keegan, Mark T; Gajic, Ognjen; Wright, R Scott; Barsness, Gregory W

2018-03-10

Optimal methods of mortality risk stratification in patients in the cardiac intensive care unit (CICU) remain uncertain. We evaluated the ability of the Sequential Organ Failure Assessment (SOFA) score to predict mortality in a large cohort of unselected patients in the CICU. Adult patients admitted to the CICU from January 1, 2007, to December 31, 2015, at a single tertiary care hospital were retrospectively reviewed. SOFA scores were calculated daily, and Acute Physiology and Chronic Health Evaluation (APACHE)-III and APACHE-IV scores were calculated on CICU day 1. Discrimination of hospital mortality was assessed using area under the receiver-operator characteristic curve values. We included 9961 patients, with a mean age of 67.5±15.2 years; all-cause hospital mortality was 9.0%. Day 1 SOFA score predicted hospital mortality, with an area under the receiver-operator characteristic curve value of 0.83; area under the receiver-operator characteristic curve values were similar for the APACHE-III score, and APACHE-IV predicted mortality ( P >0.05). Mean and maximum SOFA scores over multiple CICU days had greater discrimination for hospital mortality ( P <0.01). Patients with an increasing SOFA score from day 1 and day 2 had higher mortality. Patients with day 1 SOFA score <2 were at low risk of mortality. Increasing tertiles of day 1 SOFA score predicted higher long-term mortality ( P <0.001 by log-rank test). The day 1 SOFA score has good discrimination for short-term mortality in unselected patients in the CICU, which is comparable to APACHE-III and APACHE-IV. Advantages of the SOFA score over APACHE include simplicity, improved discrimination using serial scores, and prediction of long-term mortality. © 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Predictors of mortality in hospital survivors with type 2 diabetes mellitus and acute coronary syndromes.

PubMed

Savonitto, Stefano; Morici, Nuccia; Nozza, Anna; Cosentino, Francesco; Perrone Filardi, Pasquale; Murena, Ernesto; Morocutti, Giorgio; Ferri, Marco; Cavallini, Claudio; Eijkemans, Marinus Jc; Stähli, Barbara E; Schrieks, Ilse C; Toyama, Tadashi; Lambers Heerspink, H J; Malmberg, Klas; Schwartz, Gregory G; Lincoff, A Michael; Ryden, Lars; Tardif, Jean Claude; Grobbee, Diederick E

2018-01-01

To define the predictors of long-term mortality in patients with type 2 diabetes mellitus and recent acute coronary syndrome. A total of 7226 patients from a randomized trial, testing the effect on cardiovascular outcomes of the dual peroxisome proliferator-activated receptor agonist aleglitazar in patients with type 2 diabetes mellitus and recent acute coronary syndrome (AleCardio trial), were analysed. Median follow-up was 2 years. The independent mortality predictors were defined using Cox regression analysis. The predictive information provided by each variable was calculated as percent of total chi-square of the model. All-cause mortality was 4.0%, with cardiovascular death contributing for 73% of mortality. The mortality prediction model included N-terminal proB-type natriuretic peptide (adjusted hazard ratio = 1.68; 95% confidence interval = 1.51-1.88; 27% of prediction), lack of coronary revascularization (hazard ratio = 2.28; 95% confidence interval = 1.77-2.93; 18% of prediction), age (hazard ratio = 1.04; 95% confidence interval = 1.02-1.05; 15% of prediction), heart rate (hazard ratio = 1.02; 95% confidence interval = 1.01-1.03; 10% of prediction), glycated haemoglobin (hazard ratio = 1.11; 95% confidence interval = 1.03-1.19; 8% of prediction), haemoglobin (hazard ratio = 1.01; 95% confidence interval = 1.00-1.02; 8% of prediction), prior coronary artery bypass (hazard ratio = 1.61; 95% confidence interval = 1.11-2.32; 7% of prediction) and prior myocardial infarction (hazard ratio = 1.40; 95% confidence interval = 1.05-1.87; 6% of prediction). In patients with type 2 diabetes mellitus and recent acute coronary syndrome, mortality prediction is largely dominated by markers of cardiac, rather than metabolic, dysfunction.

Evolving biomarkers improve prediction of long-term mortality in patients with stable coronary artery disease: the BIO-VILCAD score.

PubMed

Kleber, M E; Goliasch, G; Grammer, T B; Pilz, S; Tomaschitz, A; Silbernagel, G; Maurer, G; März, W; Niessner, A

2014-08-01

Algorithms to predict the future long-term risk of patients with stable coronary artery disease (CAD) are rare. The VIenna and Ludwigshafen CAD (VILCAD) risk score was one of the first scores specifically tailored for this clinically important patient population. The aim of this study was to refine risk prediction in stable CAD creating a new prediction model encompassing various pathophysiological pathways. Therefore, we assessed the predictive power of 135 novel biomarkers for long-term mortality in patients with stable CAD. We included 1275 patients with stable CAD from the LUdwigshafen RIsk and Cardiovascular health study with a median follow-up of 9.8 years to investigate whether the predictive power of the VILCAD score could be improved by the addition of novel biomarkers. Additional biomarkers were selected in a bootstrapping procedure based on Cox regression to determine the most informative predictors of mortality. The final multivariable model encompassed nine clinical and biochemical markers: age, sex, left ventricular ejection fraction (LVEF), heart rate, N-terminal pro-brain natriuretic peptide, cystatin C, renin, 25OH-vitamin D3 and haemoglobin A1c. The extended VILCAD biomarker score achieved a significantly improved C-statistic (0.78 vs. 0.73; P = 0.035) and net reclassification index (14.9%; P < 0.001) compared to the original VILCAD score. Omitting LVEF, which might not be readily measureable in clinical practice, slightly reduced the accuracy of the new BIO-VILCAD score but still significantly improved risk classification (net reclassification improvement 12.5%; P < 0.001). The VILCAD biomarker score based on routine parameters complemented by novel biomarkers outperforms previous risk algorithms and allows more accurate classification of patients with stable CAD, enabling physicians to choose more personalized treatment regimens for their patients.

Using subjective expectations to forecast longevity: do survey respondents know something we don't know?

PubMed

Perozek, Maria

2008-02-01

Old-age mortality is notoriously difficult to predict because it requires not only an understanding of the process of senescence-which is influenced by genetic, environmental, and behavioral factors-but also a prediction of how these factors will evolve. In this paper I argue that individuals are uniquely qualified to predict their own mortality based on their own genetic background, as well as environmental and behavioral risk factors that are often known only to the individual. Given this private information, individuals form expectations about survival probabilities that may provide additional information to demographers and policymakers in their challenge to predict mortality. From expectations data from the 1992 Health and Retirement Study (HRS), I construct subjective, cohort life tables that are shown to predict the unusual direction of revisions to U.S. life expectancy by gender between 1992 and 2004: that is, for these cohorts, the Social Security Actuary (SSA) raised male life expectancy in 2004 and at the same lowered female life expectancy, narrowing the gender gap in longevity by 25% over this period. Further, although the subjective life expectancies for men appear to be roughly in line with the 2004 life tables, the subjective expectations of women suggest that female life expectancies estimated by the SSA might still be on the high side.

Application of artificial neural networks to establish a predictive mortality risk model in children admitted to a paediatric intensive care unit.

PubMed

Chan, C H; Chan, E Y; Ng, D K; Chow, P Y; Kwok, K L

2006-11-01

Paediatric risk of mortality and paediatric index of mortality (PIM) are the commonly-used mortality prediction models (MPM) in children admitted to paediatric intensive care unit (PICU). The current study was undertaken to develop a better MPM using artificial neural network, a domain of artificial intelligence. The purpose of this retrospective case series was to compare an artificial neural network (ANN) model and PIM with the observed mortality in a cohort of patients admitted to a five-bed PICU in a Hong Kong non-teaching general hospital. The patients were under the age of 17 years and admitted to our PICU from April 2001 to December 2004. Data were collected from each patient admitted to our PICU. All data were randomly allocated to either the training or validation set. The data from the training set were used to construct a series of ANN models. The data from the validation set were used to validate the ANN and PIM models. The accuracy of ANN models and PIM was assessed by area under the receiver operator characteristics (ROC) curve and calibration. All data were randomly allocated to either the training (n=274) or validation set (n=273). Three ANN models were developed using the data from the training set, namely ANN8 (trained with variables required for PIM), ANN9 (trained with variables required for PIM and pre-ICU intubation) and ANN23 (trained with variables required for ANN9 and 14 principal ICU diagnoses). Three ANN models and PIM were used to predict mortality in the validation set. We found that PIM and ANN9 had a high ROC curve (PIM: 0.808, 95 percent confidence interval 0.552 to 1.000, ANN9: 0.957, 95 percent confidence interval 0.915 to 1.000), whereas ANN8 and ANN23 gave a suboptimal area under the ROC curve. ANN8 required only five variables for the calculation of risk, compared with eight for PIM. The current study demonstrated the process of predictive mortality risk model development using ANN. Further multicentre studies are required to produce a representative ANN-based mortality prediction model for use in different PICUs.

Creatinine generation is reduced in patients requiring continuous venovenous hemodialysis and independently predicts mortality

PubMed Central

Wilson, Francis P.; Sheehan, Jessica M.; Mariani, Laura H.; Berns, Jeffrey S.

2012-01-01

Background Existing systems for grading severity of acute kidney injury (AKI) rely on a change of serum creatinine concentration over a defined time interval. The rate of change in serum creatinine increases by degree of reduction in glomerular filtration rate, but is mitigated by low creatinine generation rate (CGR). Failure to appreciate variation in CGR may lead to erroneous conclusions regarding severity of AKI and distorted predictions regarding patient outcomes based on AKI severity. Methods Cohort study of 103 patients who received continuous venovenous hemodialysis (CVVHD) over a 2-year period in a tertiary care hospital setting. Study participants entered the cohort when they were anuric, receiving a stable and uninterrupted dose of CVVHD with serum creatinine in steady state. They were followed until hospital discharge. CGR was measured based on dialyzate effluent volume and effluent creatinine concentration (prospective cohort) and via effluent volume and serum creatinine concentration (retrospective cohort). Results CGR (mean 10.5, range 1.7–22.4 mg/kg/day) was substantially lower in this patient population than what would be predicted from existing equations. Correlates of CGR in multivariable analysis included the length of hospitalization prior to measurement and presence of an oncologic diagnosis. Lower CGR was independently associated with in-hospital mortality in unadjusted analysis and after multivariable adjustment for measures of severity of illness. Conclusions Grading systems for severity of AKI fail to account for variation in CGR, limiting their ability to predict relevant outcomes. Calculation of CGR is superior to other risk metrics in predicting hospital mortality in this population. PMID:22273668

Electronic medical record-based multicondition models to predict the risk of 30 day readmission or death among adult medicine patients: validation and comparison to existing models.

PubMed

Amarasingham, Ruben; Velasco, Ferdinand; Xie, Bin; Clark, Christopher; Ma, Ying; Zhang, Song; Bhat, Deepa; Lucena, Brian; Huesch, Marco; Halm, Ethan A

2015-05-20

There is increasing interest in using prediction models to identify patients at risk of readmission or death after hospital discharge, but existing models have significant limitations. Electronic medical record (EMR) based models that can be used to predict risk on multiple disease conditions among a wide range of patient demographics early in the hospitalization are needed. The objective of this study was to evaluate the degree to which EMR-based risk models for 30-day readmission or mortality accurately identify high risk patients and to compare these models with published claims-based models. Data were analyzed from all consecutive adult patients admitted to internal medicine services at 7 large hospitals belonging to 3 health systems in Dallas/Fort Worth between November 2009 and October 2010 and split randomly into derivation and validation cohorts. Performance of the model was evaluated against the Canadian LACE mortality or readmission model and the Centers for Medicare and Medicaid Services (CMS) Hospital Wide Readmission model. Among the 39,604 adults hospitalized for a broad range of medical reasons, 2.8% of patients died, 12.7% were readmitted, and 14.7% were readmitted or died within 30 days after discharge. The electronic multicondition models for the composite outcome of 30-day mortality or readmission had good discrimination using data available within 24 h of admission (C statistic 0.69; 95% CI, 0.68-0.70), or at discharge (0.71; 95% CI, 0.70-0.72), and were significantly better than the LACE model (0.65; 95% CI, 0.64-0.66; P =0.02) with significant NRI (0.16) and IDI (0.039, 95% CI, 0.035-0.044). The electronic multicondition model for 30-day readmission alone had good discrimination using data available within 24 h of admission (C statistic 0.66; 95% CI, 0.65-0.67) or at discharge (0.68; 95% CI, 0.67-0.69), and performed significantly better than the CMS model (0.61; 95% CI, 0.59-0.62; P < 0.01) with significant NRI (0.20) and IDI (0.037, 95% CI, 0.033-0.041). A new electronic multicondition model based on information derived from the EMR predicted mortality and readmission at 30 days, and was superior to previously published claims-based models.

Developing points-based risk-scoring systems in the presence of competing risks.

PubMed

Austin, Peter C; Lee, Douglas S; D'Agostino, Ralph B; Fine, Jason P

2016-09-30

Predicting the occurrence of an adverse event over time is an important issue in clinical medicine. Clinical prediction models and associated points-based risk-scoring systems are popular statistical methods for summarizing the relationship between a multivariable set of patient risk factors and the risk of the occurrence of an adverse event. Points-based risk-scoring systems are popular amongst physicians as they permit a rapid assessment of patient risk without the use of computers or other electronic devices. The use of such points-based risk-scoring systems facilitates evidence-based clinical decision making. There is a growing interest in cause-specific mortality and in non-fatal outcomes. However, when considering these types of outcomes, one must account for competing risks whose occurrence precludes the occurrence of the event of interest. We describe how points-based risk-scoring systems can be developed in the presence of competing events. We illustrate the application of these methods by developing risk-scoring systems for predicting cardiovascular mortality in patients hospitalized with acute myocardial infarction. Code in the R statistical programming language is provided for the implementation of the described methods. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

Outcomes of patients in clinical trials with ST-segment elevation myocardial infarction among countries with different gross national incomes.

PubMed

Orlandini, Andrés; Díaz, Rafael; Wojdyla, Daniel; Pieper, Karen; Van de Werf, Frans; Granger, Christopher B; Harrington, Robert A; Boersma, Eric; Califf, Robert M; Armstrong, Paul; White, Harvey; Simes, John; Paolasso, Ernesto

2006-03-01

To evaluate whether there is an association between 30-day mortality in patients with ST-segment elevation myocardial infarction (STEMI) included in clinical trials and country gross national income (GNI). A retrospective analysis of the databases of five randomized trials including 50 310 patients with STEMI (COBALT 7169, GIK-2 2931, HERO-2 17,089, ASSENT-2 17,005, and ASSENT-3 6116 patients) from 53 countries was performed. Countries were divided into three groups according to their GNI based on the World Bank data: low (less than 2900 US dollars), medium (between 2900 US dollars and 9000 US dollars), and high GNI (more than 9000 US dollars per capita). Baseline characteristics, in-hospital management variables, and 30-day outcomes were evaluated. A previously defined logistic regression model was used to adjust for differences in baseline characteristics and to predict mortality. The observed mortality was higher than the predicted mortality in the low (12.1 vs. 11.8%) and in the medium income groups (9.4 vs. 7.9%), whereas it was lower in the high income group (4.9 vs. 5.6%). An inverse relationship between mortality and GNI was observed in STEMI clinical trials. Most of the variability in mortality can be explained by differences in baseline characteristics; however, after adjustment, lower income countries have higher mortality than the expected.

External validation of the simple clinical score and the HOTEL score, two scores for predicting short-term mortality after admission to an acute medical unit.

PubMed

Stræde, Mia; Brabrand, Mikkel

2014-01-01

Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Pre-planned prospective observational cohort study. Danish 460-bed regional teaching hospital. We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774-0.879) for 30-day mortality, and goodness-of-fit test, χ(2) = 2.68 (10 degrees of freedom), P = 0.998 and χ(2) = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901-0.962) for 24-hours mortality and goodness-of-fit test, χ(2) = 5.56 (10 degrees of freedom), P = 0.234. We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision.

[Karnosfsky index as a mortality predicting factor in patients on home-based enteral nutrition].

PubMed

Puiggròs, C; Lecha, M; Rodríguez, T; Pérez-Portabella, C; Planas, M

2009-01-01

Karnofsky Index (KI) is a widely used functional scale developed for oncology patients. It has proved useful as outcome predictor with cancer and geriatric patients. Theoretically, KI could be used to predict mortality in patients with home enteral nutrition (HEN). To determine baseline KI and its 6-month evolution in HEN patients, and to assess its relation with the mortality rate. Observational and prospective study carried out during 2002 and 2003 with tube feeding neurologic and cancer patients followed during 10 months since their HEN programme inclusion. 201 patients were included, 131 (65.2%) with neurological diseases and 70 (34.8%) with neoplasm. There were not significant differences between groups in age, days with HEN and mortality rate at the end of the study period (35.1% in neurologic patients and 40% in cancer ones). 27.1% of cancer patients had resumed full oral nutrition after ten months from the beginning of the study, whereas only 10.7% of neurologic patients did (p < 0.05). In the three measurement phases (initial, past-3 and past-6 months) KI values were higher for cancer patients than for neurologic ones (p < 0.001). In both groups we didn't found statistically significant differences in KI along the three measurements. A significant relation was observed overall between initial KI values and average survival after 10 months (p < 0.001), and an inverse relation was found between the former and mortality rate (p < 0.001). KI is a useful tool to predict mortality rate in cancer and neurologic patients under HEN.

Comorbidities and the risk of mortality in patients with bronchiectasis: an international cohort study

PubMed Central

McDonnell, Melissa J; Aliberti, Stefano; Goeminne, Pieter C.; Restrepo, Marcos I.; Finch, Simon; Pesci, Alberto; Dupont, Lieven J; Fardon, Thomas C.; Wilson, Robert; Loebinger, Michael R; Skrbic, Dusan; Obradovic, Dusanka; De Soyza, Anthony; Ward, Chris; Laffey, John G.; Rutherford, Robert M.; Chalmers, James D.

2017-01-01

Background Patients with bronchiectasis often suffer from concurrent comorbidities but their nature, prevalence and impact on disease severity and outcome is poorly understood. We aimed to evaluate comorbidities in bronchiectasis patients and determine their prognostic value on disease severity and mortality. Methods An observational cohort analysis of 986 bronchiectasis patients across four European centres was performed for score derivation. Comorbidity diagnoses were based on standardised definitions obtained on full review of hard copy and electronic records, prescriptions and investigator definitions. Weibull parametric survival analysis was used to model the prediction of 5-year mortality to construct the Bronchiectasis Aetiology Comorbidity Index (BACI). We tested the BACI as a predictor of outcomes and explored whether the BACI added further prognostic information when used alongside the Bronchiectasis Severity Index (BSI). Findings Median number of comorbidities per patient was 4 (IQR 2-6), range 0-20. Thirteen comorbidities independently predicting mortality were integrated into the BACI. The overall hazard ratio for death conferred by a one point increase in the BACI was 1.18 (1.14-1.23), p<0.0001. The BACI predicted 5-year mortality, hospitalisations, exacerbations and health-related quality of life across all BSI risk strata (p<0.0001). When used in conjunction with the BSI, the combined model was superior to either model alone. The BACI was validated in two independent international cohorts. Interpretation Multimorbidity is frequent in bronchiectasis and can negatively influence survival. The BACI complements the BSI in assessing mortality and disease outcomes in patients with bronchiectasis. Funding 1. European Bronchiectasis Network (EMBARC).2. Health Research Board Ireland. PMID:27864036

Latitudinal variation in seasonal activity and mortality in ratsnakes (Elaphe obsoleta).

PubMed

Sperry, Jinelle H; Blouin-Demers, Gabriel; Carfagno, Gerardo L F; Weatherhead, Patrick J

2010-06-01

The ecology of ectotherms should be particularly affected by latitude because so much of their biology is temperature dependent. Current latitudinal patterns should also be informative about how ectotherms will have to modify their behavior in response to climate change. We used data from a total of 175 adult black ratsnakes (Elaphe obsoleta) radio-tracked in Ontario, Illinois, and Texas, a latitudinal distance of >1500 km, to test predictions about how seasonal patterns of activity and mortality should vary with latitude. Despite pronounced differences in temperatures among study locations, and despite ratsnakes in Texas not hibernating and switching from diurnal to nocturnal activity in the summer, seasonal patterns of snake activity were remarkably similar during the months that snakes in all populations were active. Rather than being a function of temperature, activity may be driven by the timing of reproduction, which appears similar among populations. Contrary to the prediction that mortality should be highest in the most active population, overall mortality did not follow a clinal pattern. Winter mortality did increase with latitude, however, consistent with temperature limiting the northern distribution of ratsnakes. This result was opposite that found in the only previous study of latitudinal variation in winter mortality in reptiles, which may be a consequence of whether or not the animals exhibit true hibernation. Collectively, these results suggest that, at least in the northern part of their range, ratsnakes should be able to adjust easily to, and may benefit from, a warmer climate, although climate-based changes to the snakes' prey or habitat, for example, could alter that prediction.

Comparison of the Nosocomial Pneumonia Mortality Prediction (NPMP) model with standard mortality prediction tools.

PubMed

Srinivasan, M; Shetty, N; Gadekari, S; Thunga, G; Rao, K; Kunhikatta, V

2017-07-01

Severity or mortality prediction of nosocomial pneumonia could aid in the effective triage of patients and assisting physicians. To compare various severity assessment scoring systems for predicting intensive care unit (ICU) mortality in nosocomial pneumonia patients. A prospective cohort study was conducted in a tertiary care university-affiliated hospital in Manipal, India. One hundred patients with nosocomial pneumonia, admitted in the ICUs who developed pneumonia after >48h of admission, were included. The Nosocomial Pneumonia Mortality Prediction (NPMP) model, developed in our hospital, was compared with Acute Physiology and Chronic Health Evaluation II (APACHE II), Mortality Probability Model II (MPM 72  II), Simplified Acute Physiology Score II (SAPS II), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Clinical Pulmonary Infection Score (CPIS), Ventilator-Associated Pneumonia Predisposition, Insult, Response, Organ dysfunction (VAP-PIRO). Data and clinical variables were collected on the day of pneumonia diagnosis. The outcome for the study was ICU mortality. The sensitivity and specificity of the various scoring systems was analysed by plotting receiver operating characteristic (ROC) curves and computing the area under the curve for each of the mortality predicting tools. NPMP, APACHE II, SAPS II, MPM 72  II, SOFA, and VAP-PIRO were found to have similar and acceptable discrimination power as assessed by the area under the ROC curve. The AUC values for the above scores ranged from 0.735 to 0.762. CPIS and MODS showed least discrimination. NPMP is a specific tool to predict mortality in nosocomial pneumonia and is comparable to other standard scores. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

Prediction of Post-operative Mortality in Patients with HCV-related Cirrhosis Undergoing Non-Hepatic Surgeries

PubMed Central

Hemida, Khalid; Shabana, Sherif Sadek; Said, Hani; Ali-Eldin, Fatma

2016-01-01

Introduction Patients with chronic liver diseases are at great risk for both morbidity and mortality during the post-operative period due to the stress of surgery and the effects of general anaesthesia. Aim The main aim of this study was to evaluate the value of Model for End-stage Liver Disease (MELD) score, as compared to Child-Turcotte-Pugh (CTP) score, for prediction of 30- day post-operative mortality in Egyptian patients with liver cirrhosis undergoing non-hepatic surgery under general anaesthesia. Materials and Methods A total of 60 patients with Hepatitis C Virus (HCV) - related liver cirrhosis were included in this study. Sensitivity and specificity of MELD and CTP scores were evaluated for the prediction of post-operative mortality. A total of 20 patients who had no clinical, biochemical or radiological evidence of liver disease were included to serve as a control group. Results The highest sensitivity and specificity for detection of post-operative mortality was detected at a MELD score of 13.5. CTP score had a sensitivity of 75%, a specificity of 96.4%, and an overall accuracy of 95% for prediction of post-operative mortality. On the other side and at a cut-off value of 13.5, MELD score had a sensitivity of 100%, a specificity of 64.0%, and an overall accuracy of 66.6% for prediction of post-operative mortality in patients with HCV- related liver cirrhosis. Conclusion MELD score proved to be more sensitive but less specific than CTP score for prediction of post-operative mortality. CTP and MELD scores may be complementary rather than competitive in predicting post-operative mortality in patients with HCV- related liver cirrhosis. PMID:27891371

Modern modeling techniques had limited external validity in predicting mortality from traumatic brain injury.

PubMed

van der Ploeg, Tjeerd; Nieboer, Daan; Steyerberg, Ewout W

2016-10-01

Prediction of medical outcomes may potentially benefit from using modern statistical modeling techniques. We aimed to externally validate modeling strategies for prediction of 6-month mortality of patients suffering from traumatic brain injury (TBI) with predictor sets of increasing complexity. We analyzed individual patient data from 15 different studies including 11,026 TBI patients. We consecutively considered a core set of predictors (age, motor score, and pupillary reactivity), an extended set with computed tomography scan characteristics, and a further extension with two laboratory measurements (glucose and hemoglobin). With each of these sets, we predicted 6-month mortality using default settings with five statistical modeling techniques: logistic regression (LR), classification and regression trees, random forests (RFs), support vector machines (SVM) and neural nets. For external validation, a model developed on one of the 15 data sets was applied to each of the 14 remaining sets. This process was repeated 15 times for a total of 630 validations. The area under the receiver operating characteristic curve (AUC) was used to assess the discriminative ability of the models. For the most complex predictor set, the LR models performed best (median validated AUC value, 0.757), followed by RF and support vector machine models (median validated AUC value, 0.735 and 0.732, respectively). With each predictor set, the classification and regression trees models showed poor performance (median validated AUC value, <0.7). The variability in performance across the studies was smallest for the RF- and LR-based models (inter quartile range for validated AUC values from 0.07 to 0.10). In the area of predicting mortality from TBI, nonlinear and nonadditive effects are not pronounced enough to make modern prediction methods beneficial. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictive modeling of nanomaterial exposure effects in biological systems

PubMed Central

Liu, Xiong; Tang, Kaizhi; Harper, Stacey; Harper, Bryan; Steevens, Jeffery A; Xu, Roger

2013-01-01

Background Predictive modeling of the biological effects of nanomaterials is critical for industry and policymakers to assess the potential hazards resulting from the application of engineered nanomaterials. Methods We generated an experimental dataset on the toxic effects experienced by embryonic zebrafish due to exposure to nanomaterials. Several nanomaterials were studied, such as metal nanoparticles, dendrimer, metal oxide, and polymeric materials. The embryonic zebrafish metric (EZ Metric) was used as a screening-level measurement representative of adverse effects. Using the dataset, we developed a data mining approach to model the toxic endpoints and the overall biological impact of nanomaterials. Data mining techniques, such as numerical prediction, can assist analysts in developing risk assessment models for nanomaterials. Results We found several important attributes that contribute to the 24 hours post-fertilization (hpf) mortality, such as dosage concentration, shell composition, and surface charge. These findings concur with previous studies on nanomaterial toxicity using embryonic zebrafish. We conducted case studies on modeling the overall effect/impact of nanomaterials and the specific toxic endpoints such as mortality, delayed development, and morphological malformations. The results show that we can achieve high prediction accuracy for certain biological effects, such as 24 hpf mortality, 120 hpf mortality, and 120 hpf heart malformation. The results also show that the weighting scheme for individual biological effects has a significant influence on modeling the overall impact of nanomaterials. Sample prediction models can be found at http://neiminer.i-a-i.com/nei_models. Conclusion The EZ Metric-based data mining approach has been shown to have predictive power. The results provide valuable insights into the modeling and understanding of nanomaterial exposure effects. PMID:24098077

Using predicted 30 day mortality to plan postoperative colorectal surgery care: a cohort study.

PubMed

Swart, M; Carlisle, J B; Goddard, J

2017-01-01

Preoperative identification of high-risk surgical patients might help to reduce postoperative morbidity and mortality. Using a patient's predicted 30 day mortality to plan postoperative high-dependency unit (HDU) care after elective colorectal surgery might be associated with reduced postoperative morbidity. The 30 day postoperative mortality was predicted for 504 elective colorectal surgical patients in a preoperative clinic. The prediction was used to determine postoperative surgical ward or HDU care. Those with a predicted 30 day mortality of 1-3% mortality, and thus deemed at intermediate risk, had either planned HDU care (n=68) or planned ward care (n=139). The main outcome measures were emergency laparotomy and unplanned critical care admission. There were more emergency laparotomies and unplanned critical care admissions in patients with a predicted 30 day mortality of 1-3% who went to an HDU after surgery compared with patients who went to a ward: 0 vs 14 (10%), P=0.0056 and 0 vs 22 (16%), P=0.0002, respectively. Planned postoperative critical care was associated with a lower rate of complications after elective colorectal surgery. © The Author 2016. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predicting in-hospital mortality of traffic victims: A comparison between AIS-and ICD-9-CM-related injury severity scales when only ICD-9-CM is reported.

PubMed

Van Belleghem, Griet; Devos, Stefanie; De Wit, Liesbet; Hubloue, Ives; Lauwaert, Door; Pien, Karen; Putman, Koen

2016-01-01

Injury severity scores are important in the context of developing European and national goals on traffic safety, health-care benchmarking and improving patient communication. Various severity scores are available and are mostly based on Abbreviated Injury Scale (AIS) or International Classification of Diseases (ICD). The aim of this paper is to compare the predictive value for in-hospital mortality between the various severity scores if only International Classification of Diseases, 9th revision, Clinical Modification ICD-9-CM is reported. To estimate severity scores based on the AIS lexicon, ICD-9-CM codes were converted with ICD Programmes for Injury Categorization (ICDPIC) and four AIS-based severity scores were derived: Maximum AIS (MaxAIS), Injury Severity Score (ISS), New Injury Severity Score (NISS) and Exponential Injury Severity Score (EISS). Based on ICD-9-CM, six severity scores were calculated. Determined by the number of injuries taken into account and the means by which survival risk ratios (SRRs) were calculated, four different approaches were used to calculate the ICD-9-based Injury Severity Scores (ICISS). The Trauma Mortality Prediction Model (TMPM) was calculated with the ICD-9-CM-based model averaged regression coefficients (MARC) for both the single worst injury and multiple injuries. Severity scores were compared via model discrimination and calibration. Model comparisons were performed separately for the severity scores based on the single worst injury and multiple injuries. For ICD-9-based scales, estimation of area under the receiver operating characteristic curve (AUROC) ranges between 0.94 and 0.96, while AIS-based scales range between 0.72 and 0.76, respectively. The intercept in the calibration plots is not significantly different from 0 for MaxAIS, ICISS and TMPM. When only ICD-9-CM codes are reported, ICD-9-CM-based severity scores perform better than severity scores based on the conversion to AIS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Prediction of Hematopoietic Stem Cell Transplantation Related Mortality- Lessons Learned from the In-Silico Approach: A European Society for Blood and Marrow Transplantation Acute Leukemia Working Party Data Mining Study.

PubMed

Shouval, Roni; Labopin, Myriam; Unger, Ron; Giebel, Sebastian; Ciceri, Fabio; Schmid, Christoph; Esteve, Jordi; Baron, Frederic; Gorin, Norbert Claude; Savani, Bipin; Shimoni, Avichai; Mohty, Mohamad; Nagler, Arnon

2016-01-01

Models for prediction of allogeneic hematopoietic stem transplantation (HSCT) related mortality partially account for transplant risk. Improving predictive accuracy requires understating of prediction limiting factors, such as the statistical methodology used, number and quality of features collected, or simply the population size. Using an in-silico approach (i.e., iterative computerized simulations), based on machine learning (ML) algorithms, we set out to analyze these factors. A cohort of 25,923 adult acute leukemia patients from the European Society for Blood and Marrow Transplantation (EBMT) registry was analyzed. Predictive objective was non-relapse mortality (NRM) 100 days following HSCT. Thousands of prediction models were developed under varying conditions: increasing sample size, specific subpopulations and an increasing number of variables, which were selected and ranked by separate feature selection algorithms. Depending on the algorithm, predictive performance plateaued on a population size of 6,611-8,814 patients, reaching a maximal area under the receiver operator characteristic curve (AUC) of 0.67. AUCs' of models developed on specific subpopulation ranged from 0.59 to 0.67 for patients in second complete remission and receiving reduced intensity conditioning, respectively. Only 3-5 variables were necessary to achieve near maximal AUCs. The top 3 ranking variables, shared by all algorithms were disease stage, donor type, and conditioning regimen. Our findings empirically demonstrate that with regards to NRM prediction, few variables "carry the weight" and that traditional HSCT data has been "worn out". "Breaking through" the predictive boundaries will likely require additional types of inputs.

Perceived extrinsic mortality risk and reported effort in looking after health: testing a behavioral ecological prediction.

PubMed

Pepper, Gillian V; Nettle, Daniel

2014-09-01

Socioeconomic gradients in health behavior are pervasive and well documented. Yet, there is little consensus on their causes. Behavioral ecological theory predicts that, if people of lower socioeconomic position (SEP) perceive greater personal extrinsic mortality risk than those of higher SEP, they should disinvest in their future health. We surveyed North American adults for reported effort in looking after health, perceived extrinsic and intrinsic mortality risks, and measures of SEP. We examined the relationships between these variables and found that lower subjective SEP predicted lower reported health effort. Lower subjective SEP was also associated with higher perceived extrinsic mortality risk, which in turn predicted lower reported health effort. The effect of subjective SEP on reported health effort was completely mediated by perceived extrinsic mortality risk. Our findings indicate that perceived extrinsic mortality risk may be a key factor underlying SEP gradients in motivation to invest in future health.

Mortality predictors in a 60-year follow-up of adolescent males: exploring delinquency, socioeconomic status, IQ, high-school drop-out status, and personality.

PubMed

Trumbetta, Susan L; Seltzer, Benjamin K; Gottesman, Irving I; McIntyre, Kathleen M

2010-01-01

To examine whether socioeconomic status (SES), high school (HS) completion, IQ, and personality traits that predict delinquency in adolescence also could explain men's delinquency-related (Dq-r) mortality risk across the life span. Through a 60-year Social Security Death Index (SSDI) follow-up of 1812 men from Hathaway's adolescent normative Minnesota Multiphasic Personality Inventory (MMPI) sample, we examined mortality risk at various ages and at various levels of prior delinquency severity. We examined SES (using family rent level), HS completion, IQ, and MMPI indicators simultaneously as mortality predictors and tested for SES (rent level) interactions with IQ and personality. We ascertained 418 decedents. Dq-r mortality peaked between ages 45 years to 64 years and continued through age 75 years, with high delinquency severity showing earlier and higher mortality risk. IQ and rent level failed to explain Dq-r mortality. HS completion robustly conferred mortality protection through ages 55 years and 75 years, explained IQ and rent level-related risk, but did not fully explain Dq-r risk. Dq-r MMPI scales, Psychopathic Deviate, and Social Introversion, respectively, predicted risk for and protection from mortality by age 75 years, explaining mortality risk otherwise attributable to delinquency. Wiggins' scales also explained Dq-r mortality risk, as Authority Conflict conferred risk for and Social Maladjustment and Hypomania conferred protection from mortality by age 75 years. HS completion robustly predicts mortality by ages 55 years and 75 years. Dq-r personality traits predict mortality by age 75 years, accounting, in part, for Dq-r mortality.

Sarcopenia predicts 1-year mortality in elderly patients undergoing curative gastrectomy for gastric cancer: a prospective study.

PubMed

Huang, Dong-Dong; Chen, Xiao-Xi; Chen, Xi-Yi; Wang, Su-Lin; Shen, Xian; Chen, Xiao-Lei; Yu, Zhen; Zhuang, Cheng-Le

2016-11-01

One-year mortality is vital for elderly oncologic patients undergoing surgery. Recent studies have demonstrated that sarcopenia can predict outcomes after major abdominal surgeries, but the association of sarcopenia and 1-year mortality has never been investigated in a prospective study. We conducted a prospective study of elderly patients (≥65 years) who underwent curative gastrectomy for gastric cancer from July 2014 to July 2015. Sarcopenia was determined by the measurements of muscle mass, handgrip strength, and gait speed. Univariate and multivariate analyses were used to identify the risk factors associated with 1-year mortality. A total of 173 patients were included, in which 52 (30.1 %) patients were identified as having sarcopenia. Twenty-four (13.9 %) patients died within 1 year of surgery. Multivariate analysis showed that sarcopenia was an independent risk factor for 1-year mortality. Area under the receiver operating characteristic curve demonstrated an increased predictive power for 1-year mortality with the inclusion of sarcopenia, from 0.835 to 0.868. Solely low muscle mass was not predictive of 1-year mortality in the multivariate analysis. Sarcopenia is predictive of 1-year mortality in elderly patients undergoing gastric cancer surgery. The measurement of muscle function is important for sarcopenia as a preoperative assessment tool.

Mortality Differences Between Traditional Medicare and Medicare Advantage: A Risk-Adjusted Assessment Using Claims Data

PubMed Central

Beveridge, Roy A.; Mendes, Sean M.; Caplan, Arial; Rogstad, Teresa L.; Olson, Vanessa; Williams, Meredith C.; McRae, Jacquelyn M.; Vargas, Stefan

2017-01-01

Medicare Advantage (MA) has grown rapidly since the Affordable Care Act; nearly one-third of Medicare beneficiaries now choose MA. An assessment of the comparative value of the 2 options is confounded by an apparent selection bias favoring MA, as reflected in mortality differences. Previous assessments have been hampered by lack of access to claims diagnosis data for the MA population. An indirect comparison of mortality as an outcome variable was conducted by modeling mortality on a traditional fee-for-service (FFS) Medicare data set, applying the model to an MA data set, and then evaluating the ratio of actual-to-predicted mortality in the MA data set. The mortality model adjusted for clinical conditions and demographic factors. Model development considered the effect of potentially greater coding intensity in the MA population. Further analysis calculated ratios for subpopulations. Predicted, risk-adjusted mortality was lower in the MA population than in FFS Medicare. However, the ratio of actual-to-predicted mortality (0.80) suggested that the individuals in the MA data set were less likely to die than would be predicted had those individuals been enrolled in FFS Medicare. Differences between actual and predicted mortality were particularly pronounced in low income (dual eligibility), nonwhite race, high morbidity, and Health Maintenance Organization (HMO) subgroups. After controlling for baseline clinical risk as represented by claims diagnosis data, mortality differences favoring MA over FFS Medicare persisted, particularly in vulnerable subgroups and HMO plans. These findings suggest that differences in morbidity do not fully explain differences in mortality between the 2 programs. PMID:28578605

Associations of grip strength with cardiovascular, respiratory, and cancer outcomes and all cause mortality: prospective cohort study of half a million UK Biobank participants

PubMed Central

Celis-Morales, Carlos A; Welsh, Paul; Lyall, Donald M; Steell, Lewis; Petermann, Fanny; Anderson, Jana; Iliodromiti, Stamatina; Sillars, Anne; Graham, Nicholas; Mackay, Daniel F; Pell, Jill P; Gill, Jason M R; Sattar, Naveed

2018-01-01

Abstract Objective To investigate the association of grip strength with disease specific incidence and mortality and whether grip strength enhances the prediction ability of an established office based risk score. Design Prospective population based study. Setting UK Biobank. Participants 502 293 participants (54% women) aged 40-69 years. Main outcome measures All cause mortality as well as incidence of and mortality from cardiovascular disease, respiratory disease, chronic obstructive pulmonary disease, and cancer (all cancer, colorectal, lung, breast, and prostate). Results Of the participants included in analyses, 13 322 (2.7%) died over a mean of 7.1 (range 5.3-9.9) years’ follow-up. In women and men, respectively, hazard ratios per 5 kg lower grip strength were higher (all at P<0.05) for all cause mortality (1.20, 95% confidence interval 1.17 to 1.23, and 1.16, 1.15 to 1.17) and cause specific mortality from cardiovascular disease (1.19, 1.13 to 1.25, and 1.22, 1.18 to 1.26), all respiratory disease (1.31, 1.22 to 1.40, and 1.24, 1.20 to 1.28), chronic obstructive pulmonary disease (1.24, 1.05 to 1.47, and 1.19, 1.09 to 1.30), all cancer (1.17, 1.13 to 1.21, 1.10, 1.07 to 1.13), colorectal cancer (1.17, 1.04 to 1.32, and 1.18, 1.09 to 1.27), lung cancer (1.17, 1.07 to 1.27, and 1.08, 1.03 to 1.13), and breast cancer (1.24, 1.10 to 1.39) but not prostate cancer (1.05, 0.96 to 1.15). Several of these relations had higher hazard ratios in the younger age group. Muscle weakness (defined as grip strength <26 kg for men and <16 kg for women) was associated with a higher hazard for all health outcomes, except colon cancer in women and prostate cancer and lung cancer in both men and women. The addition of handgrip strength improved the prediction ability, based on C index change, of an office based risk score (age, sex, diabetes diagnosed, body mass index, systolic blood pressure, and smoking) for all cause (0.013) and cardiovascular mortality (0.012) and incidence of cardiovascular disease (0.009). Conclusion Higher grip strength was associated with a range of health outcomes and improved prediction of an office based risk score. Further work on the use of grip strength in risk scores or risk screening is needed to establish its potential clinical utility. PMID:29739772

The value of the injury severity score in pediatric trauma: Time for a new definition of severe injury?

PubMed

Brown, Joshua B; Gestring, Mark L; Leeper, Christine M; Sperry, Jason L; Peitzman, Andrew B; Billiar, Timothy R; Gaines, Barbara A

2017-06-01

The Injury Severity Score (ISS) is the most commonly used injury scoring system in trauma research and benchmarking. An ISS greater than 15 conventionally defines severe injury; however, no studies evaluate whether ISS performs similarly between adults and children. Our objective was to evaluate ISS and Abbreviated Injury Scale (AIS) to predict mortality and define optimal thresholds of severe injury in pediatric trauma. Patients from the Pennsylvania trauma registry 2000-2013 were included. Children were defined as younger than 16 years. Logistic regression predicted mortality from ISS for children and adults. The optimal ISS cutoff for mortality that maximized diagnostic characteristics was determined in children. Regression also evaluated the association between mortality and maximum AIS in each body region, controlling for age, mechanism, and nonaccidental trauma. Analysis was performed in single and multisystem injuries. Sensitivity analyses with alternative outcomes were performed. Included were 352,127 adults and 50,579 children. Children had similar predicted mortality at ISS of 25 as adults at ISS of 15 (5%). The optimal ISS cutoff in children was ISS greater than 25 and had a positive predictive value of 19% and negative predictive value of 99% compared to a positive predictive value of 7% and negative predictive value of 99% for ISS greater than 15 to predict mortality. In single-system-injured children, mortality was associated with head (odds ratio, 4.80; 95% confidence interval, 2.61-8.84; p < 0.01) and chest AIS (odds ratio, 3.55; 95% confidence interval, 1.81-6.97; p < 0.01), but not abdomen, face, neck, spine, or extremity AIS (p > 0.05). For multisystem injury, all body region AIS scores were associated with mortality except extremities. Sensitivity analysis demonstrated ISS greater than 23 to predict need for full trauma activation, and ISS greater than 26 to predict impaired functional independence were optimal thresholds. An ISS greater than 25 may be a more appropriate definition of severe injury in children. Pattern of injury is important, as only head and chest injury drive mortality in single-system-injured children. These findings should be considered in benchmarking and performance improvement efforts. Epidemiologic study, level III.

Multi-scale predictions of coniferous forest mortality in the northern hemisphere

NASA Astrophysics Data System (ADS)

McDowell, N. G.

2015-12-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our incomplete understanding of the fundamental physiological thresholds of vegetation mortality during drought limits our ability to accurately simulate future vegetation distributions and associated climate feedbacks. Here we integrate experimental evidence with models to show potential widespread loss of needleleaf evergreen trees (NET; ~ conifers) within the Southwest USA by 2100; with rising temperature being the primary cause of mortality. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ypd) thresholds (April-August mean) beyond which photosynthesis, stomatal and hydraulic conductance, and carbohydrate availability approached zero. Empirical and mechanistic models accurately predicted NET Ypd, and 91% of predictions (10/11) exceeded mortality thresholds within the 21st century due to temperature rise. Completely independent global models predicted >50% loss of northern hemisphere NET by 2100, consistent with the findings for Southwest USA. The global models disagreed with the ecosystem process models in regards to future mortality in Southwest USA, however, highlighting the potential underestimates of future NET mortality as simulated by the global models and signifying the importance of improving regional predictions. Taken together, these results from the validated regional predictions and the global simulations predict global-scale conifer loss in coming decades under projected global warming.

A review of logistic regression models used to predict post-fire tree mortality of western North American conifers

Treesearch

Travis Woolley; David C. Shaw; Lisa M. Ganio; Stephen Fitzgerald

2012-01-01

Logistic regression models used to predict tree mortality are critical to post-fire management, planning prescribed bums and understanding disturbance ecology. We review literature concerning post-fire mortality prediction using logistic regression models for coniferous tree species in the western USA. We include synthesis and review of: methods to develop, evaluate...

A biomarker-based risk score to predict death in patients with atrial fibrillation: the ABC (age, biomarkers, clinical history) death risk score

PubMed Central

Hijazi, Ziad; Oldgren, Jonas; Lindbäck, Johan; Alexander, John H; Connolly, Stuart J; Eikelboom, John W; Ezekowitz, Michael D; Held, Claes; Hylek, Elaine M; Lopes, Renato D; Yusuf, Salim; Granger, Christopher B; Siegbahn, Agneta; Wallentin, Lars

2018-01-01

Abstract Aims In atrial fibrillation (AF), mortality remains high despite effective anticoagulation. A model predicting the risk of death in these patients is currently not available. We developed and validated a risk score for death in anticoagulated patients with AF including both clinical information and biomarkers. Methods and results The new risk score was developed and internally validated in 14 611 patients with AF randomized to apixaban vs. warfarin for a median of 1.9 years. External validation was performed in 8548 patients with AF randomized to dabigatran vs. warfarin for 2.0 years. Biomarker samples were obtained at study entry. Variables significantly contributing to the prediction of all-cause mortality were assessed by Cox-regression. Each variable obtained a weight proportional to the model coefficients. There were 1047 all-cause deaths in the derivation and 594 in the validation cohort. The most important predictors of death were N-terminal pro B-type natriuretic peptide, troponin-T, growth differentiation factor-15, age, and heart failure, and these were included in the ABC (Age, Biomarkers, Clinical history)-death risk score. The score was well-calibrated and yielded higher c-indices than a model based on all clinical variables in both the derivation (0.74 vs. 0.68) and validation cohorts (0.74 vs. 0.67). The reduction in mortality with apixaban was most pronounced in patients with a high ABC-death score. Conclusion A new biomarker-based score for predicting risk of death in anticoagulated AF patients was developed, internally and externally validated, and well-calibrated in two large cohorts. The ABC-death risk score performed well and may contribute to overall risk assessment in AF. ClinicalTrials.gov identifier NCT00412984 and NCT00262600 PMID:29069359

Predicting trauma patient mortality: ICD [or ICD-10-AM] versus AIS based approaches.

PubMed

Willis, Cameron D; Gabbe, Belinda J; Jolley, Damien; Harrison, James E; Cameron, Peter A

2010-11-01

The International Classification of Diseases Injury Severity Score (ICISS) has been proposed as an International Classification of Diseases (ICD)-10-based alternative to mortality prediction tools that use Abbreviated Injury Scale (AIS) data, including the Trauma and Injury Severity Score (TRISS). To date, studies have not examined the performance of ICISS using Australian trauma registry data. This study aimed to compare the performance of ICISS with other mortality prediction tools in an Australian trauma registry. This was a retrospective review of prospectively collected data from the Victorian State Trauma Registry. A training dataset was created for model development and a validation dataset for evaluation. The multiplicative ICISS model was compared with a worst injury ICISS approach, Victorian TRISS (V-TRISS, using local coefficients), maximum AIS severity and a multivariable model including ICD-10-AM codes as predictors. Models were investigated for discrimination (C-statistic) and calibration (Hosmer-Lemeshow statistic). The multivariable approach had the highest level of discrimination (C-statistic 0.90) and calibration (H-L 7.65, P= 0.468). Worst injury ICISS, V-TRISS and maximum AIS had similar performance. The multiplicative ICISS produced the lowest level of discrimination (C-statistic 0.80) and poorest calibration (H-L 50.23, P < 0.001). The performance of ICISS may be affected by the data used to develop estimates, the ICD version employed, the methods for deriving estimates and the inclusion of covariates. In this analysis, a multivariable approach using ICD-10-AM codes was the best-performing method. A multivariable ICISS approach may therefore be a useful alternative to AIS-based methods and may have comparable predictive performance to locally derived TRISS models. © 2010 The Authors. ANZ Journal of Surgery © 2010 Royal Australasian College of Surgeons.

Long-term mortality rates (>8-year) improve as compared to the general and obese population following bariatric surgery.

PubMed

Telem, Dana A; Talamini, Mark; Shroyer, A Laurie; Yang, Jie; Altieri, Maria; Zhang, Qiao; Gracia, Gerald; Pryor, Aurora D

2015-03-01

Sparse data are available on long-term patient mortality following bariatric surgery as compared to the general population. The purpose of this study was to assess long-term mortality rates and identify risk factors for all-cause mortality following bariatric surgery. New York State (NYS) Planning and Research Cooperative System (SPARCS) longitudinal administrative data were used to identify 7,862 adult patients who underwent a primary laparoscopic bariatric surgery from 1999 to 2005. The Social Security Death Index database identified >30-day mortalities. Risk factors for mortality were screened using a univariate Cox proportional hazard (PH) model and analyzed using a multiple PH model. Based on age, gender, and race/ethnicity, actuarial projections for NYS mortality rates obtained from Centers of Disease Control were compared to the actual post-bariatric surgery mortality rates observed. The mean bariatric mortality rate was 2.5 % with 8-14 years of follow-up. Mean time to death ranged from 4 to 6 year and did not differ by operation (p = 0.073). From 1999 to 2010, the actuarial mortality rate predicted for the general NYS population was 2.1 % versus the observed 1.5 % for the bariatric surgery population (p = 0.005). Extrapolating to 2013, demonstrated the actuarial mortality predictions at 3.1 % versus the bariatric surgery patients' observed morality rate of 2.5 % (p = 0.01). Risk factors associated with an earlier time to death included: age, male gender, Medicare/Medicaid insurance, congestive heart failure, rheumatoid arthritis, pulmonary circulation disorders, and diabetes. No procedure-specific or perioperative complication impact for time-to-death was found. Long-term mortality rate of patients undergoing bariatric surgery significantly improves as compared to the general population regardless of bariatric operation performed. Additionally, perioperative complications do not increase long-term mortality risk. This study did identify specific patient risk factors for long-term mortality. Special attention and consideration should be given to these "at risk" patient sub-populations.

Using the abbreviated injury severity and Glasgow Coma Scale scores to predict 2-week mortality after traumatic brain injury.

PubMed

Timmons, Shelly D; Bee, Tiffany; Webb, Sharon; Diaz-Arrastia, Ramon R; Hesdorffer, Dale

2011-11-01

Prediction of outcome after traumatic brain injury (TBI) remains elusive. We tested the use of a single hospital Glasgow Coma Scale (GCS) Score, GCS Motor Score, and the Head component of the Abbreviated Injury Scale (AIS) Score to predict 2-week cumulative mortality in a large cohort of TBI patients admitted to the eight U.S. Level I trauma centers in the TBI Clinical Trials Network. Data on 2,808 TBI patients were entered into a centralized database. These TBI patients were categorized as severe (GCS score, 3-8), moderate (9-12), or complicated mild (13-15 with positive computed tomography findings). Intubation and chemical paralysis were recorded. The cumulative incidence of mortality in the first 2 weeks after head injury was calculated using Kaplan-Meier survival analysis. Cox proportional hazards regression was used to estimate the magnitude of the risk for 2-week mortality. Two-week cumulative mortality was independently predicted by GCS, GCS Motor Score, and Head AIS. GCS Severity Category and GCS Motor Score were stronger predictors of 2-week mortality than Head AIS. There was also an independent effect of age (<60 vs. ≥60) on mortality after controlling for both GCS and Head AIS Scores. Anatomic and physiologic scales are useful in the prediction of mortality after TBI. We did not demonstrate any added benefit to combining the total GCS or GCS Motor Scores with the Head AIS Score in the short-term prediction of death after TBI.

Mortality of atomic bomb survivors predicted from laboratory animals

NASA Technical Reports Server (NTRS)

Carnes, Bruce A.; Grahn, Douglas; Hoel, David

2003-01-01

Exposure, pathology and mortality data for mice, dogs and humans were examined to determine whether accurate interspecies predictions of radiation-induced mortality could be achieved. The analyses revealed that (1) days of life lost per unit dose can be estimated for a species even without information on radiation effects in that species, and (2) accurate predictions of age-specific radiation-induced mortality in beagles and the atomic bomb survivors can be obtained from a dose-response model for comparably exposed mice. These findings illustrate the value of comparative mortality analyses and the relevance of animal data to the study of human health effects.

Early life mortality and height in Indian states

PubMed Central

Coffey, Diane

2014-01-01

Height is a marker for health, cognitive ability and economic productivity. Recent research on the determinants of height suggests that postneonatal mortality predicts height because it is a measure of the early life disease environment to which a cohort is exposed. This article advances the literature on the determinants of height by examining the role of early life mortality, including neonatal mortality, in India, a large developing country with a very short population. It uses state level variation in neonatal mortality, postneonatal mortality, and pre-adult mortality to predict the heights of adults born between 1970 and 1983, and neonatal and postneonatal mortality to predict the heights of children born between 1995 and 2005. In contrast to what is found in the literature on developed countries, I find that state level variation in neonatal mortality is a strong predictor of adult and child heights. This may be due to state level variation in, and overall poor levels of, pre-natal nutrition in India. PMID:25499239

Ability of King's College Criteria and Model for End-Stage Liver Disease Scores to Predict Mortality of Patients With Acute Liver Failure: A Meta-analysis.

PubMed

McPhail, Mark J W; Farne, Hugo; Senvar, Naz; Wendon, Julia A; Bernal, William

2016-04-01

Several prognostic factors are used to identify patients with acute liver failure (ALF) who require emergency liver transplantation. We performed a meta-analysis to determine the accuracy of King's College criteria (KCC) versus the model for end-stage liver disease (MELD) scores in predicting hospital mortality among patients with ALF. We performed a systematic search of the literature for articles published from 2001 through 2015 that compared the accuracy of the KCC with MELD scores in predicting hospital mortality in patients with ALF. We identified 23 studies (comprising 2153 patients) and assessed the quality of data, and then performed a meta-analysis of pooled sensitivity and specificity values, diagnostic odds ratios (DORs), and summary receiver operating characteristic curves. Subgroups analyzed included study quality, era, location (Europe vs non-Europe), and size; ALF etiology (acetaminophen-associated ALF [AALF] vs nonassociated [NAALF]); and whether or not the study included patients who underwent liver transplantation and if the study center was also a transplant center. The DOR for the KCC was 5.3 (95% confidence interval [CI], 3.7-7.6; 57% heterogeneity) and the DOR for MELD score was 7.0 (95% CI, 5.1-9.7; 48% heterogeneity), so the MELD score and KCC are comparable in overall accuracy. The summary area under the receiver operating characteristic curve values was 0.76 for the KCC and 0.78 for MELD scores. The KCC identified patients with AALF who died with 58% sensitivity (95% CI, 51%-65%) and 89% specificity (95% CI, 85%-93%), whereas MELD scores identified patients with AALF who died with 80% sensitivity (95% CI, 74%-86%) and 53% specificity (95% CI, 47%-59%). The KCC predicted hospital mortality in patients with NAALF with 58% sensitivity (95% CI, 54%-63%) and 74% specificity (95% CI, 69%-78%), whereas MELD scores predicted hospital mortality in patients with NAALF with 76% sensitivity (95% CI, 72%-80%) and 73% specificity (95% CI, 69%-78%). In patients with AALF, the KCC's DOR was 10.4 (95% CI, 4.9-22.1) and the MELD score's DOR was 6.6 (95% CI, 2.1-20.2). In patients with NAALF, the KCC's DOR was 4.16 (95% CI, 2.34-7.40) and the MELD score's DOR was 8.42 (95% CI, 5.98-11.88). Based on a meta-analysis of studies, the KCC more accurately predicts hospital mortality among patients with AALF, whereas MELD scores more accurately predict mortality among patients with NAALF. However, there is significant heterogeneity among studies and neither system is optimal for all patients. Given the importance of specificity in decision making for listing for emergency liver transplantation, MELD scores should not replace the KCC in predicting hospital mortality of patients with AALF, but could have a role for NAALF. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

NASA Astrophysics Data System (ADS)

McDowell, N. G.; Williams, A. P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, S.; Pangle, R.; Limousin, J.; Plaut, J.; Mackay, D. S.; Ogee, J.; Domec, J. C.; Allen, C. D.; Fisher, R. A.; Jiang, X.; Muss, J. D.; Breshears, D. D.; Rauscher, S. A.; Koven, C.

2016-03-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April-August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted >=50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Multi-scale predictions of massive conifer mortality due to chronic temperature rise

USGS Publications Warehouse

McDowell, Nathan G.; Williams, A.P.; Xu, C.; Pockman, W. T.; Dickman, L. T.; Sevanto, Sanna; Pangle, R.; Limousin, J.; Plaut, J.J.; Mackay, D.S.; Ogee, J.; Domec, Jean-Christophe; Allen, Craig D.; Fisher, Rosie A.; Jiang, X.; Muss, J.D.; Breshears, D.D.; Rauscher, Sara A.; Koven, C.

2016-01-01

Global temperature rise and extremes accompanying drought threaten forests and their associated climatic feedbacks. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain in part owing to our failure to integrate physiological measurements, regional-scale models, and dynamic global vegetation models (DGVMs). Here we show consistent predictions of widespread mortality of needleleaf evergreen trees (NET) within Southwest USA by 2100 using state-of-the-art models evaluated against empirical data sets. Experimentally, dominant Southwest USA NET species died when they fell below predawn water potential (Ψpd) thresholds (April–August mean) beyond which photosynthesis, hydraulic and stomatal conductance, and carbohydrate availability approached zero. The evaluated regional models accurately predicted NET Ψpd, and 91% of predictions (10 out of 11) exceeded mortality thresholds within the twenty-first century due to temperature rise. The independent DGVMs predicted ≥50% loss of Northern Hemisphere NET by 2100, consistent with the NET findings for Southwest USA. Notably, the global models underestimated future mortality within Southwest USA, highlighting that predictions of future mortality within global models may be underestimates. Taken together, the validated regional predictions and the global simulations predict widespread conifer loss in coming decades under projected global warming.

Predicting two-year mortality from discharge after acute coronary syndrome: An internationally-based risk score.

PubMed

Pocock, Stuart J; Huo, Yong; Van de Werf, Frans; Newsome, Simon; Chin, Chee Tang; Vega, Ana Maria; Medina, Jesús; Bueno, Héctor

2017-08-01

Long-term risk of post-discharge mortality associated with acute coronary syndrome remains a concern. The development of a model to reliably estimate two-year mortality risk from hospital discharge post-acute coronary syndrome will help guide treatment strategies. EPICOR (long-tErm follow uP of antithrombotic management patterns In acute CORonary syndrome patients, NCT01171404) and EPICOR Asia (EPICOR Asia, NCT01361386) are prospective observational studies of 23,489 patients hospitalized for an acute coronary syndrome event, who survived to discharge and were then followed up for two years. Patients were enrolled from 28 countries across Europe, Latin America and Asia. Risk scoring for two-year all-cause mortality risk was developed using identified predictive variables and forward stepwise Cox regression. Goodness-of-fit and discriminatory power was estimated. Within two years of discharge 5.5% of patients died. We identified 17 independent mortality predictors: age, low ejection fraction, no coronary revascularization/thrombolysis, elevated serum creatinine, poor EQ-5D score, low haemoglobin, previous cardiac or chronic obstructive pulmonary disease, elevated blood glucose, on diuretics or an aldosterone inhibitor at discharge, male sex, low educational level, in-hospital cardiac complications, low body mass index, ST-segment elevation myocardial infarction diagnosis, and Killip class. Geographic variation in mortality risk was seen following adjustment for other predictive variables. The developed risk-scoring system provided excellent discrimination ( c-statistic=0.80, 95% confidence interval=0.79-0.82) with a steep gradient in two-year mortality risk: >25% (top decile) vs. ~1% (bottom quintile). A simplified risk model with 11 predictors gave only slightly weaker discrimination ( c-statistic=0.79, 95% confidence interval =0.78-0.81). This risk score for two-year post-discharge mortality in acute coronary syndrome patients ( www.acsrisk.org ) can facilitate identification of high-risk patients and help guide tailored secondary prevention measures.

The BIG Score and Prediction of Mortality in Pediatric Blunt Trauma.

PubMed

Davis, Adrienne L; Wales, Paul W; Malik, Tahira; Stephens, Derek; Razik, Fathima; Schuh, Suzanne

2015-09-01

To examine the association between in-hospital mortality and the BIG (composed of the base deficit [B], International normalized ratio [I], Glasgow Coma Scale [G]) score measured on arrival to the emergency department in pediatric blunt trauma patients, adjusted for pre-hospital intubation, volume administration, and presence of hypotension and head injury. We also examined the association between the BIG score and mortality in patients requiring admission to the intensive care unit (ICU). A retrospective 2001-2012 trauma database review of patients with blunt trauma ≤ 17 years old with an Injury Severity score ≥ 12. Charts were reviewed for in-hospital mortality, components of the BIG score upon arrival to the emergency department, prehospital intubation, crystalloids ≥ 20 mL/kg, presence of hypotension, head injury, and disposition. 50/621 (8%) of the study patients died. Independent mortality predictors were the BIG score (OR 11, 95% CI 6-25), prior fluid bolus (OR 3, 95% CI 1.3-9), and prior intubation (OR 8, 95% CI 2-40). The area under the receiver operating characteristic curve was 0.95 (CI 0.93-0.98), with the optimal BIG cutoff of 16. With BIG <16, death rate was 3/496 (0.006, 95% CI 0.001-0.007) vs 47/125 (0.38, 95% CI 0.15-0.7) with BIG ≥ 16, (P < .0001). In patients requiring admission to the ICU, the BIG score remained predictive of mortality (OR 14.3, 95% CI 7.3-32, P < .0001). The BIG score accurately predicts mortality in a population of North American pediatric patients with blunt trauma independent of pre-hospital interventions, presence of head injury, and hypotension, and identifies children with a high probability of survival (BIG <16). The BIG score is also associated with mortality in pediatric patients with trauma requiring admission to the ICU. Copyright © 2015 Elsevier Inc. All rights reserved.

Determining population based mortality risk in the Department of Veterans Affairs.

PubMed

Stefos, Theodore; Lehner, Laura; Render, Marta; Moran, Eileen; Almenoff, Peter

2012-06-01

We develop a patient level hierarchical regression model using administrative claims data to assess mortality outcomes for a national VA population. This model, which complements more traditional process driven performance measures, includes demographic variables and disease specific measures of risk classified by Diagnostic Cost Groups (DCGs). Results indicate some ability to discriminate survivors and non-survivors with an area under the Receiver Operating Characteristic Curve (C-statistic) of .86. Observed to expected mortality ranges from .86 to 1.12 across predicted mortality deciles while Risk Standardized Mortality Rates (RSMRs) range from .76 to 1.29 across 145 VA hospitals. Further research is necessary to understand mortality variation which persists even after adjusting for case mix differences. Future work is also necessary to examine the role of personal behaviors on patient outcomes and the potential impact on population survival rates from changes in treatment policy and infrastructure investment.

Socioeconomic and Behavioral Risk Factors for Mortality in a National 19-Year Prospective Study of U.S. Adults

PubMed Central

Lantz, Paula M.; Golberstein, Ezra; House, James S.; Morenoff, Jeffrey D.

2012-01-01

Many demographic, socioeconomic, and behavioral risk factors predict mortality in the United States. However, very few population-based longitudinal studies are able to investigate simultaneously the impact of a variety of social factors on mortality. We investigated the degree to which demographic characteristics, socioeconomic variables and major health risk factors were associated with mortality in a nationally-representative sample of 3,617 U.S. adults from 1986-2005, using data from the 4 waves of the Americans’ Changing Lives study. Cox proportional hazard models with time-varying covariates were employed to predict all-cause mortality verified through the National Death Index and death certificate review. The results revealed that low educational attainment was not associated with mortality when income and health risk behaviors were included in the model. The association of low-income with mortality remained after controlling for major behavioral risks. Compared to those in the “normal” weight category, neither overweight nor obesity was significantly associated with the risk of mortality. Among adults age 55 and older at baseline, the risk of mortality was actually reduced for those were overweight (hazard rate ratio=0.83, 95% C.I. = 0.71 – 0.98) and those who were obese (hazard rate ratio=0.68, 95% C.I. = 0.55 – 0.84), controlling for other health risk behaviors and health status. Having a low level of physical activity was a significant risk factor for mortality (hazard rate ratio=1.58, 95% C.I. = 1.20 – 2.07). The results from this national longitudinal study underscore the need for health policies and clinical interventions focusing on the social and behavioral determinants of health, with a particular focus on income security, smoking prevention/cessation, and physical activity. PMID:20226579

Does unemployment cause long-term mortality? Selection and causation after the 1992-96 deep Swedish recession.

PubMed

Vågerö, Denny; Garcy, Anthony M

2016-10-01

Mass unemployment in Europe is endemic, especially among the young. Does it cause mortality? We analyzed long-term effects of unemployment occurring during the deep Swedish recession 1992-96. Mortality from all and selected causes was examined in the 6-year period after the recession among those employed in 1990 (3.4 million). Direct health selection was analyzed as risk of unemployment by prior medical history based on all hospitalizations 1981-91. Unemployment effects on mortality were estimated with and without adjustment for prior social characteristics and for prior medical history. A prior circulatory disease history did not predict unemployment; a history of alcohol-related disease or suicide attempts did, in men and women. Unemployment predicted excess male, but not female, mortality from circulatory disease, both ischemic heart disease and stroke, and from all causes combined, after full adjustment. Adjustment for prior social characteristics reduced estimates considerably; additional adjustment for prior medical history did not. Mortality from external and alcohol-related causes was raised in men and women experiencing unemployment, after adjustment for social characteristics and medical history. For the youngest birth cohorts fully adjusted alcohol mortality HRs were substantial (male HR = 4.44; female HR = 5.73). The effect of unemployment on mortality was not uniform across the population; men, those with a low education, low income, unmarried or in urban employment were more vulnerable. Direct selection by medical history explains a modest fraction of any increased mortality risk following unemployment. Mass unemployment imposes long-term mortality risk on a sizeable segment of the population. © The Author 2016. Published by Oxford University Press on behalf of the European Public Health Association.

Does unemployment cause long-term mortality? Selection and causation after the 1992–96 deep Swedish recession

PubMed Central

Garcy, Anthony M.

2016-01-01

Abstract Background: Mass unemployment in Europe is endemic, especially among the young. Does it cause mortality? Methods: We analyzed long-term effects of unemployment occurring during the deep Swedish recession 1992–96. Mortality from all and selected causes was examined in the 6-year period after the recession among those employed in 1990 (3.4 million). Direct health selection was analyzed as risk of unemployment by prior medical history based on all hospitalizations 1981–91. Unemployment effects on mortality were estimated with and without adjustment for prior social characteristics and for prior medical history. Results: A prior circulatory disease history did not predict unemployment; a history of alcohol-related disease or suicide attempts did, in men and women. Unemployment predicted excess male, but not female, mortality from circulatory disease, both ischemic heart disease and stroke, and from all causes combined, after full adjustment. Adjustment for prior social characteristics reduced estimates considerably; additional adjustment for prior medical history did not. Mortality from external and alcohol-related causes was raised in men and women experiencing unemployment, after adjustment for social characteristics and medical history. For the youngest birth cohorts fully adjusted alcohol mortality HRs were substantial (male HR = 4.44; female HR = 5.73). The effect of unemployment on mortality was not uniform across the population; men, those with a low education, low income, unmarried or in urban employment were more vulnerable. Conclusions: Direct selection by medical history explains a modest fraction of any increased mortality risk following unemployment. Mass unemployment imposes long-term mortality risk on a sizeable segment of the population. PMID:27085193

Value of biologic therapy: a forecasting model in three disease areas.

PubMed

Paramore, L Clark; Hunter, Craig A; Luce, Bryan R; Nordyke, Robert J; Halbert, R J

2010-01-01

Forecast the return on investment (ROI) for advances in biologic therapies in years 2015 and 2030, based upon impact on disease prevalence, morbidity, and mortality for asthma, diabetes, and colorectal cancer. A deterministic, spreadsheet-based, forecasting model was developed based on trends in demographics and disease epidemiology. 'Return' was defined as reductions in disease burden (prevalence, morbidity, mortality) translated into monetary terms; 'investment' was defined as the incremental costs of biologic therapy advances. Data on disease prevalence, morbidity, mortality, and associated costs were obtained from government survey statistics or published literature. Expected impact of advances in biologic therapies was based on expert opinion. Gains in quality-adjusted life years (QALYs) were valued at $100,000 per QALY. The base case analysis, in which reductions in disease prevalence and mortality predicted by the expert panel are not considered, shows the resulting ROIs remain positive for asthma and diabetes but fall below $1 for colorectal cancer. Analysis involving expert panel predictions indicated positive ROI results for all three diseases at both time points, ranging from $207 for each incremental dollar spent on biologic therapies to treat asthma in 2030, to $4 for each incremental dollar spent on biologic therapies to treat colorectal cancer in 2015. If QALYs are not considered, the resulting ROIs remain positive for all three diseases at both time points. Society may expect substantial returns from investments in innovative biologic therapies. These benefits are most likely to be realized in an environment of appropriate use of new molecules. The potential variance between forecasted (from expert opinion) and actual future health outcomes could be significant. Similarly, the forecasted growth in use of biologic therapies relied upon unvalidated market forecasts.

Estimating severity of burn in children: Pediatric Risk of Mortality (PRISM) score versus Abbreviated Burn Severity Index (ABSI).

PubMed

Berndtson, Allison E; Sen, Soman; Greenhalgh, David G; Palmieri, Tina L

2013-09-01

The purpose of our study is to validate the Pediatric Risk of Mortality (PRISM) score and compare the accuracy of PRISM predicted outcomes to the Abbreviated Burn Severity Index (ABSI). We hypothesized that the PRISM score is more accurate in predicting mortality and hospital length of stay than the ABSI in children with severe burns. All children <18 years of age admitted to a regional pediatric burn center between January 1, 2008 and July 1, 2010 were reviewed. Those with a Total Body Surface Area (TBSA) burn ≥20% who were admitted within 7 days of injury were selected for our study. Measured parameters included: demographics, burn characteristics, PRISM and ABSI scores at admission, and outcomes (mortality, hospital length of stay (LOS), ventilator days and cause of death). A total of 83 patients met criteria and had complete data sets. The mean age (±SEM) was 8.0±0.6 years, mean % TBSA burn 49.9±2.1%, 62.7% were male, and 45.8% had inhalation injury. Hospital LOS was 74.4±7.9 days, with 31.5±4.9 ventilator days. Mean PRISM score ranged from 14.2 to 16.0, with ABSI scores 7.9 to 8.5. Actual overall mortality was 18.1% compared to a PRISM predicted mortality of 19.8±2.5% (p<0.001, r=0.570). ABSI predicted mortality varied from 10 to 20% for a score of 7.9 to 30-50% for a score of 8.5. Logistic regression showed that both PRISM (p<0.001) and ABSI (p<0.001) mortality predictions accurately estimated actual mortality, which remained true in a combined model. ABSI was predictive of hospital LOS (p<0.001) and ventilator days (p<0.001) while PRISM was not (p=0.326 and p=0.863). Both PRISM and ABSI scores are predictive of mortality in severely burned children. Only ABSI correlates with hospital length of stay and ventilator days, and thus may also be more useful in predicting ICU resource utilization. Copyright © 2013 Elsevier Ltd and ISBI. All rights reserved.

Usefulness of the addition of beta-2-microglobulin, cystatin C and C-reactive protein to an established risk factors model to improve mortality risk prediction in patients undergoing coronary angiography.

PubMed

Nead, Kevin T; Zhou, Margaret J; Caceres, Roxanne Diaz; Sharp, Stephen J; Wehner, Mackenzie R; Olin, Jeffrey W; Cooke, John P; Leeper, Nicholas J

2013-03-15

Evidence-based therapies are available to reduce the risk for death from cardiovascular disease, yet many patients go untreated. Novel methods are needed to identify those at highest risk for cardiovascular death. In this study, the biomarkers β2-microglobulin, cystatin C, and C-reactive protein were measured at baseline in a cohort of participants who underwent coronary angiography. Adjusted Cox proportional-hazards models were used to determine whether the biomarkers predicted all-cause and cardiovascular mortality. Additionally, improvements in risk reclassification and discrimination were evaluated by calculating the net reclassification improvement, C-index, and integrated discrimination improvement with the addition of the biomarkers to a baseline model of risk factors for cardiovascular disease and death. During a median follow-up period of 5.6 years, there were 78 deaths among 470 participants. All biomarkers independently predicted future all-cause and cardiovascular mortality. A significant improvement in risk reclassification was observed for all-cause (net reclassification improvement 35.8%, p = 0.004) and cardiovascular (net reclassification improvement 61.9%, p = 0.008) mortality compared to the baseline risk factors model. Additionally, there was significantly increased risk discrimination with C-indexes of 0.777 (change in C-index 0.057, 95% confidence interval 0.016 to 0.097) and 0.826 (change in C-index 0.071, 95% confidence interval 0.010 to 0.133) for all-cause and cardiovascular mortality, respectively. Improvements in risk discrimination were further supported using the integrated discrimination improvement index. In conclusion, this study provides evidence that β2-microglobulin, cystatin C, and C-reactive protein predict mortality and improve risk reclassification and discrimination for a high-risk cohort of patients who undergo coronary angiography. Copyright © 2013 Elsevier Inc. All rights reserved.

Mortality rates and risk factors for emergent open repair of abdominal aortic aneurysms in the endovascular era.

PubMed

Pecoraro, Felice; Gloekler, Steffen; Mader, Caecilia E; Roos, Malgorzata; Chaykovska, Lyubov; Veith, Frank J; Cayne, Neal S; Mangialardi, Nicola; Neff, Thomas; Lachat, Mario

2018-03-01

The background of this paper is to report the mortality at 30 and 90 days and at mean follow-up after open abdominal aortic aneurysms (AAA) emergent repair and to identify predictive risk factors for 30- and 90-day mortality. Between 1997 and 2002, 104 patients underwent emergent AAA open surgery. Symptomatic and ruptured AAAs were observed, respectively, in 21 and 79% of cases. Mean patient age was 70 (SD 9.2) years. Mean aneurysm maximal diameter was 7.4 (SD 1.6) cm. Primary endpoints were 30- and 90-day mortality. Significant mortality-related risk factor identification was the secondary endpoint. Open repair trend and its related perioperative mortality with a per-year analysis and a correlation subanalysis to identify predictive mortality factor were performed. Mean follow-up time was 23 (SD 23) months. Overall, 30-day mortality was 30%. Significant mortality-related risk factors were the use of computed tomography (CT) as a preoperative diagnostic tool, AAA rupture, preoperative shock, intraoperative cardiopulmonary resuscitation (CPR), use of aortic balloon occlusion, intraoperative massive blood transfusion (MBT), and development of abdominal compartment syndrome (ACS). Previous abdominal surgery was identified as a protective risk factor. The mortality rate at 90 days was 44%. Significant mortality-related risk factors were AAA rupture, aortocaval fistula, peripheral artery disease (PAD), preoperative shock, CPR, MBT, and ACS. The mortality rate at follow-up was 45%. Correlation analysis showed that MBT, shock, and ACS are the most relevant predictive mortality factor at 30 and 90 days. During the transition period from open to endovascular repair, open repair mortality outcomes remained comparable with other contemporary data despite a selection bias for higher risk patients. MBT, shock, and ACS are the most pronounced predictive mortality risk factors.

Derivation and validation of different machine-learning models in mortality prediction of trauma in motorcycle riders: a cross-sectional retrospective study in southern Taiwan

PubMed Central

Kuo, Pao-Jen; Wu, Shao-Chun; Chien, Peng-Chen; Rau, Cheng-Shyuan; Chen, Yi-Chun; Hsieh, Hsiao-Yun; Hsieh, Ching-Hua

2018-01-01

Objectives This study aimed to build and test the models of machine learning (ML) to predict the mortality of hospitalised motorcycle riders. Setting The study was conducted in a level-1 trauma centre in southern Taiwan. Participants Motorcycle riders who were hospitalised between January 2009 and December 2015 were classified into a training set (n=6306) and test set (n=946). Using the demographic information, injury characteristics and laboratory data of patients, logistic regression (LR), support vector machine (SVM) and decision tree (DT) analyses were performed to determine the mortality of individual motorcycle riders, under different conditions, using all samples or reduced samples, as well as all variables or selected features in the algorithm. Primary and secondary outcome measures The predictive performance of the model was evaluated based on accuracy, sensitivity, specificity and geometric mean, and an analysis of the area under the receiver operating characteristic curves of the two different models was carried out. Results In the training set, both LR and SVM had a significantly higher area under the receiver operating characteristic curve (AUC) than DT. No significant difference was observed in the AUC of LR and SVM, regardless of whether all samples or reduced samples and whether all variables or selected features were used. In the test set, the performance of the SVM model for all samples with selected features was better than that of all other models, with an accuracy of 98.73%, sensitivity of 86.96%, specificity of 99.02%, geometric mean of 92.79% and AUC of 0.9517, in mortality prediction. Conclusion ML can provide a feasible level of accuracy in predicting the mortality of motorcycle riders. Integration of the ML model, particularly the SVM algorithm in the trauma system, may help identify high-risk patients and, therefore, guide appropriate interventions by the clinical staff. PMID:29306885

Scoring life insurance applicants' laboratory results, blood pressure and build to predict all-cause mortality risk.

PubMed

Fulks, Michael; Stout, Robert L; Dolan, Vera F

2012-01-01

Evaluate the degree of medium to longer term mortality prediction possible from a scoring system covering all laboratory testing used for life insurance applicants, as well as blood pressure and build measurements. Using the results of testing for life insurance applicants who reported a Social Security number in conjunction with the Social Security Death Master File, the mortality associated with each test result was defined by age and sex. The individual mortality scores for each test were combined for each individual and a composite mortality risk score was developed. This score was then tested against the insurance applicant dataset to evaluate its ability to discriminate risk across age and sex. The composite risk score was highly predictive of all-cause mortality risk in a linear manner from the best to worst quintile of scores in a nearly identical fashion for each sex and decade of age. Laboratory studies, blood pressure and build from life insurance applicants can be used to create scoring that predicts all-cause mortality across age and sex. Such an approach may hold promise for preventative health screening as well.

Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit admission risk: a single-center retrospective study.

PubMed

Chan, Diana Xin Hui; Sim, Yilin Eileen; Chan, Yiong Huak; Poopalalingam, Ruban; Abdullah, Hairil Rizal

2018-03-23

Accurate surgical risk prediction is paramount in clinical shared decision making. Existing risk calculators have limited value in local practice due to lack of validation, complexities and inclusion of non-routine variables. We aim to develop a simple, locally derived and validated surgical risk calculator predicting 30-day postsurgical mortality and need for intensive care unit (ICU) stay (>24 hours) based on routinely collected preoperative variables. We postulate that accuracy of a clinical history-based scoring tool could be improved by including readily available investigations, such as haemoglobin level and red cell distribution width. Electronic medical records of 90 785 patients, who underwent non-cardiac and non-neuro surgery between 1 January 2012 and 31 October 2016 in Singapore General Hospital, were retrospectively analysed. Patient demographics, comorbidities, laboratory results, surgical priority and surgical risk were collected. Outcome measures were death within 30 days after surgery and ICU admission. After excluding patients with missing data, the final data set consisted of 79 914 cases, which was divided randomly into derivation (70%) and validation cohort (30%). Multivariable logistic regression analysis was used to construct a single model predicting both outcomes using Odds Ratio (OR) of the risk variables. The ORs were then assigned ranks, which were subsequently used to construct the calculator. Observed mortality was 0.6%. The Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator, consisting of nine variables, was constructed. The area under the receiver operating curve (AUROC) in the derivation and validation cohorts for mortality were 0.934 (0.917-0.950) and 0.934 (0.912-0.956), respectively, while the AUROC for ICU admission was 0.863 (0.848-0.878) and 0.837 (0.808-0.868), respectively. CARES also performed better than the American Society of Anaesthesiologists-Physical Status classification in terms of AUROC comparison. The development of the CARES surgical risk calculator allows for a simplified yet accurate prediction of both postoperative mortality and need for ICU admission after surgery. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Hepatic Venous Pressure Gradient Predicts Long-Term Mortality in Patients with Decompensated Cirrhosis

PubMed Central

Kim, Tae Yeob; Lee, Jae Gon; Kim, Ji Yeoun; Kim, Sun Min; Kim, Jinoo; Jeong, Woo Kyoung

2016-01-01

Purpose The present study aimed to investigate the role of hepatic venous pressure gradient (HVPG) for prediction of long-term mortality in patients with decompensated cirrhosis. Materials and Methods Clinical data from 97 non-critically-ill cirrhotic patients with HVPG measurements were retrospectively and consecutively collected between 2009 and 2012. Patients were classified according to clinical stages and presence of ascites. The prognostic accuracy of HVPG for death, survival curves, and hazard ratios were analyzed. Results During a median follow-up of 24 (interquartile range, 13-36) months, 22 patients (22.7%) died. The area under the receiver operating characteristics curves of HVPG for predicting 1-year, 2-year, and overall mortality were 0.801, 0.737, and 0.687, respectively (all p<0.01). The best cut-off value of HVPG for predicting long-term overall mortality in all patients was 17 mm Hg. The mortality rates at 1 and 2 years were 8.9% and 19.2%, respectively: 1.9% and 11.9% with HVPG ≤17 mm Hg and 16.2% and 29.4% with HVPG >17 mm Hg, respectively (p=0.015). In the ascites group, the mortality rates at 1 and 2 years were 3.9% and 17.6% with HVPG ≤17 mm Hg and 17.5% and 35.2% with HVPG >17 mm Hg, respectively (p=0.044). Regarding the risk factors for mortality, both HVPG and model for end-stage liver disease were positively related with long-term mortality in all patients. Particularly, for the patients with ascites, both prothrombin time and HVPG were independent risk factors for predicting poor outcomes. Conclusion HVPG is useful for predicting the long-term mortality in patients with decompensated cirrhosis, especially in the presence of ascites. PMID:26632394

Mortality prediction using TRISS methodology in the Spanish ICU Trauma Registry (RETRAUCI).

PubMed

Chico-Fernández, M; Llompart-Pou, J A; Sánchez-Casado, M; Alberdi-Odriozola, F; Guerrero-López, F; Mayor-García, M D; Egea-Guerrero, J J; Fernández-Ortega, J F; Bueno-González, A; González-Robledo, J; Servià-Goixart, L; Roldán-Ramírez, J; Ballesteros-Sanz, M Á; Tejerina-Alvarez, E; Pino-Sánchez, F I; Homar-Ramírez, J

2016-10-01

To validate Trauma and Injury Severity Score (TRISS) methodology as an auditing tool in the Spanish ICU Trauma Registry (RETRAUCI). A prospective, multicenter registry evaluation was carried out. Thirteen Spanish Intensive Care Units (ICUs). Individuals with traumatic disease and available data admitted to the participating ICUs. Predicted mortality using TRISS methodology was compared with that observed in the pilot phase of the RETRAUCI from November 2012 to January 2015. Discrimination was evaluated using receiver operating characteristic (ROC) curves and the corresponding areas under the curves (AUCs) (95% CI), with calibration using the Hosmer-Lemeshow (HL) goodness-of-fit test. A value of p<0.05 was considered significant. Predicted and observed mortality. A total of 1405 patients were analyzed. The observed mortality rate was 18% (253 patients), while the predicted mortality rate was 16.9%. The area under the ROC curve was 0.889 (95% CI: 0.867-0.911). Patients with blunt trauma (n=1305) had an area under the ROC curve of 0.887 (95% CI: 0.864-0.910), and those with penetrating trauma (n=100) presented an area under the curve of 0.919 (95% CI: 0.859-0.979). In the global sample, the HL test yielded a value of 25.38 (p=0.001): 27.35 (p<0.0001) in blunt trauma and 5.91 (p=0.658) in penetrating trauma. TRISS methodology underestimated mortality in patients with low predicted mortality and overestimated mortality in patients with high predicted mortality. TRISS methodology in the evaluation of severe trauma in Spanish ICUs showed good discrimination, with inadequate calibration - particularly in blunt trauma. Copyright © 2015 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

Simple Scoring System to Predict In-Hospital Mortality After Surgery for Infective Endocarditis.

PubMed

Gatti, Giuseppe; Perrotti, Andrea; Obadia, Jean-François; Duval, Xavier; Iung, Bernard; Alla, François; Chirouze, Catherine; Selton-Suty, Christine; Hoen, Bruno; Sinagra, Gianfranco; Delahaye, François; Tattevin, Pierre; Le Moing, Vincent; Pappalardo, Aniello; Chocron, Sidney

2017-07-20

Aspecific scoring systems are used to predict the risk of death postsurgery in patients with infective endocarditis (IE). The purpose of the present study was both to analyze the risk factors for in-hospital death, which complicates surgery for IE, and to create a mortality risk score based on the results of this analysis. Outcomes of 361 consecutive patients (mean age, 59.1±15.4 years) who had undergone surgery for IE in 8 European centers of cardiac surgery were recorded prospectively, and a risk factor analysis (multivariable logistic regression) for in-hospital death was performed. The discriminatory power of a new predictive scoring system was assessed with the receiver operating characteristic curve analysis. Score validation procedures were carried out. Fifty-six (15.5%) patients died postsurgery. BMI >27 kg/m 2 (odds ratio [OR], 1.79; P =0.049), estimated glomerular filtration rate <50 mL/min (OR, 3.52; P <0.0001), New York Heart Association class IV (OR, 2.11; P =0.024), systolic pulmonary artery pressure >55 mm Hg (OR, 1.78; P =0.032), and critical state (OR, 2.37; P =0.017) were independent predictors of in-hospital death. A scoring system was devised to predict in-hospital death postsurgery for IE (area under the receiver operating characteristic curve, 0.780; 95% CI, 0.734-0.822). The score performed better than 5 of 6 scoring systems for in-hospital death after cardiac surgery that were considered. A simple scoring system based on risk factors for in-hospital death was specifically created to predict mortality risk postsurgery in patients with IE. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Lactate clearance as a marker of mortality in pediatric intensive care unit.

PubMed

Munde, A; Kumar, N; Beri, R S; Puliyel, J M

2014-07-01

To correlate lactate clearance with Pediatric Intensive Care Unit (PICU) mortality. 45 (mean age 40.15 mo, 60% males) consecutive admissions in the PICU were enrolled between May 2012 to June 2013. Lactate clearance (Lactate level at admission - level 6 hr later x 100 / lactate level at admission) in first 6 hours of hospitalization was correlated to in-hospital mortality and PRISM score. Twelve out of 45 patients died. 90% died among those with delayed/poor clearance (clearance <30%) compared to 8.5% in those with good clearance (clearance >30%) (P<0.001). Lactate clearance <30% predicted mortality with sensitivity of 75%, specificity of 97%, positive predictive value of 90%, and negative predictive value of 91.42%. Predictability was comparable to PRISM score >30. Lactate clearance at six hours correlates with mortality in the PICU.

Different AIS triplets: Different mortality predictions in identical ISS and NISS.

PubMed

Aharonson-Daniel, Limor; Giveon, Adi; Stein, Michael; Peleg, Kobi

2006-09-01

Previous studies demonstrated different mortality predictions for identical Injury Severity Scores (ISS) from different Abbreviated Injury Scale (AIS) triplets. This study elaborates in both scope and volume producing results of a larger magnitude, applicable to specific injury subgroups of blunt or penetrating, traumatic brain injury, various age groups, and replicated on NISS. All patients hospitalized after trauma at 10 hospitals, with ISS/NISS (new ISS) generated by two AIS triplets, excluding patients with isolated minor or moderate injuries to a single body region were studied. Patients were separated into two groups based on the different triplets. Inpatient-mortality rates were calculated for each triplet group. Odds ratios were calculated to estimate the risk of dying in one triplet group as compared with the other. The chi test determined whether the difference in mortality rate between the two groups was significantly different. Differences were further explored for various subgroups. There were 35,827 patients who had ISS/NISS scores generated by two different AIS triplets. Significant differences in death rates were noted between triplet groups forming identical ISS/NISS. Odds ratio for being in the second group (always containing the higher AIS score) ranged from 2.3 to 7.4. ISS and NISS that are formed by different AIS triplets have significantly different inpatient-mortality rates. The triplet with the higher AIS score has higher inpatient-mortality rates, overall and in several sub-populations of varying vulnerability. The comparison of populations and the interpretation of ISS/NISS based outcome data should take this important information into account and the components of AIS triplets creating each ISS and NISS should be reported.

Distinct Age and Self-Rated Health Crossover Mortality Effects for African Americans: Evidence from a National Cohort Study

PubMed Central

Roth, David L.; Skarupski, Kimberly A.; Crews, Deidra C.; Howard, Virginia J.; Locher, Julie L.

2016-01-01

The predictive effects of age and self-rated health (SRH) on all-cause mortality are known to differ across race and ethnic groups. African American adults have higher mortality rates than Whites at younger ages, but this mortality disparity diminishes with advancing age and may “crossover” at about 75 to 80 years of age, when African Americans may show lower mortality rates. This pattern of findings reflects a lower overall association between age and mortality for African Americans than for Whites, and health-related mechanisms are typically cited as the reason for this age-based crossover mortality effect. However, a lower association between poor SRH and mortality has also been found for African Americans than for Whites, and it is not known if the reduced age and SRH associations with mortality for African Americans reflect independent or overlapping mechanisms. This study examined these two mortality predictors simultaneously in a large epidemiological study of 12,181 African Americans and 17,436 Whites. Participants were 45 or more years of age when they enrolled in the national REasons for Geographic and Racial Differences in Stroke (REGARDS) study between 2003 and 2007. Consistent with previous studies, African Americans had poorer SRH than Whites even after adjusting for demographic and health history covariates. Survival analysis models indicated statistically significant and independent race*age, race*SRH, and age*SRH interaction effects on all-cause mortality over an average 9-year follow-up period. Advanced age and poorer SRH were both weaker mortality risk factors for African Americans than for Whites. These two effects were distinct and presumably tapped different causal mechanisms. This calls into question the health-related explanation for the age-based mortality crossover effect and suggests that other mechanisms, including behavioral, social, and cultural factors, should be considered in efforts to better understand the age-based mortality crossover effect and other longevity disparities. PMID:27015163

Distinct age and self-rated health crossover mortality effects for African Americans: Evidence from a national cohort study.

PubMed

Roth, David L; Skarupski, Kimberly A; Crews, Deidra C; Howard, Virginia J; Locher, Julie L

2016-05-01

The predictive effects of age and self-rated health (SRH) on all-cause mortality are known to differ across race and ethnic groups. African American adults have higher mortality rates than Whites at younger ages, but this mortality disparity diminishes with advancing age and may "crossover" at about 75-80 years of age, when African Americans may show lower mortality rates. This pattern of findings reflects a lower overall association between age and mortality for African Americans than for Whites, and health-related mechanisms are typically cited as the reason for this age-based crossover mortality effect. However, a lower association between poor SRH and mortality has also been found for African Americans than for Whites, and it is not known if the reduced age and SRH associations with mortality for African Americans reflect independent or overlapping mechanisms. This study examined these two mortality predictors simultaneously in a large epidemiological study of 12,181 African Americans and 17,436 Whites. Participants were 45 or more years of age when they enrolled in the national REasons for Geographic and Racial Differences in Stroke (REGARDS) study between 2003 and 2007. Consistent with previous studies, African Americans had poorer SRH than Whites even after adjusting for demographic and health history covariates. Survival analysis models indicated statistically significant and independent race*age, race*SRH, and age*SRH interaction effects on all-cause mortality over an average 9-year follow-up period. Advanced age and poorer SRH were both weaker mortality risk factors for African Americans than for Whites. These two effects were distinct and presumably tapped different causal mechanisms. This calls into question the health-related explanation for the age-based mortality crossover effect and suggests that other mechanisms, including behavioral, social, and cultural factors, should be considered in efforts to better understand the age-based mortality crossover effect and other longevity disparities. Copyright © 2016. Published by Elsevier Ltd.

Urinary Sodium Concentration Is an Independent Predictor of All-Cause and Cardiovascular Mortality in a Type 2 Diabetes Cohort Population

PubMed Central

Gand, Elise; Ragot, Stéphanie; Bankir, Lise; Piguel, Xavier; Fumeron, Frédéric; Halimi, Jean-Michel; Marechaud, Richard; Roussel, Ronan; Hadjadj, Samy; Study group, SURDIAGENE

2017-01-01

Objective. Sodium intake is associated with cardiovascular outcomes. However, no study has specifically reported an association between cardiovascular mortality and urinary sodium concentration (UNa). We examined the association of UNa with mortality in a cohort of type 2 diabetes (T2D) patients. Methods. Patients were followed for all-cause death and cardiovascular death. Baseline UNa was measured from second morning spot urinary sample. We used Cox proportional hazard models to identify independent predictors of mortality. Improvement in prediction of mortality by the addition of UNa to a model including known risk factors was assessed by the relative integrated discrimination improvement (rIDI) index. Results. Participants (n = 1,439) were followed for a median of 5.7 years, during which 254 cardiovascular deaths and 429 all-cause deaths were recorded. UNa independently predicted all-cause and cardiovascular mortality. An increase of one standard deviation of UNa was associated with a decrease of 21% of all-cause mortality and 22% of cardiovascular mortality. UNa improved all-cause and cardiovascular mortality prediction beyond identified risk factors (rIDI = 2.8%, P = 0.04 and rIDI = 4.6%, P = 0.02, resp.). Conclusions. In T2D, UNa was an independent predictor of mortality (low concentration is associated with increased risk) and improved modestly its prediction in addition to traditional risk factors. PMID:28255559

Application of biomarkers in cancer risk management: evaluation from stochastic clonal evolutionary and dynamic system optimization points of view.

PubMed

Li, Xiaohong; Blount, Patricia L; Vaughan, Thomas L; Reid, Brian J

2011-02-01

Aside from primary prevention, early detection remains the most effective way to decrease mortality associated with the majority of solid cancers. Previous cancer screening models are largely based on classification of at-risk populations into three conceptually defined groups (normal, cancer without symptoms, and cancer with symptoms). Unfortunately, this approach has achieved limited successes in reducing cancer mortality. With advances in molecular biology and genomic technologies, many candidate somatic genetic and epigenetic "biomarkers" have been identified as potential predictors of cancer risk. However, none have yet been validated as robust predictors of progression to cancer or shown to reduce cancer mortality. In this Perspective, we first define the necessary and sufficient conditions for precise prediction of future cancer development and early cancer detection within a simple physical model framework. We then evaluate cancer risk prediction and early detection from a dynamic clonal evolution point of view, examining the implications of dynamic clonal evolution of biomarkers and the application of clonal evolution for cancer risk management in clinical practice. Finally, we propose a framework to guide future collaborative research between mathematical modelers and biomarker researchers to design studies to investigate and model dynamic clonal evolution. This approach will allow optimization of available resources for cancer control and intervention timing based on molecular biomarkers in predicting cancer among various risk subsets that dynamically evolve over time.

Revisiting the association of blood pressure with mortality in oldest old people in China: community based, longitudinal prospective study

PubMed Central

Lv, Yue-Bin; Gao, Xiang; Yin, Zhao-Xue; Chen, Hua-Shuai; Luo, Jie-Si; Brasher, Melanie Sereny; Kraus, Virginia Byers; Li, Tian-Tian; Zeng, Yi

2018-01-01

Abstract Objective To examine the associations of blood pressure with all cause mortality and cause specific mortality at three years among oldest old people in China. Design Community based, longitudinal prospective study. Setting 2011 and 2014 waves of the Chinese Longitudinal Healthy Longevity Survey, conducted in 22 Chinese provinces. Participants 4658 oldest old individuals (mean age 92.1 years). Main outcome measures All cause mortality and cause specific mortality assessed at three year follow-up. Results 1997 deaths were recorded at three year follow-up. U shaped associations of mortality with systolic blood pressure, mean arterial pressure, and pulse pressure were identified; values of 143.5 mm Hg, 101 mm Hg, and 66 mm Hg conferred the minimum mortality risk, respectively. After adjustment for covariates, the U shaped association remained only for systolic blood pressure (minimum mortality risk at 129 mm Hg). Compared with a systolic blood pressure value of 129 mm Hg, risk of all cause mortality decreased for values lower than 107 mm Hg (from 1.47 (95% confidence interval 1.01 to 2.17) to 1.08 (1.01 to 1.17)), and increased for values greater than 154 mm Hg (from 1.08 (1.01 to 1.17) to 1.27 (1.02 to 1.58)). In the cause specific analysis, compared with a middle range of systolic blood pressure (107-154 mm Hg), higher values (>154 mm Hg) were associated with a higher risk of cardiovascular mortality (adjusted hazard ratio 1.51 (95% confidence interval 1.12 to 2.02)); lower values (<107 mm Hg) were associated with a higher risk of non-cardiovascular mortality (1.58 (1.26 to 1.98)). The U shaped associations remained in sensitivity and subgroup analyses. Conclusions This study indicates a U shaped association between systolic blood pressure and all cause mortality at three years among oldest old people in China. This association could be explained by the finding that higher systolic blood pressure predicted a higher risk of death from cardiovascular disease, and that lower systolic blood pressure predicted a higher risk of death from non-cardiovascular causes. These results emphasise the importance of revisiting blood pressure management or establishing specific guidelines for management among oldest old individuals. PMID:29871897

Mortality prediction to hospitalized patients with influenza pneumonia: PO2 /FiO2 combined lymphocyte count is the answer.

PubMed

Shi, Shu Jing; Li, Hui; Liu, Meng; Liu, Ying Mei; Zhou, Fei; Liu, Bo; Qu, Jiu Xin; Cao, Bin

2017-05-01

Community-acquired pneumonia (CAP) severity scores perform well in predicting mortality of CAP patients, but their applicability in influenza pneumonia is powerless. The aim of our research was to test the efficiency of PO 2 /FiO 2 and CAP severity scores in predicting mortality and intensive care unit (ICU) admission with influenza pneumonia patients. We reviewed all patients with positive influenza virus RNA detection in Beijing Chao-Yang Hospital during the 2009-2014 influenza seasons. Outpatients, inpatients with no pneumonia and incomplete data were excluded. We used receiver operating characteristic curves (ROCs) to verify the accuracy of severity scores or indices as mortality predictors in the study patients. Among 170 hospitalized patients with influenza pneumonia, 30 (17.6%) died. Among those who were classified as low-risk (predicted mortality 0.1%-2.1%) by pneumonia severity index (PSI) or confusion, urea, respiratory rate, blood pressure, age ≥65 year (CURB-65), the actual mortality ranged from 5.9 to 22.1%. Multivariate logistic regression indicated that hypoxia (PO 2 /FiO 2  ≤ 250) and lymphopenia (peripheral blood lymphocyte count <0.8 × 10 9 /L) were independent risk factors for mortality, with OR value of 22.483 (95% confidence interval 4.927-102.598) and 5.853 (95% confidence interval 1.887-18.152), respectively. PO 2 /FiO 2 combined lymphocyte count performed well for mortality prediction with area under the curve (AUC) of 0.945, which was significantly better than current CAP severity scores of PSI, CURB-65 and confusion, respiratory rate, blood pressure, age ≥65 years for mortality prediction (P < 0.001). The scores or indices for ICU admission prediction to hospitalized patients with influenza pneumonia confirmed a similar pattern and PO 2 /FiO 2 combined lymphocyte count was also the best predictor for predicting ICU admission. In conclusion, we found that PO 2 /FiO 2 combined lymphocyte count is simple and reliable predictor of hospitalized patients with influenza pneumonia in predicting mortality and ICU admission. When PO 2 /FiO 2  ≤ 250 or peripheral blood lymphocyte count <0.8 × 10 9 /L, the clinician should pay great attention to the possibility of severe influenza pneumonia. © 2015 The Authors. The Clinical Respiratory Journal published by John Wiley & Sons Ltd.

Applying the Seattle Heart Failure Model in the Office Setting in the Era of Electronic Medical Records.

PubMed

Williams, Brent A; Agarwal, Shikhar

2018-02-23

Prediction models such as the Seattle Heart Failure Model (SHFM) can help guide management of heart failure (HF) patients, but the SHFM has not been validated in the office environment. This retrospective cohort study assessed the predictive performance of the SHFM among patients with new or pre-existing HF in the context of an office visit.Methods and Results:SHFM elements were ascertained through electronic medical records at an office visit. The primary outcome was all-cause mortality. A "warranty period" for the baseline SHFM risk estimate was sought by examining predictive performance over time through a series of landmark analyses. Discrimination and calibration were estimated according to the proposed warranty period. Low- and high-risk thresholds were proposed based on the distribution of SHFM estimates. Among 26,851 HF patients, 14,380 (54%) died over a mean 4.7-year follow-up period. The SHFM lost predictive performance over time, with C=0.69 and C<0.65 within 3 and beyond 12 months from baseline respectively. The diminishing predictive value was attributed to modifiable SHFM elements. Discrimination (C=0.66) and calibration for 12-month mortality were acceptable. A low-risk threshold of ∼5% mortality risk within 12 months reflects the 10% of HF patients in the office setting with the lowest risk. The SHFM has utility in the office environment.

A biophysical model of Lake Erie walleye (Sander vitreus) explains interannual variations in recruitment

USGS Publications Warehouse

Zhao, Yingming; Jones, Michael L.; Shuter, Brian J.; Roseman, Edward F.

2009-01-01

We used a three-dimensional coupled hydrodynamic-ecological model to investigate how lake currents can affect walleye (Sander vitreus) recruitment in western Lake Erie. Four years were selected based on a fall recruitment index: two high recruitment years (i.e., 1996 and 1999) and two low recruitment years (i.e., 1995 and 1998). During the low recruitment years, the model predicted that (i) walleye spawning grounds experienced destructive bottom currents capable of dislodging eggs from suitable habitats (reefs) to unsuitable habitats (i.e., muddy bottom), and (ii) the majority of newly hatched larvae were transported away from the known suitable nursery grounds at the start of their first feeding. Conversely, during two high recruitment years, predicted bottom currents at the spawning grounds were relatively weak, and the predicted movement of newly hatched larvae was toward suitable nursery grounds. Thus, low disturbance-based egg mortality and a temporal and spatial match between walleye first feeding larvae and their food resources were predicted for the two high recruitment years, and high egg mortality plus a mismatch of larvae with their food resources was predicted for the two low recruitment years. In general, mild westerly or southwesterly winds during the spawning-nursery period should favour walleye recruitment in the lake.

External Validation of the Simple Clinical Score and the HOTEL Score, Two Scores for Predicting Short-Term Mortality after Admission to an Acute Medical Unit

PubMed Central

Stræde, Mia; Brabrand, Mikkel

2014-01-01

Background Clinical scores can be of aid to predict early mortality after admission to a medical admission unit. A developed scoring system needs to be externally validated to minimise the risk of the discriminatory power and calibration to be falsely elevated. We performed the present study with the objective of validating the Simple Clinical Score (SCS) and the HOTEL score, two existing risk stratification systems that predict mortality for medical patients based solely on clinical information, but not only vital signs. Methods Pre-planned prospective observational cohort study. Setting Danish 460-bed regional teaching hospital. Findings We included 3046 consecutive patients from 2 October 2008 until 19 February 2009. 26 (0.9%) died within one calendar day and 196 (6.4%) died within 30 days. We calculated SCS for 1080 patients. We found an AUROC of 0.960 (95% confidence interval [CI], 0.932 to 0.988) for 24-hours mortality and 0.826 (95% CI, 0.774–0.879) for 30-day mortality, and goodness-of-fit test, χ2 = 2.68 (10 degrees of freedom), P = 0.998 and χ2 = 4.00, P = 0.947, respectively. We included 1470 patients when calculating the HOTEL score. Discriminatory power (AUROC) was 0.931 (95% CI, 0.901–0.962) for 24-hours mortality and goodness-of-fit test, χ2 = 5.56 (10 degrees of freedom), P = 0.234. Conclusion We find that both the SCS and HOTEL scores showed an excellent to outstanding ability in identifying patients at high risk of dying with good or acceptable precision. PMID:25144186

A new casemix adjustment index for hospital mortality among patients with congestive heart failure.

PubMed

Polanczyk, C A; Rohde, L E; Philbin, E A; Di Salvo, T G

1998-10-01

Comparative analysis of hospital outcomes requires reliable adjustment for casemix. Although congestive heart failure is one of the most common indications for hospitalization, congestive heart failure casemix adjustment has not been widely studied. The purposes of this study were (1) to describe and validate a new congestive heart failure-specific casemix adjustment index to predict in-hospital mortality and (2) to compare its performance to the Charlson comorbidity index. Data from all 4,608 admissions to the Massachusetts General Hospital from January 1990 to July 1996 with a principal ICD-9-CM discharge diagnosis of congestive heart failure were evaluated. Massachusetts General Hospital patients were randomly divided in a derivation and a validation set. By logistic regression, odds ratios for in-hospital death were computed and weights were assigned to construct a new predictive index in the derivation set. The performance of the index was tested in an internal Massachusetts General Hospital validation set and in a non-Massachusetts General Hospital external validation set incorporating data from all 1995 New York state hospital discharges with a primary discharge diagnosis of congestive heart failure. Overall in-hospital mortality was 6.4%. Based on the new index, patients were assigned to six categories with incrementally increasing hospital mortality rates ranging from 0.5% to 31%. By logistic regression, "c" statistics of the congestive heart failure-specific index (0.83 and 0.78, derivation and validation set) were significantly superior to the Charlson index (0.66). Similar incrementally increasing hospital mortality rates were observed in the New York database with the congestive heart failure-specific index ("c" statistics 0.75). In an administrative database, this congestive heart failure-specific index may be a more adequate casemix adjustment tool to predict hospital mortality in patients hospitalized for congestive heart failure.

A prognostic scoring system for arm exercise stress testing.

PubMed

Xie, Yan; Xian, Hong; Chandiramani, Pooja; Bainter, Emily; Wan, Leping; Martin, Wade H

2016-01-01

Arm exercise stress testing may be an equivalent or better predictor of mortality outcome than pharmacological stress imaging for the ≥50% for patients unable to perform leg exercise. Thus, our objective was to develop an arm exercise ECG stress test scoring system, analogous to the Duke Treadmill Score, for predicting outcome in these individuals. In this retrospective observational cohort study, arm exercise ECG stress tests were performed in 443 consecutive veterans aged 64.1 (11.1) years. (mean (SD)) between 1997 and 2002. From multivariate Cox models, arm exercise scores were developed for prediction of 5-year and 12-year all-cause and cardiovascular mortality and 5-year cardiovascular mortality or myocardial infarction (MI). Arm exercise capacity in resting metabolic equivalents (METs), 1 min heart rate recovery (HRR) and ST segment depression ≥1 mm were the stress test variables independently associated with all-cause and cardiovascular mortality by step-wise Cox analysis (all p<0.01). A score based on the relation HRR (bpm)+7.3×METs-10.5×ST depression (0=no; 1=yes) prognosticated 5-year cardiovascular mortality with a C-statistic of 0.81 before and 0.88 after adjustment for significant demographic and clinical covariates. Arm exercise scores for the other outcome end points yielded C-statistic values of 0.77-0.79 before and 0.82-0.86 after adjustment for significant covariates versus 0.64-0.72 for best fit pharmacological myocardial perfusion imaging models in a cohort of 1730 veterans who were evaluated over the same time period. Arm exercise scores, analogous to the Duke Treadmill Score, have good power for prediction of mortality or MI in patients who cannot perform leg exercise.

The utility of liver function tests for mortality prediction within one year in primary care using the algorithm for liver function investigations (ALFI).

PubMed

McLernon, David J; Dillon, John F; Sullivan, Frank M; Roderick, Paul; Rosenberg, William M; Ryder, Stephen D; Donnan, Peter T

2012-01-01

Although liver function tests (LFTs) are routinely measured in primary care, raised levels in patients with no obvious liver disease may trigger a range of subsequent expensive and unnecessary management plans. The aim of this study was to develop and validate a prediction model to guide decision-making by general practitioners, which estimates risk of one year all-cause mortality in patients with no obvious liver disease. In this population-based historical cohort study, biochemistry data from patients in Tayside, Scotland, with LFTs performed in primary care were record-linked to secondary care and prescription databases to ascertain baseline characteristics, and to mortality data. Using this derivation cohort a survival model was developed to predict mortality. The model was assessed for calibration, discrimination (using the C-statistic) and performance, and validated using a separate cohort of Scottish primary care practices. From the derivation cohort (n = 95 977), 2.7% died within one year. Predictors of mortality included: age; male gender; social deprivation; history of cancer, renal disease, stroke, ischaemic heart disease or respiratory disease; statin use; and LFTs (albumin, transaminase, alkaline phosphatase, bilirubin, and gamma-glutamyltransferase). The C-statistic for the final model was 0.82 (95% CI 0.80-0.84), and was similar in the validation cohort (n = 11 653) 0.86 (0.79-0.90). As an example of performance, for a 10% predicted probability cut-off, sensitivity = 52.8%, specificity = 94.0%, PPV = 21.0%, NPV = 98.5%. For the model without LFTs the respective values were 43.8%, 92.8%, 15.6%, 98.1%. The Algorithm for Liver Function Investigations (ALFI) is the first model to successfully estimate the probability of all-cause mortality in patients with no apparent liver disease having LFTs in primary care. While LFTs added to the model's discrimination and sensitivity, the clinical utility of ALFI remains to be established since LFTs did not improve an already high NPV for short term mortality and only modestly improved a very low PPV.

A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

PubMed

Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

2018-05-02

An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (p<0.0001). The wISS showed higher specificity, positive predictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

Clinical utility of urine neutrophil gelatinase-associated lipocalin measured at admission to predict outcomes in heterogeneous population of critically ill patients.

PubMed

Nayak, N M; Madhumitha, S; Annigeri, R A; Venkataraman, R; Balasubramaian, S; Seshadri, R; Vadamalai, V; Rao, B S; Kowdle, P C; Ramakrishnan, N; Mani, M K

2016-01-01

Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a reliable early biomarker of acute kidney injury (AKI) in a homogeneous patient population. However, its utility in a heterogeneous population of critically ill, in whom the time of onset of renal insult is often unclear, is not clearly established. We evaluated the ability of a single measurement of uNGAL in a heterogeneous adult population, on admission to intensive care unit (ICU), to predict the occurrence of AKI and hospital mortality. One hundred and two consecutive adult patients had uNGAL measured within 8 h of admission to ICU. The demographic and laboratory data were collected at admission. The diagnosis of AKI was based on AKI Network (AKIN) criteria. The primary outcome was the development of AKI, and the secondary outcome was hospital mortality. The mean age was 54 ± 16.4 years and 65% were males. Urine NGAL (ng/ml) was 69 ± 42 in patients with AKI (n = 42) and 30.4 ± 41.7 in those without AKI (P < 0.001). The area under the receiver operating characteristic (ROC) curve for prediction of AKI was 0.79 and for serum creatinine (SCr) was 0.88. The sensitivity and specificity for a cut-off value of uNGAL of 75 ng/ml to predict AKI were 0.5 and 0.85 respectively. uNGAL > 75 ng/ml was a strong (odd ratio = 5.17, 95% confidence interval: 1.39-19.3) and independent predictor of hospital mortality. A single measurement of uNGAL at admission to ICU exhibited good predictive ability for AKI though the sensitivity was low. The predictive ability of uNGAL was inferior to simultaneously measured SCr at admission, hence limited its clinical utility to predict AKI. However, admission uNGAL was a strong, independent predictor of hospital mortality.

Clinical utility of urine neutrophil gelatinase-associated lipocalin measured at admission to predict outcomes in heterogeneous population of critically ill patients

PubMed Central

Nayak, N. M.; Madhumitha, S.; Annigeri, R. A.; Venkataraman, R.; Balasubramaian, S.; Seshadri, R.; Vadamalai, V.; Rao, B. S.; Kowdle, P. C.; Ramakrishnan, N.; Mani, M. K.

2016-01-01

Urine neutrophil gelatinase-associated lipocalin (uNGAL) is a reliable early biomarker of acute kidney injury (AKI) in a homogeneous patient population. However, its utility in a heterogeneous population of critically ill, in whom the time of onset of renal insult is often unclear, is not clearly established. We evaluated the ability of a single measurement of uNGAL in a heterogeneous adult population, on admission to intensive care unit (ICU), to predict the occurrence of AKI and hospital mortality. One hundred and two consecutive adult patients had uNGAL measured within 8 h of admission to ICU. The demographic and laboratory data were collected at admission. The diagnosis of AKI was based on AKI Network (AKIN) criteria. The primary outcome was the development of AKI, and the secondary outcome was hospital mortality. The mean age was 54 ± 16.4 years and 65% were males. Urine NGAL (ng/ml) was 69 ± 42 in patients with AKI (n = 42) and 30.4 ± 41.7 in those without AKI (P < 0.001). The area under the receiver operating characteristic (ROC) curve for prediction of AKI was 0.79 and for serum creatinine (SCr) was 0.88. The sensitivity and specificity for a cut-off value of uNGAL of 75 ng/ml to predict AKI were 0.5 and 0.85 respectively. uNGAL > 75 ng/ml was a strong (odd ratio = 5.17, 95% confidence interval: 1.39–19.3) and independent predictor of hospital mortality. A single measurement of uNGAL at admission to ICU exhibited good predictive ability for AKI though the sensitivity was low. The predictive ability of uNGAL was inferior to simultaneously measured SCr at admission, hence limited its clinical utility to predict AKI. However, admission uNGAL was a strong, independent predictor of hospital mortality. PMID:27051136

Preemptive spatial competition under a reproduction-mortality constraint.

PubMed

Allstadt, Andrew; Caraco, Thomas; Korniss, G

2009-06-21

Spatially structured ecological interactions can shape selection pressures experienced by a population's different phenotypes. We study spatial competition between phenotypes subject to antagonistic pleiotropy between reproductive effort and mortality rate. The constraint we invoke reflects a previous life-history analysis; the implied dependence indicates that although propagation and mortality rates both vary, their ratio is fixed. We develop a stochastic invasion approximation predicting that phenotypes with higher propagation rates will invade an empty environment (no biotic resistance) faster, despite their higher mortality rate. However, once population density approaches demographic equilibrium, phenotypes with lower mortality are favored, despite their lower propagation rate. We conducted a set of pairwise invasion analyses by simulating an individual-based model of preemptive competition. In each case, the phenotype with the lowest mortality rate and (via antagonistic pleiotropy) the lowest propagation rate qualified as evolutionarily stable among strategies simulated. This result, for a fixed propagation to mortality ratio, suggests that a selective response to spatial competition can extend the time scale of the population's dynamics, which in turn decelerates phenotypic evolution.

Early Therapy Intensity Level (TIL) Predicts Mortality in Spontaneous Intracerebral Hemorrhage.

PubMed

Ziai, Wendy C; Siddiqui, Aazim A; Ullman, Natalie; Herrick, Daniel B; Yenokyan, Gayane; McBee, Nichol; Lane, Karen; Hanley, Daniel F

2015-10-01

Outcome from spontaneous intracerebral hemorrhage (sICH) may depend on patient-care variability. We developed as ICH-specific therapy intensity level (TIL) metric using evidence-based elements in a high severity sICH cohort. This is a cohort study of 170 patients with sICH and any intraventricular hemorrhage treated in 2 academic neuroICUs. Pre-defined quality indicators were identified based on current guidelines, scientific evidence, and likelihood of care documentation in first 72 h of hospital admission. We assessed performance on each indicator and association with discharge mortality. Significant indicators were aggregated to develop a TIL score. The predictive validity of the best fit TIL score was tested with threefold cross-validation of multivariate logistic regression models of in-hospital survival and good outcome (modified Rankin score 0-3). Median ICH score was 3; discharge mortality was 51.2%. Five/19 tested variables were significantly associated with lower discharge mortality: no DNR/withdrawal of treatment within 24 h of admission, target glucose within 4 h of high glucose, no recurrent hyperpyrexia, clinical reversal of herniation/intracranial pressure >20 mmHg within 60 min of detection, and reversal of INR (<1.4) within 2 h of first elevation. One point was given for each or if not applicable. Median TIL score was significantly higher in survivors versus non-survivors (5[1] vs. 3[1]; P < 0.001). A 4-point aggregated TIL score was most predictive of discharge survival (area under receiving operating characteristic curve 0.85, 95% CI 0.80-0.90) and good outcome (AUC 0.84) and was an independent predictor of both (survival: OR 7.10; 95% CI 3.57-14.11; P < 0.001; good outcome: OR 3.10; 95% CI 1.06-8.79; P < 0.001). A simplified TIL score using evidenced-based patient-care parameters within first 3 days of admission after sICH was significantly associated with early mortality and good outcome. The next step is prospective validation of the simplified TIL score in a large clinical trial.

Validation of CRIB II for prediction of mortality in premature babies.

PubMed

Rastogi, Pallav Kumar; Sreenivas, V; Kumar, Nirmal

2010-02-01

Validation of Clinical Risk Index for Babies (CRIB II) score in predicting the neonatal mortality in preterm neonates < or = 32 weeks gestational age. Prospective cohort study. Tertiary care neonatal unit. 86 consecutively born preterm neonates with gestational age < or = 32 weeks. The five variables related to CRIB II were recorded within the first hour of admission for data analysis. The receiver operating characteristics (ROC) curve was used to check the accuracy of the mortality prediction. HL Goodness of fit test was used to see the discrepancy between observed and expected outcomes. A total of 86 neonates (males 59.6% mean birthweight: 1228 +/- 398 grams; mean gestational age: 28.3 +/- 2.4 weeks) were enrolled in the study, of which 17 (19.8%) left hospital against medical advice (LAMA) before reaching the study end point. Among 69 neonates completing the study, 24 (34.8%) had adverse outcome during hospital stay and 45 (65.2%) had favorable outcome. CRIB II correctly predicted adverse outcome in 90.3% (Hosmer Lemeshow goodness of fit test P=0.6). Area under curve (AUC) for CRIB II was 0.9032. In intention to treat analysis with LAMA cases included as survivors, the mortality prediction was 87%. If these were included as having died then mortality prediction was 83.1%. The CRIB II score was found to be a good predictive instrument for mortality in preterm infants < or = 32 weeks gestation.

Prevalent vertebral deformities predict increased mortality and increased fracture rate in both men and women: a 10-year population-based study of 598 individuals from the Swedish cohort in the European Vertebral Osteoporosis Study.

PubMed

Hasserius, R; Karlsson, M K; Nilsson, B E; Redlund-Johnell, I; Johnell, O

2003-01-01

The aim of this study was to evaluate whether a prevalent vertebral deformity predicts mortality and fractures in both men and women. In the city of Malmö, 598 individuals (298 men, 300 women; age 50-80 years) were selected from the city's population and were included in the Swedish part of the European Vertebral Osteoporosis Study (EVOS). At baseline the participants answered a questionnaire and lateral spine radiographs were performed. The prevalence of subjects with vertebral deformity was assessed using a morphometric method. The mortality during a 10-year follow-up period was determined through the register of the National Swedish Board of Health and Welfare. Eighty-five men and 43 women died during the study period. The subsequent fracture incidence during the follow-up period was ascertained by postal questionnaires, telephone interviews and by a survey of the archives of the Department of Radiology in the city hospital. Thirty-seven men and 69 women sustained a fracture during the study period. Data are presented as hazard ratios (HR) with 95% confidence interval (95% CI) within brackets. Prevalent vertebral deformity, defined as a reduction by more than 3 standard deviations (SD) in vertebral height ratio, predicted mortality during the forthcoming decade in both men [age-adjusted HR 2.4 (95% CI 1.6-3.9)] and women [age-adjusted HR 2.3 (95% CI 1.3-4.3)]. In men there was an increased mortality due to cardiovascular and pulmonary diseases and in women due to cancer. Prevalent vertebral deformity predicted an increased risk of any fracture during the forthcoming decade in both men [age-adjusted HR 2.7 (95% CI 1.4-5.3)] and women [age-adjusted HR 1.8 (95% CI 1.1-2.9)]. Prevalent vertebral deformity predicted an increased risk of any subsequent fragility fracture in women [age-adjusted HR 2.0 (95% CI 1.1-3.5)]; however, in men the increased risk was nonsignificant [age-adjusted HR 1.9 (95% CI 0.7-5.1)]. In summary, a prevalent vertebral deformity can predict both increased mortality and increased fracture incidence during the following decade in both men and women. We conclude that prevalent vertebral deformity could be used as a risk factor in both genders for mortality and future fracture.

Nucleated red blood cells as predictors of mortality in patients with acute respiratory distress syndrome (ARDS): an observational study.

PubMed

Menk, Mario; Giebelhäuser, Lena; Vorderwülbecke, Gerald; Gassner, Martina; Graw, Jan A; Weiss, Björn; Zimmermann, Mathias; Wernecke, Klaus-D; Weber-Carstens, Steffen

2018-03-27

Nucleated red blood cells (NRBCs) in critically ill patients are associated with increased mortality and poor outcome. The aim of the present study was to evaluate the predictive value of NRBCs in patients with acute respiratory distress syndrome (ARDS). This observational study was conducted at an ARDS referral center and included patients from 2007 to 2014. Daily NRBC counts were assessed and the predictive validity of NRBCs on mortality was statistically evaluated. A cutoff for prediction of mortality based on NRBCs was evaluated using ROC analysis and specified according to Youden's method. Multivariate nonparametric analysis for longitudinal data was applied to prove for differences between groups over the whole time course. Independent predictors of mortality were identified with multiple logistic and Cox' regression analyses. Kaplan-Meier estimations visualized the survival; the corresponding curves were tested for differences with the log-rank test. A total of 404 critically ill ARDS patients were analyzed. NRBCs were found in 75.5% of the patients, which was associated with longer length of ICU stay [22 (11; 39) vs. 14 (7; 26) days; p < 0.05] and higher mortality rates (50.8 vs. 27.3%; p < 0.001). Logistic regression analysis with mortality as response showed NRBC positivity per se to be an independent risk factor for mortality in ARDS with a doubled risk for ICU death (OR 2.03; 95% CI 1.16-3.55; p < 0.05). Also, NRBC value at ICU admission was found to be an independent risk factor for mortality (OR 3.25; 95% CI 1.09-9.73, p = 0.035). A cutoff level of 220 NRBC/µl was associated with a more than tripled risk of ICU death (OR 3.2; 95% CI 1.93-5.35; p < 0.0001). ARDS patients below this threshold level had a significant survival advantage (median survival 85 days vs. 29 days; log rank p < 0.001). Presence of a severe ARDS was identified as independent risk factor for the occurrence of NRBCs > 220/µl (OR 1.81; 95% CI 1.1-2.97; p < 0.05). NRBCs may predict mortality in ARDS with high prognostic power. The presence of NRBCs in the blood might be regarded as a marker of disease severity indicating a higher risk of ICU death.

Hematoma Shape, Hematoma Size, Glasgow Coma Scale Score and ICH Score: Which Predicts the 30-Day Mortality Better for Intracerebral Hematoma?

PubMed Central

Wang, Chih-Wei; Liu, Yi-Jui; Lee, Yi-Hsiung; Hueng, Dueng-Yuan; Fan, Hueng-Chuen; Yang, Fu-Chi; Hsueh, Chun-Jen; Kao, Hung-Wen; Juan, Chun-Jung; Hsu, Hsian-He

2014-01-01

Purpose To investigate the performance of hematoma shape, hematoma size, Glasgow coma scale (GCS) score, and intracerebral hematoma (ICH) score in predicting the 30-day mortality for ICH patients. To examine the influence of the estimation error of hematoma size on the prediction of 30-day mortality. Materials and Methods This retrospective study, approved by a local institutional review board with written informed consent waived, recruited 106 patients diagnosed as ICH by non-enhanced computed tomography study. The hemorrhagic shape, hematoma size measured by computer-assisted volumetric analysis (CAVA) and estimated by ABC/2 formula, ICH score and GCS score was examined. The predicting performance of 30-day mortality of the aforementioned variables was evaluated. Statistical analysis was performed using Kolmogorov-Smirnov tests, paired t test, nonparametric test, linear regression analysis, and binary logistic regression. The receiver operating characteristics curves were plotted and areas under curve (AUC) were calculated for 30-day mortality. A P value less than 0.05 was considered as statistically significant. Results The overall 30-day mortality rate was 15.1% of ICH patients. The hematoma shape, hematoma size, ICH score, and GCS score all significantly predict the 30-day mortality for ICH patients, with an AUC of 0.692 (P = 0.0018), 0.715 (P = 0.0008) (by ABC/2) to 0.738 (P = 0.0002) (by CAVA), 0.877 (P<0.0001) (by ABC/2) to 0.882 (P<0.0001) (by CAVA), and 0.912 (P<0.0001), respectively. Conclusion Our study shows that hematoma shape, hematoma size, ICH scores and GCS score all significantly predict the 30-day mortality in an increasing order of AUC. The effect of overestimation of hematoma size by ABC/2 formula in predicting the 30-day mortality could be remedied by using ICH score. PMID:25029592

Redefining plant functional types for forests based on plant traits

NASA Astrophysics Data System (ADS)

Wei, L.; Xu, C.; Christoffersen, B. O.; McDowell, N. G.; Zhou, H.

2016-12-01

Our ability to predict forest mortality is limited by the simple plant functional types (PFTs) in current generations of Earth System models (ESMs). For example, forests were formerly separated into PFTs only based on leaf form and phenology across different regions (arctic, temperate, and tropic areas) in the Community Earth System Model (CESM). This definition of PFTs ignored the large variation in vulnerability of species to drought and shade tolerance within each PFT. We redefined the PFTs for global forests based on plant traits including phenology, wood density, leaf mass per area, xylem-specific conductivity, and xylem pressure at 50% loss of conductivity. Species with similar survival strategies were grouped into the same PFT. New PFTs highlighted variation in vulnerability and physiological adaptation to drought and shade. New PFTs were better clustered than old ones in the two-dimensional plane of the first two principle components in a principle component analysis. We expect that the new PFTs will strengthen ESMs' ability on predicting drought-induced mortality in the future.

DeepDeath: Learning to predict the underlying cause of death with Big Data.

PubMed

Hassanzadeh, Hamid Reza; Ying Sha; Wang, May D

2017-07-01

Multiple cause-of-death data provides a valuable source of information that can be used to enhance health standards by predicting health related trajectories in societies with large populations. These data are often available in large quantities across U.S. states and require Big Data techniques to uncover complex hidden patterns. We design two different classes of models suitable for large-scale analysis of mortality data, a Hadoop-based ensemble of random forests trained over N-grams, and the DeepDeath, a deep classifier based on the recurrent neural network (RNN). We apply both classes to the mortality data provided by the National Center for Health Statistics and show that while both perform significantly better than the random classifier, the deep model that utilizes long short-term memory networks (LSTMs), surpasses the N-gram based models and is capable of learning the temporal aspect of the data without a need for building ad-hoc, expert-driven features.

A scoring system to predict breast cancer mortality at 5 and 10 years.

PubMed

Paredes-Aracil, Esther; Palazón-Bru, Antonio; Folgado-de la Rosa, David Manuel; Ots-Gutiérrez, José Ramón; Compañ-Rosique, Antonio Fernando; Gil-Guillén, Vicente Francisco

2017-03-24

Although predictive models exist for mortality in breast cancer (BC) (generally all cause-mortality), they are not applicable to all patients and their statistical methodology is not the most powerful to develop a predictive model. Consequently, we developed a predictive model specific for BC mortality at 5 and 10 years resolving the above issues. This cohort study included 287 patients diagnosed with BC in a Spanish region in 2003-2016. time-to-BC death. Secondary variables: age, personal history of breast surgery, personal history of any cancer/BC, premenopause, postmenopause, grade, estrogen receptor, progesterone receptor, c-erbB2, TNM stage, multicentricity/multifocality, diagnosis and treatment. A points system was constructed to predict BC mortality at 5 and 10 years. The model was internally validated by bootstrapping. The points system was integrated into a mobile application for Android. Mean follow-up was 8.6 ± 3.5 years and 55 patients died of BC. The points system included age, personal history of BC, grade, TNM stage and multicentricity. Validation was satisfactory, in both discrimination and calibration. In conclusion, we constructed and internally validated a scoring system for predicting BC mortality at 5 and 10 years. External validation studies are needed for its use in other geographical areas.

Comparison of mortality prediction models in burns ICU patients in Pinderfields Hospital over 3 years.

PubMed

Douglas, Helen E; Ratcliffe, Andrew; Sandhu, Rajdeep; Anwar, Umair

2015-02-01

Many different burns mortality prediction models exist; however most agree that important factors that can be weighted include the age of the patient, the total percentage of body surface area burned and the presence or absence of smoke inhalation. A retrospective review of all burns primarily admitted to Pinderfields Burns ICU under joint care of burns surgeons and intensivists for the past 3 years was completed. Predicted mortality was calculated using the revised Baux score (2010), the Belgian Outcome in Burn Injury score (2009) and the Boston group score by Ryan et al. (1998). Additionally 28 of the 48 patients had APACHE II scores recorded on admission and the predicted and actual mortality of this group were compared. The Belgian score had the highest sensitivity and negative predictive value (72%/85%); followed by the Boston score (66%/78%) and then the revised Baux score (53%/70%). APACHE II scores had higher sensitivity (81%) and NPV (92%) than any of the burns scores. In our group of burns ICU patients the Belgian model was the most sensitive and specific predictor of mortality. In our subgroup of patients with APACHE II data, this score more accurately predicted survival and mortality. Copyright © 2014 Elsevier Ltd and ISBI. All rights reserved.

Brain natriuretic peptide (BNP) may play a major role in risk stratification based on cerebral oxygen saturation by near-infrared spectroscopy in patients undergoing major cardiovascular surgery

PubMed Central

Hayashida, Masakazu; Matsushita, Satoshi; Yamamoto, Makiko; Nakamura, Atsushi; Amano, Atsushi

2017-01-01

Purpose A previous study reported that low baseline cerebral oxygen saturation (ScO2) (≤50%) measured with near-infrared spectroscopy was predictive of poor clinical outcomes after cardiac surgery. However, such findings have not been reconfirmed by others. We conducted the current study to evaluate whether the previous findings would be reproducible, and to explore mechanisms underlying the ScO2-based outcome prediction. Methods We retrospectively investigated 573 consecutive patients, aged 20 to 91 (mean ± standard deviation, 67.1 ± 12.8) years, who underwent major cardiovascular surgery. Preanesthetic baseline ScO2, lowest intraoperative ScO2, various clinical variables, and hospital mortality were examined. Results Bivariate regression analyses revealed that baseline ScO2 correlated significantly with plasma brain natriuretic peptide concentration (BNP), hemoglobin concentration (Hgb), estimated glomerular filtration rate (eGFR), and left ventricular ejection fraction (LVEF) (p < 0.0001 for each). Baseline ScO2 correlated with BNP in an exponential manner, and BNP was the most significant factor influencing ScO2. Logistic regression analyses revealed that baseline and lowest intraoperative ScO2 values, but not relative ScO2 decrements, were significantly associated with hospital mortality (p < 0.05), independent of the EuroSCORE (p < 0.01). Receiver operating curve analysis of ScO2 values and hospital mortality revealed an area under the curve (AUC) of 0.715 (p < 0.01) and a cutoff value of ≤50.5% for the baseline and ScO2, and an AUC of 0.718 (p < 0.05) and a cutoff value of ≤35% for the lowest intraoperative ScO2. Low baseline ScO2 (≤50%) was associated with increases in intubation time, intensive care unit stay, hospital stay, and hospital mortality. Conclusion Baseline ScO2 was reflective of severity of systemic comorbidities and was predictive of clinical outcomes after major cardiovascular surgery. ScO2 correlated most significantly with BNP in an exponential manner, suggesting that BNP plays a major role in the ScO2-based outcome prediction. PMID:28704502

Adaptation of a Biomarker-Based Sepsis Mortality Risk Stratification Tool for Pediatric Acute Respiratory Distress Syndrome.

PubMed

Yehya, Nadir; Wong, Hector R

2018-01-01

The original Pediatric Sepsis Biomarker Risk Model and revised (Pediatric Sepsis Biomarker Risk Model-II) biomarker-based risk prediction models have demonstrated utility for estimating baseline 28-day mortality risk in pediatric sepsis. Given the paucity of prediction tools in pediatric acute respiratory distress syndrome, and given the overlapping pathophysiology between sepsis and acute respiratory distress syndrome, we tested the utility of Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II for mortality prediction in a cohort of pediatric acute respiratory distress syndrome, with an a priori plan to revise the model if these existing models performed poorly. Prospective observational cohort study. University affiliated PICU. Mechanically ventilated children with acute respiratory distress syndrome. Blood collection within 24 hours of acute respiratory distress syndrome onset and biomarker measurements. In 152 children with acute respiratory distress syndrome, Pediatric Sepsis Biomarker Risk Model performed poorly and Pediatric Sepsis Biomarker Risk Model-II performed modestly (areas under receiver operating characteristic curve of 0.61 and 0.76, respectively). Therefore, we randomly selected 80% of the cohort (n = 122) to rederive a risk prediction model for pediatric acute respiratory distress syndrome. We used classification and regression tree methodology, considering the Pediatric Sepsis Biomarker Risk Model biomarkers in addition to variables relevant to acute respiratory distress syndrome. The final model was comprised of three biomarkers and age, and more accurately estimated baseline mortality risk (area under receiver operating characteristic curve 0.85, p < 0.001 and p = 0.053 compared with Pediatric Sepsis Biomarker Risk Model and Pediatric Sepsis Biomarker Risk Model-II, respectively). The model was tested in the remaining 20% of subjects (n = 30) and demonstrated similar test characteristics. A validated, biomarker-based risk stratification tool designed for pediatric sepsis was adapted for use in pediatric acute respiratory distress syndrome. The newly derived Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model demonstrates good test characteristics internally and requires external validation in a larger cohort. Tools such as Pediatric Acute Respiratory Distress Syndrome Biomarker Risk Model have the potential to provide improved risk stratification and prognostic enrichment for future trials in pediatric acute respiratory distress syndrome.

Modelling Future Cardiovascular Disease Mortality in the United States: National Trends and Racial and Ethnic Disparities

PubMed Central

Pearson-Stuttard, Jonathan; Guzman-Castillo, Maria; Penalvo, Jose L.; Rehm, Colin D.; Afshin, Ashkan; Danaei, Goodarz; Kypridemos, Chris; Gaziano, Tom; Mozaffarian, Dariush; Capewell, Simon; O’Flaherty, Martin

2016-01-01

Background Accurate forecasting of cardiovascular disease (CVD) mortality is crucial to guide policy and programming efforts. Prior forecasts have often not incorporated past trends in rates of reduction in CVD mortality. This creates uncertainties about future trends in CVD mortality and disparities. Methods and Results To forecast US CVD mortality and disparities to 2030, we developed a hierarchical Bayesian model to determine and incorporate prior age, period and cohort (APC) effects from 1979–2012, stratified by age, gender and race; which we combined with expected demographic shifts to 2030. Data sources included the National Vital Statistics System, SEER single year population estimates, and US Bureau of Statistics 2012 National Population projections. We projected coronary disease and stroke deaths to 2030, first based on constant APC effects at 2012 values, as most commonly done (conventional); and then using more rigorous projections incorporating expected trends in APC effects (trend-based). We primarily evaluated absolute mortality. The conventional model projected total coronary and stroke deaths by 2030 to increase by approximately 18% (67,000 additional coronary deaths/year) and 50% (64,000 additional stroke deaths/year). Conversely, the trend-based model projected that coronary mortality would fall by 2030 by approximately 27% (79,000 fewer deaths/year); and stroke mortality would remain unchanged (200 fewer deaths/year). Health disparities will be improved in stroke deaths, but not coronary deaths. Conclusions After accounting for prior mortality trends and expected demographic shifts, total US coronary deaths are expected to decline, while stroke mortality will remain relatively constant. Health disparities in stroke, but not coronary, deaths will be improved but not eliminated. These APC approaches offer more plausible predictions than conventional estimates. PMID:26846769

Use of APACHE II and SAPS II to predict mortality for hemorrhagic and ischemic stroke patients.

PubMed

Moon, Byeong Hoo; Park, Sang Kyu; Jang, Dong Kyu; Jang, Kyoung Sool; Kim, Jong Tae; Han, Yong Min

2015-01-01

We studied the applicability of the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiology Score II (SAPS II) in patients admitted to the intensive care unit (ICU) with acute stroke and compared the results with the Glasgow Coma Scale (GCS) and National Institutes of Health Stroke Scale (NIHSS). We also conducted a comparative study of accuracy for predicting hemorrhagic and ischemic stroke mortality. Between January 2011 and December 2012, ischemic or hemorrhagic stroke patients admitted to the ICU were included in the study. APACHE II and SAPS II-predicted mortalities were compared using a calibration curve, the Hosmer-Lemeshow goodness-of-fit test, and the receiver operating characteristic (ROC) curve, and the results were compared with the GCS and NIHSS. Overall 498 patients were included in this study. The observed mortality was 26.3%, whereas APACHE II and SAPS II-predicted mortalities were 35.12% and 35.34%, respectively. The mean GCS and NIHSS scores were 9.43 and 21.63, respectively. The calibration curve was close to the line of perfect prediction. The ROC curve showed a slightly better prediction of mortality for APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients. The GCS and NIHSS were inferior in predicting mortality in both patient groups. Although both the APACHE II and SAPS II systems can be used to measure performance in the neurosurgical ICU setting, the accuracy of APACHE II in hemorrhagic stroke patients and SAPS II in ischemic stroke patients was superior. Copyright © 2014 Elsevier Ltd. All rights reserved.

Spatial variability of excess mortality during prolonged dust events in a high-density city: a time-stratified spatial regression approach.

PubMed

Wong, Man Sing; Ho, Hung Chak; Yang, Lin; Shi, Wenzhong; Yang, Jinxin; Chan, Ta-Chien

2017-07-24

Dust events have long been recognized to be associated with a higher mortality risk. However, no study has investigated how prolonged dust events affect the spatial variability of mortality across districts in a downwind city. In this study, we applied a spatial regression approach to estimate the district-level mortality during two extreme dust events in Hong Kong. We compared spatial and non-spatial models to evaluate the ability of each regression to estimate mortality. We also compared prolonged dust events with non-dust events to determine the influences of community factors on mortality across the city. The density of a built environment (estimated by the sky view factor) had positive association with excess mortality in each district, while socioeconomic deprivation contributed by lower income and lower education induced higher mortality impact in each territory planning unit during a prolonged dust event. Based on the model comparison, spatial error modelling with the 1st order of queen contiguity consistently outperformed other models. The high-risk areas with higher increase in mortality were located in an urban high-density environment with higher socioeconomic deprivation. Our model design shows the ability to predict spatial variability of mortality risk during an extreme weather event that is not able to be estimated based on traditional time-series analysis or ecological studies. Our spatial protocol can be used for public health surveillance, sustainable planning and disaster preparation when relevant data are available.

The Pediatric Risk of Mortality Score: Update 2015

PubMed Central

Pollack, Murray M.; Holubkov, Richard; Funai, Tomohiko; Dean, J. Michael; Berger, John T.; Wessel, David L.; Meert, Kathleen; Berg, Robert A.; Newth, Christopher J. L.; Harrison, Rick E.; Carcillo, Joseph; Dalton, Heidi; Shanley, Thomas; Jenkins, Tammara L.; Tamburro, Robert

2016-01-01

Objectives Severity of illness measures have long been used in pediatric critical care. The Pediatric Risk of Mortality is a physiologically based score used to quantify physiologic status, and when combined with other independent variables, it can compute expected mortality risk and expected morbidity risk. Although the physiologic ranges for the Pediatric Risk of Mortality variables have not changed, recent Pediatric Risk of Mortality data collection improvements have been made to adapt to new practice patterns, minimize bias, and reduce potential sources of error. These include changing the outcome to hospital survival/death for the first PICU admission only, shortening the data collection period and altering the Pediatric Risk of Mortality data collection period for patients admitted for “optimizing” care before cardiac surgery or interventional catheterization. This analysis incorporates those changes, assesses the potential for Pediatric Risk of Mortality physiologic variable subcategories to improve score performance, and recalibrates the Pediatric Risk of Mortality score, placing the algorithms (Pediatric Risk of Mortality IV) in the public domain. Design Prospective cohort study from December 4, 2011, to April 7, 2013. Measurements and Main Results Among 10,078 admissions, the unadjusted mortality rate was 2.7% (site range, 1.3–5.0%). Data were divided into derivation (75%) and validation (25%) sets. The new Pediatric Risk of Mortality prediction algorithm (Pediatric Risk of Mortality IV) includes the same Pediatric Risk of Mortality physiologic variable ranges with the subcategories of neurologic and nonneurologic Pediatric Risk of Mortality scores, age, admission source, cardiopulmonary arrest within 24 hours before admission, cancer, and low-risk systems of primary dysfunction. The area under the receiver operating characteristic curve for the development and validation sets was 0.88 ± 0.013 and 0.90 ± 0.018, respectively. The Hosmer-Lemeshow goodness of fit statistics indicated adequate model fit for both the development (p = 0.39) and validation (p = 0.50) sets. Conclusions The new Pediatric Risk of Mortality data collection methods include significant improvements that minimize the potential for bias and errors, and the new Pediatric Risk of Mortality IV algorithm for survival and death has excellent prediction performance. PMID:26492059

Gender, TIMI risk score and in-hospital mortality in STEMI patients undergoing primary PCI: results from the Belgian STEMI registry.

PubMed

Gevaert, Sofie A; De Bacquer, Dirk; Evrard, Patrick; Convens, Carl; Dubois, Philippe; Boland, Jean; Renard, Marc; Beauloye, Christophe; Coussement, Patrick; De Raedt, Herbert; de Meester, Antoine; Vandecasteele, Els; Vranckx, Pascal; Sinnaeve, Peter R; Claeys, Marc J

2014-01-22

The relationship between the predictive performance of the TIMI risk score for STEMI and gender has not been evaluated in the setting of primary PCI (pPCI). Here, we compared in-hospital mortality and predictive performance of the TIMI risk score between Belgian women and men undergoing pPCI. In-hospital mortality was analysed in 8,073 (1,920 [23.8%] female and 6,153 [76.2%] male patients) consecutive pPCI-treated STEMI patients, included in the prospective, observational Belgian STEMI registry (January 2007 to February 2011). A multivariable logistic regression model, including TIMI risk score variables and gender, evaluated differences in in-hospital mortality between men and women. The predictive performance of the TIMI risk score according to gender was evaluated in terms of discrimination and calibration. Mortality rates for TIMI scores in women and men were compared. Female patients were older, had more comorbidities and longer ischaemic times. Crude in-hospital mortality was 10.1% in women vs. 4.9% in men (OR 2.2; 95% CI: 1.82-2.66, p<0.001). When adjusting for TIMI risk score variables, mortality remained higher in women (OR 1.47, 95% CI: 1.15-1.87, p=0.002). The TIMI risk score provided a good predictive discrimination and calibration in women as well as in men (c-statistic=0.84 [95% CI: 0.809-0.866], goodness-of-fit p=0.53 and c-statistic=0.89 [95% CI: 0.873-0.907], goodness-of-fit p=0.13, respectively), but mortality prediction for TIMI scores was better in men (p=0.02 for TIMI score x gender interaction). In the Belgian STEMI registry, pPCI-treated women had a higher in-hospital mortality rate even after correcting for TIMI risk score variables. The TIMI risk score was effective in predicting in-hospital mortality but performed slightly better in men. The database was registered with clinicaltrials.gov (NCT00727623).

Incident Subjective Cognitive Decline Does Not Predict Mortality in the Elderly--Results from the Longitudinal German Study on Ageing, Cognition, and Dementia (AgeCoDe).

PubMed

Roehr, Susanne; Luck, Tobias; Heser, Kathrin; Fuchs, Angela; Ernst, Annette; Wiese, Birgitt; Werle, Jochen; Bickel, Horst; Brettschneider, Christian; Koppara, Alexander; Pentzek, Michael; Lange, Carolin; Prokein, Jana; Weyerer, Siegfried; Mösch, Edelgard; König, Hans-Helmut; Maier, Wolfgang; Scherer, Martin; Jessen, Frank; Riedel-Heller, Steffi G

2016-01-01

Subjective cognitive decline (SCD) might represent the first symptomatic representation of Alzheimer's disease (AD), which is associated with increased mortality. Only few studies, however, have analyzed the association of SCD and mortality, and if so, based on prevalent cases. Thus, we investigated incident SCD in memory and mortality. Data were derived from the German AgeCoDe study, a prospective longitudinal study on the epidemiology of mild cognitive impairment (MCI) and dementia in primary care patients over 75 years covering an observation period of 7.5 years. We used univariate and multivariate Cox regression analyses to examine the relationship of SCD and mortality. Further, we estimated survival times by the Kaplan Meier method and case-fatality rates with regard to SCD. Among 971 individuals without objective cognitive impairment, 233 (24.0%) incidentally expressed SCD at follow-up I. Incident SCD was not significantly associated with increased mortality in the univariate (HR = 1.0, 95% confidence interval = 0.8-1.3, p = .90) as well as in the multivariate analysis (HR = 0.9, 95% confidence interval = 0.7-1.2, p = .40). The same applied for SCD in relation to concerns. Mean survival time with SCD was 8.0 years (SD = 0.1) after onset. Incident SCD in memory in individuals with unimpaired cognitive performance does not predict mortality. The main reason might be that SCD does not ultimately lead into future cognitive decline in any case. However, as prevalence studies suggest, subjectively perceived decline in non-memory cognitive domains might be associated with increased mortality. Future studies may address mortality in such other cognitive domains of SCD in incident cases.

Comorbidities and risk of mortality in patients with chronic obstructive pulmonary disease.

PubMed

Divo, Miguel; Cote, Claudia; de Torres, Juan P; Casanova, Ciro; Marin, Jose M; Pinto-Plata, Victor; Zulueta, Javier; Cabrera, Carlos; Zagaceta, Jorge; Hunninghake, Gary; Celli, Bartolome

2012-07-15

Patients with chronic obstructive pulmonary disease (COPD) are afflicted by comorbidities. Few studies have prospectively evaluated COPD comorbidities and mortality risk. To prospectively evaluate COPD comorbidities and mortality risk. We followed 1,664 patients with COPD in five centers for a median of 51 months. Systematically, 79 comorbidities were recorded. We calculated mortality risk using Cox proportional hazard, and developed a graphic representation of the prevalence and strength of association to mortality in the form of a "comorbidome". A COPD comorbidity index (COPD specific comorbidity test [COTE]) was constructed based on the comorbidities that increase mortality risk using a multivariate analysis. We tested the COTE index as predictor of mortality and explored whether the COTE index added predictive information when used with the validated BODE index. Fifteen of 79 comorbidities differed in prevalence between survivors and nonsurvivors. Of those, 12 predicted mortality and were integrated into the COTE index. Increases in the COTE index were associated with an increased risk of death from COPD-related (hazard ratio [HR], 1.13; 95% confidence interval, 1.08-1.18; P < 0.001) and non-COPD-related causes (HR, 1.18; 95% confidence interval, 1.15-1.21; P < 0.001). Further, increases in the BODE and COTE were independently associated with increased risk of death. A COTE score of greater than or equal to 4 points increased by 2.2-fold the risk of death (HR, 2.26-2.68; P < 0.001) in all BODE quartile. Comorbidities are frequent in COPD and 12 of them negatively influence survival. A simple disease-specific comorbidities index (COTE) helps assess mortality risk in patients with COPD.

Timing and proximate causes of mortality in wild bird populations: testing Ashmole’s hypothesis

USGS Publications Warehouse

Barton, Daniel C.; Martin, Thomas E.

2012-01-01

Fecundity in birds is widely recognized to increase with latitude across diverse phylogenetic groups and regions, yet the causes of this variation remain enigmatic. Ashmole’s hypothesis is one of the most broadly accepted explanations for this pattern. This hypothesis suggests that increasing seasonality leads to increasing overwinter mortality due to resource scarcity during the lean season (e.g., winter) in higher latitude climates. This mortality is then thought to yield increased per-capita resources for breeding that allow larger clutch sizes at high latitudes. Support for this hypothesis has been based on indirect tests, whereas the underlying mechanisms and assumptions remain poorly explored. We used a meta-analysis of over 150 published studies to test two underlying and critical assumptions of Ashmole’s hypothesis: first, that ad ult mortality is greatest during the season of greatest resource scarcity, and second, t hat most mortality is caused by starvation. We found that the lean season (winter) was generally not the season of greatest mortality. Instead, spring or summer was most frequently the season of greatest mortality. Moreover, monthly survival rates were not explained by monthly productivity, again opposing predictions from Ashmole’s hypothesis. Finally, predation, rather than starvation, was the most frequent proximate cause o f mortality. Our results do not support the mechanistic predictions of Ashmole‘s hypothesis, and suggest alternative explanations of latitudinal variation in clutch size should remain under consideration. Our meta-analysis also highlights a paucity of data available on the timing and causes of mortality in many bird populations, particularly tropical bird populations, despite the clear theoretical and empirical importance of such data.

Surgical Risk Preoperative Assessment System (SURPAS): II. Parsimonious Risk Models for Postoperative Adverse Outcomes Addressing Need for Laboratory Variables and Surgeon Specialty-specific Models.

PubMed

Meguid, Robert A; Bronsert, Michael R; Juarez-Colunga, Elizabeth; Hammermeister, Karl E; Henderson, William G

2016-07-01

To develop parsimonious prediction models for postoperative mortality, overall morbidity, and 6 complication clusters applicable to a broad range of surgical operations in adult patients. Quantitative risk assessment tools are not routinely used for preoperative patient assessment, shared decision making, informed consent, and preoperative patient optimization, likely due in part to the burden of data collection and the complexity of incorporation into routine surgical practice. Multivariable forward selection stepwise logistic regression analyses were used to develop predictive models for 30-day mortality, overall morbidity, and 6 postoperative complication clusters, using 40 preoperative variables from 2,275,240 surgical cases in the American College of Surgeons National Surgical Quality Improvement Program data set, 2005 to 2012. For the mortality and overall morbidity outcomes, prediction models were compared with and without preoperative laboratory variables, and generic models (based on all of the data from 9 surgical specialties) were compared with specialty-specific models. In each model, the cumulative c-index was used to examine the contribution of each added predictor variable. C-indexes, Hosmer-Lemeshow analyses, and Brier scores were used to compare discrimination and calibration between models. For the mortality and overall morbidity outcomes, the prediction models without the preoperative laboratory variables performed as well as the models with the laboratory variables, and the generic models performed as well as the specialty-specific models. The c-indexes were 0.938 for mortality, 0.810 for overall morbidity, and for the 6 complication clusters ranged from 0.757 for infectious to 0.897 for pulmonary complications. Across the 8 prediction models, the first 7 to 11 variables entered accounted for at least 99% of the c-index of the full model (using up to 28 nonlaboratory predictor variables). Our results suggest that it will be possible to develop parsimonious models to predict 8 important postoperative outcomes for a broad surgical population, without the need for surgeon specialty-specific models or inclusion of laboratory variables.

The intracranial number of foreign bodies as a predictor of mortality after penetrating brain injury.

PubMed

Bolatkale, Mustafa; Acara, Ahmet Cagdas

2018-06-02

Penetrating brain injury (PBI) is the most lethal form of traumatic brain injury, which is a leading cause of mortality. PBI has a mortality rate of 23%-93% and 87%-100% with poor neurological status. Despite the use of various prognostic factors there is still a need for a specific prognostic factor for early prediction of mortality in PBI to reduce mortality and provide good outcomes with cost-effective surgical treatments. The aim of this study was to investigate the predictive value of the number of intracranial foreign bodies (FBs) on mortality in PBI in the Emergency Department. The study included 95 patients admitted with PBI caused by barrel bomb explosion. The intracranial number of FB was examined by brain computed tomography. Logistic regression was used to assess the association of the intracranial number of FB on mortality. Correlation analyses were performed to investigate the association of Glasgow Coma Scale (GCS) with intracranial number of FB. The optimal cut-off value of the intracranial number of FB calculated for mortality was 2, which was effective for predicting mortality (p < .001). In patients with >2 intracranial FB, the mortality rate was statistically significantly 51-fold higher than those with ≤2 (p < .001). A statistically significant negative correlation was determined between GCS and number of. FB (r = -0.697;p < .001). When the intracranial number of FB was >2, mortality significantly increased in patients with PBI. The intracranial number of FBs may be considered as a novel prognostic factor for the prediction of mortality in PBI. Penetrating brain injury, mortality, foreign body, barrel bomb. Copyright © 2018 Elsevier Inc. All rights reserved.

Comparison of physician referral and insurance claims data-based risk prediction as approaches to identify patients for care management in primary care: an observational study.

PubMed

Freund, Tobias; Gondan, Matthias; Rochon, Justine; Peters-Klimm, Frank; Campbell, Stephen; Wensing, Michel; Szecsenyi, Joachim

2013-10-20

Primary care-based care management (CM) could reduce hospital admissions in high-risk patients. Identification of patients most likely to benefit is needed as resources for CM are limited. This study aimed to compare hospitalization and mortality rates of patients identified for CM either by treating primary care physicians (PCPs) or predictive modelling software for hospitalization risk (PM). In 2009, a cohort of 6,026 beneficiaries of a German statutory health insurance served as a sample for patient identification for CM by PCPs or commercial PM (CSSG 0.8, Verisk Health). The resulting samples were compared regarding hospitalization and mortality rates in 2010 and in the two year period before patient selection. No CM-intervention was delivered until the end of 2010 and PCPs were blinded for the assessment of hospitalization rates. In 2010, hospitalization rates of PM-identified patients were 80% higher compared to PCP-identified patients. Mortality rates were also 8% higher in PM-identified patients if compared to PCP-identified patients (10% vs. 2%). The hospitalization rate of patients independently identified by both PM and PCPs was numerically between PM- and PCP-identified patients. Time trend between 2007 and 2010 showed decreasing hospitalization rates in PM-identified patients (-15% per year) compared to increasing rates in PCP-identified patients (+34% per year). PM identified patients with higher hospitalization and mortality rates compared to PCP-referred patients. But the latter showed increasing hospitalization rates over time thereby suggesting that PCPs may be able to predict future deterioration in patients with relatively good current health status. These patients may most likely benefit from preventive services like CM.

Prediction of forest canopy and surface fuels from Lidar and satellite time series data in a bark beetle-affected forest

USGS Publications Warehouse

Bright, Benjamin C.; Hudak, Andrew T.; Meddens, Arjan J.H.; Hawbaker, Todd J.; Briggs, Jenny S.; Kennedy, Robert E.

2017-01-01

Wildfire behavior depends on the type, quantity, and condition of fuels, and the effect that bark beetle outbreaks have on fuels is a topic of current research and debate. Remote sensing can provide estimates of fuels across landscapes, although few studies have estimated surface fuels from remote sensing data. Here we predicted and mapped field-measured canopy and surface fuels from light detection and ranging (lidar) and Landsat time series explanatory variables via random forest (RF) modeling across a coniferous montane forest in Colorado, USA, which was affected by mountain pine beetles (Dendroctonus ponderosae Hopkins) approximately six years prior. We examined relationships between mapped fuels and the severity of tree mortality with correlation tests. RF models explained 59%, 48%, 35%, and 70% of the variation in available canopy fuel, canopy bulk density, canopy base height, and canopy height, respectively (percent root-mean-square error (%RMSE) = 12–54%). Surface fuels were predicted less accurately, with models explaining 24%, 28%, 32%, and 30% of the variation in litter and duff, 1 to 100-h, 1000-h, and total surface fuels, respectively (%RMSE = 37–98%). Fuel metrics were negatively correlated with the severity of tree mortality, except canopy base height, which increased with greater tree mortality. Our results showed how bark beetle-caused tree mortality significantly reduced canopy fuels in our study area. We demonstrated that lidar and Landsat time series data contain substantial information about canopy and surface fuels and can be used for large-scale efforts to monitor and map fuel loads for fire behavior modeling at a landscape scale.

Clinical manifestation, serology marker & microscopic agglutination test (MAT) to mortality in human leptospirosis

NASA Astrophysics Data System (ADS)

Perdhana, S. A. P.; Susilo, R. S. B.; Arifin; Redhono, D.; Sumandjar, T.

2018-03-01

Leptospirosis is a potentially fatal zoonosis that is endemic in many tropical regions and causes large epidemics after heavy rainfall and flooding. Severe disease is estimated 5–15% of all human infections. Its mortality rate is 5-40%. MAT, isolation of the organism, or leptospiral DNA in PCR are used to confirm Leptospirosis. This cross-sectional analytic study recruited 26 hospitalized leptospirosis patients admitted to Dr. Moewardi Hospital Surakarta. The diagnosis was based on clinical, laboratory and epidemiological findings. The onset of the disease was the date when the first symptom started, and the end of the analysis was the date when the patient died or discharged. Modified Faine’s score ≥ 25 tend to die (45.5%) while modified Faine’s score 20 – 24 tend to heal (60%) (OR 1.250; CI 0.259-6.029; p=1.0). Seropositive IgM predicts mortality 7.8 times higher than seronegative IgM (OR 7.800; CI 1.162-52.353; p=0.038). MAT positive predict mortality 10.667 times higher than MAT negative (OR 10.667; CI 1.705-66.720; p=0.015). Clinical manifestation, MAT, and serologic marker are all correlated with mortality in Leptospirosis. However, statistically, clinical manifestation has an insignificant correlation.

The development of a VBHOM-based outcome model for lower limb amputation performed for critical ischaemia.

PubMed

Tang, T Y; Prytherch, D R; Walsh, S R; Athanassoglou, V; Seppi, V; Sadat, U; Lees, T A; Varty, K; Boyle, J R

2009-01-01

VBHOM (Vascular Biochemistry and Haematology Outcome Models) adopts the approach of using a minimum data set to model outcome and has been previously shown to be feasible after index arterial operations. This study attempts to model mortality following lower limb amputation for critical limb ischaemia using the VBHOM concept. A binary logistic regression model of risk of mortality was built using National Vascular Database items that contained the complete data required by the model from 269 admissions for lower limb amputation. The subset of NVD data items used were urea, creatinine, sodium, potassium, haemoglobin, white cell count, age on and mode of admission. This model was applied prospectively to a test set of data (n=269), which were not part of the original training set to develop the predictor equation. Outcome following lower limb amputation could be described accurately using the same model. The overall mean predicted risk of mortality was 32%, predicting 86 deaths. Actual number of deaths was 86 (chi(2)=8.05, 8 d.f., p=0.429; no evidence of lack of fit). The model demonstrated adequate discrimination (c-index=0.704). VBHOM provides a single unified model that allows good prediction of surgical mortality in this high risk group of individuals. It uses a small, simple and objective clinical data set that may also simplify comparative audit within vascular surgery.

Composite Quality Measures for Common Inpatient Medical Conditions

PubMed Central

Chen, Lena M.; Staiger, Douglas O.; Birkmeyer, John D.; Ryan, Andrew M.; Zhang, Wenying; Dimick, Justin B.

2014-01-01

Background Public reporting on quality aims to help patients select better hospitals. However, individual quality measures are sub-optimal in identifying superior and inferior hospitals based on outcome performance. Objective To combine structure, process, and outcome measures into an empirically-derived composite quality measure for heart failure (HF), acute myocardial infarction (AMI), and pneumonia (PNA). To assess how well the composite measure predicts future high and low performers, and explains variance in future hospital mortality. Research Design Using national Medicare data, we created a cohort of older patients treated at an acute care hospital for HF (n=1,203,595), AMI (n=625,595), or PNA (n=1,234,299). We ranked hospitals based on their July 2005 to June 2008 performance on the composite. We then estimated the odds of future (July to December 2009) 30-day, risk-adjusted mortality at the worst vs. best quintile of hospitals. We repeated this analysis using 2005-2008 performance on existing quality indicators, including mortality. Results The composite (vs. Hospital Compare) explained 68% (vs. 39%) of variation in future AMI mortality rates. In 2009, if an AMI patient had chosen a hospital in the worst vs. best quintile of performance using 2005-2008 composite (vs. Hospital Compare) rankings, he or she would have had 1.61 (vs. 1.39) times the odds of dying in 30 days (p-value for difference < 0.001). Results were similar for HF and PNA. Conclusions Composite measures of quality for HF, AMI, and PNA performed better than existing measures at explaining variation in future mortality and predicting future high and low performers. PMID:23942222

Mortality determinants and prediction of outcome in high risk newborns.

PubMed

Dalvi, R; Dalvi, B V; Birewar, N; Chari, G; Fernandez, A R

1990-06-01

The aim of this study was to determine independent patient-related predictors of mortality in high risk newborns admitted at our centre. The study population comprised 100 consecutive newborns each, from the premature unit (PU) and sick baby care unit (SBCU), respectively. Thirteen high risk factors (variables) for each of the two units, were entered into a multivariate regression analysis. Variables with independent predictive value for poor outcome (i.e., death) in PU were, weight less than 1 kg, hyaline membrane disease, neurologic problems, and intravenous therapy. High risk factors in SBCU included, blood gas abnormality, bleeding phenomena, recurrent convulsions, apnea, and congenital anomalies. Identification of these factors guided us in defining priority areas for improvement in our system of neonatal care. Also, based on these variables a simple predictive score for outcome was constructed. The prediction equation and the score were cross-validated by applying them to a 'test-set' of 100 newborns each for PU and SBCU. Results showed a comparable sensitivity, specificity and error rate.

Lung Injury Prediction Score Is Useful in Predicting Acute Respiratory Distress Syndrome and Mortality in Surgical Critical Care Patients

PubMed Central

Bauman, Zachary M.; Gassner, Marika Y.; Coughlin, Megan A.; Mahan, Meredith; Watras, Jill

2015-01-01

Background. Lung injury prediction score (LIPS) is valuable for early recognition of ventilated patients at high risk for developing acute respiratory distress syndrome (ARDS). This study analyzes the value of LIPS in predicting ARDS and mortality among ventilated surgical patients. Methods. IRB approved, prospective observational study including all ventilated patients admitted to the surgical intensive care unit at a single tertiary center over 6 months. ARDS was defined using the Berlin criteria. LIPS were calculated for all patients and analyzed. Logistic regression models evaluated the ability of LIPS to predict development of ARDS and mortality. A receiver operator characteristic (ROC) curve demonstrated the optimal LIPS value to statistically predict development of ARDS. Results. 268 ventilated patients were observed; 141 developed ARDS and 127 did not. The average LIPS for patients who developed ARDS was 8.8 ± 2.8 versus 5.4 ± 2.8 for those who did not (p < 0.001). An ROC area under the curve of 0.79 demonstrates LIPS is statistically powerful for predicting ARDS development. Furthermore, for every 1-unit increase in LIPS, the odds of developing ARDS increase by 1.50 (p < 0.001) and odds of ICU mortality increase by 1.22 (p < 0.001). Conclusion. LIPS is reliable for predicting development of ARDS and predicting mortality in critically ill surgical patients. PMID:26301105

GRACE risk score: Sex-based validity of in-hospital mortality prediction in Canadian patients with acute coronary syndrome.

PubMed

Gong, Inna Y; Goodman, Shaun G; Brieger, David; Gale, Chris P; Chew, Derek P; Welsh, Robert C; Huynh, Thao; DeYoung, J Paul; Baer, Carolyn; Gyenes, Gabor T; Udell, Jacob A; Fox, Keith A A; Yan, Andrew T

2017-10-01

Although there are sex differences in management and outcome of acute coronary syndromes (ACS), sex is not a component of Global Registry of Acute Coronary Events (GRACE) risk score (RS) for in-hospital mortality prediction. We sought to determine the prognostic utility of GRACE RS in men and women, and whether its predictive accuracy would be augmented through sex-based modification of its components. Canadian men and women enrolled in GRACE and Canadian Registry of Acute Coronary Events were stratified as ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation ACS (NSTE-ACS). GRACE RS was calculated as per original model. Discrimination and calibration were evaluated using the c-statistic and Hosmer-Lemeshow goodness-of-fit test, respectively. Multivariable logistic regression was undertaken to assess potential interactions of sex with GRACE RS components. For the overall cohort (n=14,422), unadjusted in-hospital mortality rate was higher in women than men (4.5% vs. 3.0%, p<0.001). Overall, GRACE RS c-statistic and goodness-of-fit test p-value were 0.85 (95% CI 0.83-0.87) and 0.11, respectively. While the RS had excellent discrimination for all subgroups (c-statistics >0.80), discrimination was lower for women compared to men with STEMI [0.80 (0.75-0.84) vs. 0.86 (0.82-0.89), respectively, p<0.05]. The goodness-of-fit test showed good calibration for women (p=0.86), but suboptimal for men (p=0.031). No significant interaction was evident between sex and RS components (all p>0.25). The GRACE RS is a valid predictor of in-hospital mortality for both men and women with ACS. The lack of interaction between sex and RS components suggests that sex-based modification is not required. Copyright © 2017 Elsevier B.V. All rights reserved.

Hypotension, bedridden, leukocytosis, thrombocytopenia and elevated serum creatinine predict mortality in geriatric patients with fever.

PubMed

Chung, Min-Hsien; Chu, Feng-Yuan; Yang, Tzu-Meng; Lin, Hung-Jung; Chen, Jiann-Hwa; Guo, How-Ran; Vong, Si-Chon; Su, Shih-Bin; Huang, Chien-Cheng; Hsu, Chien-Chin

2015-07-01

The geriatric population (aged ≥65 years) accounts for 12-24% of all emergency department (ED) visits. Of them, 10% have a fever, 70-90% will be admitted and 7-10% of will die within a month. Therefore, mortality prediction and appropriate disposition after ED treatment are of great concern for geriatric patients with fever. We tried to identify independent mortality predictors of geriatric patients with fever, and combine these predictors to predict their mortality. We enrolled consecutive geriatric patients visiting the ED between 1 June and 21 July 2010 with the following criteria of fever: a tympanic temperature ≥37.2°C or a baseline temperature elevated ≥1.3°C. We used 30-day mortality as the primary end-point. A total of 330 patients were enrolled. Hypotension, bedridden, leukocytosis, thrombocytopenia and serum creatinine >2 mg/dL, but not age, were independently associated with 30-day mortality. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) ranged from 18.2% to 90.9%, 34.7% to 100%, 9.0% to 100% and 94.5% to 98.2%, respectively, depending on how many predictors there were. The 30-day mortality increased with the number of independent mortality predictors. With at least four predictors, 100% of the patients died within 30 days. With none of the predictors, just 1.8% died. These findings might help physicians make decisions about geriatric patients with fever. © 2014 Japan Geriatrics Society.

Heat stress related dairy cow mortality during heat waves and control periods in rural Southern Ontario from 2010-2012.

PubMed

Bishop-Williams, Katherine E; Berke, Olaf; Pearl, David L; Hand, Karen; Kelton, David F

2015-11-27

Heat stress is a physiological response to extreme environmental heat such as heat waves. Heat stress can result in mortality in dairy cows when extreme heat is both rapidly changing and has a long duration. As a result of climate change, heat waves, which are defined as 3 days of temperatures of 32 °C or above, are an increasingly frequent extreme weather phenomenon in Southern Ontario. Heat waves are increasing the risk for on-farm dairy cow mortality in Southern Ontario. Heat stress indices (HSIs) are generally based on temperature and humidity and provide a relative measure of discomfort which can be used to predict increased risk of on-farm dairy cow mortality. In what follows, the heat stress distribution was described over space and presented with maps. Similarly, on-farm mortality was described and mapped. The goal of this study was to demonstrate that heat waves and related HSI increases during 2010-2012 were associated with increased on-farm dairy cow mortality in Southern Ontario. Mortality records and farm locations for all farms registered in the CanWest Dairy Herd Improvement Program in Southern Ontario were retrieved for 3 heat waves and 6 three-day control periods from 2010 to 2012. A random sample of controls (2:1) was taken from the data set to create a risk-based hybrid design. On-farm heat stress was estimated using data from 37 weather stations and subsequently interpolated across Southern Ontario by geostatistical kriging. A Poisson regression model was applied to assess the on-farm mortality in relation to varying levels of the HSI. For every one unit increase in HSI the on-farm mortality rate across Southern Ontario increases by 1.03 times (CI95% (IRR) = (1.025,1.035); p = ≤ 0.001). With a typical 8.6 unit increase in HSI from a control period to a heat wave, mortality rates are predicted to increase by 1.27 times. Southern Ontario was affected by heat waves, as demonstrated by high levels of heat stress and increased on-farm mortality. Farmers should be aware of these risks, and informed of appropriate methods to mitigate such risks.

Mortality in Code Blue; can APACHE II and PRISM scores be used as markers for prognostication?

PubMed

Bakan, Nurten; Karaören, Gülşah; Tomruk, Şenay Göksu; Keskin Kayalar, Sinem

2018-03-01

Code blue (CB) is an emergency call system developed to respond to cardiac and respiratory arrest in hospitals. However, in literature, no scoring system has been reported that can predict mortality in CB procedures. In this study, we aimed to investigate the effectiveness of estimated APACHE II and PRISM scores in the prediction of mortality in patients assessed using CB to retrospectively analyze CB calls. We retrospectively examined 1195 patients who were evaluated by the CB team at our hospital between 2009 and 2013. The demographic data of the patients, diagnosis and relevant de-partments, reasons for CB, cardiopulmonary resuscitation duration, mortality calculated from the APACHE II and PRISM scores, and the actual mortality rates were retrospectively record-ed from CB notification forms and the hospital database. In all age groups, there was a significant difference between actual mortality rate and the expected mortality rate as estimated using APACHE II and PRISM scores in CB calls (p<0.05). The actual mortality rate was significantly lower than the expected mortality. APACHE and PRISM scores with the available parameters will not help predict mortality in CB procedures. Therefore, novels scoring systems using different parameters are needed.

Acid-base disorders in critically ill neonates

PubMed Central

Lekhwani, S.; Shanker, V.; Gathwala, G.; Vaswani, N. D.

2010-01-01

Objective: To study acid–base imbalance in common pediatric diseases (such as sepsis, bronchopneumonia, diarrhea, birth-asphyxia etc.) in neonates. Design and Setting: An observational study was conducted in an emergency room of a tertiary teaching care hospital in Haryana, India. Patients and Methods: Fifty neonates (from first hour to one month) attending pediatric emergency services with various ailments. Blood gas analysis, electrolytes, plasma lactate, and plasma albumin were estimated in neonates. Results: Metabolic acidosis was the most common acid–base disorder. Hyperlactatemia was observed in more than half of such cases. Birth asphyxia was another common disorder with the highest mortality in neonates followed by bronchopneumonia and sepsis. Significant correlation between mortality and critical values of lactate was observed. Conclusion: Birth asphyxia with high-lactate levels in neonates constituted major alterations in acid–base disorders seen in an emergency room of a tertiary teaching care hospital. Plasma lactate concentration measurement provides an invaluable tool to assess type of metabolic acidosis in addition to predicting mortality in these neonates. PMID:20859489

An externally validated model for predicting long-term survival after exercise treadmill testing in patients with suspected coronary artery disease and a normal electrocardiogram.

PubMed

Lauer, Michael S; Pothier, Claire E; Magid, David J; Smith, S Scott; Kattan, Michael W

2007-12-18

The exercise treadmill test is recommended for risk stratification among patients with intermediate to high pretest probability of coronary artery disease. Posttest risk stratification is based on the Duke treadmill score, which includes only functional capacity and measures of ischemia. To develop and externally validate a post-treadmill test, multivariable mortality prediction rule for adults with suspected coronary artery disease and normal electrocardiograms. Prospective cohort study conducted from September 1990 to May 2004. Exercise treadmill laboratories in a major medical center (derivation set) and a separate HMO (validation set). 33,268 patients in the derivation set and 5821 in the validation set. All patients had normal electrocardiograms and were referred for evaluation of suspected coronary artery disease. The derivation set patients were followed for a median of 6.2 years. A nomogram-illustrated model was derived on the basis of variables easily obtained in the stress laboratory, including age; sex; history of smoking, hypertension, diabetes, or typical angina; and exercise findings of functional capacity, ST-segment changes, symptoms, heart rate recovery, and frequent ventricular ectopy in recovery. The derivation data set included 1619 deaths. Although both the Duke treadmill score and our nomogram-illustrated model were significantly associated with death (P < 0.001), the nomogram was better at discrimination (concordance index for right-censored data, 0.83 vs. 0.73) and calibration. We reclassified many patients with intermediate- to high-risk Duke treadmill scores as low risk on the basis of the nomogram. The model also predicted 3-year mortality rates well in the validation set: Based on an optimal cut-point for a negative predictive value of 0.97, derivation and validation rates were, respectively, 1.7% and 2.5% below the cut-point and 25% and 29% above the cut-point. Blood test-based measures or left ventricular ejection fraction were not included. The nomogram can be applied only to patients with a normal electrocardiogram. Clinical utility remains to be tested. A simple nomogram based on easily obtained pretest and exercise test variables predicted all-cause mortality in adults with suspected coronary artery disease and normal electrocardiograms.

Predicting the effectiveness of the Finnish population-based colorectal cancer screening programme.

PubMed

Chiu, Sherry Yueh-Hsia; Malila, Nea; Yen, Amy Ming-Fang; Chen, Sam Li-Sheng; Fann, Jean Ching-Yuan; Hakama, Matti

2017-12-01

Objective Because colorectal cancer (CRC) has a long natural history, estimating the effectiveness of CRC screening programmes requires long-term follow-up. As an alternative, we here demonstrate the use of a temporal multi-state natural history model to predict the effectiveness of CRC screening. Methods In the Finnish population-based biennial CRC screening programme using faecal occult blood tests (FOBT), which was conducted in a randomised health services study, we estimated the pre-clinical incidence, the mean sojourn time (MST), and the sensitivity of FOBT using a Markov model to analyse data from 2004 to 2007. These estimates were applied to predict, through simulation, the effects of five rounds of screening on the relative rate of reducing advanced CRC with 6 years of follow-up, and on the reduction in mortality with 10 years of follow-up, in a cohort of 500,000 subjects aged 60 to 69. Results For localised and non-localised CRC, respectively, the MST was 2.06 and 1.36 years and the sensitivity estimates were 65.12% and 73.70%. The predicted relative risk of non-localised CRC and death from CRC in the screened compared with the control population was 0.86 (95% CI: 0.79-0.98) and 0.91 (95% CI: 0.85-1.02), respectively. Conclusion Based on the preliminary results of the Finnish CRC screening programme, our model predicted a 9% reduction in CRC mortality and a 14% reduction in advanced CRC.

Predictive Mortality Index for Community-Dwelling Elderly Koreans

PubMed Central

Kim, Nan H.; Cho, Hyun J.; Kim, Soriul; Seo, Ji H.; Lee, Hyun J.; Yu, Ji H.; Chung, Hye S.; Yoo, Hye J.; Seo, Ji A.; Kim, Sin Gon; Baik, Sei Hyun; Choi, Dong Seop; Shin, Chol; Choi, Kyung Mook

2016-01-01

Abstract There are very few predictive indexes for long-term mortality among community-dwelling elderly Asian individuals, despite its importance, given the rapid and continuous increase in this population. We aimed to develop 10-year predictive mortality indexes for community-dwelling elderly Korean men and women based on routinely collected clinical data. We used data from 2244 elderly individuals (older than 60 years of age) from the southwest Seoul Study, a prospective cohort study, for the development of a prognostic index. An independent longitudinal cohort of 679 elderly participants was selected from the Korean Genome Epidemiology Study in Ansan City for validation. During a 10-year follow-up, 393 participants (17.5%) from the development cohort died. Nine risk factors were identified and weighed in the Cox proportional regression model to create a point scoring system: age, male sex, smoking, diabetes, systolic blood pressure, triglyceride, total cholesterol, white blood cell count, and hemoglobin. In the development cohort, the 10-year mortality risk was 6.6%, 14.8%, 18.2%, and 38.4% among subjects with 1 to 4, 5 to 7, 8 to 9, and ≥10 points, respectively. In the validation cohort, the 10-year mortality risk was 5.2%, 12.0%, 16.0%, and 16.0% according to these categories. The C-statistic for the point system was 0.73 and 0.67 in the development and validation cohorts, respectively. The present study provides valuable information for prognosis among elderly Koreans and may guide individualized approaches for appropriate care in a rapidly aging society. PMID:26844511

Performance of the PSI and CURB-65 scoring systems in predicting 30-day mortality in healthcare-associated pneumonia.

PubMed

Murillo-Zamora, Efrén; Medina-González, Alfredo; Zamora-Pérez, Liliana; Vázquez-Yáñez, Andrés; Guzmán-Esquivel, José; Trujillo-Hernández, Benjamín

2018-02-09

Healthcare-associated pneumonia (HCAP) is the leading cause of infection in a hospital setting and is associated with a high mortality rate. This study aimed to evaluate the performance of the pneumonia severity index (PSI) and confusion, urea, respiratory rate, blood pressure, age≥65 (CURB-65) systems in predicting 30-day mortality in HCAP in adult patients. A cross-sectional study took place and data from 109 non-immunocompromised individuals aged>18 years were analyzed. The clinical diagnosis of HCAP included the presence of radiographic infiltrates in patients≥48hours after hospital admission. The PSI and CURB-65 scores were calculated and performance measures were estimated. Summary statistics were used to describe the study sample. The PSI and CURB-65 scores were calculated based on 20 and 5 criteria, respectively, and the performance indicators of the screening tools were estimated. The overall 30-day mortality was 59.6%. At every given threshold, PSI sensitivity was higher, but showed a lower specificity than the CURB-65, and the highest Youden index (0.392) was observed at cut-off V in the PSI. The area under the ROC curve was 0.737 (95% CI: 0.646-0.827) and 0.698 (95% CI: 0.600-0.797) using the PSI and CURB-65 systems, respectively (P=.323). Our findings suggest that the performance of the PSI and CURB-65 is reasonable for predicting 30-day mortality in adult HCAP patients and may be used in healthcare settings. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Validation of the CORB75 (confusion, oxygen saturation, respiratory rate, blood pressure, and age ≥ 75 years) as a simpler pneumonia severity rule.

PubMed

Ochoa-Gondar, O; Vila-Corcoles, A; Rodriguez-Blanco, T; Hospital, I; Salsench, E; Ansa, X; Saun, N

2014-04-01

This study compares the ability of two simpler severity rules (classical CRB65 vs. proposed CORB75) in predicting short-term mortality in elderly patients with community-acquired pneumonia (CAP). A population-based study was undertaken involving 610 patients ≥ 65 years old with radiographically confirmed CAP diagnosed between 2008 and 2011 in Tarragona, Spain (350 cases in the derivation cohort, 260 cases in the validation cohort). Severity rules were calculated at the time of diagnosis, and 30-day mortality was considered as the dependent variable. The area under the receiver operating characteristic curves (AUC) was used to compare the discriminative power of the severity rules. Eighty deaths (46 in the derivation and 34 in the validation cohorts) were observed, which gives a mortality rate of 13.1 % (15.6 % for hospitalized and 3.3 % for outpatient cases). After multivariable analyses, besides CRB (confusion, respiration rate ≥ 30/min, systolic blood pressure <90 mmHg or diastolic ≤ 60 mmHg), peripheral oxygen saturation (≤ 90 %) and age ≥ 75 years appeared to be associated with increasing 30-day mortality in the derivation cohort. The model showed adequate calibration for the derivation and validation cohorts. A modified CORB75 scoring system (similar to the classical CRB65, but adding oxygen saturation and increasing the age to 75 years) was constructed. The AUC statistics for predicting mortality in the derivation and validation cohorts were 0.79 and 0.82, respectively. In the derivation cohort, a CORB75 score ≥ 2 showed 78.3 % sensitivity and 65.5 % specificity for mortality (in the validation cohort, these were 82.4 and 71.7 %, respectively). The proposed CORB75 scoring system has good discriminative power in predicting short-term mortality among elderly people with CAP, which supports its use for severity assessment of these patients in primary care.

The use of customised versus population-based birthweight standards in predicting perinatal mortality.

PubMed

Zhang, X; Platt, R W; Cnattingius, S; Joseph, K S; Kramer, M S

2007-04-01

The objective of this study was to critically examine potential artifacts and biases underlying the use of 'customised' standards of birthweight for gestational age (GA). Population-based cohort study. Sweden. A total of 782,303 singletons > or =28 weeks of gestation born in 1992-2001 to Nordic mothers with complete data on birthweight; GA; and maternal age, parity, height, and pre-pregnancy weight. We compared perinatal mortality in four groups of infants based on the following classification of small for gestational age (SGA): non-SGA based on either population-based or customised standards (the reference group), SGA based on the population-based standard only, SGA based on the customised standard only, and SGA according to both standards. We used graphical methods to compare GA-specific birthweight cutoffs for SGA using the two standards and also used logistic regression to control for differences in GA and maternal pre-pregnancy body mass index (BMI) in the four groups. Perinatal mortality, including stillbirth and neonatal death. Customisation led to a large artifactual increase in the proportion of SGA infants born preterm. Adjustment for differences in GA and maternal BMI markedly reduced the excess risk among infants classified as SGA by customised standards only. The large increase in perinatal mortality risk among infants classified as SGA based on customised standards is largely an artifact due to inclusion of more preterm births.

Improving Predictions of Tree Drought Mortality in the Community Land Model Using Hydraulic Physiology Theory and its Effects on Carbon Metabolism

NASA Astrophysics Data System (ADS)

McNellis, B.; Hudiburg, T. W.

2017-12-01

Tree mortality due to drought is predicted to have increasing impacts on ecosystem structure and function during the 21st century. Models can attempt to predict which forests are most at risk from drought, but novel environments may preclude analysis that relies on past observations. The inclusion of more mechanistic detail may reduce uncertainty in predictions, but can also compound model complexity, especially in global models. The Community Land Model version 5 (CLM5), itself a component of the Community Earth System Model (CESM), has recently integrated cohort-based demography into its dynamic vegetation component and is in the process of coupling this demography to a model of plant hydraulic physiology (FATES-Hydro). Previous treatment of drought stress and plant mortality within CLM has been relatively broad, but a detailed hydraulics module represents a key step towards accurate mortality prognosis. Here, we examine the structure of FATES-Hydro with respect to two key physiological attributes: tissue osmotic potentials and embolism refilling. Specifically, we ask how FATES-Hydro captures mechanistic realism within each attribute and how much support there is within the physiological literature for its further elaboration within the model structure. Additionally, connections to broader aspects of carbon metabolism within FATES are explored to better resolve emergent consequences of drought stress on ecosystem function and tree demographics. An on-going field experiment in managed stands of Pinus ponderosa and mixed conifers is assessed for model parameterization and performance across PNW forests, with important implications for future forest management strategy.

A geographical information system-based analysis of cancer mortality and population exposure to coal mining activities in West Virginia, United States of America.

PubMed

Hendryx, Michael; Fedorko, Evan; Anesetti-Rothermel, Andrew

2010-05-01

Cancer incidence and mortality rates are high in West Virginia compared to the rest of the United States of America. Previous research has suggested that exposure to activities of the coal mining industry may contribute to elevated cancer mortality, although exposure measures have been limited. This study tests alternative specifications of exposure to mining activity to determine whether a measure based on location of mines, processing plants, coal slurry impoundments and underground slurry injection sites relative to population levels is superior to a previously-reported measure of exposure based on tons mined at the county level, in the prediction of age-adjusted cancer mortality rates. To this end, we utilize two geographical information system (GIS) techniques--exploratory spatial data analysis and inverse distance mapping--to construct new statistical analyses. Total, respiratory and "other" age-adjusted cancer mortality rates in West Virginia were found to be more highly associated with the GIS-exposure measure than the tonnage measure, before and after statistical control for smoking rates. The superior performance of the GIS measure, based on where people in the state live relative to mining activity, suggests that activities of the industry contribute to cancer mortality. Further confirmation of observed phenomena is necessary with person-level studies, but the results add to the body of evidence that coal mining poses environmental risks to population health in West Virginia.

A Risk Prediction Model for In-hospital Mortality in Patients with Suspected Myocarditis

PubMed Central

Xu, Duo; Zhao, Ruo-Chi; Gao, Wen-Hui; Cui, Han-Bin

2017-01-01

Background: Myocarditis is an inflammatory disease of the myocardium that may lead to cardiac death in some patients. However, little is known about the predictors of in-hospital mortality in patients with suspected myocarditis. Thus, the aim of this study was to identify the independent risk factors for in-hospital mortality in patients with suspected myocarditis by establishing a risk prediction model. Methods: A retrospective study was performed to analyze the clinical medical records of 403 consecutive patients with suspected myocarditis who were admitted to Ningbo First Hospital between January 2003 and December 2013. A total of 238 males (59%) and 165 females (41%) were enrolled in this study. We divided the above patients into two subgroups (survival and nonsurvival), according to their clinical in-hospital outcomes. To maximize the effectiveness of the prediction model, we first identified the potential risk factors for in-hospital mortality among patients with suspected myocarditis, based on data pertaining to previously established risk factors and basic patient characteristics. We subsequently established a regression model for predicting in-hospital mortality using univariate and multivariate logistic regression analyses. Finally, we identified the independent risk factors for in-hospital mortality using our risk prediction model. Results: The following prediction model for in-hospital mortality in patients with suspected myocarditis, including creatinine clearance rate (Ccr), age, ventricular tachycardia (VT), New York Heart Association (NYHA) classification, gender and cardiac troponin T (cTnT), was established in the study: P = ea/(1 + ea) (where e is the exponential function, P is the probability of in-hospital death, and a = −7.34 + 2.99 × [Ccr <60 ml/min = 1, Ccr ≥60 ml/min = 0] + 2.01 × [age ≥50 years = 1, age <50 years = 0] + 1.93 × [VT = 1, no VT = 0] + 1.39 × [NYHA ≥3 = 1, NYHA <3 = 0] + 1.25 × [male = 1, female = 0] + 1.13 × [cTnT ≥50 μg/L = 1, cTnT <50 μg/L = 0]). The area under the receiver operating characteristic curve was 0.96 (standard error = 0.015, 95% confidence interval [CI]: 0.93-0.99). The model demonstrated that a Ccr <60 ml/min (odds ratio [OR] = 19.94, 95% CI: 5.66–70.26), an age ≥50 years (OR = 7.43, 95% CI: 2.18–25.34), VT (OR = 6.89, 95% CI: 1.86–25.44), a NYHA classification ≥3 (OR = 4.03, 95% CI: 1.13–14.32), male gender (OR = 3.48, 95% CI: 0.99–12.20), and a cTnT level ≥50 μg/L (OR = 3.10, 95% CI: 0.91–10.62) were the independent risk factors for in-hospital mortality. Conclusions: A Ccr <60 ml/min, an age ≥50 years, VT, an NYHA classification ≥3, male gender, and a cTnT level ≥50 μg/L were the independent risk factors resulting from the prediction model for in-hospital mortality in patients with suspected myocarditis. In addition, sufficient life support during the early stage of the disease might improve the prognoses of patients with suspected myocarditis with multiple risk factors for in-hospital mortality. PMID:28345541

Association of estimated glomerular filtration rate and urine albumin-to-creatinine ratio with incidence of cardiovascular diseases and mortality in chinese patients with type 2 diabetes mellitus - a population-based retrospective cohort study.

PubMed

Fung, Colman Siu Cheung; Wan, Eric Yuk Fai; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen

2017-02-02

Estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR) are renal markers associated with risks of cardiovascular diseases (CVD) and all-cause mortality in diabetic patients. This study aims to quantify such risks in Chinese diabetic patients based on eGFR and UACR. This was a territory-wide retrospective cohort study on primary care diabetic patients with documented eGFR and UACR but without baseline CVD in 2008/2009. They were followed up till 2013 on CVD events and mortality. Associations between eGFR/UACR and incidence of CVD/mortality were evaluated by multivariable Cox proportional models adjusted with socio-demographic and clinical characteristics. The data of 66,311 patients who had valid baseline eGFR and UACR values were analysed. The risks of CVD events and mortality increased exponentially with the decrease in eGFR, with a hazard ratio (HR) increasing from 1.63 to 4.55 for CVD, and from 1.70 to 9.49 for mortality, associated with Stage 3 to 5 CKD, compared to Stage 1 CKD. UACR showed a positive linear association with CVD events and mortality. Microalbuminuria was associated with a HR of 1.58 and 2.08 for CVD and mortality in male (1.48 and 1.79 for female), respectively, compared to no microalbuminuria. Male patients with UACR 1-1.4 mg/mmol and eGFR ≥90 ml/min/1.73 m 2 (60-89 ml/min/1.73 m 2 ) had a HR of 1.25 (1.43) for CVD. Female patients with UACR 2.5-3.4 mg/ml and eGFR ≥90 ml/min/1.73 m 2 (60-89 ml/min/1.73 m 2 ) had a HR of 1.45 (1.65) for CVD. Risks of CVD events and mortality increased exponentially with eGFR drop, while UACR showed positive predictive linear relationships, and the risks started even in high-normal albuminuria. UACR-based HR was further modified according to eGFR level, with risk progressed with CKD stage. Combining eGFR and UACR level was more accurate in predicting risk of CVD/mortality. The findings call for more aggressive screening and intervention of microalbuminuria in diabetic patients.

Estimation and application of a growth and yield model for uneven-aged mixed conifer stands in California.

Treesearch

Jingjing Liang; J. Buongiorno; R.A. Monserud

2005-01-01

A growth model for uneven-aged mixed-conifer stands in California was developed with data from 205 permanent plots. The model predicts the number of softwood and hardwood trees in nineteen diameter classes, based on equations for diameter growth rates, mortality arid recruitment. The model gave unbiased predictions of the expected number of trees by diameter class and...

Socioeconomic Status, Structural and Functional Measures of Social Support, and Mortality

PubMed Central

Stringhini, Silvia; Berkman, Lisa; Dugravot, Aline; Ferrie, Jane E.; Marmot, Michael; Kivimaki, Mika; Singh-Manoux, Archana

2012-01-01

The authors examined the associations of social support with socioeconomic status (SES) and with mortality, as well as how SES differences in social support might account for SES differences in mortality. Analyses were based on 9,333 participants from the British Whitehall II Study cohort, a longitudinal cohort established in 1985 among London-based civil servants who were 35–55 years of age at baseline. SES was assessed using participant's employment grades at baseline. Social support was assessed 3 times in the 24.4-year period during which participants were monitored for death. In men, marital status, and to a lesser extent network score (but not low perceived support or high negative aspects of close relationships), predicted both all-cause and cardiovascular mortality. Measures of social support were not associated with cancer mortality. Men in the lowest SES category had an increased risk of death compared with those in the highest category (for all-cause mortality, hazard ratio = 1.59, 95% confidence interval: 1.21, 2.08; for cardiovascular mortality, hazard ratio = 2.48, 95% confidence interval: 1.55, 3.92). Network score and marital status combined explained 27% (95% confidence interval: 14, 43) and 29% (95% confidence interval: 17, 52) of the associations between SES and all-cause and cardiovascular mortality, respectively. In women, there was no consistent association between social support indicators and mortality. The present study suggests that in men, social isolation is not only an important risk factor for mortality but is also likely to contribute to differences in mortality by SES. PMID:22534202

Five year experience in management of perforated peptic ulcer and validation of common mortality risk prediction models - are existing models sufficient? A retrospective cohort study.

PubMed

Anbalakan, K; Chua, D; Pandya, G J; Shelat, V G

2015-02-01

Emergency surgery for perforated peptic ulcer (PPU) is associated with significant morbidity and mortality. Accurate and early risk stratification is important. The primary aim of this study is to validate the various existing MRPMs and secondary aim is to audit our experience of managing PPU. 332 patients who underwent emergency surgery for PPU at a single intuition from January 2008 to December 2012 were studied. Clinical and operative details were collected. Four MRPMs: American Society of Anesthesiology (ASA) score, Boey's score, Mannheim peritonitis index (MPI) and Peptic ulcer perforation (PULP) score were validated. Median age was 54.7 years (range 17-109 years) with male predominance (82.5%). 61.7% presented within 24 h of onset of abdominal pain. Median length of stay was 7 days (range 2-137 days). Intra-abdominal collection, leakage, re-operation and 30-day mortality rates were 8.1%, 2.1%, 1.2% and 7.2% respectively. All the four MRPMs predicted intra-abdominal collection and mortality; however, only MPI predicted leak (p = 0.01) and re-operation (p = 0.02) rates. The area under curve for predicting mortality was 75%, 72%, 77.2% and 75% for ASA score, Boey's score, MPI and PULP score respectively. Emergency surgery for PPU has low morbidity and mortality in our experience. MPI is the only scoring system which predicts all - intra-abdominal collection, leak, reoperation and mortality. All four MRPMs had a similar and fair accuracy to predict mortality, however due to geographic and demographic diversity and inherent weaknesses of exiting MRPMs, quest for development of an ideal model should continue. Copyright © 2015 Surgical Associates Ltd. Published by Elsevier Ltd. All rights reserved.

A new metric of inclusive fitness predicts the human mortality profile.

PubMed

Newman, Saul J; Easteal, Simon

2015-01-01

Biological species have evolved characteristic patterns of age-specific mortality across their life spans. If these mortality profiles are shaped by natural selection they should reflect underlying variation in the fitness effect of mortality with age. Direct fitness models, however, do not accurately predict the mortality profiles of many species. For several species, including humans, mortality rates vary considerably before and after reproductive ages, during life-stages when no variation in direct fitness is possible. Variation in mortality rates at these ages may reflect indirect effects of natural selection acting through kin. To test this possibility we developed a new two-variable measure of inclusive fitness, which we term the extended genomic output or EGO. Using EGO, we estimate the inclusive fitness effect of mortality at different ages in a small hunter-gatherer population with a typical human mortality profile. EGO in this population predicts 90% of the variation in age-specific mortality. This result represents the first empirical measurement of inclusive fitness of a trait in any species. It shows that the pattern of human survival can largely be explained by variation in the inclusive fitness cost of mortality at different ages. More generally, our approach can be used to estimate the inclusive fitness of any trait or genotype from population data on birth dates and relatedness.

Single non-invasive model to diagnose non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH).

PubMed

Otgonsuren, Munkhzul; Estep, Michael J; Hossain, Nayeem; Younossi, Elena; Frost, Spencer; Henry, Linda; Hunt, Sharon; Fang, Yun; Goodman, Zachary; Younossi, Zobair M

2014-12-01

Non-alcoholic steatohepatitis (NASH) is the progressive form of non-alcoholic fatty liver disease (NAFLD). A liver biopsy is considered the "gold standard" for diagnosing/staging NASH. Identification of NAFLD/NASH using non-invasive tools is important for intervention. The study aims were to: develop/validate the predictive performance of a non-invasive model (index of NASH [ION]); assess the performance of a recognized non-invasive model (fatty liver index [FLI]) compared with ION for NAFLD diagnosis; determine which non-invasive model (FLI, ION, or NAFLD fibrosis score [NFS]) performed best in predicting age-adjusted mortality. From the National Health and Nutrition Examination Survey III database, anthropometric, clinical, ultrasound, laboratory, and mortality data were obtained (n = 4458; n = 861 [19.3%] NAFLD by ultrasound) and used to develop the ION model, and then to compare the ION and FLI models for NAFLD diagnosis. For validation and diagnosis of NASH, liver biopsy data were used (n = 152). Age-adjusted Cox proportional hazard modeling estimated the association among the three non-invasive tests (FLI, ION, and NFS) and mortality. FLI's threshold score > 60 and ION's threshold score > 22 had similar specificity (FLI = 80% vs ION = 82%) for NAFLD diagnosis; FLI < 30 (80% sensitivity) and ION < 11 (81% sensitivity) excluded NAFLD. An ION score > 50 predicted histological NASH (92% specificity); the FLI model did not predict NASH or mortality. The ION model was best in predicting cardiovascular/diabetes-related mortality; NFS predicted overall or diabetes-related mortality. The ION model was superior in predicting NASH and mortality compared with the FLI model. Studies are needed to validate ION. © 2014 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

Evaluation of the DAVROS (Development And Validation of Risk-adjusted Outcomes for Systems of emergency care) risk-adjustment model as a quality indicator for healthcare

PubMed Central

Wilson, Richard; Goodacre, Steve W; Klingbajl, Marcin; Kelly, Anne-Maree; Rainer, Tim; Coats, Tim; Holloway, Vikki; Townend, Will; Crane, Steve

2014-01-01

Background and objective Risk-adjusted mortality rates can be used as a quality indicator if it is assumed that the discrepancy between predicted and actual mortality can be attributed to the quality of healthcare (ie, the model has attributional validity). The Development And Validation of Risk-adjusted Outcomes for Systems of emergency care (DAVROS) model predicts 7-day mortality in emergency medical admissions. We aimed to test this assumption by evaluating the attributional validity of the DAVROS risk-adjustment model. Methods We selected cases that had the greatest discrepancy between observed mortality and predicted probability of mortality from seven hospitals involved in validation of the DAVROS risk-adjustment model. Reviewers at each hospital assessed hospital records to determine whether the discrepancy between predicted and actual mortality could be explained by the healthcare provided. Results We received 232/280 (83%) completed review forms relating to 179 unexpected deaths and 53 unexpected survivors. The healthcare system was judged to have potentially contributed to 10/179 (8%) of the unexpected deaths and 26/53 (49%) of the unexpected survivors. Failure of the model to appropriately predict risk was judged to be responsible for 135/179 (75%) of the unexpected deaths and 2/53 (4%) of the unexpected survivors. Some 10/53 (19%) of the unexpected survivors died within a few months of the 7-day period of model prediction. Conclusions We found little evidence that deaths occurring in patients with a low predicted mortality from risk-adjustment could be attributed to the quality of healthcare provided. PMID:23605036

Mortality Prediction Using Acute Physiology and Chronic Health Evaluation II and Acute Physiology and Chronic Health Evaluation IV Scoring Systems: Is There a Difference?

PubMed Central

Venkataraman, Ramesh; Gopichandran, Vijayaprasad; Ranganathan, Lakshmi; Rajagopal, Senthilkumar; Abraham, Babu K; Ramakrishnan, Nagarajan

2018-01-01

Background: Mortality prediction in the Intensive Care Unit (ICU) setting is complex, and there are several scoring systems utilized for this process. The Acute Physiology and Chronic Health Evaluation (APACHE) II has been the most widely used scoring system; although, the more recent APACHE IV is considered an updated and advanced prediction model. However, these two systems may not give similar mortality predictions. Objectives: The aim of this study is to compare the mortality prediction ability of APACHE II and APACHE IV scoring systems among patients admitted to a tertiary care ICU. Methods: In this prospective longitudinal observational study, APACHE II and APACHE IV scores of ICU patients were computed using an online calculator. The outcome of the ICU admissions for all the patients was collected as discharged or deceased. The data were analyzed to compare the discrimination and calibration of the mortality prediction ability of the two scores. Results: Out of the 1670 patients' data analyzed, the area under the receiver operating characteristic of APACHE II score was 0.906 (95% confidence interval [CI] – 0.890–0.992), and APACHE IV score was 0.881 (95% CI – 0.862–0.890). The mean predicted mortality rate of the study population as given by the APACHE II scoring system was 44.8 ± 26.7 and as given by APACHE IV scoring system was 29.1 ± 28.5. The observed mortality rate was 22.4%. Conclusions: The APACHE II and IV scoring systems have comparable discrimination ability, but the calibration of APACHE IV seems to be better than that of APACHE II. There is a need to recalibrate the scales with weights derived from the Indian population. PMID:29910542

Mortality Prediction Using Acute Physiology and Chronic Health Evaluation II and Acute Physiology and Chronic Health Evaluation IV Scoring Systems: Is There a Difference?

PubMed

Venkataraman, Ramesh; Gopichandran, Vijayaprasad; Ranganathan, Lakshmi; Rajagopal, Senthilkumar; Abraham, Babu K; Ramakrishnan, Nagarajan

2018-05-01

Mortality prediction in the Intensive Care Unit (ICU) setting is complex, and there are several scoring systems utilized for this process. The Acute Physiology and Chronic Health Evaluation (APACHE) II has been the most widely used scoring system; although, the more recent APACHE IV is considered an updated and advanced prediction model. However, these two systems may not give similar mortality predictions. The aim of this study is to compare the mortality prediction ability of APACHE II and APACHE IV scoring systems among patients admitted to a tertiary care ICU. In this prospective longitudinal observational study, APACHE II and APACHE IV scores of ICU patients were computed using an online calculator. The outcome of the ICU admissions for all the patients was collected as discharged or deceased. The data were analyzed to compare the discrimination and calibration of the mortality prediction ability of the two scores. Out of the 1670 patients' data analyzed, the area under the receiver operating characteristic of APACHE II score was 0.906 (95% confidence interval [CI] - 0.890-0.992), and APACHE IV score was 0.881 (95% CI - 0.862-0.890). The mean predicted mortality rate of the study population as given by the APACHE II scoring system was 44.8 ± 26.7 and as given by APACHE IV scoring system was 29.1 ± 28.5. The observed mortality rate was 22.4%. The APACHE II and IV scoring systems have comparable discrimination ability, but the calibration of APACHE IV seems to be better than that of APACHE II. There is a need to recalibrate the scales with weights derived from the Indian population.

Development and validation of immune dysfunction score to predict 28-day mortality of sepsis patients

PubMed Central

Fang, Wen-Feng; Douglas, Ivor S.; Chen, Yu-Mu; Lin, Chiung-Yu; Kao, Hsu-Ching; Fang, Ying-Tang; Huang, Chi-Han; Chang, Ya-Ting; Huang, Kuo-Tung; Wang, Yi-His; Wang, Chin-Chou

2017-01-01

Background Sepsis-induced immune dysfunction ranging from cytokines storm to immunoparalysis impacts outcomes. Monitoring immune dysfunction enables better risk stratification and mortality prediction and is mandatory before widely application of immunoadjuvant therapies. We aimed to develop and validate a scoring system according to patients’ immune dysfunction status for 28-day mortality prediction. Methods A prospective observational study from a cohort of adult sepsis patients admitted to ICU between August 2013 and June 2016 at Kaohsiung Chang Gung Memorial Hospital in Taiwan. We evaluated immune dysfunction status through measurement of baseline plasma Cytokine levels, Monocyte human leukocyte-DR expression by flow cytometry, and stimulated immune response using post LPS stimulated cytokine elevation ratio. An immune dysfunction score was created for 28-day mortality prediction and was validated. Results A total of 151 patients were enrolled. Data of the first consecutive 106 septic patients comprised the training cohort, and of other 45 patients comprised the validation cohort. Among the 106 patients, 21 died and 85 were still alive on day 28 after ICU admission. (mortality rate, 19.8%). Independent predictive factors revealed via multivariate logistic regression analysis included segmented neutrophil-to-monocyte ratio, granulocyte-colony stimulating factor, interleukin-10, and monocyte human leukocyte antigen-antigen D–related levels, all of which were selected to construct the score, which predicted 28-day mortality with area under the curve of 0.853 and 0.789 in the training and validation cohorts, respectively. Conclusions The immune dysfunction scoring system developed here included plasma granulocyte-colony stimulating factor level, interleukin-10 level, serum segmented neutrophil-to-monocyte ratio, and monocyte human leukocyte antigen-antigen D–related expression appears valid and reproducible for predicting 28-day mortality. PMID:29073262

Comparison of three scoring systems for risk stratification in elderly patients wıth acute upper gastrointestinal bleeding.

PubMed

Kalkan, Çağdaş; Soykan, Irfan; Karakaya, Fatih; Tüzün, Ali; Gençtürk, Zeynep Bıyıklı

2017-04-01

Acute gastrointestinal bleeding is a potentially life-threatening condition that requires rapid assessment and dynamic management. Several scoring systems are used to predict mortality and rebleeding in such cases. The aim of the present study was to compare three scoring systems for predicting short-term mortality, rebleeding, duration of hospitalization and the need for blood transfusion in elderly patients with upper gastrointestinal bleeding. The present study included 335 elderly patients with upper gastrointestinal bleeding. Pre- and post-endoscopic Rockall, Glasgow-Blatchford and AIMS65 scores were calculated. The ability of these scores to predict rebleeding, mortality, duration of hospitalization and the need for blood transfusion was determined. Pre- (4.5) and post-endoscopic (7.5) Rockall scores were superior to the Glasgow-Blatchford (12.5) score for predicting mortality (P = 0.006 and P = 0.015). Likewise, pre- (4.5) and post-endoscopic Rockall scores were superior to the respective Glasgow-Blatchford scores for predicting rebleeding (P = 0.013 and P = 0.03). There was an association between duration of hospitalization and mortality; as the duration of hospitalization increased the mortality rate increased. In all, 94% of patients hospitalized for a mean of 5 days were alive versus 56.1% of those hospitalized for 20 days, and 20.2% of those hospitalized for 40 days. In elderly patients with upper gastrointestinal bleeding, the Rockall score is clinically more useful for predicting mortality and rebleeding than the Glasgow-Blatchford and AIMS65 scores; however, for predicting duration of hospitalization and the need for blood transfusion, the Glasgow-Blatchford score is superior to the Rockall and AIMS65 scores. Geriatr Gerontol Int 2017; 17: 575-583. © 2016 Japan Geriatrics Society.

Glasgow Coma Scale score, mortality, and functional outcome in head-injured patients.

PubMed

Udekwu, Pascal; Kromhout-Schiro, Sharon; Vaslef, Steven; Baker, Christopher; Oller, Dale

2004-05-01

Preresuscitation Glasgow Coma Scale (P-GCS) score is frequently obtained in injured patients and incorporated into mortality prediction. Data on functional outcome in head injury is sparse. A large group of patients with head injuries was analyzed to assess relationships between P-GCS score, mortality, and functional outcome as measured by the Functional Independence Measure (FIM). Records for patients with International Classification of Diseases, Ninth Revision diagnosis codes indicating head injury in a statewide trauma registry between 1994 and 2002 were selected. P-GCS score, mortality, and FIM score at hospital discharge were integrated and analyzed. Of 138,750 patients, 22,924 patients were used for the mortality study and 7,150 patients for the FIM study. A good correlation exists between P-GCS score and FIM, as determined by rank correlation coefficients, whereas mortality falls steeply between a P-GCS score of 3 and a P-GCS score of 7 followed by a shallow fall. Although P-GCS score is related to mortality in head-injured patients, its relationship is nonlinear, which casts doubt on its use as a continuous measure or an equivalent set of categorical measures incorporated into outcome prediction models. The average FIM scores indicate substantial likelihood of good outcomes in survivors with low P-GCS scores, further complicating the use of the P-GCS score in the prediction of poor outcome at the time of initial patient evaluation. Although the P-GCS score is related to functional outcome as measured by the FIM score and mortality in head injury, current mortality prediction models may need to be modified to account for the nonlinear relationship between P-GCS score and mortality. The P-GCS score is not a good clinical tool for outcome prediction in individual head-injured patients, given the variability in mortality rates and functional outcomes at all scores.

Interpretable Topic Features for Post-ICU Mortality Prediction.

PubMed

Luo, Yen-Fu; Rumshisky, Anna

2016-01-01

Electronic health records provide valuable resources for understanding the correlation between various diseases and mortality. The analysis of post-discharge mortality is critical for healthcare professionals to follow up potential causes of death after a patient is discharged from the hospital and give prompt treatment. Moreover, it may reduce the cost derived from readmissions and improve the quality of healthcare. Our work focused on post-discharge ICU mortality prediction. In addition to features derived from physiological measurements, we incorporated ICD-9-CM hierarchy into Bayesian topic model learning and extracted topic features from medical notes. We achieved highest AUCs of 0.835 and 0.829 for 30-day and 6-month post-discharge mortality prediction using baseline and topic proportions derived from Labeled-LDA. Moreover, our work emphasized the interpretability of topic features derived from topic model which may facilitates the understanding and investigation of the complexity between mortality and diseases.

Optimism and death: predicting the course and consequences of depression trajectories in response to heart attack.

PubMed

Galatzer-Levy, Isaac R; Bonanno, George A

2014-12-01

The course of depression in relation to myocardial infarction (MI), commonly known as heart attack, and the consequences for mortality are not well characterized. Further, optimism may predict both the effects of MI on depression as well as mortality secondary to MI. In the current study, we utilized a large population-based prospective sample of older adults (N=2,147) to identify heterogeneous trajectories of depression from 6 years prior to their first-reported MI to 4 years after. Findings indicated that individuals were at significantly increased risk for mortality when depression emerged after their first-reported MI, compared with resilient individuals who had no significant post-MI elevation in depression symptomatology. Individuals with chronic depression and those demonstrating pre-event depression followed by recovery after MI were not at increased risk. Further, optimism, measured before MI, prospectively differentiated all depressed individuals from participants who were resilient. © The Author(s) 2014.

Triglyceride-to-high-density-lipoprotein-cholesterol ratio is an index of heart disease mortality and of incidence of type 2 diabetes mellitus in men.

PubMed

Vega, Gloria Lena; Barlow, Carolyn E; Grundy, Scott M; Leonard, David; DeFina, Laura F

2014-02-01

High triglyceride (TG) and low high-density lipoprotein cholesterol (HDL-C) impart risk for heart disease. This study examines the relationships of TG/HDL-C ratio to mortality from all causes, coronary heart disease (CHD), or cardiovascular disease (CVD). Survival analysis was done in 39,447 men grouped by TG/HDL-C ratio cut point of 3.5 and for metabolic syndrome. National Death Index International Classification of Diseases (ICD-9 and ICD-10) codes were used for CVD and CHD deaths occurring from 1970 to 2008. Incidence of type 2 diabetes mellitus (DM) according to ratio was estimated in 22,215 men. Triglyceride/HDL-C ratio and cross-product of TG and fasting blood glucose (TyG index) were used in analysis. Men were followed up for 581,194 person-years. Triglyceride/HDL-C ratio predicted CHD, CVD, and all-cause mortality after adjustment for established risk factors and non-HDL-C. Mortality rates were higher in individuals with a high ratio than in those with a low ratio. Fifty-five percent of men had metabolic syndrome that was also predictive of CHD, CVD, and all-cause mortality. Annual incidence of DM was 2 times higher in men with high TG/HDL-C ratio than in those with a low ratio. Individuals with high TG/HDL-C ratio had a higher incidence of DM than those with a low ratio. The TyG index was not equally predictive of causes of mortality to TG/HDL-C, but both were equally predictive of diabetes incidence. Triglyceride/HDL-C ratio predicts CHD and CVD mortality as well as or better than do metabolic syndrome in men. Also, a high ratio predisposes to DM. The TyG index does not predict CHD, CVD, or all-cause mortality equally well, but like TG/HDL-C ratio, it predicts DM incidence.

Can information on functional and cognitive status improve short-term mortality risk prediction among community-dwelling older people? A cohort study using a UK primary care database

PubMed Central

Sultana, Janet; Fontana, Andrea; Giorgianni, Francesco; Basile, Giorgio; Patorno, Elisabetta; Pilotto, Alberto; Molokhia, Mariam; Stewart, Robert; Sturkenboom, Miriam; Trifirò, Gianluca

2018-01-01

Background Functional and cognitive domains have rarely been evaluated for their prognostic value in general practice databases. The aim of this study was to identify functional and cognitive domains in The Health Improvement Network (THIN) and to evaluate their additional value for the prediction of 1-month and 1-year mortality in elderly people. Materials and methods A cohort study was conducted using a UK nationwide general practitioner database. A total of 1,193,268 patients aged 65 years or older, of whom 15,300 had dementia, were identified from 2000 to 2012. Information on mobility, dressing and accommodation was recorded frequently enough to be analyzed further in THIN. Cognition data could not be used due to very poor recording of data in THIN. One-year and 1-month mortality was predicted using logistic models containing variables such as age, sex, disease score and functionality status. Results A significant but moderate improvement in 1-year and 1-month mortality prediction in elderly people was observed by adding accommodation to the variables age, sex and disease score, as the c-statistic (95% confidence interval [CI]) increased from 0.71 (0.70–0.72) to 0.76 (0.75–0.77) and 0.73 (0.71–0.75) to 0.79 (0.77–0.80), respectively. A less notable improvement in the prediction of 1-year and 1-month mortality was observed in people with dementia. Conclusion Functional domains moderately improved the accuracy of a model including age, sex and comorbidities in predicting 1-year and 1-month mortality risk among community-dwelling older people, but they were much less able to predict mortality in people with dementia. Cognition could not be explored as a predictor of mortality due to insufficient data being recorded. PMID:29296099

Speed of Heart Rate Recovery in Response to Orthostatic Challenge.

PubMed

McCrory, Cathal; Berkman, Lisa F; Nolan, Hugh; O'Leary, Neil; Foley, Margaret; Kenny, Rose Anne

2016-08-19

Speed of heart rate recovery (HRR) may serve as an important biomarker of aging and mortality. To examine whether the speed of HRR after an orthostatic maneuver (ie, active stand from supine position) predicts mortality. A longitudinal cohort study involving a nationally representative sample of community-dwelling older individuals aged ≥50 years. A total of 4475 participants completed an active stand at baseline as part of a detailed clinic-based cardiovascular assessment. Beat-to-beat heart rate and blood pressure responses to standing were measured during a 2-minute window using a finometer and binned in 10-s intervals. We modeled HRR to the stand by age group, cardiovascular disease burden, and mortality status using a random effects model. Mortality status during a mean follow-up duration of 4.3 years served as the primary end point (n=138). Speed of HRR in the immediate 20 s after standing was a strong predictor of mortality. A 1-bpm slower HRR between 10 and 20 s after standing increased the hazard of mortality by 6% controlling for established risk factors. A clear dose-response relationship was evident. Sixty-nine participants in the slowest HRR quartile died during the observation period compared with 14 participants in the fastest HRR quartile. Participants in the slowest recovery quartile were 2.3× more likely to die compared with those in the fastest recovery quartile. Speed of orthostatic HRR predicts mortality and may aid clinical decision making. Attenuated orthostatic HRR may reflect dysregulation of the parasympathetic branch of the autonomic nervous system. © 2016 American Heart Association, Inc.

Application of a global reference for fetal-weight and birthweight percentiles in predicting infant mortality.

PubMed

Ding, G; Tian, Y; Zhang, Y; Pang, Y; Zhang, J S; Zhang, J

2013-12-01

To determine whether the recently published A global reference for fetal-weight and birthweight percentiles (Global Reference) improves small- (SGA), appropriate- (AGA), and large-for-gestational-age (LGA) definitions in predicting infant mortality. Population-based cohort study. The US Linked Livebirth and Infant Death records between 1995 and 2004. Singleton births with birthweight >500 g born at 24-41 weeks of gestation. We compared infant mortality rates of SGA, AGA, and LGA infants classified by three different references: the Global Reference; a commonly used birthweight reference; and Hadlock's ultrasound reference. Infant mortality rates. Among 33 997 719 eligible liveborn singleton births, 25% of preterm and 9% of term infants were classified differently for SGA, AGA, and LGA by the Global Reference and the birthweight reference. The Global Reference indicated higher mortality rates in preterm SGA and preterm LGA infants than the birthweight reference. The mortality rate was considerably higher in infants classified as preterm SGA by the Global Reference but not by the birthweight reference, compared with the corresponding infants classified by the birthweight reference but not by the Global Reference (105.7 versus 12.9 per 1000, RR 8.17, 95% CI 7.38-9.06). Yet, the differences in mortality rates were much smaller in term infants than in preterm infants. Black infants had a particularly higher mortality rate than other races in AGA and LGA preterm and term infants. In respect to the commonly used birthweight reference, the Global Reference increases the identification of infant deaths by improved classification of abnormal newborn size at birth, and these advantages were more obvious in preterm than in term infants. © 2013 RCOG.

Status epilepticus severity score (STESS): A useful tool to predict outcome of status epilepticus.

PubMed

Goyal, Manoj Kumar; Chakravarthi, Sudheer; Modi, Manish; Bhalla, Ashish; Lal, Vivek

2015-12-01

The treatment protocols for status epilepticus (SE) range from small doses of intravenous benzodiazepines to induction of coma. The pros and cons of more aggressive treatment regimen remain debatable. The importance of an index need not be overemphasized which can predict outcome of SE and guide the intensity of treatment. We tried to evaluate utility of one such index Status epilepticus severity score (STESS). 44 consecutive patients of SE were enrolled in the study. STESS results were compared with various outcome measures: (a) mortality, (b) final neurological outcome at discharge as defined by functional independence measure (FIM) (good outcome: FIM score 5-7; bad outcome: FIM score 1-4), (c) control of SE within 1h of start of treatment and (d) need for coma induction. A higher STESS score correlated significantly with poor neurological outcome at discharge (p=0.0001), need for coma induction (p=0.0001) and lack of response to treatment within 1h (p=0.001). A STESS of <3 was found to have a negative predictive value of 96.9% for mortality, 96.7% for poor neurological outcome at discharge and 96.7% for need of coma induction, while a STESS of <2 had negative predictive value of 100% for mortality, coma induction and poor neurological outcome at discharge. STESS can reliably predict the outcome of status epilepticus. Further studies on STESS based treatment approach may help in designing better therapeutic regimens for SE. Copyright © 2015 Elsevier B.V. All rights reserved.

Prediction of postoperative outcome after hepatectomy with a new bedside test for maximal liver function capacity.

PubMed

Stockmann, Martin; Lock, Johan F; Riecke, Björn; Heyne, Karsten; Martus, Peter; Fricke, Michael; Lehmann, Sina; Niehues, Stefan M; Schwabe, Michael; Lemke, Arne-Jörn; Neuhaus, Peter

2009-07-01

To validate the LiMAx test, a new bedside test for the determination of maximal liver function capacity based on C-methacetin kinetics. To investigate the diagnostic performance of different liver function tests and scores including the LiMAx test for the prediction of postoperative outcome after hepatectomy. Liver failure is a major cause of mortality after hepatectomy. Preoperative prediction of residual liver function has been limited so far. Sixty-four patients undergoing hepatectomy were analyzed in a prospective observational study. Volumetric analysis of the liver was carried out using preoperative computed tomography and intraoperative measurements. Perioperative factors associated with morbidity and mortality were analyzed. Cutoff values of the LiMAx test were evaluated by receiver operating characteristic. Residual LiMAx demonstrated an excellent linear correlation with residual liver volume (r = 0.94, P < 0.001) after hepatectomy. The multivariate analysis revealed LiMAx on postoperative day 1 as the only predictor of liver failure (P = 0.003) and mortality (P = 0.004). AUROC for the prediction of liver failure and liver failure related death by the LiMAx test was both 0.99. Preoperative volume/function analysis combining CT volumetry and LiMAx allowed an accurate calculation of the remnant liver function capacity prior to surgery (r = 0.85, P < 0.001). Residual liver function is the major factor influencing the outcome of patients after hepatectomy and can be predicted preoperatively by a combination of LiMAx and CT volumetry.

PREDICT: a diagnostic accuracy study of a tool for predicting mortality within one year: who should have an advance healthcare directive?

PubMed

Richardson, Philip; Greenslade, Jaimi; Shanmugathasan, Sulochana; Doucet, Katherine; Widdicombe, Neil; Chu, Kevin; Brown, Anthony

2015-01-01

CARING is a screening tool developed to identify patients who have a high likelihood of death in 1 year. This study sought to validate a modified CARING tool (termed PREDICT) using a population of patients presenting to the Emergency Department. In total, 1000 patients aged over 55 years who were admitted to hospital via the Emergency Department between January and June 2009 were eligible for inclusion in this study. Data on the six prognostic indicators comprising PREDICT were obtained retrospectively from patient records. One-year mortality data were obtained from the State Death Registry. Weights were applied to each PREDICT criterion, and its final score ranged from 0 to 44. Receiver operator characteristic analyses and diagnostic accuracy statistics were used to assess the accuracy of PREDICT in identifying 1-year mortality. The sample comprised 976 patients with a median (interquartile range) age of 71 years (62-81 years) and a 1-year mortality of 23.4%. In total, 50% had ≥1 PREDICT criteria with a 1-year mortality of 40.4%. Receiver operator characteristic analysis gave an area under the curve of 0.86 (95% confidence interval: 0.83-0.89). Using a cut-off of 13 points, PREDICT had a 95.3% (95% confidence interval: 93.6-96.6) specificity and 53.9% (95% confidence interval: 47.5-60.3) sensitivity for predicting 1-year mortality. PREDICT was simpler than the CARING criteria and identified 158 patients per 1000 admitted who could benefit from advance care planning. PREDICT was successfully applied to the Australian healthcare system with findings similar to the original CARING study conducted in the United States. This tool could improve end-of-life care by identifying who should have advance care planning or an advance healthcare directive. © The Author(s) 2014.

Functional status and mortality prediction in community-acquired pneumonia.

PubMed

Jeon, Kyeongman; Yoo, Hongseok; Jeong, Byeong-Ho; Park, Hye Yun; Koh, Won-Jung; Suh, Gee Young; Guallar, Eliseo

2017-10-01

Poor functional status (FS) has been suggested as a poor prognostic factor in both pneumonia and severe pneumonia in elderly patients. However, it is still unclear whether FS is associated with outcomes and improves survival prediction in community-acquired pneumonia (CAP) in the general population. Data on hospitalized patients with CAP and FS, assessed by the Eastern Cooperative Oncology Group (ECOG) scale were prospectively collected between January 2008 and December 2012. The independent association of FS with 30-day mortality in CAP patients was evaluated using multivariable logistic regression. Improvement in mortality prediction when FS was added to the CRB-65 (confusion, respiratory rate, blood pressure and age 65) score was evaluated for discrimination, reclassification and calibration. The 30-day mortality of study participants (n = 1526) was 10%. Mortality significantly increased with higher ECOG score (P for trend <0.001). In multivariable analysis, ECOG ≥3 was strongly associated with 30-day mortality (adjusted OR: 5.70; 95% CI: 3.82-8.50). Adding ECOG ≥3 significantly improved the discriminatory power of CRB-65. Reclassification indices also confirmed the improvement in discrimination ability when FS was combined with the CRB-65, with a categorized net reclassification index (NRI) of 0.561 (0.437-0.686), a continuous NRI of 0.858 (0.696-1.019) and a relative integrated discrimination improvement in the discrimination slope of 139.8 % (110.8-154.6). FS predicted 30-day mortality and improved discrimination and reclassification in consecutive CAP patients. Assessment of premorbid FS should be considered in mortality prediction in patients with CAP. © 2017 Asian Pacific Society of Respirology.

Definition of prepartum hyperketonemia in dairy goats.

PubMed

Doré, V; Dubuc, J; Bélanger, A M; Buczinski, S

2015-07-01

A prospective cohort study was conducted on 1,081 dairy goats from 10 commercial herds in Québec (Canada) to define prepartum hyperketonemia based on optimal blood β-hydroxybutyrate acid threshold values for the early prediction of pregnancy toxemia (PT) and mortality in late-gestation dairy goats. All pregnant goats had blood sampled weekly during the last 5wk of pregnancy. The blood was analyzed directly on the farm for β-hydroxybutyrate acid quantification using a Precision Xtra meter (Abbott Diabetes Care, Saint-Laurent, QC, Canada). Body condition scores on the lumbar region and sternum were noted. Each goat was classified as being at low (n=973) or high risk (n=108) of having PT by producers based on a standardized definition. The optimal threshold for predicting a PT diagnosis or mortality for each week before kidding was determined based on the highest sum of sensitivity and specificity. The association between hyperketonemia and subsequent PT was tested using a multivariable logistic regression model considering hyperketonemia at wk 4 prepartum, litter size, and body condition score at wk 4 prepartum as covariates, and herd and parturition cohort as random effects. The association between mortality and hyperketonemia was also tested using a logistic regression model accounting for the presence or absence of treatment during the last month of pregnancy. The hyperketonemia definition based on PT varied between ≥0.4 and ≥0.9mmol/L during the last 5wk prepartum. Goats affected by hyperketonemia at wk 4 prepartum and with a large litter size (≥3 fetuses) had 2.1 and 40.5 times the odds, respectively, of subsequent PT than other goats. Hyperketonemia definitions based on mortality varied between ≥0.6 and ≥1.4mmol/L during the last 4wk prepartum, and was ≥1.7mmol/L during the first week postpartum. Goats affected by hyperketonemia and treated by producers had 3.4 and 11.8 times the odds, respectively, of subsequent mortality than did other goats. These results showed that prepartum hyperketonemia could be defined in dairy goats using subsequent risks of PT or mortality during the last month of pregnancy. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

PubMed

El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

2015-04-01

This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

Effect of public reporting of surgeons' outcomes on patient selection, "gaming," and mortality in colorectal cancer surgery in England: population based cohort study.

PubMed

Vallance, Abigail E; Fearnhead, Nicola S; Kuryba, Angela; Hill, James; Maxwell-Armstrong, Charles; Braun, Michael; van der Meulen, Jan; Walker, Kate

2018-05-02

To determine the effect of surgeon specific outcome reporting in colorectal cancer surgery on risk averse clinical practice, "gaming" of clinical data, and 90 day postoperative mortality. National cohort study. English National Health Service hospital trusts. 111 431 patients diagnosed as having colorectal cancer from 1 April 2011 to 31 March 2015 included in the National Bowel Cancer Audit. Public reporting of surgeon specific 90 day mortality in elective colorectal cancer surgery in England introduced in June 2013. Proportion of patients with colorectal cancer who had an elective major resection, predicted 90 day mortality based on characteristics of patients and tumours, and observed 90 day mortality adjusted for differences in characteristics of patients and tumours, comparing patients who had surgery between April 2011 and June 2013 and between July 2013 and March 2015. The proportion of patients with colorectal cancer undergoing major resection did not change after the introduction of surgeon specific public outcome reporting (39 792/62 854 (63.3%) before versus 30 706/48 577 (63.2%) after; P=0.8). The proportion of these major resections categorised as elective or scheduled also did not change (33 638/39 792 (84.5%) before versus 25 905/30 706 (84.4%) after; P=0.5). The predicted 90 day mortality remained the same (2.7% v 2.7%; P=0.3), but the observed 90 day mortality fell (952/33 638 (2.8%) v 552/25 905 (2.1%)). Change point analysis showed that this reduction was over and above the existing downward trend in mortality before the introduction of public outcome reporting (P=0.03). This study did not find evidence that the introduction of public reporting of surgeon specific 90 day postoperative mortality in elective colorectal cancer surgery has led to risk averse clinical practice behaviour or "gaming" of data. However, its introduction coincided with a significant reduction in 90 day mortality. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Morbidity and mortality after emergency lower extremity embolectomy.

PubMed

Casillas-Berumen, Sergio; Sadri, Lili; Farber, Alik; Eslami, Mohammad H; Kalish, Jeffrey A; Rybin, Denis; Doros, Gheorghe; Siracuse, Jeffrey J

2017-03-01

Emergency lower extremity embolectomy is a common vascular surgical procedure that has poorly defined outcomes. Our goal was to define the perioperative morbidity for emergency embolectomy and develop a risk prediction model for perioperative mortality. The American College of Surgeons National Surgical Quality Improvement database was queried to identify patients undergoing emergency unilateral and lower extremity embolectomy. Patients with previous critical limb ischemia, bilateral embolectomy, nonemergency indication, and those undergoing concurrent bypass were excluded. Patient characteristics and postoperative morbidity and mortality were analyzed. Multivariate analysis for predictors of mortality was performed, and from this, a risk prediction model was developed to identify preoperative predictors of mortality. There were 1749 patients (47.9% male) who met the inclusion criteria. The average age was 68.2 ± 14.8 years. Iliofemoral-popliteal embolectomy was performed in 1231 patients (70.4%), popliteal-tibioperoneal embolectomy in 303 (17.3%), and at both levels in 215 (12.3%). Fasciotomies were performed concurrently with embolectomy in 308 patients (17.6%). The 30-day postoperative mortality was 13.9%. Postoperative complications included myocardial infarction or cardiac arrest (4.7%), pulmonary complications (16.0%), and wound complications (8.2%). The rate of return to the operating room ≤30 days was 25.7%. Hospital length of stay was 9.8 ± 11.5 days, and the 30-day readmission rate was 16.3%. A perioperative mortality risk prediction model based on factors identified in multivariate analysis included age >70 years, male gender, functional dependence, history of chronic obstructive pulmonary disease, congestive heart failure, recent myocardial infarction/angina, chronic renal insufficiency, and steroid use. The model showed good discrimination (C = 0.769; 95% confidence interval, 0733-0.806) and calibrated well. Emergency lower extremity embolectomy has high morbidity, mortality, and resource utilization. These data provide a benchmark for this complex patient population and may assist in risk stratifying patients, allowing for improved informed consent and goals of care at the time of presentation. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

Work-based predictors of mortality: a 20-year follow-up of healthy employees.

PubMed

Shirom, Arie; Toker, Sharon; Alkaly, Yasmin; Jacobson, Orit; Balicer, Ran

2011-05-01

This study investigated the effects of the Job-Demand-Control-Support (JDC-S) model's components, workload, control, peer and supervisor social support, on the risk of all-cause mortality. Also examined was the expectation that the above work-based components interact in predicting all-cause mortality. The study's hypotheses were tested after controlling for physiological variables and health behaviors known to be risk factors for mortality. The design used was prospective. Baseline data were obtained from healthy employees (N = 820) who underwent periodic health examinations in 1988. Follow-up data on all-cause mortality were obtained from the participants' computerized medical file, kept by their HMO, in 2008. The baseline data covered socioeconomic, behavioral, and biological risk factors in addition to the components of the JDC-S model. During the period of follow-up, 53 deaths were recorded. Data were analyzed using Cox regressions. Only one main effect was found: the risk of mortality was significantly lower for those reporting high levels of peer social support. The study found two significant interactions. Higher levels of control reduced the risk of mortality for the men and increased it for the women. The main effect of peer social support on mortality risk was significantly higher for those whose baseline age ranged from 38 to 43 but not for the older than 43 or the younger than 38 participants. Peer social support is a protective factor, reducing the risk of mortality, while perceived control reduces the risk of mortality among men but increases it among women. (c) 2011 APA, all rights reserved.

Mortality Risk After Transcatheter Aortic Valve Implantation: Analysis of the Predictive Accuracy of the Transcatheter Valve Therapy Registry Risk Assessment Model.

PubMed

Codner, Pablo; Malick, Waqas; Kouz, Remi; Patel, Amisha; Chen, Cheng-Han; Terre, Juan; Landes, Uri; Vahl, Torsten Peter; George, Isaac; Nazif, Tamim; Kirtane, Ajay J; Khalique, Omar K; Hahn, Rebecca T; Leon, Martin B; Kodali, Susheel

2018-05-08

Risk assessment tools currently used to predict mortality in transcatheter aortic valve implantation (TAVI) were designed for patients undergoing cardiac surgery. We aim to assess the accuracy of the TAVI dedicated American College of Cardiology / Transcatheter Valve Therapies (ACC/TVT) risk score in predicting mortality outcomes. Consecutive patients (n=1038) undergoing TAVI at a single institution from 2014 to 2016 were included. The ACC/TVT registry mortality risk score, the Society of Thoracic Surgeons - Patient Reported Outcomes (STS-PROM) score and the EuroSCORE II were calculated for all patients. In hospital and 30-day all-cause mortality rates were 1.3% and 2.9%, respectively. The ACC/TVT risk stratification tool scored higher for patients who died in-hospital than in those who survived the index hospitalization (6.4 ± 4.6 vs. 3.5 ± 1.6, p = 0.03; respectively). The ACC/TVT score showed a high level of discrimination, C-index for in-hospital mortality 0.74, 95% CI [0.59 - 0.88]. There were no significant differences between the performance of the ACC/TVT registry risk score, the EuroSCORE II and the STS-PROM for in hospital and 30-day mortality rates. The ACC/TVT registry risk model is a dedicated tool to aid in the prediction of in-hospital mortality risk after TAVI.

Ratio of Systolic Blood Pressure to Right Atrial Pressure, a Novel Marker to Predict Morbidity and Mortality in Acute Systolic Heart Failure.

PubMed

Omar, Hesham R; Charnigo, Richard; Guglin, Maya

2017-04-01

Congestion is the main contributor to heart failure (HF) morbidity and mortality. We assessed the combined role of congestion and decreased forward flow in predicting morbidity and mortality in acute systolic HF. The Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness trial data set was used to determine if the ratio of simultaneously measured systolic blood pressure (SBP)/right atrial pressure (RAP) on admission predicted HF rehospitalization and 6-month mortality. One hundred ninety-five patients (mean age 56.5 years, 75% men) who received pulmonary artery catheterization were studied. The RAP, SBP, and SBP/RAP had an area under the curve (AUC) of 0.593 (p = 0.0205), 0.585 (p = 0.0359), and 0.621 (p = 0.0026), respectively, in predicting HF rehospitalization. The SBP/RAP was a superior marker of HF rehospitalization compared with RAP alone (difference in AUC 0.0289, p = 0.0385). The optimal criterion of SBP/RAP <11 provided the highest combined sensitivity (77.1%) and specificity (50.9%) in predicting HF rehospitalization. The SBP/RAP had an AUC 0.622, p = 0.0108, and a cut-off value of SBP/RAP <8 had a sensitivity of 61.9% and specificity 64.1% in predicting mortality. Multivariate analysis showed that an SBP/RAP <11 independently predicted rehospitalization for HF (estimated odds ratio 3.318, 95% confidence interval 1.692 to 6.506, p = 0.0005) and an SBP/RAP <8 independently predicted mortality (estimated hazard ratio 2.025, 95% confidence interval 1.069 to 3.833, p = 0.030). In conclusion, SBP/RAP ratio is a marker that identifies a spectrum of complications after hospitalization of patients with decompensated systolic HF, starting with increased incidence of HF rehospitalization at SBP/RAP <11 to increased mortality with SBP/RAP <8. Copyright © 2017 Elsevier Inc. All rights reserved.

FireStem2D — A two-dimensional heat transfer model for simulating tree stem injury in fires

Treesearch

Efthalia K. Chatziefstratiou; Gil Bohrer; Anthony S. Bova; Ravishankar Subramanian; Renato P.M. Frasson; Amy Scherzer; Bret W. Butler; Matthew B. Dickinson

2013-01-01

FireStem2D, a software tool for predicting tree stem heating and injury in forest fires, is a physically-based, two-dimensional model of stem thermodynamics that results from heating at the bark surface. It builds on an earlier one-dimensional model (FireStem) and provides improved capabilities for predicting fire-induced mortality and injury before a fire occurs by...

Extensions and evaluations of a general quantitative theory of forest structure and dynamics

PubMed Central

Enquist, Brian J.; West, Geoffrey B.; Brown, James H.

2009-01-01

Here, we present the second part of a quantitative theory for the structure and dynamics of forests under demographic and resource steady state. The theory is based on individual-level allometric scaling relations for how trees use resources, fill space, and grow. These scale up to determine emergent properties of diverse forests, including size–frequency distributions, spacing relations, canopy configurations, mortality rates, population dynamics, successional dynamics, and resource flux rates. The theory uniquely makes quantitative predictions for both stand-level scaling exponents and normalizations. We evaluate these predictions by compiling and analyzing macroecological datasets from several tropical forests. The close match between theoretical predictions and data suggests that forests are organized by a set of very general scaling rules. Our mechanistic theory is based on allometric scaling relations, is complementary to “demographic theory,” but is fundamentally different in approach. It provides a quantitative baseline for understanding deviations from predictions due to other factors, including disturbance, variation in branching architecture, asymmetric competition, resource limitation, and other sources of mortality, which are not included in the deliberately simplified theory. The theory should apply to a wide range of forests despite large differences in abiotic environment, species diversity, and taxonomic and functional composition. PMID:19363161

Performance of Quick Sequential (Sepsis Related) and Sequential (Sepsis Related) Organ Failure Assessment to Predict Mortality in Patients with Acute Pyelonephritis Associated with Upper Urinary Tract Calculi.

PubMed

Fukushima, Hiroshi; Kobayashi, Masaki; Kawano, Keizo; Morimoto, Shinji

2018-06-01

The Third International Consensus Definitions for Sepsis and Septic Shock Task Force proposed a new definition of sepsis based on the SOFA (Sequential [Sepsis-related] Organ Failure Assessment) score and introduced a novel scoring system, quickSOFA, to screen patients at high risk for sepsis. However, the clinical usefulness of these systems is unclear. Therefore, we investigated predictive performance for mortality in patients with acute pyelonephritis associated with upper urinary tract calculi. This retrospective study included 141 consecutive patients who were clinically diagnosed with acute pyelonephritis associated with upper urinary tract calculi outside the intensive care unit. We evaluated the performance of the quickSOFA, SOFA and SIRS (systemic inflammatory response syndrome) scores to predict in-hospital mortality and intensive care unit admission using the AUC of the ROC curve, net reclassification, integrated discrimination improvements and decision curve analysis. A total of 11 patients (8%) died in the hospital and 26 (18%) were admitted to the intensive care unit. The AUC of quickSOFA to predict in-hospital mortality and intensive care unit admission was significantly greater than that of SIRS (each p <0.001) and comparable to that of SOFA (p = 0.47 and 0.57, respectively). When incorporated into the baseline model consisting of patient age, gender and the Charlson Comorbidity Index, quickSOFA and SOFA provided a greater change in AUC, and in net classification and integrated discrimination improvements than SIRS for each outcome. Decision curve analyses revealed that the quickSOFA and SOFA incorporated models showed a superior net benefit compared to the SIRS incorporated model for most examined probabilities of the 2 outcomes. The in-hospital mortality rate of patients with a quickSOFA score of 2 or greater and a SOFA score of 7 or greater, which were the optimal cutoffs determined by the Youden index, was 18% and 28%, respectively. SOFA and quickSOFA are more clinically useful scoring systems than SIRS to predict mortality in patients with acute pyelonephritis associated with upper urinary tract calculi. Copyright © 2018 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Associations of all-cause mortality with census-based neighbourhood deprivation and population density in Japan: a multilevel survival analysis.

PubMed

Nakaya, Tomoki; Honjo, Kaori; Hanibuchi, Tomoya; Ikeda, Ai; Iso, Hiroyasu; Inoue, Manami; Sawada, Norie; Tsugane, Shoichiro

2014-01-01

Despite evidence that neighbourhood conditions affect residents' health, no prospective studies of the association between neighbourhood socio-demographic factors and all-cause mortality have been conducted in non-Western societies. Thus, we examined the effects of areal deprivation and population density on all-cause mortality in Japan. We employed census and survival data from the Japan Public Health Center-based Prospective Study, Cohort I (n = 37,455), consisting of middle-aged residents (40 to 59 years at the baseline in 1990) living in four public health centre districts. Data spanned between 1990 and 2010. A multilevel parametric proportional-hazard regression model was applied to estimate the hazard ratios (HRs) of all-cause mortality by two census-based areal variables--areal deprivation index and population density--as well as individualistic variables such as socioeconomic status and various risk factors. We found that areal deprivation and population density had moderate associations with all-cause mortality at the neighbourhood level based on the survival data with 21 years of follow-ups. Even when controlling for individualistic socio-economic status and behavioural factors, the HRs of the two areal factors (using quartile categorical variables) significantly predicted mortality. Further, this analysis indicated an interaction effect of the two factors: areal deprivation prominently affects the health of residents in neighbourhoods with high population density. We confirmed that neighbourhood socio-demographic factors are significant predictors of all-cause death in Japanese non-metropolitan settings. Although further study is needed to clarify the cause-effect relationship of this association, the present findings suggest that health promotion policies should consider health disparities between neighbourhoods and possibly direct interventions towards reducing mortality in densely populated and highly deprived neighbourhoods.

Associations of All-Cause Mortality with Census-Based Neighbourhood Deprivation and Population Density in Japan: A Multilevel Survival Analysis

PubMed Central

Nakaya, Tomoki; Honjo, Kaori; Hanibuchi, Tomoya; Ikeda, Ai; Iso, Hiroyasu; Inoue, Manami; Sawada, Norie; Tsugane, Shoichiro

2014-01-01

Background Despite evidence that neighbourhood conditions affect residents' health, no prospective studies of the association between neighbourhood socio-demographic factors and all-cause mortality have been conducted in non-Western societies. Thus, we examined the effects of areal deprivation and population density on all-cause mortality in Japan. Methods We employed census and survival data from the Japan Public Health Center-based Prospective Study, Cohort I (n = 37,455), consisting of middle-aged residents (40 to 59 years at the baseline in 1990) living in four public health centre districts. Data spanned between 1990 and 2010. A multilevel parametric proportional-hazard regression model was applied to estimate the hazard ratios (HRs) of all-cause mortality by two census-based areal variables —areal deprivation index and population density—as well as individualistic variables such as socioeconomic status and various risk factors. Results We found that areal deprivation and population density had moderate associations with all-cause mortality at the neighbourhood level based on the survival data with 21 years of follow-ups. Even when controlling for individualistic socio-economic status and behavioural factors, the HRs of the two areal factors (using quartile categorical variables) significantly predicted mortality. Further, this analysis indicated an interaction effect of the two factors: areal deprivation prominently affects the health of residents in neighbourhoods with high population density. Conclusions We confirmed that neighbourhood socio-demographic factors are significant predictors of all-cause death in Japanese non-metropolitan settings. Although further study is needed to clarify the cause-effect relationship of this association, the present findings suggest that health promotion policies should consider health disparities between neighbourhoods and possibly direct interventions towards reducing mortality in densely populated and highly deprived neighbourhoods. PMID:24905731

Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis.

PubMed

Bos, L D; Schouten, L R; van Vught, L A; Wiewel, M A; Ong, D S Y; Cremer, O; Artigas, A; Martin-Loeches, I; Hoogendijk, A J; van der Poll, T; Horn, J; Juffermans, N; Calfee, C S; Schultz, M J

2017-10-01

We hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality. Consecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality. Two phenotypes were identified in 454 patients, which we named 'uninflamed' (N=218) and 'reactive' (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p<0.001) in the training cohort and 13.6% and 37.5% (p<0.001) in the validation cohort (N=207). The 'reactive phenotype' was independent from confounders associated with intensive care unit mortality (training cohort: OR 1.13, 95% CI 1.04 to 1.23; validation cohort: OR 1.18, 95% CI 1.06 to 1.31). Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

The association between plasma big endothelin-1 levels at admission and long-term outcomes in patients with atrial fibrillation.

PubMed

Wu, Shuang; Yang, Yan-Min; Zhu, Jun; Ren, Jia-Meng; Wang, Juan; Zhang, Han; Shao, Xing-Hui

2018-05-01

The prognostic role of big endothelin-1 (ET-1) in atrial fibrillation (AF) is unclear. We aimed to assess its predictive value in patients with AF. A total of 716 AF patients were enrolled and divided into two groups based on the optimal cut-off value of big ET-1 in predicting all-cause mortality. The primary outcomes were all-cause mortality and major adverse events (MAEs). Cox regression analysis and net reclassification improvement (NRI) analysis were performed to assess the predictive value of big ET-1 on outcomes. With the optimal cut-off value of 0.55 pmol/L, 326 patients were classified into the high big ET-1 levels group. Cardiac dysfunction and left atrial dilation were factors related to high big ET-1 levels. During a median follow-up of 3 years, patients with big ET-1 ≥ 0.55 pmol/L had notably higher risk of all-cause death (44.8% vs. 11.5%, p < 0.001), MAEs (51.8% vs. 17.4%, p < 0.001), cardiovascular death, major bleeding, and tended to have higher thromboembolic risk. After adjusting for confounding factors, high big ET-1 level was an independent predictor of all-cause mortality (hazard ratio (HR) 2.11, 95% confidence interval (CI) 1.46-3.05; p < 0.001), MAEs (HR 2.05, 95% CI 1.50-2.80; p = 0.001), and cardiovascular death (HR 2.44, 95% CI 1.52-3.93; p < 0.001). NRI analysis showed that big ET-1 allowed a significant improvement of 0.32 in the accuracy of predicting the risk of both all-cause mortality and MAEs. Elevated big ET-1 levels is an independent predictor of long-term all-cause mortality, MAEs, and cardiovascular death in patients with AF. Copyright © 2018 Elsevier B.V. All rights reserved.

Fractal analysis of heart rate dynamics as a predictor of mortality in patients with depressed left ventricular function after acute myocardial infarction. TRACE Investigators. TRAndolapril Cardiac Evaluation

NASA Technical Reports Server (NTRS)

Makikallio, T. H.; Hoiber, S.; Kober, L.; Torp-Pedersen, C.; Peng, C. K.; Goldberger, A. L.; Huikuri, H. V.

1999-01-01

A number of new methods have been recently developed to quantify complex heart rate (HR) dynamics based on nonlinear and fractal analysis, but their value in risk stratification has not been evaluated. This study was designed to determine whether selected new dynamic analysis methods of HR variability predict mortality in patients with depressed left ventricular (LV) function after acute myocardial infarction (AMI). Traditional time- and frequency-domain HR variability indexes along with short-term fractal-like correlation properties of RR intervals (exponent alpha) and power-law scaling (exponent beta) were studied in 159 patients with depressed LV function (ejection fraction <35%) after an AMI. By the end of 4-year follow-up, 72 patients (45%) had died and 87 (55%) were still alive. Short-term scaling exponent alpha (1.07 +/- 0.26 vs 0.90 +/- 0.26, p <0.001) and power-law slope beta (-1.35 +/- 0.23 vs -1.44 +/- 0.25, p <0.05) differed between survivors and those who died, but none of the traditional HR variability measures differed between these groups. Among all analyzed variables, reduced scaling exponent alpha (<0.85) was the best univariable predictor of mortality (relative risk 3.17, 95% confidence interval 1.96 to 5.15, p <0.0001), with positive and negative predictive accuracies of 65% and 86%, respectively. In the multivariable Cox proportional hazards analysis, mortality was independently predicted by the reduced exponent alpha (p <0.001) after adjustment for several clinical variables and LV function. A short-term fractal-like scaling exponent was the most powerful HR variability index in predicting mortality in patients with depressed LV function. Reduction in fractal correlation properties implies more random short-term HR dynamics in patients with increased risk of death after AMI.

Usefulness of serum interleukin-18 in predicting cardiovascular mortality in patients with chronic kidney disease--systems and clinical approach.

PubMed

Formanowicz, Dorota; Wanic-Kossowska, Maria; Pawliczak, Elżbieta; Radom, Marcin; Formanowicz, Piotr

2015-12-16

The aim of this study was to check if serum interleukin-18 (IL-18) predicts 2-year cardiovascular mortality in patients at various stages of chronic kidney disease (CKD) and history of acute myocardial infarction (AMI) within the previous year. Diabetes mellitus was one of the key factors of exclusion. It was found that an increase in serum concentration of IL-18 above the cut-off point (1584.5 pg/mL) was characterized by 20.63-fold higher risk of cardiovascular deaths among studied patients. IL-18 serum concentration was found to be superior to the well-known cardiovascular risk parameters, like high sensitivity C-reactive protein (hsCRP), carotid intima media thickness (CIMT), glomerular filtration rate, albumins, ferritin, N-terminal prohormone of brain natriuretic peptide (NT-proBNP) in prognosis of cardiovascular mortality. The best predictive for IL-18 were 4 variables, such as CIMT, NT-proBNP, albumins and hsCRP, as they predicted its concentration at 89.5%. Concluding, IL-18 seems to be important indicator and predictor of cardiovascular death in two-year follow-up among non-diabetic patients suffering from CKD, with history of AMI in the previous year. The importance of IL-18 in the process of atherosclerotic plaque formation has been confirmed by systems analysis based on a formal model expressed in the language of Petri nets theory.

Model-based evaluation of highly and low pathogenic avian influenza dynamics in wild birds

USGS Publications Warehouse

Hénaux, Viviane; Samuel, Michael D.; Bunck, Christine M.

2010-01-01

There is growing interest in avian influenza (AI) epidemiology to predict disease risk in wild and domestic birds, and prevent transmission to humans. However, understanding the epidemic dynamics of highly pathogenic (HPAI) viruses remains challenging because they have rarely been detected in wild birds. We used modeling to integrate available scientific information from laboratory and field studies, evaluate AI dynamics in individual hosts and waterfowl populations, and identify key areas for future research. We developed a Susceptible-Exposed-Infectious-Recovered (SEIR) model and used published laboratory challenge studies to estimate epidemiological parameters (rate of infection, latency period, recovery and mortality rates), considering the importance of age classes, and virus pathogenicity. Infectious contact leads to infection and virus shedding within 1–2 days, followed by relatively slower period for recovery or mortality. We found a shorter infectious period for HPAI than low pathogenic (LP) AI, which may explain that HPAI has been much harder to detect than LPAI during surveillance programs. Our model predicted a rapid LPAI epidemic curve, with a median duration of infection of 50–60 days and no fatalities. In contrast, HPAI dynamics had lower prevalence and higher mortality, especially in young birds. Based on field data from LPAI studies, our model suggests to increase surveillance for HPAI in post-breeding areas, because the presence of immunologically naïve young birds is predicted to cause higher HPAI prevalence and bird losses during this season. Our results indicate a better understanding of the transmission, infection, and immunity-related processes is required to refine predictions of AI risk and spread, improve surveillance for HPAI in wild birds, and develop disease control strategies to reduce potential transmission to domestic birds and/or humans.

A Two-Biomarker Model Predicts Mortality in the Critically Ill with Sepsis.

PubMed

Mikacenic, Carmen; Price, Brenda L; Harju-Baker, Susanna; O'Mahony, D Shane; Robinson-Cohen, Cassianne; Radella, Frank; Hahn, William O; Katz, Ronit; Christiani, David C; Himmelfarb, Jonathan; Liles, W Conrad; Wurfel, Mark M

2017-10-15

Improving the prospective identification of patients with systemic inflammatory response syndrome (SIRS) and sepsis at low risk for organ dysfunction and death is a major clinical challenge. To develop and validate a multibiomarker-based prediction model for 28-day mortality in critically ill patients with SIRS and sepsis. A derivation cohort (n = 888) and internal test cohort (n = 278) were taken from a prospective study of critically ill intensive care unit (ICU) patients meeting two of four SIRS criteria at an academic medical center for whom plasma was obtained within 24 hours. The validation cohort (n = 759) was taken from a prospective cohort enrolled at another academic medical center ICU for whom plasma was obtained within 48 hours. We measured concentrations of angiopoietin-1, angiopoietin-2, IL-6, IL-8, soluble tumor necrosis factor receptor-1, soluble vascular cell adhesion molecule-1, granulocyte colony-stimulating factor, and soluble Fas. We identified a two-biomarker model in the derivation cohort that predicted mortality (area under the receiver operator characteristic curve [AUC], 0.79; 95% confidence interval [CI], 0.74-0.83). It performed well in the internal test cohort (AUC, 0.75; 95% CI, 0.65-0.85) and the external validation cohort (AUC, 0.77; 95% CI, 0.72-0.83). We determined a model score threshold demonstrating high negative predictive value (0.95) for death. In addition to a low risk of death, patients below this threshold had shorter ICU length of stay, lower incidence of acute kidney injury, acute respiratory distress syndrome, and need for vasopressors. We have developed a simple, robust biomarker-based model that identifies patients with SIRS/sepsis at low risk for death and organ dysfunction.

Selecting the minimum prediction base of historical data to perform 5-year predictions of the cancer burden: The GoF-optimal method.

PubMed

Valls, Joan; Castellà, Gerard; Dyba, Tadeusz; Clèries, Ramon

2015-06-01

Predicting the future burden of cancer is a key issue for health services planning, where a method for selecting the predictive model and the prediction base is a challenge. A method, named here Goodness-of-Fit optimal (GoF-optimal), is presented to determine the minimum prediction base of historical data to perform 5-year predictions of the number of new cancer cases or deaths. An empirical ex-post evaluation exercise for cancer mortality data in Spain and cancer incidence in Finland using simple linear and log-linear Poisson models was performed. Prediction bases were considered within the time periods 1951-2006 in Spain and 1975-2007 in Finland, and then predictions were made for 37 and 33 single years in these periods, respectively. The performance of three fixed different prediction bases (last 5, 10, and 20 years of historical data) was compared to that of the prediction base determined by the GoF-optimal method. The coverage (COV) of the 95% prediction interval and the discrepancy ratio (DR) were calculated to assess the success of the prediction. The results showed that (i) models using the prediction base selected through GoF-optimal method reached the highest COV and the lowest DR and (ii) the best alternative strategy to GoF-optimal was the one using the base of prediction of 5-years. The GoF-optimal approach can be used as a selection criterion in order to find an adequate base of prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Inflammation-based prognostic score is a novel predictor of postoperative outcome in patients with colorectal cancer.

PubMed

Ishizuka, Mitsuru; Nagata, Hitoshi; Takagi, Kazutoshi; Horie, Toru; Kubota, Keiichi

2007-12-01

To investigate the significance of preoperative Glasgow prognostic score (GPS) for postoperative prognostication of patients with colorectal cancer. Recent studies have revealed that the GPS, an inflammation-based prognostic score that includes only C-reactive protein (CRP) and albumin, is a useful tool for predicting postoperative outcome in cancer patients. However, few studies have investigated the GPS in the field of colorectal surgery. The GPS was calculated on the basis of admission data as follows: patients with an elevated level of both CRP (>10 mg/L) and hypoalbuminemia (Alb <35 g/L) were allocated a score of 2, and patients showing 1 or none of these blood chemistry abnormalities were allocated a score of 1 or 0, respectively. Prognostic significance was analyzed by univariate and multivariate analyses. A total of 315 patients were evaluated. Kaplan-Meier analysis and log-rank test revealed that a higher GPS predicted a higher risk of postoperative mortality (P < 0.01). Univariate analyses revealed that postoperative TNM was the most sensitive predictor of postoperative mortality (odds ratio, 0.148; 95% confidence interval, 0.072-0.304; P < 0.0001). Multivariate analyses using factors such as age, sex, tumor site, serum carcinoembryonic antigen, CA19-9, CA72-4, CRP, albumin, and GPS revealed that GPS (odds ratio, 0.165; 95% confidence interval, 0.037-0.732; P = 0.0177) was associated with postoperative mortality. Preoperative GPS is considered to be a useful predictor of postoperative mortality in patients with colorectal cancer.

How do masculinity, paternity leave, and mortality associate? -A study of fathers in the Swedish parental & child cohort of 1988/89.

PubMed

Månsdotter, Anna; Lundin, Andreas

2010-08-01

One of the proposed causes for the gender gap in longevity is the attitudes and practices culturally prescribed for men, often conceptualised as 'masculinity'. It has also been suggested that paternity leave, indicating a change from breadwinning to caring, could benefit men's lifetime health. In this study, the objective was to examine associations between 'masculinity' (assessed at the age of 18-19 years), paternity leave (1988-1990), and mortality patterns (1991-2008) based on a population of Swedish men who had a child in 1988/89 (N=72,569). 'Masculinity' was measured during the compulsory military conscription process by a psychologist based on leisure and occupational interests, and paternity leave was measured in fulltime days by registry data. The main finding was that low 'masculinity' ranking increased the risk of all-cause mortality, and mortality from alcohol and violent causes, while taking paternity leave between 30 and 135 days decreased the risk of all-cause mortality. However, the weak association found between 'masculinity' and paternity leave indicates that entering a caring role as a father is not predicted by 'masculinity' assessed in late adolescence, and that the studied phenomena influence male mortality independently of each other. Copyright 2010 Elsevier Ltd. All rights reserved.

[Comparison of predictive factors related to the mortality and rebleeding caused by variceal bleeding: Child-Pugh score, MELD score, and Rockall score].

PubMed

Lee, Ja Young; Lee, Jin Heon; Kim, Soo Jin; Choi, Dae Rho; Kim, Kyung Ho; Kim, Yong Bum; Kim, Hak Yang; Yoo, Jae Young

2002-12-01

The first episode of variceal bleeding is one of the most frequent causes of death in patients with liver cirrhosis. The Child-Pugh(CP) scoring system has been widely accepted for prognostic assessment. Recently, MELD has been known to be better than the CP scoring system for predicting mortality in patients with end-stage liver diseases. The Rockall risk scoring system was developed to predict the outcome of upper GI bleeding including variceal bleeding. The aim of this study was to investigate the mortality rate of first variceal bleeding and the predictability of each scoring system. We evaluated the 6-week mortality rate, rebleeding rate, and 1-year mortality rate of all the 136 patients with acute variceal bleeding without previous episode of hemorrhage between January 1, 1998 and December 31, 2000. The CP score, MELD score, and Rockall score were estimated and analyzed. Among 136 patients, 35 patients with hepatoma and 8 patients with follow-up loss were excluded. Six-week mortality rate, 1-year mortality rate, and rebleeding rate of first variceal bleeding were 24.7%, 35.5%, and 12.9%, respectively. The c-statistics of CP, MELD, and Rockall score for predicting 6-week mortality rate were 0.809 (p<0.001, 95% CI, 0.720-0.898), 0.804 (p<0.001, 95% CI, 0.696-0.911), 0.787 (p<0.001, 95% CI, 0.683-0.890), respectively. For 1-year mortality rate, c-statistics were 0.765 (p<0.005, 95% CI, 0.665-0.865), 0.780 (p<0.005, 95% CI, 0.676-0.883), 0.730 (p<0.01, 95% CI, 0.627-0.834), respectively. The CP, MELD, and Rockall scores were reliable measures of mortality risk in patients with first variceal bleeding. The CP classification is useful in its easy applicability.

The autophagy marker LC3 strongly predicts immediate mortality after surgical resection for hepatocellular carcinoma.

PubMed

Lin, Chih-Wen; Lin, Chih-Che; Lee, Po-Huang; Lo, Gin-Ho; Hsieh, Pei-Min; Koh, Kah Wee; Lee, Chih-Yuan; Chen, Yao-Li; Dai, Chia-Yen; Huang, Jee-Fu; Chuang, Wang-Long; Chen, Yaw-Sen; Yu, Ming-Lung

2017-11-03

The remnant liver's ability to regenerate may affect post-hepatectomy immediate mortality. The promotion of autophagy post-hepatectomy could enhance liver regeneration and reduce mortality. This study aimed to identify predictive factors of immediate mortality after surgical resection for hepatocellular carcinoma (HCC). A total of 535 consecutive HCC patients who had undergone their first surgical resection in Taiwan were enrolled between 2010 and 2014. Clinicopathological data and immediate mortality, defined as all cause-mortality within three months after surgery, were analyzed. The expression of autophagy proteins (LC3, Beclin-1, and p62) in adjacent non-tumor tissues was scored by immunohistochemical staining. Approximately 5% of patients had immediate mortality after surgery. The absence of LC3, hypoalbuminemia (<3.5 g/dl), high alanine aminotransferase, and major liver surgery were significantly associated with immediate mortality in univariate analyses. Multivariate logistic regression demonstrated that absence of LC3 (hazard ratio/95% confidence interval: 40.8/5.14-325) and hypoalbuminemia (2.88/1.11-7.52) were significantly associated with immediate mortality. The 3-month cumulative incidence of mortality was 12.1%, 13.0%, 21.4% and 0.4%, respectively, among patients with absence of LC3 expression, hypoalbuminemia, both, or neither of the two. In conclusion, the absence of LC3 expression in adjacent non-tumor tissues and hypoalbuminemia were strongly predictive of immediate mortality after resection for HCC.

Kidney measures beyond traditional risk factors for cardiovascular prediction: A collaborative meta-analysis

PubMed Central

Matsushita, Kunihiro; Coresh, Josef; Sang, Yingying; Chalmers, John; Fox, Caroline; Guallar, Eliseo; Jafar, Tazeen; Jassal, Simerjot K.; Landman, Gijs W.D.; Muntner, Paul; Roderick, Paul; Sairenchi, Toshimi; Schöttker, Ben; Shankar, Anoop; Shlipak, Michael; Tonelli, Marcello; Townend, Jonathan; van Zuilen, Arjan; Yamagishi, Kazumasa; Yamashita, Kentaro; Gansevoort, Ron; Sarnak, Mark; Warnock, David G.; Woodward, Mark; Ärnlöv, Johan

2015-01-01

Background The utility of estimated glomerular filtration rate (eGFR) and albuminuria for cardiovascular prediction is controversial. Methods We meta-analyzed individual-level data from 24 cohorts (with a median follow-up time longer than 4 years, varying from 4.2 to 19.0 years) in the Chronic Kidney Disease Prognosis Consortium (637,315 participants without a history of cardiovascular disease) and assessed C-statistic difference and reclassification improvement for cardiovascular mortality and fatal and non-fatal cases of coronary heart disease, stroke, and heart failure in 5-year timeframe, contrasting prediction models consisting of traditional risk factors with and without creatinine-based eGFR and/or albuminuria (either albumin-to-creatinine ratio [ACR] or semi-quantitative dipstick proteinuria). Findings The addition of eGFR and ACR significantly improved the discrimination of cardiovascular outcomes beyond traditional risk factors in general populations, but the improvement was greater with ACR than with eGFR and more evident for cardiovascular mortality (c-statistic difference 0.0139 [95%CI 0.0105–0.0174] and 0.0065 [0.0042–0.0088], respectively) and heart failure (0.0196 [0.0108–0.0284] and 0.0109 [0.0059–0.0159]) than for coronary disease (0.0048 [0.0029–0.0067] and 0.0036 [0.0019–0.0054]) and stroke (0.0105 [0.0058–0.0151] and 0.0036 [0.0004–0.0069]). Dipstick proteinuria demonstrated smaller improvement than ACR. The discrimination improvement with kidney measures was especially evident in individuals with diabetes or hypertension but remained significant with ACR for cardiovascular mortality and heart failure in those without either of these conditions. In participants with chronic kidney disease (CKD), the combination of eGFR and ACR for risk discrimination outperformed most single traditional predictors; the c-statistic for cardiovascular mortality declined by 0.023 [0.016–0.030] vs. <0.007 when omitting eGFR and ACR vs. any single modifiable traditional predictors, respectively. Interpretation Creatinine-based eGFR and albuminuria should be taken into account for cardiovascular prediction, especially when they are already assessed for clinical purpose and/or cardiovascular mortality and heart failure are the outcomes of interest (e.g., the European guidelines on cardiovascular prevention). ACR may have particularly broad implications for cardiovascular prediction. In CKD populations, the simultaneous assessment of eGFR and ACR will facilitate improved cardiovascular risk classification, supporting current CKD guidelines. Funding US National Kidney Foundation and NIDDK PMID:26028594

Bioelectrical impedance analysis-derived phase angle at admission as a predictor of 90-day mortality in intensive care patients.

PubMed

Stapel, Sandra N; Looijaard, Wilhelmus G P M; Dekker, Ingeborg M; Girbes, Armand R J; Weijs, Peter J M; Oudemans-van Straaten, Heleen M

2018-05-11

A low bioelectrical impedance analysis (BIA)-derived phase angle (PA) predicts morbidity and mortality in different patient groups. An association between PA and long-term mortality in ICU patients has not been demonstrated before. The purpose of the present study was to determine whether PA on ICU admission independently predicts 90-day mortality. This prospective observational study was performed in a mixed university ICU. BIA was performed in 196 patients within 24 h of ICU admission. To test the independent association between PA and 90-day mortality, logistic regression analysis was performed using the APACHE IV predicted mortality as confounder. The optimal cutoff value of PA for mortality prediction was determined by ROC curve analysis. Using this cutoff value, patients were categorized into low or normal PA group and the association with 90-day mortality was tested again. The PA of survivors was higher than of the non-survivors (5.0° ± 1.3° vs. 4.1° ± 1.2°, p < 0.001). The area under the ROC curve of PA for 90-day mortality was 0.70 (CI 0.59-0.80). PA was associated with 90-day mortality (OR = 0.56, CI: 0.38-0.77, p = 0.001) on univariate logistic regression analysis and also after adjusting for BMI, gender, age, and APACHE IV on multivariable logistic regression (OR = 0.65, CI: 0.44-0.96, p = 0.031). A PA < 4.8° was an independent predictor of 90-day mortality (adjusted OR = 3.65, CI: 1.34-9.93, p = 0.011). Phase angle at ICU admission is an independent predictor of 90-day mortality. This biological marker can aid in long-term mortality risk assessment of critically ill patients.

Evaluating the predictive performance of empirical estimators of natural mortality rate using information on over 200 fish species

USGS Publications Warehouse

Then, Amy Y.; Hoenig, John M; Hall, Norman G.; Hewitt, David A.

2015-01-01

Many methods have been developed in the last 70 years to predict the natural mortality rate, M, of a stock based on empirical evidence from comparative life history studies. These indirect or empirical methods are used in most stock assessments to (i) obtain estimates of M in the absence of direct information, (ii) check on the reasonableness of a direct estimate of M, (iii) examine the range of plausible M estimates for the stock under consideration, and (iv) define prior distributions for Bayesian analyses. The two most cited empirical methods have appeared in the literature over 2500 times to date. Despite the importance of these methods, there is no consensus in the literature on how well these methods work in terms of prediction error or how their performance may be ranked. We evaluate estimators based on various combinations of maximum age (tmax), growth parameters, and water temperature by seeing how well they reproduce >200 independent, direct estimates of M. We use tenfold cross-validation to estimate the prediction error of the estimators and to rank their performance. With updated and carefully reviewed data, we conclude that a tmax-based estimator performs the best among all estimators evaluated. The tmax-based estimators in turn perform better than the Alverson–Carney method based on tmax and the von Bertalanffy K coefficient, Pauly’s method based on growth parameters and water temperature and methods based just on K. It is possible to combine two independent methods by computing a weighted mean but the improvement over the tmax-based methods is slight. Based on cross-validation prediction error, model residual patterns, model parsimony, and biological considerations, we recommend the use of a tmax-based estimator (M=4.899tmax−0.916">M=4.899t−0.916maxM=4.899tmax−0.916, prediction error = 0.32) when possible and a growth-based method (M=4.118K0.73L∞−0.33">M=4.118K0.73L−0.33∞M=4.118K0.73L∞−0.33 , prediction error = 0.6, length in cm) otherwise.

Age, PaO2/FIO2, and Plateau Pressure Score: A Proposal for a Simple Outcome Score in Patients With the Acute Respiratory Distress Syndrome.

PubMed

Villar, Jesús; Ambrós, Alfonso; Soler, Juan Alfonso; Martínez, Domingo; Ferrando, Carlos; Solano, Rosario; Mosteiro, Fernando; Blanco, Jesús; Martín-Rodríguez, Carmen; Fernández, María Del Mar; López, Julia; Díaz-Domínguez, Francisco J; Andaluz-Ojeda, David; Merayo, Eleuterio; Pérez-Méndez, Lina; Fernández, Rosa Lidia; Kacmarek, Robert M

2016-07-01

Although there is general agreement on the characteristic features of the acute respiratory distress syndrome, we lack a scoring system that predicts acute respiratory distress syndrome outcome with high probability. Our objective was to develop an outcome score that clinicians could easily calculate at the bedside to predict the risk of death of acute respiratory distress syndrome patients 24 hours after diagnosis. A prospective, multicenter, observational, descriptive, and validation study. A network of multidisciplinary ICUs. Six-hundred patients meeting Berlin criteria for moderate and severe acute respiratory distress syndrome enrolled in two independent cohorts treated with lung-protective ventilation. None. Using individual demographic, pulmonary, and systemic data at 24 hours after acute respiratory distress syndrome diagnosis, we derived our prediction score in 300 acute respiratory distress syndrome patients based on stratification of variable values into tertiles, and validated in an independent cohort of 300 acute respiratory distress syndrome patients. Primary outcome was in-hospital mortality. We found that a 9-point score based on patient's age, PaO2/FIO2 ratio, and plateau pressure at 24 hours after acute respiratory distress syndrome diagnosis was associated with death. Patients with a score greater than 7 had a mortality of 83.3% (relative risk, 5.7; 95% CI, 3.0-11.0), whereas patients with scores less than 5 had a mortality of 14.5% (p < 0.0000001). We confirmed the predictive validity of the score in a validation cohort. A simple 9-point score based on the values of age, PaO2/FIO2 ratio, and plateau pressure calculated at 24 hours on protective ventilation after acute respiratory distress syndrome diagnosis could be used in real time for rating prognosis of acute respiratory distress syndrome patients with high probability.

Does inclusion of education and marital status improve SCORE performance in central and eastern europe and former soviet union? findings from MONICA and HAPIEE cohorts.

PubMed

Vikhireva, Olga; Broda, Grazyna; Kubinova, Ruzena; Malyutina, Sofia; Pająk, Andrzej; Tamosiunas, Abdonas; Skodova, Zdena; Simonova, Galina; Bobak, Martin; Pikhart, Hynek

2014-01-01

The SCORE scale predicts the 10-year risk of fatal atherosclerotic cardiovascular disease (CVD), based on conventional risk factors. The high-risk version of SCORE is recommended for Central and Eastern Europe and former Soviet Union (CEE/FSU), due to high CVD mortality rates in these countries. Given the pronounced social gradient in cardiovascular mortality in the region, it is important to consider social factors in the CVD risk prediction. We investigated whether adding education and marital status to SCORE benefits its prognostic performance in two sets of population-based CEE/FSU cohorts. The WHO MONICA (MONItoring of trends and determinants in CArdiovascular disease) cohorts from the Czech Republic, Poland (Warsaw and Tarnobrzeg), Lithuania (Kaunas), and Russia (Novosibirsk) were followed from the mid-1980s (577 atherosclerotic CVD deaths among 14,969 participants with non-missing data). The HAPIEE (Health, Alcohol, and Psychosocial factors In Eastern Europe) study follows Czech, Polish (Krakow), and Russian (Novosibirsk) cohorts from 2002-05 (395 atherosclerotic CVD deaths in 19,900 individuals with non-missing data). In MONICA and HAPIEE, the high-risk SCORE ≥5% at baseline strongly and significantly predicted fatal CVD both before and after adjustment for education and marital status. After controlling for SCORE, lower education and non-married status were significantly associated with CVD mortality in some samples. SCORE extension by these additional risk factors only slightly improved indices of calibration and discrimination (integrated discrimination improvement <5% in men and ≤1% in women). Extending SCORE by education and marital status failed to substantially improve its prognostic performance in population-based CEE/FSU cohorts.

Comorbidities and the risk of mortality in patients with bronchiectasis: an international multicentre cohort study.

PubMed

McDonnell, Melissa J; Aliberti, Stefano; Goeminne, Pieter C; Restrepo, Marcos I; Finch, Simon; Pesci, Alberto; Dupont, Lieven J; Fardon, Thomas C; Wilson, Robert; Loebinger, Michael R; Skrbic, Dusan; Obradovic, Dusanka; De Soyza, Anthony; Ward, Chris; Laffey, John G; Rutherford, Robert M; Chalmers, James D

2016-12-01

Patients with bronchiectasis often have concurrent comorbidities, but the nature, prevalence, and impact of these comorbidities on disease severity and outcome are poorly understood. We aimed to investigate comorbidities in patients with bronchiectasis and establish their prognostic value on disease severity and mortality rate. An international multicentre cohort analysis of outpatients with bronchiectasis from four European centres followed up for 5 years was done for score derivation. Eligible patients were those with bronchiectasis confirmed by high-resolution CT and a compatible clinical history. Comorbidity diagnoses were based on standardised definitions and were obtained from full review of paper and electronic medical records, prescriptions, and investigator definitions. Weibull parametric survival analysis was used to model the prediction of the 5 year mortality rate to construct the Bronchiectasis Aetiology Comorbidity Index (BACI). We tested the BACI as a predictor of outcomes and explored whether the BACI added further prognostic information when used alongside the Bronchiectasis Severity Index (BSI). The BACI was validated in two independent international cohorts from the UK and Serbia. Between June 1, 2006, and Nov 22, 2013, 1340 patients with bronchiectasis were screened and 986 patients were analysed. Patients had a median of four comorbidities (IQR 2-6; range 0-20). 13 comorbidities independently predicting mortality rate were integrated into the BACI. The overall hazard ratio for death conferred by a one-point increase in the BACI was 1·18 (95% CI 1·14-1·23; p<0·0001). The BACI predicted 5 year mortality rate, hospital admissions, exacerbations, and health-related quality of life across all BSI risk strata (p<0·0001 for mortality and hospital admissions, p=0·03 for exacerbations, p=0·0008 for quality of life). When used in conjunction with the BSI, the combined model was superior to either model alone (p=0·01 for combined vs BACI; p=0·008 for combined vs BSI). Multimorbidity is frequent in bronchiectasis and can negatively affect survival. The BACI complements the BSI in the assessment and prediction of mortality and disease outcomes in patients with bronchiectasis. European Bronchiectasis Network (EMBARC). Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of hospital performance with a case-mix standardized mortality model using an existing administrative database in Japan.

PubMed

Miyata, Hiroaki; Hashimoto, Hideki; Horiguchi, Hiromasa; Fushimi, Kiyohide; Matsuda, Shinya

2010-05-19

Few studies have examined whether risk adjustment is evenly applicable to hospitals with various characteristics and case-mix. In this study, we applied a generic prediction model to nationwide discharge data from hospitals with various characteristics. We used standardized data of 1,878,767 discharged patients provided by 469 hospitals from July 1 to October 31, 2006. We generated and validated a case-mix in-hospital mortality prediction model using 50/50 split sample validation. We classified hospitals into two groups based on c-index value (hospitals with c-index > or = 0.8; hospitals with c-index < 0.8) and examined differences in their characteristics. The model demonstrated excellent discrimination as indicated by the high average c-index and small standard deviation (c-index = 0.88 +/- 0.04). Expected mortality rate of each hospital was highly correlated with observed mortality rate (r = 0.693, p < 0.001). Among the studied hospitals, 446 (95%) had a c-index of >/=0.8 and were classified as the higher c-index group. A significantly higher proportion of hospitals in the lower c-index group were specialized hospitals and hospitals with convalescent wards. The model fits well to a group of hospitals with a wide variety of acute care events, though model fit is less satisfactory for specialized hospitals and those with convalescent wards. Further sophistication of the generic prediction model would be recommended to obtain optimal indices to region specific conditions.

Can Fish Morphological Characteristics be Used to Re-design Hydroelectric Turbines?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cada, G. F.; Richmond, Marshall C.

2011-07-19

Safe fish passage affects not only migratory species, but also populations of resident fish by altering biomass, biodiversity, and gene flow. Consequently, it is important to estimate turbine passage survival of a wide range of susceptible fish. Although fish-friendly turbines show promise for reducing turbine passage mortality, experimental data on their beneficial effects are limited to only a few species, mainly salmon and trout. For thousands of untested species and sizes of fish, the particular causes of turbine passage mortality and the benefits of fish-friendly turbine designs remain unknown. It is not feasible to measure the turbine-passage survival of everymore » species of fish in every hydroelectric turbine design. We are attempting to predict fish mortality based on an improved understanding of turbine-passage stresses (pressure, shear stress, turbulence, strike) and information about the morphological, behavioral, and physiological characteristics of different fish taxa that make them susceptible to the stresses. Computational fluid dynamics and blade strike models of the turbine environment are re-examined in light of laboratory and field studies of fish passage effects. Comparisons of model-predicted stresses to measured injuries and mortalities will help identify fish survival thresholds and the aspects of turbines that are most in need of re-design. The coupled model and fish morphology evaluations will enable us to make predictions of turbine-passage survival among untested fish species, for both conventional and advanced turbines, and to guide the design of hydroelectric turbines to improve fish passage survival.« less

[Validation of the Pneumonia Severity Index for hospitalizing patients with community-acquired pneumonia].

PubMed

Querol-Ribelles, José M; Tenías, José M; Querol-Borrás, José M; González-Granda, Damiana; Hernández, Manuel; Ferreruela, Rosa; Martínez, Isidoro

2004-04-10

Our main objective was to assess the utility of the Pneumonia Severity Index (PSI) to decide the site of care home or hospital of patients with community-acquired pneumonia (CAP). All CAP patients who came to the emergency department from 1 January to 31 December, 2000, were prospectively assessed with a protocol based on the PSI and additional admission criteria applied to classes I, II and III. Mortality within 30 days and poor outcome were used as endpoints. We tested the diagnostic efficacy of the PSI scale in predicting mortality or unfavourable events by calculating the area below the ROC curve. Of the 243 CAP patients included, 124 (51%) belonged to classes I, II and III, and 119 (49%) belonged to classes IV and V. One hundred and fifty six (64%) patients were admitted. Fifteen (6.2%) patients died, all of them belonging to classes IV and V. Forty four (18%) patients showed a poor outcome. Only one patient who was initially sent home had a poor outcome. The prognostic value of the PSI scale to predict mortality (ROC = 0.92; CI 95%, 0.88-0.95) was high. Our results confirm that the PSI scale is a good prognostic index in clinical practice for predicting mortality due to CAP. In order to use the PSI to decide the site of care of patients with CAP, not only the score obtained but also additional factors should be taken into account.

Severe acute malnutrition in childhood: hormonal and metabolic status at presentation, response to treatment, and predictors of mortality.

PubMed

Bartz, Sarah; Mody, Aaloke; Hornik, Christoph; Bain, James; Muehlbauer, Michael; Kiyimba, Tonny; Kiboneka, Elizabeth; Stevens, Robert; Bartlett, John; St Peter, John V; Newgard, Christopher B; Freemark, Michael

2014-06-01

Malnutrition is a major cause of childhood morbidity and mortality. To identify and target those at highest risk, there is a critical need to characterize biomarkers that predict complications prior to and during treatment. We used targeted and nontargeted metabolomic analysis to characterize changes in a broad array of hormones, cytokines, growth factors, and metabolites during treatment of severe childhood malnutrition. Children aged 6 months to 5 years were studied at presentation to Mulago Hospital and during inpatient therapy with milk-based formulas and outpatient supplementation with ready-to-use food. We assessed the relationship between baseline hormone and metabolite levels and subsequent mortality. Seventy-seven patients were enrolled in the study; a subset was followed up from inpatient treatment to the outpatient clinic. Inpatient and outpatient therapies increased weight/height z scores and induced striking changes in the levels of fatty acids, amino acids, acylcarnitines, inflammatory cytokines, and various hormones including leptin, insulin, GH, ghrelin, cortisol, IGF-I, glucagon-like peptide-1, and peptide YY. A total of 12.2% of the patients died during hospitalization; the major biochemical factor predicting mortality was a low level of leptin (P = .0002), a marker of adipose tissue reserve and a critical modulator of immune function. We have used metabolomic analysis to provide a comprehensive hormonal and metabolic profile of severely malnourished children at presentation and during nutritional rehabilitation. Our findings suggest that fatty acid metabolism plays a central role in the adaptation to acute malnutrition and that low levels of the adipose tissue hormone leptin associate with, and may predict, mortality prior to and during treatment.

Severe Acute Malnutrition in Childhood: Hormonal and Metabolic Status at Presentation, Response to Treatment, and Predictors of Mortality

PubMed Central

Bartz, Sarah; Mody, Aaloke; Hornik, Christoph; Bain, James; Muehlbauer, Michael; Kiyimba, Tonny; Kiboneka, Elizabeth; Stevens, Robert; Bartlett, John; St Peter, John V.; Newgard, Christopher B.

2014-01-01

Objective: Malnutrition is a major cause of childhood morbidity and mortality. To identify and target those at highest risk, there is a critical need to characterize biomarkers that predict complications prior to and during treatment. Methods: We used targeted and nontargeted metabolomic analysis to characterize changes in a broad array of hormones, cytokines, growth factors, and metabolites during treatment of severe childhood malnutrition. Children aged 6 months to 5 years were studied at presentation to Mulago Hospital and during inpatient therapy with milk-based formulas and outpatient supplementation with ready-to-use food. We assessed the relationship between baseline hormone and metabolite levels and subsequent mortality. Results: Seventy-seven patients were enrolled in the study; a subset was followed up from inpatient treatment to the outpatient clinic. Inpatient and outpatient therapies increased weight/height z scores and induced striking changes in the levels of fatty acids, amino acids, acylcarnitines, inflammatory cytokines, and various hormones including leptin, insulin, GH, ghrelin, cortisol, IGF-I, glucagon-like peptide-1, and peptide YY. A total of 12.2% of the patients died during hospitalization; the major biochemical factor predicting mortality was a low level of leptin (P = .0002), a marker of adipose tissue reserve and a critical modulator of immune function. Conclusions: We have used metabolomic analysis to provide a comprehensive hormonal and metabolic profile of severely malnourished children at presentation and during nutritional rehabilitation. Our findings suggest that fatty acid metabolism plays a central role in the adaptation to acute malnutrition and that low levels of the adipose tissue hormone leptin associate with, and may predict, mortality prior to and during treatment. PMID:24606092

Weather radar data correlate to hail-induced mortality in grassland birds

USGS Publications Warehouse

Carver, Amber; Ross, Jeremy D.; Augustine, David J.; Skagen, Susan K.; Dwyer, Angela M.; Tomback, Diana F.; Wunder, Michael B.

2017-01-01

Small-bodied terrestrial animals such as songbirds (Order Passeriformes) are especially vulnerable to hail-induced mortality; yet, hail events are challenging to predict, and they often occur in locations where populations are not being studied. Focusing on nesting grassland songbirds, we demonstrate a novel approach to estimate hail-induced mortality. We quantify the relationship between the probability of nests destroyed by hail and measured Level-III Next Generation Radar (NEXRAD) data, including atmospheric base reflectivity, maximum estimated size of hail and maximum estimated azimuthal wind shear. On 22 June 2014, a hailstorm in northern Colorado destroyed 102 out of 203 known nests within our research site. Lark bunting (Calamospiza melanocorys) nests comprised most of the sample (n = 186). Destroyed nests were more likely to be found in areas of higher storm intensity, and distributions of NEXRAD variables differed between failed and surviving nests. For 133 ground nests where nest-site vegetation was measured, we examined the ameliorative influence of woody vegetation, nest cover and vegetation density by comparing results for 13 different logistic regression models incorporating the independent and additive effects of weather and vegetation variables. The most parsimonious model used only the interactive effect of hail size and wind shear to predict the probability of nest survival, and the data provided no support for any of the models without this predictor. We conclude that vegetation structure may not mitigate mortality from severe hailstorms and that weather radar products can be used remotely to estimate potential for hail mortality of nesting grassland birds. These insights will improve the efficacy of grassland bird population models under predicted climate change scenarios.

Effects of Extrinsic Mortality on the Evolution of Aging: A Stochastic Modeling Approach

PubMed Central

Shokhirev, Maxim Nikolaievich; Johnson, Adiv Adam

2014-01-01

The evolutionary theories of aging are useful for gaining insights into the complex mechanisms underlying senescence. Classical theories argue that high levels of extrinsic mortality should select for the evolution of shorter lifespans and earlier peak fertility. Non-classical theories, in contrast, posit that an increase in extrinsic mortality could select for the evolution of longer lifespans. Although numerous studies support the classical paradigm, recent data challenge classical predictions, finding that high extrinsic mortality can select for the evolution of longer lifespans. To further elucidate the role of extrinsic mortality in the evolution of aging, we implemented a stochastic, agent-based, computational model. We used a simulated annealing optimization approach to predict which model parameters predispose populations to evolve longer or shorter lifespans in response to increased levels of predation. We report that longer lifespans evolved in the presence of rising predation if the cost of mating is relatively high and if energy is available in excess. Conversely, we found that dramatically shorter lifespans evolved when mating costs were relatively low and food was relatively scarce. We also analyzed the effects of increased predation on various parameters related to density dependence and energy allocation. Longer and shorter lifespans were accompanied by increased and decreased investments of energy into somatic maintenance, respectively. Similarly, earlier and later maturation ages were accompanied by increased and decreased energetic investments into early fecundity, respectively. Higher predation significantly decreased the total population size, enlarged the shared resource pool, and redistributed energy reserves for mature individuals. These results both corroborate and refine classical predictions, demonstrating a population-level trade-off between longevity and fecundity and identifying conditions that produce both classical and non-classical lifespan effects. PMID:24466165

Prognostic indices for early mortality in ischaemic stroke - meta-analysis.

PubMed

Mattishent, K; Kwok, C S; Mahtani, A; Pelpola, K; Myint, P K; Loke, Y K

2016-01-01

Several models have been developed to predict mortality in ischaemic stroke. We aimed to evaluate systematically the performance of published stroke prognostic scores. We searched MEDLINE and EMBASE in February 2014 for prognostic models (published between 2003 and 2014) used in predicting early mortality (<6 months) after ischaemic stroke. We evaluated discriminant ability of the tools through meta-analysis of the area under the curve receiver operating characteristic curve (AUROC) or c-statistic. We evaluated the following components of study validity: collection of prognostic variables, neuroimaging, treatment pathways and missing data. We identified 18 articles (involving 163 240 patients) reporting on the performance of prognostic models for mortality in ischaemic stroke, with 15 articles providing AUC for meta-analysis. Most studies were either retrospective, or post hoc analyses of prospectively collected data; all but three reported validation data. The iSCORE had the largest number of validation cohorts (five) within our systematic review and showed good performance in four different countries, pooled AUC 0.84 (95% CI 0.82-0.87). We identified other potentially useful prognostic tools that have yet to be as extensively validated as iSCORE - these include SOAR (2 studies, pooled AUC 0.79, 95% CI 0.78-0.80), GWTG (2 studies, pooled AUC 0.72, 95% CI 0.72-0.72) and PLAN (1 study, pooled AUC 0.85, 95% CI 0.84-0.87). Our meta-analysis has identified and summarized the performance of several prognostic scores with modest to good predictive accuracy for early mortality in ischaemic stroke, with the iSCORE having the broadest evidence base. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Comparing the predictive value of the pelvic ring injury classification systems by Tile and by Young and Burgess.

PubMed

Osterhoff, Georg; Scheyerer, Max J; Fritz, Yannick; Bouaicha, Samy; Wanner, Guido A; Simmen, Hans-Peter; Werner, Clément M L

2014-04-01

Radiology-based classifications of pelvic ring injuries and their relevance for the prognosis of morbidity and mortality are disputed in the literature. The purpose of this study was to evaluate potential differences between the pelvic ring injury classification systems by Tile and by Young and Burgess with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Two-hundred-and-eighty-five consecutive patients with pelvic ring fractures were analyzed for mortality within 30 days after admission, number of blood units and total volume of fluid infused during the first 24h after trauma, the Abbreviated Injury Severity (AIS) scores for head, chest, spine, abdomen and extremities as a function of the Tile and the Young-Burgess classifications. There was no significant relationship between occurrence of death and fracture pattern but a significant relationship between fracture pattern and need for blood units/total fluid volume for Tile (p<.001/p<.001) and Young-Burgess (p<.001/p<.001). In both classifications, open book fractures were associated with more fluid requirement and more severe injuries of the abdomen, spine and extremities (p<.05). When divided into the larger subgroups "partially stable" and "unstable", unstable fractures were associated with a higher mortality rate in the Young-Burgess system (p=.036). In both classifications, patients with unstable fractures required significantly more blood transfusions (p<.001) and total fluid infusion (p<.001) and higher AIS scores. In this first direct comparison of both classifications, we found no clinical relevant differences with regard to their predictive value on mortality, transfusion/infusion requirement and concomitant injuries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Nutrition-related risk indexes and long-term mortality in noncritically ill inpatients who receive total parenteral nutrition (prospective multicenter study).

PubMed

Tapia, María José; Ocón, Julia; Cabrejas-Gómez, Carmen; Ballesteros-Pomar, María D; Vidal-Casariego, Alfonso; Arraiza-Irigoyen, Carmen; Olivares, Josefina; Conde-García, Ma Carmen; García-Manzanares, Álvaro; Botella-Romero, Francisco; Quílez-Toboso, Rosa P; Cabrerizo, Lucio; Rubio, Miguel A; Chicharro, Luisa; Burgos, Rosa; Pujante, Pedro; Ferrer, Mercedes; Zugasti, Ana; Petrina, Estrella; Manjón, Laura; Diéguez, Marta; Carrera, Ma José; Vila-Bundo, Anna; Urgelés, Juan Ramón; Aragón-Valera, Carmen; Sánchez-Vilar, Olga; Bretón, Irene; García-Peris, Pilar; Muñoz-Garach, Araceli; Márquez, Efren; del Olmo, Dolores; Pereira, José Luis; Tous, María C; Olveira, Gabriel

2015-10-01

Malnutrition in hospitalized patients is associated with an increased risk of death, in both the short and the long term. The purpose of this study was to determine which nutrition-related risk index predicts long-term mortality better (three years) in patients who receive total parenteral nutrition (TPN). This prospective, multicenter study involved noncritically ill patients who were prescribed TPN during hospitalization. Data were collected on Subjective Global Assessment (SGA), Nutritional Risk Index (NRI), Geriatric Nutritional Risk Index (GNRI), body mass index, albumin and prealbumin, as well as long-term mortality. Over the 1- and 3-year follow-up periods, 174 and 244 study subjects (28.8% and 40.3%) respectively, died. Based on the Cox proportional hazards survival model, the nutrition-related risk indexes most strongly associated with mortality were SGA and albumin (<2.5 g/dL) (after adjustment for age, gender, C-reactive protein levels, prior comorbidity, mean capillary blood glucose during TPN infusion, diabetes status prior to TPN, diagnosis, and infectious complications during hospitalization). The SGA and very low albumin levels are simple tools that predict the risk of long-term mortality better than other tools in noncritically ill patients who receive TPN during hospitalization. Copyright © 2014 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Impact of parental socioeconomic factors on childhood cancer mortality: a population-based registry study.

PubMed

Tolkkinen, Anniina; Madanat-Harjuoja, Laura; Taskinen, Mervi; Rantanen, Matti; Malila, Nea; Pitkäniemi, Janne

2018-06-04

Parental socioeconomic status has been proposed to have an influence on childhood cancer mortality even in high-income countries. Our study investigated the influence of parental socioeconomic factors on childhood cancer mortality. We identified 4437 patients diagnosed with cancer under the age of 20 from 1990 to 2009 and their parents from the Finnish cancer and central population registers. Information on death from primary cancer during five-year follow-up and parental socioeconomic factors was obtained from Statistics Finland. Poisson regression modeling was used to estimate hazard ratios (HRs) for factors related to cause-specific mortality and recursive tree based survival analysis to identify important risk factors and interactions. Mortality was lower in the highest quartile of combined parental disposable income (HR 0.68, CI 95% 0.52-0.89) compared to the lowest quartile. In the most recent diagnostic period from 2000 to 2009, highest attained education of either parent being post-secondary predicted lower mortality (HR 0.73, CI 95% 0.60-0.88) compared to parents who had attained primary or lower education. Despite high quality public health care and comprehensive social security, both high parental income and education were associated with lower mortality after childhood cancer. Lower health literacy and financial pressures limiting treatment adherence may explain higher mortality in children with less educated parents and parents with lower income. Motivation and support during treatment and follow-up period is needed concerning the families of these patients.

Predictive value of C-reactive protein/albumin ratio in acute pancreatitis.

PubMed

Kaplan, Mustafa; Ates, Ihsan; Akpinar, Muhammed Yener; Yuksel, Mahmut; Kuzu, Ufuk Baris; Kacar, Sabite; Coskun, Orhan; Kayacetin, Ertugrul

2017-08-15

Serum C-reactive protein (CRP) increases and albumin decreases in patients with inflammation and infection. However, their role in patients with acute pancreatitis is not clear. The present study was to investigate the predictive significance of the CRP/albumin ratio for the prognosis and mortality in acute pancreatitis patients. This study was performed retrospectively with 192 acute pancreatitis patients between January 2002 and June 2015. Ranson scores, Atlanta classification and CRP/albumin ratios of the patients were calculated. The CRP/albumin ratio was higher in deceased patients compared to survivors. The CRP/albumin ratio was positively correlated with Ranson score and Atlanta classification in particular and with important prognostic markers such as hospitalization time, CRP and erythrocyte sedimentation rate. In addition to the CRP/albumin ratio, necrotizing pancreatitis type, moderately severe and severe Atlanta classification, and total Ranson score were independent risk factors of mortality. It was found that an increase of 1 unit in the CRP/albumin ratio resulted in an increase of 1.52 times in mortality risk. A prediction value about CRP/albumin ratio >16.28 was found to be a significant marker in predicting mortality with 92.1% sensitivity and 58.0% specificity. It was seen that Ranson and Atlanta classification were higher in patients with CRP/albumin ratio >16.28 compared with those with CRP/albumin ratio ≤16.28. Patients with CRP/albumin ratio >16.28 had a 19.3 times higher chance of death. The CRP/albumin ratio is a novel but promising, easy-to-measure, repeatable, non-invasive inflammation-based prognostic score in acute pancreatitis. Copyright © 2017 The Editorial Board of Hepatobiliary & Pancreatic Diseases International. Published by Elsevier B.V. All rights reserved.

Heart rate turbulence predicts ICD-resistant mortality in ischaemic heart disease.

PubMed

Marynissen, Thomas; Floré, Vincent; Heidbuchel, Hein; Nuyens, Dieter; Ector, Joris; Willems, Rik

2014-07-01

In high-risk patients, implantable cardioverter-defibrillators (ICDs) can convert the mode of death from arrhythmic to pump failure death. Therefore, we introduced the concept of 'ICD-resistant mortality' (IRM), defined as death (a) without previous appropriate ICD intervention (AI), (b) within 1 month after the first AI, or (c) within 1 year after the initial ICD implantation. Implantable cardioverter-defibrillator implantation in patients with a high risk of IRM should be avoided. Implantable cardioverter-defibrillator patients with ischaemic heart disease were included if a digitized 24 h Holter was available pre-implantation. Demographic, electrocardiographic, echocardiographic, and 24 h Holter risk factors were collected at device implantation. The primary endpoint was IRM. Cox regression analyses were used to test the association between predictors and outcome. We included 130 patients, with a mean left ventricular ejection fraction (LVEF) of 33.6 ± 10.3%. During a follow-up of 52 ± 31 months, 33 patients died. There were 21 cases of IRM. Heart rate turbulence (HRT) was the only Holter parameter associated with IRM and total mortality. A higher New York Heart Association (NYHA) class and a lower body mass index were the strongest predictors of IRM. Left ventricular ejection fraction predicted IRM on univariate analysis, and was the strongest predictor of total mortality. The only parameter that predicted AI was non-sustained ventricular tachycardia. Implantable cardioverter-defibrillator implantation based on NYHA class and LVEF leads to selection of patients with a higher risk of IRM and death. Heart rate turbulence may have added value for the identification of poor candidates for ICD therapy. Available Holter parameters seem limited in their ability to predict AI. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2013. For permissions please email: journals.permissions@oup.com.

Clinical Utility of Five Genetic Variants for Predicting Prostate Cancer Risk and Mortality

PubMed Central

Salinas, Claudia A.; Koopmeiners, Joseph S.; Kwon, Erika M.; FitzGerald, Liesel; Lin, Daniel W.; Ostrander, Elaine A.; Feng, Ziding; Stanford, Janet L.

2009-01-01

Background A recent report suggests that the combination of five single-nucleotide polymorphisms (SNPs) at 8q24, 17q12, 17q24.3 and a family history of the disease may predict risk of prostate cancer. The present study tests the performance of these factors in prediction models for prostate cancer risk and prostate cancer-specific mortality. Methods SNPs were genotyped in population-based samples from Caucasians in King County, Washington. Incident cases (n=1308), aged 35–74, were compared to age-matched controls (n=1266) using logistic regression to estimate odds ratios (OR) associated with genotypes and family history. Cox proportional hazards models estimated hazard ratios for prostate cancer-specific mortality according to genotypes. Results The combination of SNP genotypes and family history was significantly associated with prostate cancer risk (ptrend=1.5 × 10−20). Men with ≥ five risk factors had an OR of 4.9 (95% CI 1.6 to 18.5) compared to men with none. However, this combination of factors did not improve the ROC curve after accounting for known risk predictors (i.e., age, serum PSA, family history). Neither the individual nor combined risk factors was associated with prostate cancer-specific mortality. Conclusion Genotypes for five SNPs plus family history are associated with a significant elevation in risk for prostate cancer and may explain up to 45% of prostate cancer in our population. However, they do not improve prediction models for assessing who is at risk of getting or dying from the disease, once known risk or prognostic factors are taken into account. Thus, this SNP panel may have limited clinical utility. PMID:19058137

Prognostic and Pathogenetic Value of Combining Clinical and Biochemical Indices in Patients With Acute Lung Injury

PubMed Central

Koyama, Tatsuki; Billheimer, D. Dean; Wu, William; Bernard, Gordon R.; Thompson, B. Taylor; Brower, Roy G.; Standiford, Theodore J.; Martin, Thomas R.; Matthay, Michael A.

2010-01-01

Background: No single clinical or biologic marker reliably predicts clinical outcomes in acute lung injury (ALI)/ARDS. We hypothesized that a combination of biologic and clinical markers would be superior to either biomarkers or clinical factors alone in predicting ALI/ARDS mortality and would provide insight into the pathogenesis of clinical ALI/ARDS. Methods: Eight biologic markers that reflect endothelial and epithelial injury, inflammation, and coagulation (von Willebrand factor antigen, surfactant protein D [SP-D]), tumor necrosis factor receptor-1, interleukin [IL]-6, IL-8, intercellular adhesion molecule-1, protein C, plasminogen activator inhibitor-1) were measured in baseline plasma from 549 patients in the ARDSNet trial of low vs high positive end-expiratory pressure. Mortality was modeled with multivariable logistic regression. Predictors were selected using backward elimination. Comparisons between candidate models were based on the receiver operating characteristics (ROC) and tests of integrated discrimination improvement. Results: Clinical predictors (Acute Physiology And Chronic Health Evaluation III [APACHE III], organ failures, age, underlying cause, alveolar-arterial oxygen gradient, plateau pressure) predicted mortality with an area under the ROC curve (AUC) of 0.82; a combination of eight biomarkers and the clinical predictors had an AUC of 0.85. The best performing biomarkers were the neutrophil chemotactic factor, IL-8, and SP-D, a product of alveolar type 2 cells, supporting the concept that acute inflammation and alveolar epithelial injury are important pathogenetic pathways in human ALI/ARDS. Conclusions: A combination of biomarkers and clinical predictors is superior to clinical predictors or biomarkers alone for predicting mortality in ALI/ARDS and may be useful for stratifying patients in clinical trials. From a pathogenesis perspective, the degree of acute inflammation and alveolar epithelial injury are highly associated with the outcome of human ALI/ARDS. PMID:19858233

Telemetry-based mortality estimates of juvenile spot in two North Carolina estuarine creeks

USGS Publications Warehouse

Friedl, Sarah E.; Buckel, Jeffery A.; Hightower, Joseph E.; Scharf, Frederick S.; Pollock, Kenneth H.

2013-01-01

We estimated natural mortality rates (M) of age-1 Spot Leiostomus xanthurus by using a sonic telemetry approach. Sonic transmitters were surgically implanted into a total of 123 age-1 Spot in two North Carolina estuarine creeks during spring 2009 and 2010, and the fish were monitored by using a stationary acoustic receiver array and manual tracking. Fates of telemetered Spot were inferred based on telemetry information from estimated locations and swimming speeds. Potential competitors of age-1 Spot were assessed through simultaneous otter trawl sampling, while potential predators of Spot were collected using gill nets and trammel nets. The number of inferred natural mortalities was zero in 2009 (based on 29 telemetered Spot at risk) and four in 2010 (based on 52 fish at risk), with fish being at risk for up to about 70 d each year. Catches of potential competitors or predators did not differ between years, and age-1 Spot were not found in analyzed stomach contents of potential predators. Our estimated 30-d M of 0.03 (95% credible interval = 0.01–0.07) was lower than that predicted from weight-based (M = 0.07) and life-history-based (M = 0.06–0.36) estimates. Our field-based estimate of M for age-1 Spot in this estuarine system can assist in the assessment and management of Spot by allowing a direct comparison with M-values predicted from fish size or life history characteristics. The field telemetry and statistical analysis techniques developed here provide guidance for future telemetry studies of relatively small fish in open, dynamic habitat systems, as they highlight strengths and weaknesses of using a telemetry approach to estimate M.

Serial evaluation of the MODS, SOFA and LOD scores to predict ICU mortality in mixed critically ill patients.

PubMed

Khwannimit, Bodin

2008-09-01

To perform a serial assessment and compare ability in predicting the intensive care unit (ICU) mortality of the multiple organ dysfunction score (MODS), sequential organ failure assessment (SOFA) and logistic organ dysfunction (LOD) score. The data were collected prospectively on consecutive ICU admissions over a 24-month period at a tertiary referral university hospital. The MODS, SOFA, and LOD scores were calculated on initial and repeated every 24 hrs. Two thousand fifty four patients were enrolled in the present study. The maximum and delta-scores of all the organ dysfunction scores correlated with ICU mortality. The maximum score of all models had better ability for predicting ICU mortality than initial or delta score. The areas under the receiver operating characteristic curve (AUC) for maximum scores was 0.892 for the MODS, 0.907 for the SOFA, and 0.92for the LOD. No statistical difference existed between all maximum scores and Acute Physiology and Chronic Health Evaluation II (APACHE II) score. Serial assessment of organ dysfunction during the ICU stay is reliable with ICU mortality. The maximum scores is the best discrimination comparable with APACHE II score in predicting ICU mortality.

Chronic Conditions and Mortality Among the Oldest Old

PubMed Central

Lee, Sei J.; Go, Alan S.; Lindquist, Karla; Bertenthal, Daniel; Covinsky, Kenneth E.

2008-01-01

Objectives. We sought to determine whether chronic conditions and functional limitations are equally predictive of mortality among older adults. Methods. Participants in the 1998 wave of the Health and Retirement Study (N=19430) were divided into groups by decades of age, and their vital status in 2004 was determined. We used multivariate Cox regression to determine the ability of chronic conditions and functional limitations to predict mortality. Results. As age increased, the ability of chronic conditions to predict mortality declined rapidly, whereas the ability of functional limitations to predict mortality declined more slowly. In younger participants (aged 50–59 years), chronic conditions were stronger predictors of death than were functional limitations (Harrell C statistic 0.78 vs. 0.73; P=.001). In older participants (aged 90–99 years), functional limitations were stronger predictors of death than were chronic conditions (Harrell C statistic 0.67 vs. 0.61; P=.004). Conclusions. The importance of chronic conditions as a predictor of death declined rapidly with increasing age. Therefore, risk-adjustment models that only consider comorbidities when comparing mortality rates across providers may be inadequate for adults older than 80 years. PMID:18511714

Alcohol dependence and physical comorbidity: Increased prevalence but reduced relevance of individual comorbidities for hospital-based mortality during a 12.5-year observation period in general hospital admissions in urban North-West England.

PubMed

Schoepf, D; Heun, R

2015-06-01

Alcohol dependence (AD) is associated with an increase in physical comorbidities. The effects of these diseases on general hospital-based mortality are unclear. Consequently, we conducted a mortality study in which we investigated if the burden of physical comorbidities and their relevance on general hospital-based mortality differs between individuals with and without AD during a 12.5-year observation period in general hospital admissions. During 1 January 2000 and 30 June 2012, 23,371 individuals with AD were admitted at least once to seven General Manchester Hospitals. Their physical comorbidities with a prevalence≥1% were compared to those of 233,710 randomly selected hospital controls, group-matched for age and gender (regardless of primary admission diagnosis or specialized treatments). Physical comorbidities that increased the risk of hospital-based mortality (but not outside of the hospital) during the observation period were identified using multiple logistic regression analyses. Hospital-based mortality rates were 20.4% in the AD sample and 8.3% in the control sample. Individuals with AD compared to controls had a higher burden of physical comorbidities, i.e. alcoholic liver and pancreatic diseases, diseases of the conducting airways, neurological and circulatory diseases, diseases of the upper gastrointestinal tract, renal diseases, cellulitis, iron deficiency anemia, fracture neck of femur, and peripheral vascular disease. In contrast, coronary heart related diseases, risk factors of cardiovascular disease, diverticular disease and cataracts were less frequent in individuals with AD than in controls. Thirty-two individual physical comorbidities contributed to the prediction of hospital-based mortality in univariate analyses in the AD sample; alcoholic liver disease (33.7%), hypertension (16.9%), chronic obstructive pulmonary disease (14.1%), and pneumonia (13.3%) were the most frequent diagnoses in deceased individuals with AD. Multiple forward logistic regression analysis, accounting for possible associations of diseases, identified twenty-three physical comorbidities contributing to hospital-based mortality in individuals with AD. However, all these comorbidities had an equal or even lower impact on hospital-based mortality than in the comparison sample. The excess of in-hospital deaths in general hospitals in individuals with AD is due to an increase of multiple physical comorbidities, even though individual diseases have an equal or even reduced impact on general hospital-based mortality in individuals with AD compared to controls. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Risk adjusted surgical audit in gynaecological oncology: P-POSSUM does not predict outcome.

PubMed

Das, N; Talaat, A S; Naik, R; Lopes, A D; Godfrey, K A; Hatem, M H; Edmondson, R J

2006-12-01

To assess the Physiological and Operative Severity Score for the enumeration of mortality and morbidity (POSSUM) and its validity for use in gynaecological oncology surgery. All patients undergoing gynaecological oncology surgery at the Northern Gynaecological Oncology Centre (NGOC) Gateshead, UK over a period of 12months (2002-2003) were assessed prospectively. Mortality and morbidity predictions using the Portsmouth modification of the POSSUM algorithm (P-POSSUM) were compared to the actual outcomes. Performance of the model was also evaluated using the Hosmer and Lemeshow Chi square statistic (testing the goodness of fit). During this period 468 patients were assessed. The P-POSSUM appeared to over predict mortality rates for our patients. It predicted a 7% mortality rate for our patients compared to an observed rate of 2% (35 predicted deaths in comparison to 10 observed deaths), a difference that was statistically significant (H&L chi(2)=542.9, d.f. 8, p<0.05). The P-POSSUM algorithm overestimates the risk of mortality for gynaecological oncology patients undergoing surgery. The P-POSSUM algorithm will require further adjustments prior to adoption for gynaecological cancer surgery as a risk adjusted surgical audit tool.

Predicting mortality over different time horizons: which data elements are needed?

PubMed

Goldstein, Benjamin A; Pencina, Michael J; Montez-Rath, Maria E; Winkelmayer, Wolfgang C

2017-01-01

Electronic health records (EHRs) are a resource for "big data" analytics, containing a variety of data elements. We investigate how different categories of information contribute to prediction of mortality over different time horizons among patients undergoing hemodialysis treatment. We derived prediction models for mortality over 7 time horizons using EHR data on older patients from a national chain of dialysis clinics linked with administrative data using LASSO (least absolute shrinkage and selection operator) regression. We assessed how different categories of information relate to risk assessment and compared discrete models to time-to-event models. The best predictors used all the available data (c-statistic ranged from 0.72-0.76), with stronger models in the near term. While different variable groups showed different utility, exclusion of any particular group did not lead to a meaningfully different risk assessment. Discrete time models performed better than time-to-event models. Different variable groups were predictive over different time horizons, with vital signs most predictive for near-term mortality and demographic and comorbidities more important in long-term mortality. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

An Emergency Department Validation of the SEP-3 Sepsis and Septic Shock Definitions and Comparison With 1992 Consensus Definitions.

PubMed

Henning, Daniel J; Puskarich, Michael A; Self, Wesley H; Howell, Michael D; Donnino, Michael W; Yealy, Donald M; Jones, Alan E; Shapiro, Nathan I

2017-10-01

The Third International Consensus Definitions Task Force (SEP-3) proposed revised criteria defining sepsis and septic shock. We seek to evaluate the performance of the SEP-3 definitions for prediction of inhospital mortality in an emergency department (ED) population and compare the performance of the SEP-3 definitions to that of the previous definitions. This was a secondary analysis of 3 prospectively collected, observational cohorts of infected ED subjects aged 18 years or older. The primary outcome was all-cause inhospital mortality. In accordance with the SEP-3 definitions, we calculated test characteristics of sepsis (quick Sequential Organ Failure Assessment [qSOFA] score ≥2) and septic shock (vasopressor dependence plus lactate level >2.0 mmol/L) for mortality and compared them to the original 1992 consensus definitions. We identified 7,754 ED patients with suspected infection overall; 117 had no documented mental status evaluation, leaving 7,637 patients included in the analysis. The mortality rate for the overall population was 4.4% (95% confidence interval [CI] 3.9% to 4.9%). The mortality rate for patients with qSOFA score greater than or equal to 2 was 14.2% (95% CI 12.2% to 16.2%), with a sensitivity of 52% (95% CI 46% to 57%) and specificity of 86% (95% CI 85% to 87%) to predict mortality. The original systemic inflammatory response syndrome-based 1992 consensus sepsis definition had a 6.8% (95% CI 6.0% to 7.7%) mortality rate, sensitivity of 83% (95% CI 79% to 87%), and specificity of 50% (95% CI 49% to 51%). The SEP-3 septic shock mortality was 23% (95% CI 16% to 30%), with a sensitivity of 12% (95% CI 11% to 13%) and specificity of 98.4% (95% CI 98.1% to 98.7%). The original 1992 septic shock definition had a 22% (95% CI 17% to 27%) mortality rate, sensitivity of 23% (95% CI 18% to 28%), and specificity of 96.6% (95% CI 96.2% to 97.0%). Both the new SEP-3 and original sepsis definitions stratify ED patients at risk for mortality, albeit with differing performances. In terms of mortality prediction, the SEP-3 definitions had improved specificity, but at the cost of sensitivity. Use of either approach requires a clearly intended target: more sensitivity versus specificity. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

A contemporary risk model for predicting 30-day mortality following percutaneous coronary intervention in England and Wales.

PubMed

McAllister, Katherine S L; Ludman, Peter F; Hulme, William; de Belder, Mark A; Stables, Rodney; Chowdhary, Saqib; Mamas, Mamas A; Sperrin, Matthew; Buchan, Iain E

2016-05-01

The current risk model for percutaneous coronary intervention (PCI) in the UK is based on outcomes of patients treated in a different era of interventional cardiology. This study aimed to create a new model, based on a contemporary cohort of PCI treated patients, which would: predict 30 day mortality; provide good discrimination; and be well calibrated across a broad risk-spectrum. The model was derived from a training dataset of 336,433 PCI cases carried out between 2007 and 2011 in England and Wales, with 30 day mortality provided by record linkage. Candidate variables were selected on the basis of clinical consensus and data quality. Procedures in 2012 were used to perform temporal validation of the model. The strongest predictors of 30-day mortality were: cardiogenic shock; dialysis; and the indication for PCI and the degree of urgency with which it was performed. The model had an area under the receiver operator characteristic curve of 0.85 on the training data and 0.86 on validation. Calibration plots indicated a good model fit on development which was maintained on validation. We have created a contemporary model for PCI that encompasses a range of clinical risk, from stable elective PCI to emergency primary PCI and cardiogenic shock. The model is easy to apply and based on data reported in national registries. It has a high degree of discrimination and is well calibrated across the risk spectrum. The examination of key outcomes in PCI audit can be improved with this risk-adjusted model. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

POSSUM and P-POSSUM for risk assessment in general surgery in the elderly.

PubMed

Igari, Kimihiro; Ochiai, Takanori; Yamazaki, Shigeru

2013-09-01

The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) and Portsmouth POSSUM (P-POSSUM) use preoperative and intraoperative factors to evaluate risk. We examined our surgical results to investigate predictive factors for morbidity and mortality, and evaluate the accuracy of the POSSUM and P-POSSUM. Patients (n = 593) aged ≥80 years, undergoing general surgical procedures were enrolled. Logistic regression analysis was used to determine the independent predictors. The predicted outcomes using POSSUM and P-POSSUM were also compared with actual outcomes. Physiological score (PS) and operative severity score (OS) were independent predictors of morbidity and mortality. Using POSSUM, the observed/expected (O/E) morbidity ratio was 1.44 and O/E mortality ratio was 0.98. Using P-POSSUM, the O/E mortality ratio was 1.0. Even though POSSUM tended to underestimate the morbidity rate, POSSUM and P-POSSUM accurately predicted the mortality rate after general surgical procedures.

Plant hydraulics improves and topography mediates prediction of aspen mortality in southwestern USA.

PubMed

Tai, Xiaonan; Mackay, D Scott; Anderegg, William R L; Sperry, John S; Brooks, Paul D

2017-01-01

Elevated forest mortality has been attributed to climate change-induced droughts, but prediction of spatial mortality patterns remains challenging. We evaluated whether introducing plant hydraulics and topographic convergence-induced soil moisture variation to land surface models (LSM) can help explain spatial patterns of mortality. A scheme predicting plant hydraulic safety loss from soil moisture was developed using field measurements and a plant physiology-hydraulics model, TREES. The scheme was upscaled to Populus tremuloides forests across Colorado, USA, using LSM-modeled and topography-mediated soil moisture, respectively. The spatial patterns of hydraulic safety loss were compared against aerial surveyed mortality. Incorporating hydraulic safety loss raised the explanatory power of mortality by 40% compared to LSM-modeled soil moisture. Topographic convergence was mostly influential in suppressing mortality in low and concave areas, explaining an additional 10% of the variations in mortality for those regions. Plant hydraulics integrated water stress along the soil-plant continuum and was more closely tied to plant physiological response to drought. In addition to the well-recognized topo-climate influence due to elevation and aspect, we found evidence that topographic convergence mediates tree mortality in certain parts of the landscape that are low and convergent, likely through influences on plant-available water. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

A new approach on seismic mortality estimations based on average population density

NASA Astrophysics Data System (ADS)

Zhu, Xiaoxin; Sun, Baiqing; Jin, Zhanyong

2016-12-01

This study examines a new methodology to predict the final seismic mortality from earthquakes in China. Most studies established the association between mortality estimation and seismic intensity without considering the population density. In China, however, the data are not always available, especially when it comes to the very urgent relief situation in the disaster. And the population density varies greatly from region to region. This motivates the development of empirical models that use historical death data to provide the path to analyze the death tolls for earthquakes. The present paper employs the average population density to predict the final death tolls in earthquakes using a case-based reasoning model from realistic perspective. To validate the forecasting results, historical data from 18 large-scale earthquakes occurred in China are used to estimate the seismic morality of each case. And a typical earthquake case occurred in the northwest of Sichuan Province is employed to demonstrate the estimation of final death toll. The strength of this paper is that it provides scientific methods with overall forecast errors lower than 20 %, and opens the door for conducting final death forecasts with a qualitative and quantitative approach. Limitations and future research are also analyzed and discussed in the conclusion.

Brainstem response patterns in deeply-sedated critically-ill patients predict 28-day mortality.

PubMed

Rohaut, Benjamin; Porcher, Raphael; Hissem, Tarik; Heming, Nicholas; Chillet, Patrick; Djedaini, Kamel; Moneger, Guy; Kandelman, Stanislas; Allary, Jeremy; Cariou, Alain; Sonneville, Romain; Polito, Andréa; Antona, Marion; Azabou, Eric; Annane, Djillali; Siami, Shidasp; Chrétien, Fabrice; Mantz, Jean; Sharshar, Tarek

2017-01-01

Deep sedation is associated with acute brain dysfunction and increased mortality. We had previously shown that early-assessed brainstem reflexes may predict outcome in deeply sedated patients. The primary objective was to determine whether patterns of brainstem reflexes might predict mortality in deeply sedated patients. The secondary objective was to generate a score predicting mortality in these patients. Observational prospective multicenter cohort study of 148 non-brain injured deeply sedated patients, defined by a Richmond Assessment sedation Scale (RASS) <-3. Brainstem reflexes and Glasgow Coma Scale were assessed within 24 hours of sedation and categorized using latent class analysis. The Full Outline Of Unresponsiveness score (FOUR) was also assessed. Primary outcome measure was 28-day mortality. A "Brainstem Responses Assessment Sedation Score" (BRASS) was generated. Two distinct sub-phenotypes referred as homogeneous and heterogeneous brainstem reactivity were identified (accounting for respectively 54.6% and 45.4% of patients). Homogeneous brainstem reactivity was characterized by preserved reactivity to nociceptive stimuli and a partial and topographically homogenous depression of brainstem reflexes. Heterogeneous brainstem reactivity was characterized by a loss of reactivity to nociceptive stimuli associated with heterogeneous brainstem reflexes depression. Heterogeneous sub-phenotype was a predictor of increased risk of 28-day mortality after adjustment to Simplified Acute Physiology Score-II (SAPS-II) and RASS (Odds Ratio [95% confidence interval] = 6.44 [2.63-15.8]; p<0.0001) or Sequential Organ Failure Assessment (SOFA) and RASS (OR [95%CI] = 5.02 [2.01-12.5]; p = 0.0005). The BRASS (and marginally the FOUR) predicted 28-day mortality (c-index [95%CI] = 0.69 [0.54-0.84] and 0.65 [0.49-0.80] respectively). In this prospective cohort study, around half of all deeply sedated critically ill patients displayed an early particular neurological sub-phenotype predicting 28-day mortality, which may reflect a dysfunction of the brainstem.

Alcoholic hepatitis histological score has high accuracy to predict 90-day mortality and response to steroids.

PubMed

Andrade, Patrícia; Silva, Marco; Rodrigues, Susana; Lopes, Joanne; Lopes, Susana; Macedo, Guilherme

2016-06-01

A histological classification system (AHHS) has been recently proposed to predict 90-day mortality in patients with alcoholic hepatitis (AH). We analyzed the spectrum of histological features in patients with AH and assessed the ability of AHHS for predicting both response to steroids and 90-day mortality. Retrospective study of patients admitted to our tertiary centre between 2010 and 2014 with biopsy-proven AH. Histological features were analyzed and AHHS value was calculated. Kaplan-Meyer curves were calculated to assess the ability of AHHS to predict response to steroids and 90-day mortality. We included 34 patients (70.6% men, mean age 48.5±8.9 years). Transjugular liver biopsy was performed 3.5±2.9 days after admission. Presence of bilirubinostasis (p=0.049), degree of bilirubinostasis (p<0.001), absence of megamitochondria (p<0.001) and degree of polymorphonuclear infiltration (p=0.018) were significantly associated with higher mortality at 90 days. Patients who responded to steroids had a significantly lower AHHS value than non-responders (5.4±0.9 vs 8.1±1.1, p=0.003). AAHS value was significantly higher in patients who died compared to patients who survived at 90 days (9.0±0.7 vs 5.0±0.9, p<0.001). AHHS predicted response to steroids [AUROC 0.90 (CI95% 0.742-1.000), p=0.004] and 90-day mortality [AUROC 1.0 (CI95% 1.0-1.0), p<0.001] with high accuracy. In this cohort of patients, presence and degree of bilirubinostasis, absence of megamitochondria and degree of PMN infiltration were significantly associated with 90-day mortality. AHHS had a high accuracy for predicting response to steroids and 90-day mortality in this cohort of patients. Copyright © 2016 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Left ventricular ejection fraction to predict early mortality in patients with non-ST-segment elevation acute coronary syndromes.

PubMed

Bosch, Xavier; Théroux, Pierre

2005-08-01

Improvement in risk stratification of patients with non-ST-segment elevation acute coronary syndrome (ACS) is a gateway to a more judicious treatment. This study examines whether the routine determination of left ventricular ejection fraction (EF) adds significant prognostic information to currently recommended stratifiers. Several predictors of inhospital mortality were prospectively characterized in a registry study of 1104 consecutive patients, for whom an EF was determined, who were admitted for an ACS. Multiple regression models were constructed using currently recommended clinical, electrocardiographic, and blood marker stratifiers, and values of EF were incorporated into the models. Age, ST-segment shifts, elevation of cardiac markers, and the Thrombolysis in Myocardial Infarction (TIMI) risk score all predicted mortality (P < .0001). Adding EF into the model improved the prediction of mortality (C statistic 0.73 vs 0.67). The odds of death increased by a factor of 1.042 for each 1% decrement in EF. By receiver operating curves, an EF cutoff of 48% provided the best predictive value. Mortality rates were 3.3 times higher within each TIMI risk score stratum in patients with an EF of 48% or lower as compared with those with higher. The TIMI risk score predicts inhospital mortality in a broad population of patients with ACS. The further consideration of EF adds significant prognostic information.

Frailty Index Developed From a Cancer-Specific Geriatric Assessment and the Association With Mortality Among Older Adults With Cancer.

PubMed

Guerard, Emily J; Deal, Allison M; Chang, YunKyung; Williams, Grant R; Nyrop, Kirsten A; Pergolotti, Mackenzi; Muss, Hyman B; Sanoff, Hanna K; Lund, Jennifer L

2017-07-01

Background: An objective measure is needed to identify frail older adults with cancer who are at increased risk for poor health outcomes. The primary objective of this study was to develop a frailty index from a cancer-specific geriatric assessment (GA) and evaluate its ability to predict all-cause mortality among older adults with cancer. Patients and Methods: Using a unique and novel data set that brings together GA data with cancer-specific and long-term mortality data, we developed the Carolina Frailty Index (CFI) from a cancer-specific GA based on the principles of deficit accumulation. CFI scores (range, 0-1) were categorized as robust (0-0.2), pre-frail (0.2-0.35), and frail (>0.35). The primary outcome for evaluating predictive validity was all-cause mortality. The Kaplan-Meier method and log-rank tests were used to compare survival between frailty groups, and Cox proportional hazards regression models were used to evaluate associations. Results: In our sample of 546 older adults with cancer, the median age was 72 years, 72% were women, 85% were white, and 47% had a breast cancer diagnosis. Overall, 58% of patients were robust, 24% were pre-frail, and 18% were frail. The estimated 5-year survival rate was 72% in robust patients, 58% in pre-frail patients, and 34% in frail patients (log-rank test, P <.0001). Frail patients had more than a 2-fold increased risk of all-cause mortality compared with robust patients (adjusted hazard ratio, 2.36; 95% CI, 1.51-3.68). Conclusions: The CFI was predictive of all-cause mortality in older adults with cancer, a finding that was independent of age, sex, cancer type and stage, and number of medical comorbidities. The CFI has the potential to become a tool that oncologists can use to objectively identify frailty in older adults with cancer. Copyright © 2017 by the National Comprehensive Cancer Network.

[Prediction of mortality in patients with acute hepatic failure].

PubMed

Eremeeva, L F; Berdnikov, A P; Musaeva, T S; Zabolotskikh, I B

2013-01-01

The article deals with a study of 243 patients (from 18 to 65 years old) with acute hepatic failure. Purpose of the study was to evaluate the predictive capability of severity scales APACHE III, SOFA, MODS, Child-Pugh and to identify mortality predictors in patients with acute hepatic failure. Results; The best predictive ability in patients with acute hepatic failure and multiple organ failure had APACHE III and SOFA scales. The strongest mortality predictors were: serum creatinine > 132 mmol/L, fibrinogen < 1.4 g/L, Na < 129 mmol/L.

Upper gastrointestinal bleeding in patients with hepatic cirrhosis: clinical course and mortality prediction.

PubMed

Afessa, B; Kubilis, P S

2000-02-01

We conducted this study to describe the complications and validate the accuracy of previously reported prognostic indices in predicting the mortality of cirrhotic patients hospitalized for upper GI bleeding. This prospective, observational study included 111 consecutive hospitalizations of 85 cirrhotic patients admitted for GI bleeding. Data obtained included intensive care unit (ICU) admission status, Child-Pugh score, the development of systemic inflammatory response syndrome (SIRS), organ failure, and inhospital mortality. The performances of Garden's, Gatta's, and Acute Physiology and Chronic Health Evaluation (APACHE) II prognostic systems in predicting mortality were assessed. Patients' mean age was 48.7 yr, and the median APACHE II and Child-Pugh scores were 17 and 9, respectively. Their ICU admission rate was 71%. Organ failure developed in 57%, and SIRS in 46% of the patients. Nine patients had acute respiratory distress syndrome, and three patients had hepatorenal syndrome. The inhospital mortality was 21%. The APACHE II, Garden's, and Gatta' s predicted mortality rates were 39%, 24%, and 20%, respectively, and their areas under the receiver operating characteristic curve (AUC) were 0.78, 0.70, and 0.71, respectively. The AUC for Child-Pugh score was 0.76. SIRS and organ failure develop in many patients with hepatic cirrhosis hospitalized for upper GI bleeding, and are associated with increased mortality. Although the APACHE II prognostic system overestimated the mortality of these patients, the receiver operating characteristic curves did not show significant differences between the various prognostic systems.

A decision tree to assess short-term mortality after an emergency department visit for an exacerbation of COPD: a cohort study.

PubMed

Esteban, Cristóbal; Arostegui, Inmaculada; Garcia-Gutierrez, Susana; Gonzalez, Nerea; Lafuente, Iratxe; Bare, Marisa; Fernandez de Larrea, Nerea; Rivas, Francisco; Quintana, José M

2015-12-22

Creating an easy-to-use instrument to identify predictors of short-term (30/60-day) mortality after an exacerbation of chronic obstructive pulmonary disease (eCOPD) could help clinicians choose specific measures of medical care to decrease mortality in these patients. The objective of this study was to develop and validate a classification and regression tree (CART) to predict short term mortality among patients evaluated in an emergency department (ED) for an eCOPD. We conducted a prospective cohort study including participants from 16 hospitals in Spain. COPD patients with an exacerbation attending the emergency department (ED) of any of the hospitals between June 2008 and September 2010 were recruited. Patients were randomly divided into derivation (50%) and validation samples (50%). A CART based on a recursive partitioning algorithm was created in the derivation sample and applied to the validation sample. Two thousand four hundred eighty-seven patients, 1252 patients in the derivation sample and 1235 in the validation sample, were enrolled in the study. Based on the results of the univariate analysis, five variables (baseline dyspnea, cardiac disease, the presence of paradoxical breathing or use of accessory inspiratory muscles, age, and Glasgow Coma Scale score) were used to build the CART. Mortality rates 30 days after discharge ranged from 0% to 55% in the five CART classes. The lowest mortality rate was for the branch composed of low baseline dyspnea and lack of cardiac disease. The highest mortality rate was in the branch with the highest baseline dyspnea level, use of accessory inspiratory muscles or paradoxical breathing upon ED arrival, and Glasgow score <15. The area under the receiver-operating curve (AUC) in the derivation sample was 0.835 (95% CI: 0.783, 0.888) and 0.794 (95% CI: 0.723, 0.865) in the validation sample. CART was improved to predict 60-days mortality risk by adding the Charlson Comorbidity Index, reaching an AUC in the derivation sample of 0.817 (95% CI: 0.776, 0.859) and 0.770 (95% CI: 0.716, 0.823) in the validation sample. We identified several easy-to-determine variables that allow clinicians to classify eCOPD patients by short term mortality risk, which can provide useful information for establishing appropriate clinical care. NCT02434536.

Patient survival and surgical re-intervention predictors for intracapsular hip fractures.

PubMed

González Quevedo, David; Mariño, Iskandar Tamimi; Sánchez Siles, Juan Manuel; Escribano, Esther Romero; Granero Molina, Esther Judith; Enrique, David Bautista; Smoljanović, Tomislav; Pareja, Francisco Villanueva

2017-08-01

Choosing between total hip replacement (THR) and partial hip replacement (PHR) for patients with intracapsular hip fractures is often based on subjective factors. Predicting the survival of these patients and risk of surgical re-intervention is essential to select the most adequate implant. We conducted a retrospective cohort study on mortality of patients over 70 years with intracapsular hip fractures who were treated between January 2010 and December 2013, with either PHR or THR. Patients' information was withdrawn from our local computerized database. The age-adjusted Charlson comorbidity index (ACCI) and American Society of Anesthesiologists (ASA) score were calculated for all patients. The patients were followed for 2 years after surgery. Survival and surgical re-intervention rates were compared between the two groups using a Multivariate Cox proportional hazard model. A total of 356 individuals were included in this study. At 2 years of follow-up, 221 (74.4%) of the patients with ACCI score≤7 were still alive, in contrast to only 20 (29.0%) of those with ACCI score>7. In addition, 201 (76.2%) of the patients with ASA score≤3 were still alive after 2 years, compared to 30 (32.6%) of individuals with ASA >3. Patients with the ACCI score>7, and ASA score>3 had a significant increase in all-cause 2-year mortality (adjusted hazard ratio of 3.2, 95% CI 2.2-4.6; and 3.12, 95% CI 2.2-4.5, respectively). Patients with an ASA score>3 had a quasi-significant increase in the re-intervention risk (adjusted hazard ratio 2.2, 95% CI 1.0-5.1). The sensitivity, specificity, positive predictive value and negative predictive values of ACCI in predicting 2-year mortality were 39.2%, 91.1%, 71%, and 74.4%, respectively. On the other hand, the sensitivity, specificity, positive predictive value and negative predictive values of ASA score in predicting 2-year mortality were 49.6%, 79.1%, 67.4%, and 76.1%, respectively. Both ACCI and ASA scales were able to predict the 2-year survival of patients with intracapsular hip fractures. The ASA scale was also able to predict the risk of re-intervention in these patients. Copyright © 2017 Elsevier Ltd. All rights reserved.

All-Cause Mortality for Life Insurance Applicants with a History of Prostate Cancer.

PubMed

Freitas, Stephen A; MacKenzie, Ross; Wylde, David N; Roudebush, Bradley T; Bergstrom, Richard L; Holowaty, J Carl; Beckman, Margaret; Rigatti, Steven J; Gill, Stacy

2017-01-01

- To determine the all-cause mortality of life insurance applicants diagnosed with prostate cancer currently or at some time in the past. - Prostate cancer is common and a frequent cause of cancer death. Both the frequency of prostate cancer in men and its propensity for causing premature mortality require insurance company medical directors and underwriters to have a good understanding of prostate cancer-related mortality trends, patterns, and outcomes in the insured population. - Life insurance applicants with reported prostate cancer were extracted from data covering United States residents between November 2007 and November 2014. Information about these applicants was matched to the Social Security Death Master (SSDMF) file for deaths occurring from 2007 to 2011 and to another commercially available death source file (Other Death Source, ODS) for deaths occurring from 2007 to 2014 to determine vital status. Actual to Expected (A/E) mortality ratios were calculated using the Society of Actuaries 2015 Valuation Basic Table (2015VBT), select and ultimate table (age last birthday) and the 2013 US population as expected mortality ratios. All expected bases were not smoker distinct. - The study covered applicants between the ages of 45 and 75 and had approximately 405,000 person-years of exposure. Older aged applicants had a lower mortality ratio than those who were younger. Applicants 45 to 54 had the highest mortality ratios in the first year after diagnosis which steadily decreased in years 6 to 10 with an increase in the mortality ratio for those over 10 years from diagnosis. Relative mortality rate was close to unity for those with localized cancer across all age groups. The mortality ratio was 2 to 4 times greater for those with cancer in 1 positive node, and much greater with 3 positive nodes. For each time-from-diagnosis category, the relative mortality ratios compared to age were highest in the 45-54 age group. The A/E mortality ratios based on the 2015VBT were consistently 3 to 4 times that of the mortality ratios based on the 2013 US population. - The mortality patterns of insurance applicants with prostate cancer were similar to that observed in individuals with prostate cancer in the general population. Applicant age, time to diagnosis and cancer severity were the most significant variables to predict mortality.

Mortality Prediction in the Oldest Old with Five Different Equations to Estimate Glomerular Filtration Rate: The Health and Anemia Population-based Study

PubMed Central

Mandelli, Sara; Riva, Emma; Tettamanti, Mauro; Detoma, Paolo; Giacomin, Adriano; Lucca, Ugo

2015-01-01

Background Kidney function declines considerably with age, but little is known about its clinical significance in the oldest-old. Objectives To study the association between reduced glomerular filtration rate (GFR) estimated according to five equations with mortality in the oldest-old. Design Prospective population-based study. Setting Municipality of Biella, Piedmont, Italy. Participants 700 subjects aged 85 and older participating in the “Health and Anemia” Study in 2007–2008. Measurements GFR was estimated using five creatinine-based equations: the Cockcroft-Gault (C-G), Modification of Diet in Renal Disease (MDRD), MAYO Clinic, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Berlin Initiative Study-1 (BIS-1). Survival analysis was used to study mortality in subjects with reduced eGFR (<60 mL/min/1.73m2) compared to subjects with eGFR ≥60 mL/min/1.73m2. Results Prevalence of reduced GFR was 90.7% with the C-G, 48.1% with MDRD, 23.3% with MAYO, 53.6% with CKD-EPI and 84.4% with BIS-1. After adjustment for confounders, two-year mortality was significantly increased in subjects with reduced eGFR using BIS-1 and C-G equations (adjusted HRs: 2.88 and 3.30, respectively). Five-year mortality was significantly increased in subjects with eGFR <60 mL/min/1.73m2 using MAYO, CKD-EPI and, in a graduated fashion in reduced eGFR categories, MDRD. After 5 years, oldest old with an eGFR <30 mL/min/1.73m2 showed a significantly higher risk of death whichever equation was used (adjusted HRs between 2.04 and 2.70). Conclusion In the oldest old, prevalence of reduced eGFR varies noticeably depending on the equation used. In this population, risk of mortality was significantly higher for reduced GFR estimated with the BIS-1 and C-G equations over the short term. Though after five years the MDRD appeared on the whole a more consistent predictor, differences in mortality prediction among equations over the long term were less apparent. Noteworthy, subjects with a severely reduced GFR were consistently at higher risk of death regardless of the equation used to estimate GFR. PMID:26317988

Mortality Prediction in the Oldest Old with Five Different Equations to Estimate Glomerular Filtration Rate: The Health and Anemia Population-based Study.

PubMed

Mandelli, Sara; Riva, Emma; Tettamanti, Mauro; Detoma, Paolo; Giacomin, Adriano; Lucca, Ugo

2015-01-01

Kidney function declines considerably with age, but little is known about its clinical significance in the oldest-old. To study the association between reduced glomerular filtration rate (GFR) estimated according to five equations with mortality in the oldest-old. Prospective population-based study. Municipality of Biella, Piedmont, Italy. 700 subjects aged 85 and older participating in the "Health and Anemia" Study in 2007-2008. GFR was estimated using five creatinine-based equations: the Cockcroft-Gault (C-G), Modification of Diet in Renal Disease (MDRD), MAYO Clinic, Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Berlin Initiative Study-1 (BIS-1). Survival analysis was used to study mortality in subjects with reduced eGFR (<60 mL/min/1.73 m(2)) compared to subjects with eGFR ≥ 60 mL/min/1.73 m(2). Prevalence of reduced GFR was 90.7% with the C-G, 48.1% with MDRD, 23.3% with MAYO, 53.6% with CKD-EPI and 84.4% with BIS-1. After adjustment for confounders, two-year mortality was significantly increased in subjects with reduced eGFR using BIS-1 and C-G equations (adjusted HRs: 2.88 and 3.30, respectively). Five-year mortality was significantly increased in subjects with eGFR <60 mL/min/1.73 m(2) using MAYO, CKD-EPI and, in a graduated fashion in reduced eGFR categories, MDRD. After 5 years, oldest old with an eGFR <30 mL/min/1.73 m(2) showed a significantly higher risk of death whichever equation was used (adjusted HRs between 2.04 and 2.70). In the oldest old, prevalence of reduced eGFR varies noticeably depending on the equation used. In this population, risk of mortality was significantly higher for reduced GFR estimated with the BIS-1 and C-G equations over the short term. Though after five years the MDRD appeared on the whole a more consistent predictor, differences in mortality prediction among equations over the long term were less apparent. Noteworthy, subjects with a severely reduced GFR were consistently at higher risk of death regardless of the equation used to estimate GFR.

The AIMS65 score compared with the Glasgow-Blatchford score in predicting outcomes in upper GI bleeding.

PubMed

Hyett, Brian H; Abougergi, Marwan S; Charpentier, Joseph P; Kumar, Navin L; Brozovic, Suzana; Claggett, Brian L; Travis, Anne C; Saltzman, John R

2013-04-01

We previously derived and validated the AIMS65 score, a mortality prognostic scale for upper GI bleeding (UGIB). To validate the AIMS65 score in a different patient population and compare it with the Glasgow-Blatchford risk score (GBRS). Retrospective cohort study. Adults with a primary diagnosis of UGIB. inpatient mortality. composite clinical endpoint of inpatient mortality, rebleeding, and endoscopic, radiologic or surgical intervention; blood transfusion; intensive care unit admission; rebleeding; length of stay; timing of endoscopy. The area under the receiver-operating characteristic curve (AUROC) was calculated for each score. Of the 278 study patients, 6.5% died and 35% experienced the composite clinical endpoint. The AIMS65 score was superior in predicting inpatient mortality (AUROC, 0.93 vs 0.68; P < .001), whereas the GBRS was superior in predicting blood transfusions (AUROC, 0.85 vs 0.65; P < .01) The 2 scores were similar in predicting the composite clinical endpoint (AUROC, 0.62 vs 0.68; P = .13) as well as the secondary outcomes. A GBRS of 10 and 12 or more maximized the sum of the sensitivity and specificity for inpatient mortality and rebleeding, respectively. The cutoff was 2 or more for the AIMS65 score for both outcomes. Retrospective, single-center study. The AIMS65 score is superior to the GBRS in predicting inpatient mortality from UGIB, whereas the GBRS is superior for predicting blood transfusion. Both scores are similar in predicting the composite clinical endpoint and other outcomes in clinical care and resource use. Copyright © 2013 American Society for Gastrointestinal Endoscopy. Published by Mosby, Inc. All rights reserved.

Size-related mortality due to gnathiid isopod micropredation correlates with settlement size in coral reef fishes

NASA Astrophysics Data System (ADS)

Grutter, A. S.; Blomberg, S. P.; Fargher, B.; Kuris, A. M.; McCormick, M. I.; Warner, R. R.

2017-06-01

The transition between the planktonic and the benthic habitat is a critical period for the larvae of many demersal marine organisms. Understanding the potential constraints on the timing of this habitat transition, called settlement, is important to understanding their biology. Size-specific mortality can set the limits on lifestyle and help explain ontogenetic habitat shifts. We examined whether size-based mortality risks after settlement may include micropredation by ectoparasites by testing whether survival of settlement-stage fish varies with fish size when exposed to a reef-associated micropredator. Fish (14 species) were exposed to one blood-sucking gnathiid isopod overnight, with appropriate controls; gnathiid feeding success and survival, and fish mortality were recorded relative to fish size. After adjusting for fish relatedness, we found the relationship between fish mortality and size differed with gnathiid exposure: for gnathiid-exposed fish, the mean mortality of the smallest fish was much higher (57%) than unexposed controls (10%), and decreased to 0% for fish >12 mm standard length (SL); mortality was almost nil in controls. Thus, a predicted optimal size to switch habitat and reduce mortality risk from micropredation should be >12 mm SL. We then asked what species might be at greater risk and if the steep increase in survival at 12 mm SL might coincide with settlement at larger sizes among fishes. Across 102 other species (32 families), 61% settled at ≥12 mm SL. After adjusting for relatedness, mean fish settlement size was 15.0 mm and this was not significantly different from 12 mm. Thus, settlement size clusters around the minimum fish size threshold our gnathiid experiment predicted would be large enough to survive a gnathiid encounter. These results suggest micropredators may contribute to size-selective mortality during settlement processes and are consistent with the hypothesis that the pelagic phase provides fish an escape from certain micropredators.

Post-fire Tree Mortality: Heating Increases Vulnerability to Cavitation in Longleaf Pine Branches

NASA Astrophysics Data System (ADS)

Lodge, A.; Kavanagh, K.; Dickinson, M. B.

2016-12-01

Tree mortality following wild and prescribed fires is of interest to both researchers and land managers. While some models exist that can predict mortality following fires, process-based models that incorporate physiological mechanisms of mortality are still being developed and improved. Delayed post-fire tree mortality has recently received increased attention, in part due to an increased use of prescribed fire as a restoration and management tool. One hypothesized mechanism of delayed mortality in trees is disruption of water transport in xylem due to exposure to the heat plume of a fire. This heat plume rapidly increases the vapor pressure deficit in the tree canopy, quickly increasing the tension on the water held in the xylem and leaves, potentially leading to cavitation. Cavitated xylem conduits can no longer transport water, eventually leading to tree death. We conducted a laboratory experiment examining whether heating stems increases their vulnerability to cavitation. We placed longleaf pine (Pinus palustris) branches in a water bath at sub-lethal temperatures (<60°C) and applied pressure in a cavitation chamber to simulate a range of xylem tension levels that may occur during fire. Percent loss of conductivity was measured following cavitation induced by various levels of applied pressure. When we compared the resulting vulnerability curves of heated branches to those of branches pressurized at room temperature, we observed increased vulnerability to cavitation in the heated samples especially at lower pressures. P50, or the pressure at which 50% of conductivity has been lost, decreased by 18% on branches heated to approximately 54°C. This suggests that stems heated during fires may be more vulnerable to cavitation, and provides some support for hydraulic disruption as a mechanism for post-fire tree mortality. Continued advancement in understanding of the mechanisms leading to delayed mortality will improve models predicting tree mortality.

Applying Latent Class Analysis to Risk Stratification for Perioperative Mortality in Patients Undergoing Intraabdominal General Surgery.

PubMed

Kim, Minjae; Wall, Melanie M; Li, Guohua

2016-07-01

Perioperative risk stratification is often performed using individual risk factors without consideration of the syndemic of these risk factors. We used latent class analysis (LCA) to identify the classes of comorbidities and risk factors associated with perioperative mortality in patients presenting for intraabdominal general surgery. The 2005 to 2010 American College of Surgeons National Surgical Quality Improvement Program was used to obtain a cohort of patients undergoing intraabdominal general surgery. Risk factors and comorbidities were entered into LCA models to identify the latent classes, and individuals were assigned to a class based on the highest posterior probability of class membership. Relative risk regression was used to determine the associations between the latent classes and 30-day mortality, with adjustments for procedure. A 9-class model was fit using LCA on 466,177 observations. After combining classes with similar adjusted mortality risks, 5 risk classes were obtained. Compared with the class with average mortality risk (class 4), the risk ratios (95% confidence interval) ranged from 0.020 (0.014-0.027) in the lowest risk class (class 1) to 6.75 (6.46-7.02) in the highest risk class. After adjusting for procedure and ASA physical status, the latent classes remained significantly associated with 30-day mortality. The addition of the risk class variable to a model containing ASA physical status and surgical procedure demonstrated a significant increase in the area under the receiver operator characteristic curve (0.892 vs 0.915; P < 0.0001). Latent classes of risk factors and comorbidities in patients undergoing intraabdominal surgery are predictive of 30-day mortality independent of the ASA physical status and improve risk prediction with the ASA physical status.

The evaluation of acute physiology and chronic health evaluation II score, poisoning severity score, sequential organ failure assessment score combine with lactate to assess the prognosis of the patients with acute organophosphate pesticide poisoning.

PubMed

Yuan, Shaoxin; Gao, Yusong; Ji, Wenqing; Song, Junshuai; Mei, Xue

2018-05-01

The aim of this study was to assess the ability of acute physiology and chronic health evaluation II (APACHE II) score, poisoning severity score (PSS) as well as sequential organ failure assessment (SOFA) score combining with lactate (Lac) to predict mortality in the Emergency Department (ED) patients who were poisoned with organophosphate.A retrospective review of 59 stands-compliant patients was carried out. Receiver operating characteristic (ROC) curves were constructed based on the APACHE II score, PSS, SOFA score with or without Lac, respectively, and the areas under the ROC curve (AUCs) were determined to assess predictive value. According to SOFA-Lac (a combination of SOFA and Lac) classification standard, acute organophosphate pesticide poisoning (AOPP) patients were divided into low-risk and high-risk groups. Then mortality rates were compared between risk levels.Between survivors and non-survivors, there were significant differences in the APACHE II score, PSS, SOFA score, and Lac (all P < .05). The AUCs of the APACHE II score, PSS, and SOFA score were 0.876, 0.811, and 0.837, respectively. However, after combining with Lac, the AUCs were 0.922, 0.878, and 0.956, respectively. According to SOFA-Lac, the mortality of high-risk group was significantly higher than low-risk group (P < .05) and the patients of the non-survival group were all at high risk.These data suggest the APACHE II score, PSS, SOFA score can all predict the prognosis of AOPP patients. For its simplicity and objectivity, the SOFA score is a superior predictor. Lac significantly improved the predictive abilities of the 3 scoring systems, especially for the SOFA score. The SOFA-Lac system effectively distinguished the high-risk group from the low-risk group. Therefore, the SOFA-Lac system is significantly better at predicting mortality in AOPP patients.

The AIMS65 Score Is a Useful Predictor of Mortality in Patients with Nonvariceal Upper Gastrointestinal Bleeding: Urgent Endoscopy in Patients with High AIMS65 Scores

PubMed Central

Park, Sun Wook; Song, Young Wook; Tak, Dae Hyun; Ahn, Byung Moo; Kang, Sun Hyung; Moon, Hee Seok; Sung, Jae Kyu; Jeong, Hyun Yong

2015-01-01

Background/Aims: To validate the AIMS65 score for predicting mortality of patients with nonvariceal upper gastrointestinal bleeding and to evaluate the effectiveness of urgent (<8 hours) endoscopic procedures in patients with high AIMS65 scores. Methods: This was a 5-year single-center, retrospective study. Nonvariceal, upper gastrointestinal bleeding was assessed by using the AIM65 and Rockall scores. Scores for mortality were assessed by calculating the area under the receiver-operating characteristic curve (AUROC). Patients with high AIMS65 scores (≥2) were allocated to either the urgent or non-urgent endoscopic procedure group. In-hospital mortality, success of endoscopic procedure, recurrence of bleeding, admission period, and dose of transfusion were compared between groups. Results: A total of 634 patients were analyzed. The AIMS65 score successfully predicted mortality (AUROC=0.943; 95% confidence interval [CI], 0.876 to 0.99) and was superior to the Rockall score (AUROC=0.856; 95% CI, 0.743 to 0.969) in predicting mortality. The group with high AIMS65 score included 200 patients. The urgent endoscopic procedure group had reduced hospitalization periods (p<0.05) Conclusions: AIMS65 score may be useful in predicting mortality in patients with nonvariceal upper gastrointestinal bleeding. Urgent endoscopic procedures in patients with high scores may be related to reduced hospitalization periods. PMID:26668799

Utility of Cardiac Troponin to Predict Drug Overdose Mortality

PubMed Central

Stimmel, Barry; Hoffman, Robert S.; Vlahov, David

2016-01-01

Drug overdose is now the leading cause of injury-related mortality in the USA, but the prognostic utility of cardiac biomarkers is unknown. We investigated whether serum cardiac troponin I (cTnI) was associated with overdose mortality. This prospective observational cohort studied adults with suspected acute drug overdose at two university hospital emergency departments (ED) over 3 years. The endpoint was in-hospital mortality, which was used to determine test characteristics of initial/peak cTnI. There were 437 overdoses analyzed, of whom there were 20 (4.6 %) deaths. Mean initial cTnI was significantly associated with mortality (1.2 vs. 0.06 ng/mL, p <0.001), and the ROC curve revealed excellent cTnI prediction of mortality (AUC 0.87, CI 0.76–0.98). Test characteristics for initial cTnI (90 % specificity, 99 % negative predictive value) were better than peak cTnI (88.2 % specificity, 99.2 % negative predictive value), and initial cTnI was normal in only one death out of the entire cohort (1/437, CI 0.1–1.4 %). Initial cTnI results were highly associated with drug overdose mortality. Future research should focus on high-risk overdose features to optimize strategies for utilization of cTnI as part of the routine ED evaluation for acute drug overdose. PMID:26541348

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients

PubMed Central

Hayano, Junichiro; Yasuma, Fumihiko; Watanabe, Eiichi; Carney, Robert M.; Stein, Phyllis K.; Blumenthal, James A.; Arsenos, Petros; Gatzoulis, Konstantinos A.; Takahashi, Hiroshi; Ishii, Hideki; Kiyono, Ken; Yamamoto, Yoshiharu; Yoshida, Yutaka; Yuda, Emi; Kodama, Itsuo

2017-01-01

Abstract Aims Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. Methods and results CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2–3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4–2.2], P < 0.001), ESRD (1.5 [1.3–1.8], P < 0.001), and CHF (1.4 [1.1–1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, β-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. Conclusion Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients. PMID:27789562

Predicting the mortality in geriatric patients with dengue fever

PubMed Central

Huang, Hung-Sheng; Hsu, Chien-Chin; Ye, Je-Chiuan; Su, Shih-Bin; Huang, Chien-Cheng; Lin, Hung-Jung

2017-01-01

Abstract Geriatric patients have high mortality for dengue fever (DF); however, there is no adequate method to predict mortality in geriatric patients. Therefore, we conducted this study to develop a tool in an attempt to address this issue. We conducted a retrospective case–control study in a tertiary medical center during the DF outbreak in Taiwan in 2015. All the geriatric patients (aged ≥65 years) who visited the study hospital between September 1, 2015, and December 31, 2015, were recruited into this study. Variables included demographic data, vital signs, symptoms and signs, comorbidities, living status, laboratory data, and 30-day mortality. We investigated independent mortality predictors by univariate analysis and multivariate logistic regression analysis and then combined these predictors to predict the mortality. A total of 627 geriatric DF patients were recruited, with a mortality rate of 4.3% (27 deaths and 600 survivals). The following 4 independent mortality predictors were identified: severe coma [Glasgow Coma Scale: ≤8; adjusted odds ratio (AOR): 11.36; 95% confidence interval (CI): 1.89–68.19], bedridden (AOR: 10.46; 95% CI: 1.58–69.16), severe hepatitis (aspartate aminotransferase >1000 U/L; AOR: 96.08; 95% CI: 14.11–654.40), and renal failure (serum creatinine >2 mg/dL; AOR: 6.03; 95% CI: 1.50–24.24). When we combined the predictors, we found that the sensitivity, specificity, positive predictive value, and negative predictive value for patients with 1 or more predictors were 70.37%, 88.17%, 21.11%, and 98.51%, respectively. For patients with 2 or more predictors, the respective values were 33.33%, 99.44%, 57.14%, and 98.51%. We developed a new method to help decision making. Among geriatric patients with none of the predictors, the survival rate was 98.51%, and among those with 2 or more predictors, the mortality rate was 57.14%. This method is simple and useful, especially in an outbreak. PMID:28906367

Blunted cyclic variation of heart rate predicts mortality risk in post-myocardial infarction, end-stage renal disease, and chronic heart failure patients.

PubMed

Hayano, Junichiro; Yasuma, Fumihiko; Watanabe, Eiichi; Carney, Robert M; Stein, Phyllis K; Blumenthal, James A; Arsenos, Petros; Gatzoulis, Konstantinos A; Takahashi, Hiroshi; Ishii, Hideki; Kiyono, Ken; Yamamoto, Yoshiharu; Yoshida, Yutaka; Yuda, Emi; Kodama, Itsuo

2017-08-01

Cyclic variation of heart rate (CVHR) associated with sleep-disordered breathing is thought to reflect cardiac autonomic responses to apnoeic/hypoxic stress. We examined whether blunted CVHR observed in ambulatory ECG could predict the mortality risk. CVHR in night-time Holter ECG was detected by an automated algorithm, and the prognostic relationships of the frequency (FCV) and amplitude (ACV) of CVHR were examined in 717 patients after myocardial infarction (post-MI 1, 6% mortality, median follow-up 25 months). The predictive power was prospectively validated in three independent cohorts: a second group of 220 post-MI patients (post-MI 2, 25.5% mortality, follow-up 45 months); 299 patients with end-stage renal disease on chronic haemodialysis (ESRD, 28.1% mortality, follow-up 85 months); and 100 patients with chronic heart failure (CHF, 35% mortality, follow-up 38 months). Although CVHR was observed in ≥96% of the patients in all cohorts, FCV did not predict mortality in any cohort. In contrast, decreased ACV was a powerful predictor of mortality in the post-MI 1 cohort (hazard ratio [95% CI] per 1 ln [ms] decrement, 2.9 [2.2-3.7], P < 0.001). This prognostic relationship was validated in the post-MI 2 (1.8 [1.4-2.2], P < 0.001), ESRD (1.5 [1.3-1.8], P < 0.001), and CHF (1.4 [1.1-1.8], P = 0.02) cohorts. The prognostic value of ACV was independent of age, gender, diabetes, β-blocker therapy, left ventricular ejection fraction, sleep-time mean R-R interval, and FCV. Blunted CVHR detected by decreased ACV in a night-time Holter ECG predicts increased mortality risk in post-MI, ESRD, and CHF patients. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Cardiology.

Predicting the mortality in geriatric patients with dengue fever.

PubMed

Huang, Hung-Sheng; Hsu, Chien-Chin; Ye, Je-Chiuan; Su, Shih-Bin; Huang, Chien-Cheng; Lin, Hung-Jung

2017-09-01

Geriatric patients have high mortality for dengue fever (DF); however, there is no adequate method to predict mortality in geriatric patients. Therefore, we conducted this study to develop a tool in an attempt to address this issue.We conducted a retrospective case-control study in a tertiary medical center during the DF outbreak in Taiwan in 2015. All the geriatric patients (aged ≥65 years) who visited the study hospital between September 1, 2015, and December 31, 2015, were recruited into this study. Variables included demographic data, vital signs, symptoms and signs, comorbidities, living status, laboratory data, and 30-day mortality. We investigated independent mortality predictors by univariate analysis and multivariate logistic regression analysis and then combined these predictors to predict the mortality.A total of 627 geriatric DF patients were recruited, with a mortality rate of 4.3% (27 deaths and 600 survivals). The following 4 independent mortality predictors were identified: severe coma [Glasgow Coma Scale: ≤8; adjusted odds ratio (AOR): 11.36; 95% confidence interval (CI): 1.89-68.19], bedridden (AOR: 10.46; 95% CI: 1.58-69.16), severe hepatitis (aspartate aminotransferase >1000 U/L; AOR: 96.08; 95% CI: 14.11-654.40), and renal failure (serum creatinine >2 mg/dL; AOR: 6.03; 95% CI: 1.50-24.24). When we combined the predictors, we found that the sensitivity, specificity, positive predictive value, and negative predictive value for patients with 1 or more predictors were 70.37%, 88.17%, 21.11%, and 98.51%, respectively. For patients with 2 or more predictors, the respective values were 33.33%, 99.44%, 57.14%, and 98.51%.We developed a new method to help decision making. Among geriatric patients with none of the predictors, the survival rate was 98.51%, and among those with 2 or more predictors, the mortality rate was 57.14%. This method is simple and useful, especially in an outbreak.

A comparison of three organ dysfunction scores: MODS, SOFA and LOD for predicting ICU mortality in critically ill patients.

PubMed

Khwannimit, Bodin

2007-06-01

To compare the validity of the Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), and Logistic Organ Dysfunction Score (LOD) for predicting ICU mortality of Thai critically ill patients. A retrospective study was made of prospective data collected between the 1st July 2004 and 31st March 2006 at Songklanagarind Hospital. One thousand seven hundred and eighty two patients were enrolled in the present study. Two hundred and ninety three (16.4%) deaths were recorded in the ICU. The areas under the Receiver Operating Curves (A UC) for the prediction of ICU mortality the results were 0.861 for MODS, 0.879 for SOFA and 0.880 for LOD. The AUC of SOFA and LOD showed a statistical significance higher than the MODS score (p = 0.014 and p = 0.042, respectively). Of all the models, the neurological failure score showed the best correlation with ICU mortality. All three organ dysfunction scores satisfactorily predicted ICU mortality. The LOD and neurological failure had the best correlation with ICU outcome.

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

PubMed

Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

2010-01-01

The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75). We have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

Brain age predicts mortality

PubMed Central

Cole, J H; Ritchie, S J; Bastin, M E; Valdés Hernández, M C; Muñoz Maniega, S; Royle, N; Corley, J; Pattie, A; Harris, S E; Zhang, Q; Wray, N R; Redmond, P; Marioni, R E; Starr, J M; Cox, S R; Wardlaw, J M; Sharp, D J; Deary, I J

2018-01-01

Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, ‘brain-predicted age’, derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. Having a brain-predicted age indicative of an older-appearing brain was associated with: weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk. Furthermore, while combining brain-predicted age with grey matter and cerebrospinal fluid volumes (themselves strong predictors) not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death. PMID:28439103

Loss of life expectancy derived from a standardized mortality ratio in Denmark, Finland, Norway and Sweden.

PubMed

Skriver, Mette Vinther; Væth, Michael; Støvring, Henrik

2018-01-01

The standardized mortality ratio (SMR) is a widely used measure. A recent methodological study provided an accurate approximate relationship between an SMR and difference in lifetime expectancies. This study examines the usefulness of the theoretical relationship, when comparing historic mortality data in four Scandinavian populations. For Denmark, Finland, Norway and Sweden, data on mortality every fifth year in the period 1950 to 2010 were obtained. Using 1980 as the reference year, SMRs and difference in life expectancy were calculated. The assumptions behind the theoretical relationship were examined graphically. The theoretical relationship predicts a linear association with a slope, [Formula: see text], between log(SMR) and difference in life expectancies, and the theoretical prediction and calculated differences in lifetime expectancies were compared. We examined the linear association both for life expectancy at birth and at age 30. All analyses were done for females, males and the total population. The approximate relationship provided accurate predictions of actual differences in lifetime expectancies. The accuracy of the predictions was better when age was restricted to above 30, and improved if the changes in mortality rate were close to a proportional change. Slopes of the linear relationship were generally around 9 for females and 10 for males. The theoretically derived relationship between SMR and difference in life expectancies provides an accurate prediction for comparing populations with approximately proportional differences in mortality, and was relatively robust. The relationship may provide a useful prediction of differences in lifetime expectancies, which can be more readily communicated and understood.

Trends and predictions to 2020 in breast cancer mortality in Europe.

PubMed

Carioli, Greta; Malvezzi, Matteo; Rodriguez, Teresa; Bertuccio, Paola; Negri, Eva; La Vecchia, Carlo

2017-12-01

We analyzed trends in mortality from breast cancer in women in 36 European countries and the European Union (EU) over the period 1970-2014, and predicted numbers of deaths and rates to 2020. We derived breast cancer death certification data and population figures from the World Health Organization and Eurostat databases. We obtained 2020 estimates using a joinpoint regression model. Overall, EU breast cancer mortality rates (world standard) declined from 17.9/100,000 in 2002 to 15.2 in 2012. The predicted 2020 rate is 13.4/100,000. The falls were largest in young women (20-49 years, -22% between 2002 and 2012). Within the EU, declines were larger in the United Kingdom (UK) and other northern and western European countries than in most central and eastern Europe. The UK has the second lowest predicted breast cancer mortality rate in 2020 (after Spain), starting from the highest one in 1970. Breast cancer mortality is predicted to rise in Poland, where the predicted 2020 rate is 15.3/100,000. We estimated that about 32,500 breast cancer deaths will be avoided in 2020 in the EU as compared to the peak rate of 1989, and a total of 475,000 breast cancer deaths over the period 1990-2020. The overall favourable breast cancer mortality trends are mainly due to a succession of improvements in the management and treatment of breast cancer, though early diagnosis and screening played a role, too. Improving breast cancer management in central and eastern Europe is a priority. Copyright © 2017 Elsevier Ltd. All rights reserved.

POSTERIOR PREDICTIVE MODEL CHECKS FOR DISEASE MAPPING MODELS. (R827257)

EPA Science Inventory

Disease incidence or disease mortality rates for small areas are often displayed on maps. Maps of raw rates, disease counts divided by the total population at risk, have been criticized as unreliable due to non-constant variance associated with heterogeneity in base population si...

The Ecohydrological Context of Drought and Classification of Plant Responses

NASA Astrophysics Data System (ADS)

Feng, X.; Ackerly, D.; Dawson, T. E.; Manzoni, S.; Skelton, R. P.; Vico, G.; Thompson, S. E.

2017-12-01

Many recent studies on drought-induced vegetation mortality have explored how plant functional traits, and classifications of such traits along axes of, e.g., isohydry - anisohydry, might contribute to predicting drought survival and recovery. As these studies proliferate, concerns are growing about the consistency and predictive value of such classifications. Here, we outline the basis for a systematic classification of drought strategies that accounts for both environmental conditions and functional traits. We (1) identify drawbacks of exiting isohydricity and trait-based metrics, (2) identify major axes of trait and environmental variation that determine drought mortality pathways (hydraulic failure and carbon starvation) using non-dimensional trait groups, and (3) demonstrate that these trait groupings predict physiological drought outcomes using both measured and synthetic data. In doing so we untangle some confounding effects of environment and trait variations that undermine current classification schemes, outline a pathway to progress towards a general classification of drought vulnerability, and advocate for more careful treatment of the environmental conditions within which plant drought responses occur.

Postfire mortality of ponderosa pine and Douglas-fir: a review of methods to predict tree death

Treesearch

James F. Fowler; Carolyn Hull Sieg

2004-01-01

This review focused on the primary literature that described, modeled, or predicted the probability of postfire mortality in ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii). The methods and measurements that were used to predict postfire tree death tended to fall into two general categories: those focusing...

Improving longleaf pine mortality predictions in the Southern Variant of the Forest Vegetation Simulator

Treesearch

R. Justin DeRose; John D. Shaw; Giorgio Vacchiano; James N. Long

2008-01-01

The Southern Variant of the Forest Vegetation Simulator (FVS-SN) is made up of individual submodels that predict tree growth, recruitment and mortality. Forest managers on Ft. Bragg, North Carolina, discovered biologically unrealistic longleaf pine (Pinus palustris) size-density predictions at large diameters when using FVS-SN to project red-cockaded...

Drought impact on vegetation growth and mortality

NASA Astrophysics Data System (ADS)

Xu, C.; Wang, M.; Allen, C. D.; McDowell, N. G.; Middleton, R. S.

2017-12-01

Vegetation is a key regulator of the global carbon cycle via CO2 absorption through photosynthesis and subsequent growth; however, low water availability, heat stress, and disturbances associated with droughts could substantially reduce vegetation growth and increase vegetation mortality. As far as we know, there are few studies have assessed the drought impact on vegetation growth and mortality at regional and global scales. In this study, we analyzed 13 Earth System models (ESMs) to quantify the impact of drought on GPP and linked the remote-sensing based tree mortality to observed drought indices to assess the drought impact on tree mortality in continental US (CONUS). Our analysis of 13 Earth System models (ESMs) shows that the average global gross primary production (GPP) reduction per year associated with extreme droughts over years 2075-2099 is predicted to be 3-5 times larger than that over years 1850-1999. The annual drought-associated reduction in GPP over years 2075-2099 could be 52 and 74 % of annual fossil fuel carbon emission during years 2000-2007. Increasing drought impacts on GPP are driven primarily by the increasing drought frequency. The risks of drought-associated GPP reduction are particularly high for temperate and tropical regions. The consistent prediction of higher drought-associated reduction in NPP across 13 ESMs suggests increasing impacts of drought on the global carbon cycle with atmospheric warming. Our analysis of drought impact on tree mortality showed that drought-associated carbon loss accounts for 12% of forest carbon loss in CONUS for 2000-2014, which is about one-fifth of that resulting from timber harvesting and 1.35 % of average annual fossil fuel emissions in the U.S. for the same period. The carbon stock loss from natural disturbances for 2000-2014 is approximately 75% of the total carbon loss from anthropogenic disturbance (timber harvesting), suggesting that natural disturbances play a very important role on forest carbon loss from dead trees. Our results clearly demonstrate the importance of drought impact on forest carbon stocks at the continental level and will provide critical data for future model improvement to better predict the vegetation mortality under droughts.

Associations of coronary artery calcified plaque density with mortality in type 2 diabetes: the Diabetes Heart Study.

PubMed

Raffield, Laura M; Cox, Amanda J; Criqui, Michael H; Hsu, Fang-Chi; Terry, James G; Xu, Jianzhao; Freedman, Barry I; Carr, J Jeffrey; Bowden, Donald W

2018-05-11

Coronary artery calcified plaque (CAC) is strongly predictive of cardiovascular disease (CVD) events and mortality, both in general populations and individuals with type 2 diabetes at high risk for CVD. CAC is typically reported as an Agatston score, which is weighted for increased plaque density. However, the role of CAC density in CVD risk prediction, independently and with CAC volume, remains unclear. We examined the role of CAC density in individuals with type 2 diabetes from the family-based Diabetes Heart Study and the African American-Diabetes Heart Study. CAC density was calculated as mass divided by volume, and associations with incident all-cause and CVD mortality [median follow-up 10.2 years European Americans (n = 902, n = 286 deceased), 5.2 years African Americans (n = 552, n = 93 deceased)] were examined using Cox proportional hazards models, independently and in models adjusted for CAC volume. In European Americans, CAC density, like Agatston score and volume, was consistently associated with increased risk of all-cause and CVD mortality (p ≤ 0.002) in models adjusted for age, sex, statin use, total cholesterol, HDL, systolic blood pressure, high blood pressure medication use, and current smoking. However, these associations were no longer significant when models were additionally adjusted for CAC volume. CAC density was not significantly associated with mortality, either alone or adjusted for CAC volume, in African Americans. CAC density is not associated with mortality independent from CAC volume in European Americans and African Americans with type 2 diabetes.

Hopelessly mortal: The role of mortality salience, immortality and trait self-esteem in personal hope.

PubMed

Wisman, Arnaud; Heflick, Nathan A

2016-08-01

Do people lose hope when thinking about death? Based on Terror Management Theory, we predicted that thoughts of death (i.e., mortality salience) would reduce personal hope for people low, but not high, in self-esteem, and that this reduction in hope would be ameliorated by promises of immortality. In Studies 1 and 2, mortality salience reduced personal hope for people low in self-esteem, but not for people high in self-esteem. In Study 3, mortality salience reduced hope for people low in self-esteem when they read an argument that there is no afterlife, but not when they read "evidence" supporting life after death. In Study 4, this effect was replicated with an essay affirming scientific medical advances that promise immortality. Together, these findings uniquely demonstrate that thoughts of mortality interact with trait self-esteem to cause changes in personal hope, and that literal immortality beliefs can aid psychological adjustment when thinking about death. Implications for understanding personal hope, trait self-esteem, afterlife beliefs and terror management are discussed.

The prognostic value of the strong ion gap in acute pancreatitis.

PubMed

Shen, Xiao; Ke, Lu; Yang, Dongliang; Sun, Jing; Tong, Zhihui; Li, Baiqiang; Li, Gang; Li, Weiqin; Li, Jieshou; Bellomo, Rinaldo

2016-12-01

In this study, we aimed to evaluate the predictive value of Stewart-derived parameters for the development of severe type of acute pancreatitis (AP) and for AP-related mortality. We studied 186 patients admitted to the hospital with AP. We performed blood gas and biochemical analysis for each patient on admission. We calculated multiple metrics according to the Stewart's acid-base theory and assessed their accuracy as predictors of AP severity and mortality. Of the 186 patients presenting with AP, 85 (45.7%) developed severe AP and 33 (17.7%) died during hospitalization. Patients with severe AP had significantly higher median strong ion gap (SIG) than did patients with mild or moderate AP (7.88 vs 2.11 mEq/L, P< .001). In multivariate logistic regression analysis, SIG had an odds ratio (OR) of 1.56 (P< .001). In addition, SIG had good predictive power for mortality (OR, 1.26; P= .014) as well as acute kidney injury (OR, 1.34; P< .001). In a cohort of patients with AP, SIG was a strong independent predictor of severity and mortality. Besides, SIG might also be an early marker for acute kidney injury in AP patients. Additional research is needed to identify the nature of the unmeasured anions responsible for such findings. Copyright © 2016 Elsevier Inc. All rights reserved.

Multifactorial Analysis of Mortality in Screening Detected Lung Cancer.

PubMed

Digumarthy, Subba R; De Man, Ruben; Canellas, Rodrigo; Otrakji, Alexi; Wang, Ge; Kalra, Mannudeep K

2018-01-01

We hypothesized that severity of coronary artery calcification (CAC), emphysema, muscle mass, and fat attenuation can help predict mortality in patients with lung cancer participating in the National Lung Screening Trial (NLST). Following regulatory approval from the Cancer Data Access System (CDAS), all patients diagnosed with lung cancer at the time of the screening study were identified. These subjects were classified into two groups: survivors and nonsurvivors at the conclusion of the NLST trial. These groups were matched based on their age, gender, body mass index (BMI), smoking history, lung cancer stage, and survival time. CAC, emphysema, muscle mass, and subcutaneous fat attenuation were quantified on baseline low-dose chest CT (LDCT) for all patients in both groups. Nonsurvivor group had significantly greater CAC, decreased muscle mass, and higher fat attenuation compared to the survivor group ( p < 0.01). No significant difference in severity of emphysema was noted between the two groups ( p > 0.1). We thus conclude that it is possible to create a quantitative prediction model for lung cancer mortality for subjects with lung cancer detected on screening low-dose CT (LDCT).

Pediatric intracranial gunshot wounds: the Memphis experience.

PubMed

DeCuypere, Michael; Muhlbauer, Michael S; Boop, Frederick A; Klimo, Paul

2016-05-01

OBJECTIVE Penetrating brain injury in civilians is much less common than blunt brain injury but is more severe overall. Gunshot wounds (GSWs) cause high morbidity and mortality related to penetrating brain injury; however, there are few reports on the management and outcome of intracranial GSWs in children. The goals of this study were to identify clinical and radiological factors predictive for death in children and to externally validate a recently proposed pediatric prognostic scale. METHODS The authors conducted a retrospective review of penetrating, isolated GSWs sustained in children whose ages ranged from birth to 18 years and who were treated at 2 major metropolitan Level 1 trauma centers from 1996 through 2013. Several standard clinical, laboratory, and radiological factors were analyzed for their ability to predict death in these patients. The authors then applied the St. Louis Scale for Pediatric Gunshot Wounds to the Head, a scoring algorithm that was designed to provide rapid prognostic information for emergency management decisions. The scale's sensitivity, specificity, and positive and negative predictability were determined, with death as the primary outcome. RESULTS Seventy-one children (57 male, 14 female) had a mean age of 14 years (range 19 months to 18 years). Overall mortality among these children was 47.9%, with 81% of survivors attaining a favorable clinical outcome (Glasgow Outcome Scale score ≥ 4). A number of predictors of mortality were identified (all p < 0.05): 1) bilateral fixed pupils; 2) deep nuclear injury; 3) transventricular projectile trajectory; 4) bihemispheric injury; 5) injury to ≥ 3 lobes; 6) systolic blood pressure < 100 mm Hg; 7) anemia (hematocrit < 30%); 8) Glasgow Coma Scale score ≤ 5; and 9) a blood base deficit < -5 mEq/L. Patient age, when converted to a categorical variable (0-9 or 10-18 years), was not predictive. Based on data from the 71 patients in this study, the positive predictive value of the St. Louis scale in predicting death (score ≥ 5) was 78%. CONCLUSIONS This series of pediatric cranial GSWs underscores the importance of the initial clinical exam and CT studies along with adequate resuscitation to make the appropriate management decision(s). Based on our population, the St. Louis Scale seems to be more useful as a predictor of who will survive than who will succumb to their injury.

Predictive Value of Matrix Metalloproteinases and Their Inhibitors for Mortality in Septic Patients: A Cohort Study.

PubMed

Serrano-Gomez, Sergio; Burgos-Angulo, Gabriel; Niño-Vargas, Daniela Camila; Niño, María Eugenia; Cárdenas, María Eugenia; Chacón-Valenzuela, Estephania; McCosham, Diana Margarita; Peinado-Acevedo, Juan Sebastián; Lopez, M Marcos; Cunha, Fernando; Pazin-Filho, Antonio; Ilarraza, Ramses; Schulz, Richard; Torres-Dueñas, Diego

2017-01-01

Over 170 biomarkers are being investigated regarding their prognostic and diagnostic accuracy in sepsis in order to find new tools to reduce morbidity and mortality. Matrix metalloproteinases (MMPs) and their inhibitors have been recently studied as promising new prognostic biomarkers in patients with sepsis. This study is aimed at determining the utility of several cutoff points of these biomarkers to predict mortality in patients with sepsis. A multicenter, prospective, analytic cohort study was performed in the metropolitan area of Bucaramanga, Colombia. A total of 289 patients with sepsis and septic shock were included. MMP-9, MMP-2, tissue inhibitor of metalloproteinase 1 (TIMP-1), TIMP-2, TIMP-1/MMP-9 ratio, and TIMP-2/MMP-2 ratio were determined in blood samples. Value ranges were correlated with mortality to estimate sensitivity, specificity, positive predictive value, negative predictive value, and area under the receiving operating characteristic curve. Sensitivity ranged from 33.3% (MMP-9/TIMP-1 ratio) to 60.6% (TIMP-1) and specificity varied from 38.8% (MMP-2/TIMP-2 ratio) to 58.5% (TIMP-1). As for predictive values, positive predictive value range was from 17.5% (MMP-9/TIMP-1 ratio) to 70.4% (MMP-2/TIMP-2 ratio), whereas negative predictive values were between 23.2% (MMP-2/TIMP-2 ratio) and 80.9% (TIMP-1). Finally, area under the curve scores ranged from 0.31 (MMP-9/TIMP-1 ratio) to 0.623 (TIMP-1). Although TIMP-1 showed higher sensitivity, specificity, and negative predictive value, with a representative population sample, we conclude that none of the evaluated biomarkers had significant predictive value for mortality.

Pulmonary function levels as predictors of mortality in a national sample of US adults.

PubMed

Neas, L M; Schwartz, J

1998-06-01

Single breath pulmonary diffusing capacity for carbon monoxide (DL(CO)) was examined as a predictor of all-cause mortality among 4,333 subjects who were aged 25-74 years at baseline in the First National Health and Nutrition Examination Survey (NHANES I) conducted from 1971 to 1975. The relation of the percentage of predicted DL(CO) to all-cause mortality was examined in a Cox proportional hazard model that included age, sex, race, current smoking status, systolic blood pressure, serum cholesterol, alcohol consumption, body mass index, percentage of predicted forced vital capacity (FVC), and the ratio of forced expiratory volume at 1 second (FEV1) to FVC. Mortality had a linear association with the percentage of predicted FVC (rate ratio (RR) = 1.12, 95% confidence interval (CI) 1.08-1.17, for a 10% decrement) and a significantly nonlinear association with the percentage of predicted DL(CO) with an adverse effect that was clearly evident for levels below 85% of those predicted (RR = 1.24, 95% CI 1.12-1.37 for a 10% decrement). The relative hazard for the percentage of predicted DL(CO) below 85% was not modified by sex, smoking status, or exclusion of subjects with clinical respiratory disease on the initial examination. This association with the percentage of predicted DL(CO) was present among 3,005 subjects with FEV1 levels above 90% of those predicted. Thus, pulmonary diffusing capacity below 85% of predicted levels is a significant predictor of the all-cause mortality rate within the general US population independent of standard spirometry measures and even in the absence of apparent clinical respiratory disease.

Short- and long-term major cardiovascular adverse events in carotid artery interventions: a nationwide population-based cohort study in Taiwan.

PubMed

Tsai, Ming-Lung; Mao, Chun-Tai; Chen, Dong-Yi; Hsieh, I-Chang; Wen, Ming-Shien; Chen, Tien-Hsing

2015-01-01

Carotid artery stenosis is one of the leading causes of ischemic stroke. Carotid artery stenting has become well-established as an effective treatment option for carotid artery stenosis. For this study, we aimed to determine the efficacy and safety of carotid stenting in a population-based large cohort of patients by analyzing the Taiwan National Healthcare Insurance (NHI) database. 2,849 patients who received carotid artery stents in the NHI database from 2004 to 2010 were identified. We analyzed the risk factors of outcomes including major adverse cardiovascular events including death, acute myocardial infarction, and cerebral vascular accidents at 30 days, 1 year, and overall period and further evaluated cause of death after carotid artery stenting. The periprocedural stroke rate was 2.7% and the recurrent stroke rate for the overall follow-up period was 20.3%. Male, diabetes mellitus, and heart failure were significant risk factors for overall recurrent stroke (Hazard Ratio (HR) = 1.35, p = 0.006; HR = 1.23, p = 0.014; HR = 1.61, p < 0.001, respectively). The periprocedural acute myocardial infarction rate was 0.3%. Age and Diabetes mellitus were the significant factors to predict periprocedural myocardial infarction (HR = 3.06, p = 0.019; HR = 1.68, p < 0.001, respectively). Periprocedural and overall mortality rates were 1.9% and 17.3%, respectively. The most significant periprocedural mortality risk factor was acute renal failure. Age, diabetes mellitus, acute or chronic renal failure, heart failure, liver disease, and malignancy were factors correlated to the overall period mortality. Periprocedural acute renal failure significantly increased the mortality rate and the number of major adverse cardiovascular events, and the predict power persisted more than one year after the procedure. Age and diabetes mellitus were significant risk factors to predict acute myocardial infarction after carotid artery stenting.

Risk of mortality associated to chronic kidney disease in patients with type 2 diabetes mellitus: a 13-year follow-up.

PubMed

Gimeno-Orna, José Antonio; Blasco-Lamarca, Yolanda; Campos-Gutierrez, Belén; Molinero-Herguedas, Edmundo; Lou-Arnal, Luis Miguel; García-García, Blanca

2015-01-01

Our aim was to assess the usefulness of glomerular filtration rate (GFR) and urinary albumin excretion (UAE) to predict the risk of mortality in patients with type 2 diabetes mellitus. This is a prospective cohort study in patients with type 2 diabetes mellitus. Clinical end-point was mortality rate. GFR was measured in ml/min/1.73 m2 and stratified in 3 categories (≥60; 45-59; <45); UAE was measured in mg/24hours and was also stratified in 3 categories (<30; 30-300; >300). Mortality rates were reported per 1000 patient-years. Cox regression models were used to predict mortality risk associated with combined GFR and UAE. The predictive power was estimated with C-Harrell statistic. A total of 453 patients (39.3% males), aged 64.9 (SD 9.3) years were included; mean diabetes duration was 10.4 (SD 7.5) years. Median follow-up was 13 years. Total mortality rate was 39.5/1000. The progressive increase in mortality in the successive categories of GFR and UAE was statistically significant (P<.001). In a multivariable analysis, UAE (HR30-300=1.02 and HR>300=2.83; X2=11.6; P =.003) and GFR (HR45-59=1.34 and HR<45=1.84; X2=6.4; P =.041) were independent predictors for mortality, with no significant interaction. Simultaneous inclusion of GFR and UAE improved the predictive power of models (C-Harrell 0.741 vs. 0.726; P =.045). GFR and UAE are independent predictors for mortality in type 2 diabetic patients and do not show a statistically significant interaction. Copyright © 2015 The Authors. Published by Elsevier España, S.L.U. All rights reserved.

Limitations of the Parsonnet score for measuring risk stratified mortality in the north west of England

PubMed Central

Wynne-Jones, K; Jackson, M; Grotte, G; Bridgewater, B; North, W

2000-01-01

OBJECTIVE—To study the use of the Parsonnet score to predict mortality following adult cardiac surgery.
DESIGN—Prospective study.
SETTING—All centres performing adult cardiac surgery in the north west of England.
SUBJECTS—8210 patients undergoing surgery between April 1997 and March 1999.
MAIN OUTCOME MEASURES—Risk factors and in-hospital mortality were recorded according to agreed definitions. Ten per cent of cases from each centre were selected at random for validation. A Parsonnet score was derived for each patient and its predictive ability was studied.
RESULTS—Data collection was complete. The operative mortality was 3.5% (95% confidence interval 3.1% to 3.9%), ranging from 2.7% to 3.8% across the centres. On validation, the incidence of discrepancies ranged from 0% to 13% for the different risk factors. The predictive ability of the Parsonnet score measured by area under the receiver operating characteristic curve was 0.74. The mean Parsonnet score for the region was 7.0, giving an observed to expected mortality ratio of 0.51 (range 0.4 to 0.64 across the centres). A new predictive model was derived from the data by multivariate analysis which includes nine objective risk factors, all with a significant association with mortality, which highlights some of the deficits of the Parsonnet score.
CONCLUSIONS—Risk stratified mortality data were collected on 100% of patients undergoing adult cardiac surgery in two years within a defined geographical region and were used to set an audit standard. Problems with the Parsonnet score of subjectivity, inclusion of many items not associated with mortality, and the overprediction of mortality have been highlighted.


Keywords: risk stratification; cardiac surgery; Parsonnet score; audit PMID:10862595

Lactate clearance cut off for early mortality prediction in adult sepsis and septic shock patients

NASA Astrophysics Data System (ADS)

Sinto, R.; Widodo, D.; Pohan, H. T.

2018-03-01

Previous lactate clearance cut off for early mortality prediction in sepsis and septic shock patient was determined by consensus from small sample size-study. We investigated the best lactate clearance cut off and its ability to predict early mortality in sepsis and septic shock patients. This cohort study was conducted in Intensive Care Unit of CiptoMangunkusumo Hospital in 2013. Patients’ lactate clearance and eight other resuscitationendpoints were recorded, and theoutcome was observed during the first 120 hours. The clearance cut off was determined using receiver operating characteristic (ROC) analysis, and its ability was investigated with Cox’s proportional hazard regression analysis using other resuscitation endpoints as confounders. Total of 268 subjects was included, of whom 70 (26.11%) subjects died within the first 120 hours. The area under ROC of lactate clearance to predict early mortality was 0.78 (95% % confidence interval [CI] 0.71-0.84) with best cut off was <7.5% (sensitivity and specificity 88.99% and 81.4% respectively). Compared with group achieving lactate clearance target, group not achieving lactate clearance target had to increase early mortality risk (adjusted hazard ratio 13.42; 95%CI 7.19-25.07). In conclusion, the best lactate clearance cut off as anearly mortality predictor in sepsis and septic shock patients is 7.5%.

Variable life-adjusted display (VLAD) for hip fracture patients: a prospective trial.

PubMed

Williams, H; Gwyn, R; Smith, A; Dramis, A; Lewis, J

2015-08-01

With restructuring within the NHS, there is increased public and media interest in surgical outcomes. The Nottingham Hip Fracture Score (NHFS) is a well-validated tool in predicting 30-day mortality in hip fractures. VLAD provides a visual plot in real time of the difference between the cumulative expected mortality and the actual death occurring. Survivors are incorporated as a positive value equal to 1 minus the probability of survival and deaths as a negative value equal to the probability of survival. Downward deflections indicate mortality and potentially suboptimal care. We prospectively included every hip fracture admitted to UHW that underwent surgery from January-August 2014. NHFS was then calculated and predicted survival identified. A VLAD plot was then produced comparing the predicted with the actual 30-day mortality. Two hundred and seventy-seven patients have completed the 30-day follow-up, and initial results showed that the actual 30-day mortality (7.2 %) was much lower than that predicted by the NHFS (8.0 %). This was reflected by a positive trend on the VLAD plot. Variable life-adjusted display provides an easy-to-use graphical representation of risk-adjusted survival over time and can act as an "early warning" system to identify trends in mortality for hip fractures.

Mortality from leukaemia and cancer in shipyard nuclear workers.

PubMed

Najarian, T; Colton, T

1978-05-13

A review of death certificates in New Hampshire, Maine, and Massachusetts for 1959-77 yielded a total of 1722 deaths among former workers at the Portsmouth Naval Shipyard where nuclear submarines are repaired and refuelled. Next of kin were contacted for 592. All deaths under age 80 were classified as being in former nuclear or non-nuclear workers depending on information supplied by next of kin. With U.S. age-specific proportional cancer mortality for White males as a standard, the observed/expected ratio of leukaemia deaths was 5.62 (6 observed, 1.1 expected) among the 146 former nuclear workers. For all cancer deaths, this ratio was 1.78. Among non-nuclear workers there was no statistically significant increase in proportional mortality from either leukaemia or from all cancers. The excess proportional leukaemia and cancer mortality among nuclear workers exceeds predictions based on previous data of radiation effects in man.

Using cluster analysis to identify phenotypes and validation of mortality in men with COPD.

PubMed

Chen, Chiung-Zuei; Wang, Liang-Yi; Ou, Chih-Ying; Lee, Cheng-Hung; Lin, Chien-Chung; Hsiue, Tzuen-Ren

2014-12-01

Cluster analysis has been proposed to examine phenotypic heterogeneity in chronic obstructive pulmonary disease (COPD). The aim of this study was to use cluster analysis to define COPD phenotypes and validate them by assessing their relationship with mortality. Male subjects with COPD were recruited to identify and validate COPD phenotypes. Seven variables were assessed for their relevance to COPD, age, FEV(1) % predicted, BMI, history of severe exacerbations, mMRC, SpO(2), and Charlson index. COPD groups were identified by cluster analysis and validated prospectively against mortality during a 4-year follow-up. Analysis of 332 COPD subjects identified five clusters from cluster A to cluster E. Assessment of the predictive validity of these clusters of COPD showed that cluster E patients had higher all cause mortality (HR 18.3, p < 0.0001), and respiratory cause mortality (HR 21.5, p < 0.0001) than those in the other four groups. Cluster E patients also had higher all cause mortality (HR 14.3, p = 0.0002) and respiratory cause mortality (HR 10.1, p = 0.0013) than patients in cluster D alone. COPD patient with severe airflow limitation, many symptoms, and a history of frequent severe exacerbations was a novel and distinct clinical phenotype predicting mortality in men with COPD.

Predictors of 90-day mortality in patients with severe alcoholic hepatitis: Experience with 183 patients at a tertiary care center from India.

PubMed

Daswani, Ravi; Kumar, Ashish; Anikhindi, Shrihari Anil; Sharma, Praveen; Singla, Vikas; Bansal, Naresh; Arora, Anil

2018-03-01

Severe alcoholic hepatitis (AH) is not an uncommon indication for hospital admission in India. However, there is limited data from India on predictors of mortality in patients of severe AH. We analyzed the data on patients with severe AH admitted to our institute and compared various parameters and severity scores in predicting 90-day mortality. In this prospective study, we analyzed patients with severe AH (defined as discriminant function ≥ 32) admitted from January 2015 to February 2017 to our institute. All patients were administered standard treatment according to various guidelines, and their 90-day mortality was determined. Various hematologic, biochemical factors, and severity scores were compared between survivors and patients who died. A total of 183 patients (98% males, median age 41 years [range 20-70 years]) were included in our study. The median model for end-stage liver disease (MELD) was 26 (15-40). Ascites were present in 83% and hepatic encephalopathy in 38%. Only 21 (12%) could be offered steroid therapy, due to contraindications in the remaining. By 90 days, only 103 (56%) patients survived while 80 (44%) died. All patients died due to progressive liver failure and its complications. On multivariate analysis, presence of ascites, hepatic encephalopathy, high bilirubin, low albumin, high creatinine, high INR, and low potassium independently predicted 90-day mortality. All the scores performed significantly in predicting 90-day mortality with no statistically significant difference between them. MELD score had a maximum area under the curve 0.76 for 90-day mortality. A combination of Child class and presence of acute kidney injury (creatinine ≥ 1.35) was good in predicting 90-day mortality. Our patients had severe AH characterized by a median MELD score of 26 and had a 90-day mortality of 44%. Most patients were not eligible to receive corticosteroids. Presence of Child C status and high serum creatinine value (≥ 1.35 mg/dL) accurately predicted mortality. Newer treatment options need to be explored for these patients.

Comparison of Glasgow Coma Scale, Full Outline of Unresponsiveness and Acute Physiology and Chronic Health Evaluation in Prediction of Mortality Rate Among Patients With Traumatic Brain Injury Admitted to Intensive Care Unit

PubMed Central

Hosseini, Seyed Hossein; Ayyasi, Mitra; Akbari, Hooshang; Heidari Gorji, Mohammad Ali

2016-01-01

Background Traumatic brain injury (TBI) is a common cause of mortality and disability worldwide. Choosing an appropriate diagnostic tool is critical in early stage for appropriate decision about primary diagnosis, medical care and prognosis. Objectives This study aimed to compare the Glasgow coma scale (GCS), full outline of unresponsiveness (FOUR) and acute physiology and chronic health evaluation (APACHE II) with respect to prediction of the mortality rate of patients with TBI admitted to intensive care unit. Patients and Methods This diagnostic study was conducted on 80 patients with TBI in educational hospitals. The scores of APACHE II, GCS and FOUR were recorded during the first 24 hours of admission of patients. In this study, early mortality means the patient death before 14 days and delayed mortality means the patient death 15 days after admitting to hospital. The collected data were analyzed using descriptive and inductive statistics. Results The results showed that the mean age of the patients was 33.80 ± 12.60. From a total of 80 patients with TBI, 16 (20%) were females and 64 (80%) males. The mortality rate was 15 (18.7%). The results showed no significant difference among three tools. In prediction of early mortality, the areas under the curve (AUCs) were 0.92 (CI = 0.95. 0.81 - 0.97), 0.90 (CI = 0.95. 0.74 - 0.94), and 0.96 (CI = 0.95. 0.87 - 0.9) for FOUR, APACHE II and GCS, respectively. In delayed mortality, the AUCs were 0.89 (CI = 0.95. 0.81-0.94), 0.94 (CI = 0.95. 0.74 - 0.97) and 0.90 (CI = 0.95. 0.87 - 0.95) for FOUR, APACHE II and GCS, respectively. Conclusions Considering that GCS is easy to use and the FOUR can diagnose a locking syndrome along same values of subscales. These two subscales are superior to APACHI II in prediction of early mortality. Conversation APACHE II is more punctual in the prediction of delayed mortality. PMID:29696116

Environmental Predictors of US County Mortality Patterns on a National Basis.

PubMed

Chan, Melissa P L; Weinhold, Robert S; Thomas, Reuben; Gohlke, Julia M; Portier, Christopher J

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level.

Environmental Predictors of US County Mortality Patterns on a National Basis

PubMed Central

Thomas, Reuben; Gohlke, Julia M.; Portier, Christopher J.

2015-01-01

A growing body of evidence has found that mortality rates are positively correlated with social inequalities, air pollution, elevated ambient temperature, availability of medical care and other factors. This study develops a model to predict the mortality rates for different diseases by county across the US. The model is applied to predict changes in mortality caused by changing environmental factors. A total of 3,110 counties in the US, excluding Alaska and Hawaii, were studied. A subset of 519 counties from the 3,110 counties was chosen by using systematic random sampling and these samples were used to validate the model. Step-wise and linear regression analyses were used to estimate the ability of environmental pollutants, socio-economic factors and other factors to explain variations in county-specific mortality rates for cardiovascular diseases, cancers, chronic obstructive pulmonary disease (COPD), all causes combined and lifespan across five population density groups. The estimated models fit adequately for all mortality outcomes for all population density groups and, adequately predicted risks for the 519 validation counties. This study suggests that, at local county levels, average ozone (0.07 ppm) is the most important environmental predictor of mortality. The analysis also illustrates the complex inter-relationships of multiple factors that influence mortality and lifespan, and suggests the need for a better understanding of the pathways through which these factors, mortality, and lifespan are related at the community level. PMID:26629706

Validation of the Combined Comorbidity Index of Charlson and Elixhauser to Predict 30-Day Mortality Across ICD-9 and ICD-10.

PubMed

Simard, Marc; Sirois, Caroline; Candas, Bernard

2018-05-01

To validate and compare performance of an International Classification of Diseases, tenth revision (ICD-10) version of a combined comorbidity index merging conditions of Charlson and Elixhauser measures against individual measures in the prediction of 30-day mortality. To select a weight derivation method providing optimal performance across ICD-9 and ICD-10 coding systems. Using 2 adult population-based cohorts of patients with hospital admissions in ICD-9 (2005, n=337,367) and ICD-10 (2011, n=348,820), we validated a combined comorbidity index by predicting 30-day mortality with logistic regression. To appreciate performance of the Combined index and both individual measures, factors impacting indices performance such as population characteristics and weight derivation methods were accounted for. We applied 3 scoring methods (Van Walraven, Schneeweiss, and Charlson) and determined which provides best predictive values. Combined index [c-statistics: 0.853 (95% confidence interval: CI, 0.848-0.856)] performed better than original Charlson [0.841 (95% CI, 0.835-0.844)] or Elixhauser [0.841 (95% CI, 0.837-0.844)] measures on ICD-10 cohort. All weight derivation methods provided close high discrimination results for the Combined index (Van Walraven: 0.852, Schneeweiss: 0.851, Charlson: 0.849). Results were consistent across both coding systems. The Combined index remains valid with both ICD-9 and ICD-10 coding systems and the 3 weight derivation methods evaluated provided consistent high performance across those coding systems.

Modeling total cholesterol as predictor of mortality: the low-cholesterol paradox.

PubMed

Wesley, David; Cox, Hugh F

2011-01-01

Elevated total cholesterol is well-established as a risk factor for coronary artery disease and cardiovascular mortality. However, less attention is paid to the association between low cholesterol levels and mortality--the low cholesterol paradox. In this paper, restricted cubic splines (RCS) and complex survey methodology are used to show the low-cholesterol paradox is present in the laboratory, examination, and mortality follow-up data from the Third National Health and Nutrition Examination Survey (NHANES III). A series of Cox proportional hazard models, demonstrate that RCS are necessary to incorporate desired covariates while avoiding the use of categorical variables. Valid concerns regarding the accuracy of such predictive models are discussed. The one certain conclusion is that low cholesterol levels are markers for excess mortality, just as are high levels. Restricted cubic splines provide the necessary flexibility to demonstrate the U-shaped relationship between cholesterol and mortality without resorting to binning results. Cox PH models perform well at identifying associations between risk factors and outcomes of interest such as mortality. However, the predictions from such a model may not be as accurate as common statistics suggest and predictive models should be used with caution.

Association of an inter-arm systolic blood pressure difference with all-cause and cardiovascular mortality: An updated meta-analysis of cohort studies.

PubMed

Cao, Kaiwu; Xu, Jingsong; Shangguan, Qing; Hu, Weitong; Li, Ping; Cheng, Xiaoshu; Su, Hai

2015-01-01

To evaluate whether an association exists between an inter-arm systolic blood pressure difference (sIAD) and all-cause and cardiovascular mortality. We searched for cohort studies that evaluated the association of a sIAD and all-cause or cardiovascular mortality in the electronic databases Medline/PubMed and Embase (August 2014). Random effects models were used to calculate pooled hazard ratios (HRs) and 95% confidence intervals (CIs). Nine cohort studies (4 prospective and 5 retrospective) enrolling 15,617 participants were included. The pooled HR of all-cause mortality for a sIAD of ≥ 10 mm Hg was 1.53 (95% CI 1.14-2.06), and that for a sIAD of ≥ 15 mm Hg was 1.46 (1.13-1.88). Pooled HRs of cardiovascular mortality were 2.21 (95% CI 1.52-3.21) for a sIAD of ≥ 10mm Hg, and 1.89 (1.32-2.69) for a sIAD of ≥ 15 mm Hg. In the patient-based cohorts including hospital- and diabetes-based cohorts, both sIADs of ≥ 10 and ≥ 15 mm Hg were associated with increased all-cause (pooled HR 1.95, 95% CI 1.01-3.78 and 1.59, 1.06-2.38, respectively) and cardiovascular mortality (pooled HR 2.98, 95% CI 1.88-4.72 and 2.10, 1.07-4.13, respectively). In the community-based cohorts, however, only a sIAD of ≥ 15 mm Hg was associated with increased cardiovascular mortality (pooled HR 1.94, 95 % CI 1.12-3.35). In the patient populations, a sIAD of ≥ 10 or of ≥ 15 mm Hg could be a useful indictor for increased all-cause and cardiovascular mortality, and a sIAD of ≥ 15 mm Hg might help to predict increased cardiovascular mortality in the community populations. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Clinical prediction of functional outcome after ischemic stroke: the surprising importance of periventricular white matter disease and race.

PubMed

Kissela, Brett; Lindsell, Christopher J; Kleindorfer, Dawn; Alwell, Kathleen; Moomaw, Charles J; Woo, Daniel; Flaherty, Matthew L; Air, Ellen; Broderick, Joseph; Tsevat, Joel

2009-02-01

We sought to build models that address questions of interest to patients and families by predicting short- and long-term mortality and functional outcome after ischemic stroke, while allowing for risk restratification as comorbid events accumulate. A cohort of 451 ischemic stroke subjects in 1999 were interviewed during hospitalization, at 3 months, and at approximately 4 years. Medical records from the acute hospitalization were abstracted. All hospitalizations for 3 months poststroke were reviewed to ascertain medical and psychiatric comorbidities, which were categorized for analysis. Multivariable models were derived to predict mortality and functional outcome (modified Rankin Scale) at 3 months and 4 years. Comorbidities were included as modifiers of the 3-month models, and included in 4-year predictions. Poststroke medical and psychiatric comorbidities significantly increased short-term poststroke mortality and morbidity. Severe periventricular white matter disease (PVWMD) was significantly associated with poor functional outcome at 3 months, independent of other factors, such as diabetes and age; inclusion of this imaging variable eliminated other traditional risk factors often found in stroke outcomes models. Outcome at 3 months was a significant predictor of long-term mortality and functional outcome. Black race was a predictor of 4-year mortality. We propose that predictive models for stroke outcome, as well as analysis of clinical trials, should include adjustment for comorbid conditions. The effects of PVWMD on short-term functional outcomes and black race on long-term mortality are findings that require confirmation.

Retrospective evaluation of prognostic score performances in cirrhotic patients admitted to an intermediate care unit.

PubMed

Dupont, Benoît; Delvincourt, Maxime; Koné, Mamadou; du Cheyron, Damien; Ollivier-Hourmand, Isabelle; Piquet, Marie-Astrid; Terzi, Nicolas; Dao, Thông

2015-08-01

The prognosis of cirrhotic patients in the Intensive Care Unit requires the development of predictive tools for mortality. We aimed to evaluate the ability of different prognostic scores to predict hospital mortality in these patients. A single-centre retrospective analysis was conducted of 281 hospital stays of cirrhotic patients at an Intermediate Care Unit between June 2009 and December 2010. The performance of the Simplified Acute Physiology Score (SOFA), the Simplified Acute Physiology Score (SAPS) II or III, Child-Pugh, Model for End-Stage Liver Disease (MELD), MELD-Na and the Chronic Liver Failure-Consortium Acute-on-Chronic Liver Failure score (CLIF-C ACLF) in predicting hospital mortality were compared. Mean age was 58.2±12.1 years; 77% were male. The main cause of admission was acute gastrointestinal bleeding (47%). The in-hospital mortality rate was 25.3%. Receiver operating characteristic curve analyses demonstrated that SOFA (0.82) MELD-Na (0.82) or MELD (0.81) scores at admission predicted in-hospital mortality better than Child-Pugh (0.76), SAPS II (0.77), SAPS III (0.75) or CLIF-C ACLF (0.75). We then developed the cirrhosis prognostic score (Ci-Pro), which performed better (0.89) than SOFA. SOFA, MELD and especially the Ci-Pro score show the best performance in predicting hospital mortality of cirrhotic patients admitted to an Intermediate Care Unit. Copyright © 2015 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

Mortality in severe trauma patients attended by emergency services in Navarre, Spain: validation of a new prediction model and comparison with the Revised Injury Severity Classification Score II.

PubMed

Ali Ali, Bismil; Lefering, Rolf; Fortún Moral, Mariano; Belzunegui Otano, Tomás

2018-01-01

To validate the Mortality Prediction Model of Navarre (MPMN) to predict death after severe trauma and compare it to the Revised Injury Severity Classification Score II (RISCII). Retrospective analysis of a cohort of severe trauma patients (New Injury Severity Score >15) who were attended by emergency services in the Spanish autonomous community of Navarre between 2013 and 2015. The outcome variable was 30-day all-cause mortality. Risk was calculated with the MPMN and the RISCII. The performance of each model was assessed with the area under the receiver operating characteristic (ROC) curve and precision with respect to observed mortality. Calibration was assessed with the Hosmer-Lemeshow test. We included 516 patients. The mean (SD) age was 56 (23) years, and 363 (70%) were males. Ninety patients (17.4%) died within 30 days. The 30-day mortality rates predicted by the MPMN and RISCII were 16.4% and 15.4%, respectively. The areas under the ROC curves were 0.925 (95% CI, 0.902-0.952) for the MPMN and 0.941 (95% CI, 0.921-0.962) for the RISCII (P=0.269, DeLong test). Calibration statistics were 13.6 (P=.09) for the MPMN and 8.9 (P=.35) for the RISCII. Both the MPMN and the RISCII show good ability to discriminate risk and predict 30-day all-cause mortality in severe trauma patients.

Modeling the population-level effects of hypoxia on a coastal fish: implications of a spatially-explicit individual-based model

NASA Astrophysics Data System (ADS)

Rose, K.; Creekmore, S.; Thomas, P.; Craig, K.; Neilan, R.; Rahman, S.; Wang, L.; Justic, D.

2016-02-01

The northwestern Gulf of Mexico (USA) currently experiences a large hypoxic area ("dead zone") during the summer. The population-level effects of hypoxia on coastal fish are largely unknown. We developed a spatially-explicit, individual-based model to analyze how hypoxia effects on reproduction, growth, and mortality of individual Atlantic croaker could lead to population-level responses. The model follows the hourly growth, mortality, reproduction, and movement of individuals on a 300 x 800 spatial grid of 1 km2 cells for 140 years. Chlorophyll-a concentration and water temperature were specified daily for each grid cell. Dissolved oxygen (DO) was obtained from a 3-D water quality model for four years that differed in their severity of hypoxia. A bioenergetics model was used to represent growth, mortality was assumed stage- and age-dependent, and movement behavior was based on temperature preferences and avoidance of low DO. Hypoxia effects were imposed using exposure-effects sub-models that converted time-varying exposure to DO to reductions in growth and fecundity, and increases in mortality. Using sequences of mild, intermediate, and severe hypoxia years, the model predicted a 20% decrease in population abundance. Additional simulations were performed under the assumption that river-based nutrients loadings that lead to more hypoxia also lead to higher primary production and more food for croaker. Twenty-five percent and 50% nutrient reduction scenarios were simulated by adjusting the cholorphyll-a concentrations used as food proxy for the croaker. We then incrementally increased the DO concentrations to determine how much hypoxia would need to be reduced to offset the lower food production resulting from reduced nutrients. We discuss the generality of our results, the hidden effects of hypoxia on fish, and our overall strategy of combining laboratory and field studies with modeling to produce robust predictions of population responses to stressors under dynamic and multi-stressor conditions.

Theory of Partitioning of Disease Prevalence and Mortality in Observational Data

PubMed Central

Akushevich, I.; Yashkin, A.; Kravchenko, J.; Fang, F.; Arbeev, K.; Sloan, F.; Yashin, AI

2017-01-01

In this study, we present a new theory of partitioning of disease prevalence and incidence-based mortality and demonstrate how this theory practically works for analyses of Medicare data. In the theory, the prevalence of a disease and incidence-based mortality are modeled in terms of disease incidence and survival after diagnosis supplemented by information on disease prevalence at the initial age and year available in a dataset. Partitioning of the trends of prevalence and mortality is calculated with minimal assumptions. The resulting expressions for the components of the trends are given by continuous functions of data. The estimator is consistent and stable. The developed methodology is applied for data on type 2 diabetes using individual records from a nationally representative 5% sample of Medicare beneficiaries age 65+. Numerical estimates show excellent concordance between empirical estimates and theoretical predictions. Evaluated partitioning model showed that both prevalence and mortality increase with time. The primary driving factors of the observed prevalence increase are improved survival and increased prevalence at age 65. The increase in diabetes-related mortality is driven by increased prevalence and unobserved trends in time-periods and age-groups outside of the range of the data used in the study. Finally, the properties of the new estimator, possible statistical and systematical uncertainties, and future practical applications of this methodology in epidemiology, demography, public health and health forecasting are discussed. PMID:28130147

High levels of cynical distrust partly predict premature mortality in middle-aged to ageing men.

PubMed

Šmigelskas, Kastytis; Joffė, Roza; Jonynienė, Jolita; Julkunen, Juhani; Kauhanen, Jussi

2017-08-01

The aim of this study was to evaluate the effect of cynical distrust on mortality in middle-aged and aging men. The analysis is based on Kuopio Ischemic Heart Disease study, follow-up from 1984 to 2011. Sample consisted of 2682 men, aged 42-61 years at baseline. Data on mortality was provided by the National Death Registry, causes of death were classified by the National Center of Statistics of Finland. Cynical distrust was measured at baseline using Cynical Distrust Scale. Survival analyses were conducted using Cox regression models. In crude estimates after 28 years of follow-up, high cynical distrust was associated with 1.5-1.7 higher hazards for earlier death compared to low cynical distrust. Adjusted for conventional risk factors, high cynical distrust was significantly associated regarding CVD-free men and CVD mortality, while non-CVD mortality in study sample was consistently but not significantly associated. The risk effects were more expressed after 12-20 years rather than in earlier or later follow-up. To conclude, high cynical distrust associates with increased risk of CVD mortality in CVD-free men. The associations with non-CVD mortality are weaker and not reach statistical significance.

Predictive variables for mortality after acute ischemic stroke.

PubMed

Carter, Angela M; Catto, Andrew J; Mansfield, Michael W; Bamford, John M; Grant, Peter J

2007-06-01

Stroke is a major healthcare issue worldwide with an incidence comparable to coronary events, highlighting the importance of understanding risk factors for stroke and subsequent mortality. In the present study, we determined long-term (all-cause) mortality in 545 patients with ischemic stroke compared with a cohort of 330 age-matched healthy control subjects followed up for a median of 7.4 years. We assessed the effect of selected demographic, clinical, biochemical, hematologic, and hemostatic factors on mortality in patients with ischemic stroke. Stroke subtype was classified according to the Oxfordshire Community Stroke Project criteria. Patients who died 30 days or less after the acute event (n=32) were excluded from analyses because this outcome is considered to be directly attributable to the acute event. Patients with ischemic stroke were at more than 3-fold increased risk of death compared with the age-matched control cohort. In multivariate analyses, age, stroke subtype, atrial fibrillation, and previous stroke/transient ischemic attack were predictive of mortality in patients with ischemic stroke. Albumin and creatinine and the hemostatic factors von Willebrand factor and beta-thromboglobulin were also predictive of mortality in patients with ischemic stroke after accounting for demographic and clinical variables. The results indicate that subjects with acute ischemic stroke are at increased risk of all-cause mortality. Advancing age, large-vessel stroke, atrial fibrillation, and previous stroke/transient ischemic attack predict mortality; and analysis of albumin, creatinine, von Willebrand factor, and beta-thromboglobulin will aid in the identification of patients at increased risk of death after stroke.

Predicting fire-based perennial bunchgrass mortality in low elevation big sagebrush plant communities

USDA-ARS?s Scientific Manuscript database

Maintenance and post-fire rehabilitation of perennial bunchgrasses is important for reducing the spread of annual grass species in low elevation big sagebrush plant communities. Post-fire rehabilitation decisions are hampered by a lack of tools for determining extent of fire-induced perennial grass...

The National Early Warning Score (NEWS) for outcome prediction in emergency department patients with community-acquired pneumonia: results from a 6-year prospective cohort study

PubMed Central

Sbiti-Rohr, Diana; Kutz, Alexander; Christ-Crain, Mirjam; Thomann, Robert; Zimmerli, Werner; Hoess, Claus; Henzen, Christoph; Mueller, Beat; Schuetz, Philipp

2016-01-01

Objective To investigate the accuracy of the National Early Warning Score (NEWS) to predict mortality and adverse clinical outcomes for patients with community-acquired pneumonia (CAP) compared to standard risk scores such as the pneumonia severity index (PSI) and CURB-65. Design Secondary analysis of patients included in a previous randomised-controlled trial with a median follow-up of 6.1 years. Settings Patients with CAP included on admission to the emergency departments (ED) of 6 tertiary care hospitals in Switzerland. Participants A total of 925 patients with confirmed CAP were included. NEWS, PSI and CURB-65 scores were calculated on admission to the ED based on admission data. Main outcome measure Our primary outcome was all-cause mortality within 6 years of follow-up. Secondary outcomes were adverse clinical outcome defined as intensive care unit (ICU) admission, empyema and unplanned hospital readmission all occurring within 30 days after admission. We used regression models to study associations of baseline risk scores and outcomes with the area under the receiver operating curve (AUC) as a measure of discrimination. Results 6-year overall mortality was 45.1% (n=417) with a stepwise increase with higher NEWS categories. For 30 day and 6-year mortality prediction, NEWS showed only low discrimination (AUC 0.65 and 0.60) inferior compared to PSI and CURB-65. For prediction of ICU admission, NEWS showed moderate discrimination (AUC 0.73) and improved the prognostic accuracy of a regression model, including PSI (AUC from 0.66 to 0.74, p=0.001) and CURB-65 (AUC from 0.64 to 0.73, p=0.015). NEWS was also superior to PSI and CURB-65 for prediction of empyema, but did not well predict rehospitalisation. Conclusions NEWS provides additional prognostic information with regard to risk of ICU admission and complications and thereby improves traditional clinical-risk scores in the management of patients with CAP in the ED setting. Trial registration number ISRCTN95122877; Post-results. PMID:27683509

The National Early Warning Score (NEWS) for outcome prediction in emergency department patients with community-acquired pneumonia: results from a 6-year prospective cohort study.

PubMed

Sbiti-Rohr, Diana; Kutz, Alexander; Christ-Crain, Mirjam; Thomann, Robert; Zimmerli, Werner; Hoess, Claus; Henzen, Christoph; Mueller, Beat; Schuetz, Philipp

2016-09-28

To investigate the accuracy of the National Early Warning Score (NEWS) to predict mortality and adverse clinical outcomes for patients with community-acquired pneumonia (CAP) compared to standard risk scores such as the pneumonia severity index (PSI) and CURB-65. Secondary analysis of patients included in a previous randomised-controlled trial with a median follow-up of 6.1 years. Patients with CAP included on admission to the emergency departments (ED) of 6 tertiary care hospitals in Switzerland. A total of 925 patients with confirmed CAP were included. NEWS, PSI and CURB-65 scores were calculated on admission to the ED based on admission data. Our primary outcome was all-cause mortality within 6 years of follow-up. Secondary outcomes were adverse clinical outcome defined as intensive care unit (ICU) admission, empyema and unplanned hospital readmission all occurring within 30 days after admission. We used regression models to study associations of baseline risk scores and outcomes with the area under the receiver operating curve (AUC) as a measure of discrimination. 6-year overall mortality was 45.1% (n=417) with a stepwise increase with higher NEWS categories. For 30 day and 6-year mortality prediction, NEWS showed only low discrimination (AUC 0.65 and 0.60) inferior compared to PSI and CURB-65. For prediction of ICU admission, NEWS showed moderate discrimination (AUC 0.73) and improved the prognostic accuracy of a regression model, including PSI (AUC from 0.66 to 0.74, p=0.001) and CURB-65 (AUC from 0.64 to 0.73, p=0.015). NEWS was also superior to PSI and CURB-65 for prediction of empyema, but did not well predict rehospitalisation. NEWS provides additional prognostic information with regard to risk of ICU admission and complications and thereby improves traditional clinical-risk scores in the management of patients with CAP in the ED setting. ISRCTN95122877; Post-results. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

The PER (Preoperative Esophagectomy Risk) Score: A Simple Risk Score to Predict Short-Term and Long-Term Outcome in Patients with Surgically Treated Esophageal Cancer.

PubMed

Reeh, Matthias; Metze, Johannes; Uzunoglu, Faik G; Nentwich, Michael; Ghadban, Tarik; Wellner, Ullrich; Bockhorn, Maximilian; Kluge, Stefan; Izbicki, Jakob R; Vashist, Yogesh K

2016-02-01

Esophageal resection in patients with esophageal cancer (EC) is still associated with high mortality and morbidity rates. We aimed to develop a simple preoperative risk score for the prediction of short-term and long-term outcomes for patients with EC treated by esophageal resection. In total, 498 patients suffering from esophageal carcinoma, who underwent esophageal resection, were included in this retrospective cohort study. Three preoperative esophagectomy risk (PER) groups were defined based on preoperative functional evaluation of different organ systems by validated tools (revised cardiac risk index, model for end-stage liver disease score, and pulmonary function test). Clinicopathological parameters, morbidity, and mortality as well as disease-free survival (DFS) and overall survival (OS) were correlated to the PER score. The PER score significantly predicted the short-term outcome of patients with EC who underwent esophageal resection. PER 2 and PER 3 patients had at least double the risk of morbidity and mortality compared to PER 1 patients. Furthermore, a higher PER score was associated with shorter DFS (P < 0.001) and OS (P < 0.001). The PER score was identified as an independent predictor of tumor recurrence (hazard ratio [HR] 2.1; P < 0.001) and OS (HR 2.2; P < 0.001). The PER score allows preoperative objective allocation of patients with EC into different risk categories for morbidity, mortality, and long-term outcomes. Thus, multicenter studies are needed for independent validation of the PER score.

Cardiovascular mortality prediction in veterans with arm exercise vs pharmacologic myocardial perfusion imaging.

PubMed

Martin, Wade H; Xian, Hong; Chandiramani, Pooja; Bainter, Emily; Klein, Andrew J P

2015-08-01

No data exist comparing outcome prediction from arm exercise vs pharmacologic myocardial perfusion imaging (MPI) stress test variables in patients unable to perform treadmill exercise. In this retrospective study, 2,173 consecutive lower extremity disabled veterans aged 65.4 ± 11.0years (mean ± SD) underwent either pharmacologic MPI (1730 patients) or arm exercise stress tests (443 patients) with MPI (n = 253) or electrocardiography alone (n = 190) between 1997 and 2002. Cox multivariate regression models and reclassification analysis by integrated discrimination improvement (IDI) were used to characterize stress test and MPI predictors of cardiovascular mortality at ≥10-year follow-up after inclusion of significant demographic, clinical, and other variables. Cardiovascular death occurred in 561 pharmacologic MPI and 102 arm exercise participants. Multivariate-adjusted cardiovascular mortality was predicted by arm exercise resting metabolic equivalents (hazard ratio [HR] 0.52, 95% CI 0.39-0.69, P < .001), 1-minute heart rate recovery (HR 0.61, 95% CI 0.44-0.86, P < .001), and pharmacologic and arm exercise delta (peak-rest) heart rate (both P < .001). Only an abnormal arm exercise MPI prognosticated cardiovascular death by multivariate Cox analysis (HR 1.98, 95% CI 1.04-3.77, P < .05). Arm exercise MPI defect number, type, and size provided IDI over covariates for prediction of cardiovascular mortality (IDI = 0.074-0.097). Only pharmacologic defect size prognosticated cardiovascular mortality (IDI = 0.022). Arm exercise capacity, heart rate recovery, and pharmacologic and arm exercise heart rate responses are robust predictors of cardiovascular mortality. Arm exercise MPI results are equivalent and possibly superior to pharmacologic MPI for cardiovascular mortality prediction in patients unable to perform treadmill exercise. Published by Elsevier Inc.

Heart rate turbulence predicts all-cause mortality and sudden death in congestive heart failure patients.

PubMed

Cygankiewicz, Iwona; Zareba, Wojciech; Vazquez, Rafael; Vallverdu, Montserrat; Gonzalez-Juanatey, Jose R; Valdes, Mariano; Almendral, Jesus; Cinca, Juan; Caminal, Pere; de Luna, Antoni Bayes

2008-08-01

Abnormal heart rate turbulence (HRT) has been documented as a strong predictor of total mortality and sudden death in postinfarction patients, but data in patients with congestive heart failure (CHF) are limited. The aim of this study was to evaluate the prognostic significance of HRT for predicting mortality in CHF patients in New York Heart Association (NYHA) class II-III. In 651 CHF patients with sinus rhythm enrolled into the MUSIC (Muerte Subita en Insuficiencia Cardiaca) study, the standard HRT parameters turbulence onset (TO) and slope (TS), as well as HRT categories, were assessed for predicting total mortality and sudden death. HRT was analyzable in 607 patients, mean age 63 years (434 male), 50% of ischemic etiology. During a median follow up of 44 months, 129 patients died, 52 from sudden death. Abnormal TS and HRT category 2 (HRT2) were independently associated with increased all-cause mortality (HR: 2.10, CI: 1.41 to 3.12, P <.001 and HR: 2.52, CI: 1.56 to 4.05, P <.001; respectively), sudden death (HR: 2.25, CI: 1.13 to 4.46, P = .021 for HRT2), and death due to heart failure progression (HR: 4.11, CI: 1.84 to 9.19, P <.001 for HRT2) after adjustment for clinical covariates in multivariate analysis. The prognostic value of TS for predicting total mortality was similar in various groups dichotomized by age, gender, NYHA class, left ventricular ejection fraction, and CHF etiology. TS was found to be predictive for total mortality only in patients with QRS > 120 ms. HRT is a potent risk predictor for both heart failure and arrhythmic death in patients with class II and III CHF.

Climate Patterns and Trends of Tree-Mortality in the Southwestern United States

NASA Astrophysics Data System (ADS)

Yi, C.; Mu, G.; Hendrey, G. R.; Vicente-Serrano, S.

2016-12-01

Evidence suggests a world-wide increase in tree mortality associated with climate change in regions subjected to prolonged drought. This is particularly evident in the Southwestern USA (SWUSA) where trees are dying at an accelerating and alarming rate where we investigated climate patterns and trends over the past century in combination with abundant tree-ring data, and thresholds of tree-mortality. In this drought-prone region we found a strong correlation between annual tree-ring width and the corresponding annual average temperature and amount of precipitation. A standardized precipitation-evapotranspiration index (SPEI) was a robust predictor of annual tree growth. At a SPEI of -1.6, tree-ring width was found to be zero. We hypothesize that this is a tipping point for tree-ring mortality. This is confirmed in that approximately 225 million trees died in SWUSA in 2002 when SPEI fell below this tipping point. An analysis of future trends in SPEI based on four GHG concentration scenarios of the IPCC predicts that in coming decades, the conifer forest in SWUSA is expected to be lost entirely due to the prolonged drought there, as the SPEI is predicted to pass the tipping point. It can be anticipated that as the area impacted by prolonged drought increases with SPEI falling below -1.6 tree mortality will become a regional or semi-continental phenomenon. Acknowledgement:This research was supported by PSC-CUNY award (PSC-CUNY-ENHC-68849-0046) and the CUNY Collaborative Incentive Research Grant (CUNY-CIRG-80209-08 22).

Use of cumulative mortality data in patients with acute myocardial infarction for early detection of variation in clinical practice: observational study.

PubMed

Lawrance, R A; Dorsch, M F; Sapsford, R J; Mackintosh, A F; Greenwood, D C; Jackson, B M; Morrell, C; Robinson, M B; Hall, A S

2001-08-11

Use of cumulative mortality adjusted for case mix in patients with acute myocardial infarction for early detection of variation in clinical practice. Observational study. 20 hospitals across the former Yorkshire region. All 2153 consecutive patients with confirmed acute myocardial infarction identified during three months. Variable life-adjusted displays showing cumulative differences between observed and expected mortality of patients; expected mortality calculated from risk model based on admission characteristics of age, heart rate, and systolic blood pressure. The performance of two individual hospitals over three months was examined as an example. One, the smallest district hospital in the region, had a series of 30 consecutive patients but had five more deaths than predicted. The variable life-adjusted display showed minimal variation from that predicted for the first 15 patients followed by a run of unexpectedly high mortality. The second example was the main tertiary referral centre for the region, which admitted 188 consecutive patients. The display showed a period of apparently poor performance followed by substantial improvement, where the plot rose steadily from a cumulative net lives saved of -4 to 7. These variations in patient outcome are unlikely to have been revealed during conventional audit practice. Variable life-adjusted display has been integrated into surgical care as a graphical display of risk-adjusted survival for individual surgeons or centres. In combination with a simple risk model, it may have a role in monitoring performance and outcome in patients with acute myocardial infarction.

Liver Transplantation for Hepatic Trauma: A Study From the European Liver Transplant Registry.

PubMed

Krawczyk, Marek; Grąt, Michał; Adam, Rene; Polak, Wojciech G; Klempnauer, Jurgen; Pinna, Antonio; Di Benedetto, Fabrizio; Filipponi, Franco; Senninger, Norbert; Foss, Aksel; Rufián-Peña, Sebastian; Bennet, William; Pratschke, Johann; Paul, Andreas; Settmacher, Utz; Rossi, Giorgio; Salizzoni, Mauro; Fernandez-Selles, Carlos; Martínez de Rituerto, Santiago T; Gómez-Bravo, Miguel A; Pirenne, Jacques; Detry, Olivier; Majno, Pietro E; Nemec, Petr; Bechstein, Wolf O; Bartels, Michael; Nadalin, Silvio; Pruvot, Francois R; Mirza, Darius F; Lupo, Luigi; Colledan, Michele; Tisone, Giuseppe; Ringers, Jan; Daniel, Jorge; Charco Torra, Ramón; Moreno González, Enrique; Bañares Cañizares, Rafael; Cuervas-Mons Martinez, Valentin; San Juan Rodríguez, Fernando; Yilmaz, Sezai; Remiszewski, Piotr

2016-11-01

Liver transplantation is the most extreme form of surgical management of patients with hepatic trauma, with very limited literature data supporting its use. The aim of this study was to assess the results of liver transplantation for hepatic trauma. This retrospective analysis based on European Liver Transplant Registry comprised data of 73 recipients of liver transplantation for hepatic trauma performed in 37 centers in the period between 1987 and 2013. Mortality and graft loss rates at 90 days were set as primary and secondary outcome measures, respectively. Mortality and graft loss rates at 90 days were 42.5% and 46.6%, respectively. Regarding general variables, cross-clamping without extracorporeal veno-venous bypass was the only independent risk factor for both mortality (P = 0.031) and graft loss (P = 0.034). Regarding more detailed factors, grade of liver trauma exceeding IV increased the risk of mortality (P = 0.005) and graft loss (P = 0.018). Moreover, a tendency above the level of significance was observed for the negative impact of injury severity score (ISS) on mortality (P = 0.071). The optimal cut-off for ISS was 33, with sensitivity of 60.0%, specificity of 80.0%, positive predictive value of 75.0%, and negative predictive value of 66.7%. Liver transplantation seems to be justified in selected patients with otherwise fatal severe liver injuries, particularly in whom cross-clamping without extracorporeal bypass can be omitted. The ISS cutoff less than 33 may be useful in the selection process.

Gender differences in the association between depressive mood and mortality: a 12-year follow-up population-based study.

PubMed

Lemogne, C; Niedhammer, I; Khlat, M; Ravaud, J F; Guillemin, F; Consoli, S M; Fossati, P; Chau, N

2012-02-01

Depressive mood has been associated with all-cause mortality in both men and women. This study aimed at exploring gender differences in the association between depressive mood and specific causes of mortality as well as factors that may account for it, including education, marital status, social support, health behaviors, and chronic diseases. A population-based survey including 6043 subjects (2892 men and 3151 women) was conducted in 1996 in the north-east of France with a questionnaire covering education, marital status, social support, health behaviors (smoking status, alcohol consumption, body mass index), and chronic diseases. Depressive mood was measured using the Duke Health Profile questionnaire. Cox regression models were used to examine its association with subsequent natural all-cause mortality, and cardiovascular and cancer mortality. During a follow-up of 12.5 years, 406 men and 303 women died from a natural cause. Adjusting for all covariates, depressive mood predicted natural mortality in both men [Hazard Ratio (HR)=1.30; 95% confidence interval (CI): 1.00-1.69] and women (HR=1.37; 95% CI: 1.06-1.77). However, this association was significant for cardiovascular mortality in men (HR=1.63; 95% CI: 1.00-2.65) whereas it was significant for cancer mortality in women (HR=1.71; 95% CI: 1.11-2.64). Baseline data were self-reported and the response rate was low. Preventive strategies aiming at reducing the increased mortality associated with depressive mood should take gender into account. Depressed men may warrant a better screening for cardiovascular risk factors and diseases, whereas depressed women may benefit from better cancer prevention measures. Copyright © 2011 Elsevier B.V. All rights reserved.

Validation of prognostic scores for clinical outcomes in cirrhotic patients with acute variceal bleeding.

PubMed

Motola-Kuba, Miguel; Escobedo-Arzate, Angélica; Tellez-Avila, Félix; Altamirano, José; Aguilar-Olivos, Nancy; González-Angulo, Alberto; Zamarripa-Dorsey, Felipe; Uribe, Misael; Chávez-Tapia, Norberto C

Background. The Rockall, Glasgow-Blatchford, and AIMS65 are useful and validated scoring systems for predicting the outcomes of patients with nonvariceal gastrointestinal bleeding. However, there are no validated evidence for using them to predict outcomes on variceal bleeding. The aim of this study was to evaluate and compare the prognostic accuracy of different nonvariceal bleeding scores with other liver-specific scoring systems in cirrhotic patients. A retrospective multicenter study that included 160 cirrhotic patients with acute variceal bleeding. The AUROC's to predict in-hospital mortality, and rebleeding, were analyzed for each scoring system. Overall in-hospital mortality occurred in 13% and in-hospital rebleeding in 12% of patients. The systems with the best AUROC value for predicting mortality were MELD (0.828; 95% CI 0.748-0.909), and AIMS65 (0.817; 95% CI 0.724-0.909). The best score systems for predicting rebleeding were Glasgow-Blatchford (0.756; 95% CI 0.640- 0.827), and Rockall (0.691; 95% CI 0.580-0.802). In addition to liver-specific scores, the AIMS65 score is accurate for predicting in-hospital mortality in cirrhotic patients with acute variceal bleeding. Other scoring systems might be useful for predicting significant clinical outcomes in these patients.

Development of a five-year mortality model in systemic sclerosis patients by different analytical approaches.

PubMed

Beretta, Lorenzo; Santaniello, Alessandro; Cappiello, Francesca; Chawla, Nitesh V; Vonk, Madelon C; Carreira, Patricia E; Allanore, Yannick; Popa-Diaconu, D A; Cossu, Marta; Bertolotti, Francesca; Ferraccioli, Gianfranco; Mazzone, Antonino; Scorza, Raffaella

2010-01-01

Systemic sclerosis (SSc) is a multiorgan disease with high mortality rates. Several clinical features have been associated with poor survival in different populations of SSc patients, but no clear and reproducible prognostic model to assess individual survival prediction in scleroderma patients has ever been developed. We used Cox regression and three data mining-based classifiers (Naïve Bayes Classifier [NBC], Random Forests [RND-F] and logistic regression [Log-Reg]) to develop a robust and reproducible 5-year prognostic model. All the models were built and internally validated by means of 5-fold cross-validation on a population of 558 Italian SSc patients. Their predictive ability and capability of generalisation was then tested on an independent population of 356 patients recruited from 5 external centres and finally compared to the predictions made by two SSc domain experts on the same population. The NBC outperformed the Cox-based classifier and the other data mining algorithms after internal cross-validation (area under receiving operator characteristic curve, AUROC: NBC=0.759; RND-F=0.736; Log-Reg=0.754 and Cox= 0.724). The NBC had also a remarkable and better trade-off between sensitivity and specificity (e.g. Balanced accuracy, BA) than the Cox-based classifier, when tested on an independent population of SSc patients (BA: NBC=0.769, Cox=0.622). The NBC was also superior to domain experts in predicting 5-year survival in this population (AUROC=0.829 vs. AUROC=0.788 and BA=0.769 vs. BA=0.67). We provide a model to make consistent 5-year prognostic predictions in SSc patients. Its internal validity, as well as capability of generalisation and reduced uncertainty compared to human experts support its use at bedside. Available at: http://www.nd.edu/~nchawla/survival.xls.

A BAYESIAN SPATIAL AND TEMPORAL MODELING APPROACH TO MAPPING GEOGRAPHIC VARIATION IN MORTALITY RATES FOR SUBNATIONAL AREAS WITH R-INLA.

PubMed

Khana, Diba; Rossen, Lauren M; Hedegaard, Holly; Warner, Margaret

2018-01-01

Hierarchical Bayes models have been used in disease mapping to examine small scale geographic variation. State level geographic variation for less common causes of mortality outcomes have been reported however county level variation is rarely examined. Due to concerns about statistical reliability and confidentiality, county-level mortality rates based on fewer than 20 deaths are suppressed based on Division of Vital Statistics, National Center for Health Statistics (NCHS) statistical reliability criteria, precluding an examination of spatio-temporal variation in less common causes of mortality outcomes such as suicide rates (SRs) at the county level using direct estimates. Existing Bayesian spatio-temporal modeling strategies can be applied via Integrated Nested Laplace Approximation (INLA) in R to a large number of rare causes of mortality outcomes to enable examination of spatio-temporal variations on smaller geographic scales such as counties. This method allows examination of spatiotemporal variation across the entire U.S., even where the data are sparse. We used mortality data from 2005-2015 to explore spatiotemporal variation in SRs, as one particular application of the Bayesian spatio-temporal modeling strategy in R-INLA to predict year and county-specific SRs. Specifically, hierarchical Bayesian spatio-temporal models were implemented with spatially structured and unstructured random effects, correlated time effects, time varying confounders and space-time interaction terms in the software R-INLA, borrowing strength across both counties and years to produce smoothed county level SRs. Model-based estimates of SRs were mapped to explore geographic variation.

Identifying neonates at a very high risk for mortality among children with congenital diaphragmatic hernia managed with extracorporeal membrane oxygenation.

PubMed

Haricharan, Ramanath N; Barnhart, Douglas C; Cheng, Hong; Delzell, Elizabeth

2009-01-01

The purpose of this study was to identify mortality risk factors in children with congenital diaphragmatic hernia (CDH) treated with extracorporeal membrane oxygenation (ECMO) and generate a prediction score for those at a very high risk for mortality. Data on first ECMO runs of all neonates with CDH, between January 1997 and June 2007, were obtained from the Extracorporeal Life Support Organization registry (N = 2678). The data were split into "training data (TD)" (n = 2006) and "validation data" (n = 672). The primary outcome analyzed was in-hospital mortality. Modified Poisson regression was used for analyses. Overall in-hospital mortality among 2678 neonates (males, 57%; median age at ECMO, 1 day) was 52%. The univariate and multivariable analyses were performed using TD. An empirically weighted mortality prediction score was generated with possible scores ranging from 0 to 35 points. Of 69 who scored 14 or higher in the TD, 62 died (positive predictive value [PPV], 90%), of 37 with 15 or higher, 35 died (PPV, 95%), of 23 with 16 or higher, 22 died (PPV, 96%). A cut-off point of 15 was chosen and was tested using the separate validation dataset. In validation data, the cut-off point 15 had a PPV of 96% (23 died of 24). Scoring 15 or higher on the prediction score identifies neonates with CDH at a very high risk for mortality among those managed with ECMO and could be used in surgical decision making and counseling.

FOUR Score Predicts Early Outcome in Patients After Traumatic Brain Injury.

PubMed

Nyam, Tee-Tau Eric; Ao, Kam-Hou; Hung, Shu-Yu; Shen, Mei-Li; Yu, Tzu-Chieh; Kuo, Jinn-Rung

2017-04-01

The aim of the study was to determine whether the Full Outline of UnResponsiveness (FOUR) score, which includes eyes opening (E), motor function (M), brainstem reflex (B), and respiratory pattern (R), can be used as an alternate method to the Glasgow Coma Scale (GCS) in predicting intensive care unit (ICU) mortality in traumatic brain injury (TBI) patients. From January 2015 to June 2015, patients with isolated TBI admitted to the ICU were enrolled. Three advanced practice nurses administered the FOUR score, GCS, Acute Physiology and Chronic Health Evaluation II (APACHE II), and Therapeutic Intervention Scoring System (TISS) concurrently from ICU admissions. The endpoint of observation was mortality when the patients left the ICU. Data are presented as frequency with percentages, mean with standard deviation, or median with interquartile range. Each measurement tool used area under the receiver operating characteristic curve to compare the predictive power between these four tools. In addition, the difference between survival and death was estimated using the Wilcoxon rank sum test. From 55 TBI patients, males (72.73 %) were represented more than females, the mean age was 63.1 ± 17.9, and 19 of 55 observations (35 %) had a maximum FOUR score of 16. The overall mortality rate was 14.6 %. The area under the receiver operating characteristic curve was 74.47 % for the FOUR score, 74.73 % for the GCS, 81.78 % for the APACHE II, and 53.32 % for the TISS. The FOUR score has similar predictive power of mortality compared to the GCS and APACHE II. Each of the parameters-E, M, B, and R-of the FOUR score showed a significant difference between mortality and survival group, while the verbal and eye-opening components of the GCS did not. Having similar predictive power of mortality compared to the GCS and APACHE II, the FOUR score can be used as an alternative in the prediction of early mortality in TBI patients in the ICU.

Comparison and relationship of thyroid hormones, IL-6, IL-10 and albumin as mortality predictors in case-mix critically ill patients.

PubMed

Quispe E, Álvaro; Li, Xiang-Min; Yi, Hong

2016-05-01

To compare the ability of thyroid hormones, IL-6, IL-10, and albumin to predict mortality, and to assess their relationship in case-mix acute critically ill patients. APACHE II scores and serum thyroid hormones (FT3, FT4, and TSH), IL-6, IL-10, and albumin were obtained at EICU admission for 79 cases of mix acute critically ill patients without previous history of thyroid disease. Patients were followed for 28 days with patient's death as the primary outcome. All mean values were compared, correlations assessed with Pearson' test, and mortality prediction assessed by multivariate logistic regression and ROC. Non survivors were older, with higher APACHE II score (p=0.000), IL-6 (p<0.05), IL-10 (p=0.000) levels, and lower albumin (p=0.000) levels compared to survivors at 28 days. IL-6 and IL-10 had significant negative correlation with albumin (p=0.001) and FT3 (p ⩽ 0.05) respectively, while low albumin had a direct correlation with FT3 (p<0.05). In the mortality prediction assessment, IL-10, albumin and APACHE II were independent morality predictors and showed to have a good (0.70-0.79) AUC-ROC (p<0.05). Despite that the entire cohort showed low FT3 serum levels (p=0.000), there was not statistical difference between survivors and non-survivors; neither showed any significance as mortality predictor. IL-6 and IL-10 are correlated with Low FT3 and hypoalbuminemia. Thyroid hormones assessed at EICU admission did not have any predictive value in our study. And finally, high levels of IL-6 and IL-10 in conjunction with albumin could improve our ability to evaluate disease's severity and predict mortality in the critically ill patients. When use in combination with APACHE II scores, our model showed improved mortality prediction. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mid-arm and calf circumferences are stronger mortality predictors than body mass index for patients with chronic obstructive pulmonary disease.

PubMed

Ho, Shu-Chuan; Wang, Jiun-Yi; Kuo, Han-Pin; Huang, Chien-Da; Lee, Kang-Yun; Chuang, Hsiao-Chi; Feng, Po-Hao; Chen, Tzu-Tao; Hsu, Min-Fang

2016-01-01

Chronic obstructive pulmonary disease (COPD) is currently the third most common cause of death in the world. Patients with COPD experience airflow obstruction, weight loss, skeletal muscle dysfunction, and comorbidities. Anthropometric indicators are risk factors for mortality in geriatric assessment. This study examined and compared the associations of anthropometric indicators, such as low body mass index (BMI), low mid-arm circumference (MAC), and low calf circumference (CC), with the prediction of a 3-year follow-up mortality risk in patients with COPD. We recruited nonhospitalized patients with COPD without acute conditions from a general hospital in Taiwan. The BMI, MAC, and CC of all patients were measured, and they were followed for 3 years through telephone interviews and chart reviews. The Kaplan-Meier survival curves stratified by BMI, MAC, and CC were analyzed. Variables univariately associated with survival were entered into a multivariate Cox regression model. The Bayesian information criterion was used to compare the predictive ability of the three anthropometric indicators to predict mortality rate. In total, 104 patients were included (mean ± standard deviation age, 74.2±6.9 years; forced expiratory volume in 1 second [%], 58.4±20.4 predicted; males, 94.2%); 22 patients (21.2%) died during the 36-month follow-up. During this long-term follow-up, the three anthropometric indicators could predict mortality risk in patients with COPD (low BMI [<21 kg/m(2)], hazard ratio [HR] =2.78, 95% confidence interval [CI] =1.10-7.10; low MAC [<23.5 cm], HR =3.09, 95% CI =1.30-7.38; low CC [<30 cm], HR =4.40, 95% CI =1.82-10.63). CC showed the strongest potential in predicting the mortality risk, followed by MAC and BMI. Among the three anthropometric variables examined, CC can be considered a strong predictor of mortality risk in patients with COPD.

The effects of raking on sugar pine mortality following prescribed fire in Sequoia and Kings Canyon National Parks, California, USA

USGS Publications Warehouse

Nesmith, Jonathan C. B.; O'Hara, Kevin L.; van Mantgem, Phillip J.; de Valpine, Perry

2010-01-01

Prescribed fire is an important tool for fuel reduction, the control of competing vegetation, and forest restoration. The accumulated fuels associated with historical fire exclusion can cause undesirably high tree mortality rates following prescribed fires and wildfires. This is especially true for sugar pine (Pinus lambertiana Douglas), which is already negatively affected by the introduced pathogen white pine blister rust (Cronartium ribicola J.C. Fisch. ex Rabenh). We tested the efficacy of raking away fuels around the base of sugar pine to reduce mortality following prescribed fire in Sequoia and Kings Canyon national parks, California, USA. This study was conducted in three prescribed fires and included 457 trees, half of which had the fuels around their bases raked away to mineral soil to 0.5 m away from the stem. Fire effects were assessed and tree mortality was recorded for three years after prescribed fires. Overall, raking had no detectable effect on mortality: raked trees averaged 30% mortality compared to 36% for unraked trees. There was a significant effect, however, between the interaction of raking and average pre-treatment forest floor fuel depth: the predicted probability of survival of a 50 cm dbh tree was 0.94 vs. 0.96 when average pre-treatment fuel depth was 0 cm for a raked and unraked tree, respectively. When average pre-treatment forest floor fuel depth was 30 cm, the predicted probability of survival for a raked 50 cm dbh tree was 0.60 compared to only 0.07 for an unraked tree. Raking did not affect mortality when fire intensity, measured as percent crown volume scorched, was very low (0% scorch) or very high (>80% scorch), but the raking treatment significantly increased the proportion of trees that survived by 9.6% for trees that burned under moderate fire intensity (1% to 80% scorch). Raking significantly reduced the likelihood of bole charring and bark beetle activity three years post fire. Fuel depth and anticipated fire intensity need to be accounted for to maximize the effectiveness of the treatments. Raking is an important management option to reduce tree mortality from prescribed fire, but is most effective under specific fuel and burning conditions.

A novel nomogram accurately quantifies the risk of mortality in elderly patients undergoing colorectal surgery.

PubMed

Kiran, Ravi P; Attaluri, Vikram; Hammel, Jeff; Church, James

2013-05-01

The ability to accurately predict postoperative mortality is expected to improve preoperative decisions for elderly patients considered for colorectal surgery. Patients undergoing colorectal surgery were identified from the National Surgical Quality Improvement Program database (2005-2007) and stratified as elderly (>70 years) and nonelderly (<70 years). Univariate analysis of preoperative risk factors and 30-day mortality and morbidity were analyzed on 70% of the population. A nomogram for mortality was created and tested on the remaining 30%. Of 30,900 colorectal cases, 10,750 were elderly (>70 years). Mortality increased steadily with age (0.5% every 5 years) and at a faster rate (1.2% every 5 years) after 70 years, which defined "elderly" in this study. Elderly (mean age: 78.4 years) and nonelderly patients (52.8 years) had mortality of 7.6% versus 2.0% and a morbidity of 32.8% versus 25.7%, respectively. Elderly patients had greater preoperative comorbidities including chronic obstructive pulmonary disease (10.5% vs 3.8%), diabetes (18.7% vs 11.1%), and renal insufficiency (1.7% vs 1.3%). A multivariate model for 30-day mortality and nomogram were created. Increasing age was associated with mortality [age >70 years: odds ratio (OR) = 2.0 (95% confidence interval (CI): 1.7-2.4); >85 years: OR = 4.3 (95% CI: 3.3-5.5)]. The nomogram accurately predicted mortality, including very high-risk (>50% mortality) with a concordant index for this model of 0.89. Colorectal surgery in elderly patients is associated with significantly higher mortality. This novel nomogram that predicts postoperative mortality may facilitate preoperative treatment decisions.

Mechanisms to explain purse seine bycatch mortality of coho salmon.

PubMed

Raby, Graham D; Hinch, Scott G; Patterson, David A; Hills, Jayme A; Thompson, Lisa A; Cooke, Steven J

2015-10-01

Research on fisheries bycatch and discards frequently involves the assessment of reflex impairment, injury, or blood physiology as means of quantifying vitality and predicting post-release mortality, but exceptionally few studies have used all three metrics concurrently. We conducted an experimental purse seine fishery for Pacific salmon in the Juan de Fuca Strait, with a focus on understanding the relationships between different sublethal indicators and whether mortality could be predicted in coho salmon (Oncorhynchus kisutch) bycatch. We monitored mortality using a ~24-h net pen experiment (N = 118) and acoustic telemetry (N = 50), two approaches commonly used to assess bycatch mortality that have rarely been directly compared. Short-term mortality was 21% in the net pen experiment (~24 h) and estimated at 20% for telemetry-tagged fish (~48-96 h). Mortality was predicted by injury and reflex impairment, but only in the net pen experiment. Higher reflex impairment was mirrored by perturbations to plasma ions and lactate, supporting the notion that reflex impairment can be used as a proxy for departure from physiological homeostasis. Reflex impairment also significantly correlated with injury scores, while injury scores were significantly correlated with plasma ion concentrations. The higher time-specific mortality rate in the net pen and the fact that reflexes and injury corresponded with mortality in that experiment, but not in the telemetry-tagged fish released into the wild could be explained partly by confinement stress. While holding experiments offer the potential to provide insights into the underlying causes of mortality, chronic confinement stress can complicate the interpretation of patterns and ultimately affect mortality rates. Collectively, these results help refine our understanding of the different sublethal metrics used to assess bycatch and the mechanisms that can lead to mortality.

The novel EuroSCORE II algorithm predicts the hospital mortality of thoracic aortic surgery in 461 consecutive Japanese patients better than both the original additive and logistic EuroSCORE algorithms.

PubMed

Nishida, Takahiro; Sonoda, Hiromichi; Oishi, Yasuhisa; Tanoue, Yoshihisa; Nakashima, Atsuhiro; Shiokawa, Yuichi; Tominaga, Ryuji

2014-04-01

The European System for Cardiac Operative Risk Evaluation (EuroSCORE) II was developed to improve the overestimation of surgical risk associated with the original (additive and logistic) EuroSCOREs. The purpose of this study was to evaluate the significance of the EuroSCORE II by comparing its performance with that of the original EuroSCOREs in Japanese patients undergoing surgery on the thoracic aorta. We have calculated the predicted mortalities according to the additive EuroSCORE, logistic EuroSCORE and EuroSCORE II algorithms in 461 patients who underwent surgery on the thoracic aorta during a period of 20 years (1993-2013). The actual in-hospital mortality rates in the low- (additive EuroSCORE of 3-6), moderate- (7-11) and high-risk (≥11) groups (followed by overall mortality) were 1.3, 6.2 and 14.4% (7.2% overall), respectively. Among the three different risk groups, the expected mortality rates were 5.5 ± 0.6, 9.1 ± 0.7 and 13.5 ± 0.2% (9.5 ± 0.1% overall) by the additive EuroSCORE algorithm, 5.3 ± 0.1, 16 ± 0.4 and 42.4 ± 1.3% (19.9 ± 0.7% overall) by the logistic EuroSCORE algorithm and 1.6 ± 0.1, 5.2 ± 0.2 and 18.5 ± 1.3% (7.4 ± 0.4% overall) by the EuroSCORE II algorithm, indicating poor prediction (P < 0.0001) of the mortality in the high-risk group, especially by the logistic EuroSCORE. The areas under the receiver operating characteristic curves of the additive EuroSCORE, logistic EuroSCORE and EuroSCORE II algorithms were 0.6937, 0.7169 and 0.7697, respectively. Thus, the mortality expected by the EuroSCORE II more closely matched the actual mortality in all three risk groups. In contrast, the mortality expected by the logistic EuroSCORE overestimated the risks in the moderate- (P = 0.0002) and high-risk (P < 0.0001) patient groups. Although all of the original EuroSCOREs and EuroSCORE II appreciably predicted the surgical mortality for thoracic aortic surgery in Japanese patients, the EuroSCORE II best predicted the mortalities in all risk groups.

Machine learning for prediction of 30-day mortality after ST elevation myocardial infraction: An Acute Coronary Syndrome Israeli Survey data mining study.

PubMed

Shouval, Roni; Hadanny, Amir; Shlomo, Nir; Iakobishvili, Zaza; Unger, Ron; Zahger, Doron; Alcalai, Ronny; Atar, Shaul; Gottlieb, Shmuel; Matetzky, Shlomi; Goldenberg, Ilan; Beigel, Roy

2017-11-01

Risk scores for prediction of mortality 30-days following a ST-segment elevation myocardial infarction (STEMI) have been developed using a conventional statistical approach. To evaluate an array of machine learning (ML) algorithms for prediction of mortality at 30-days in STEMI patients and to compare these to the conventional validated risk scores. This was a retrospective, supervised learning, data mining study. Out of a cohort of 13,422 patients from the Acute Coronary Syndrome Israeli Survey (ACSIS) registry, 2782 patients fulfilled inclusion criteria and 54 variables were considered. Prediction models for overall mortality 30days after STEMI were developed using 6 ML algorithms. Models were compared to each other and to the Global Registry of Acute Coronary Events (GRACE) and Thrombolysis In Myocardial Infarction (TIMI) scores. Depending on the algorithm, using all available variables, prediction models' performance measured in an area under the receiver operating characteristic curve (AUC) ranged from 0.64 to 0.91. The best models performed similarly to the Global Registry of Acute Coronary Events (GRACE) score (0.87 SD 0.06) and outperformed the Thrombolysis In Myocardial Infarction (TIMI) score (0.82 SD 0.06, p<0.05). Performance of most algorithms plateaued when introduced with 15 variables. Among the top predictors were creatinine, Killip class on admission, blood pressure, glucose level, and age. We present a data mining approach for prediction of mortality post-ST-segment elevation myocardial infarction. The algorithms selected showed competence in prediction across an increasing number of variables. ML may be used for outcome prediction in complex cardiology settings. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

[Predictive factors of mortality in extremely preterm infants].

PubMed

Lin, L; Fang, M C; Jiang, H; Zhu, M L; Chen, S Q; Lin, Z L

2018-04-02

Objective: To investigate the predictive factors of mortality in extremely preterm infants. Methods: The retrospective case-control study was accomplished in the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University. A total of 268 extremely preterm infants seen from January 1, 1999 to December 31, 2015 were divided into survival group (192 cases) and death group (76 cases). The potential predictive factors of mortality were identified by univariate analysis, and then analyzed by multivariate unconditional Logistic regression analysis. The mortality and predictive factors were also compared between two time periods, which were January 1, 1999 to December 31, 2007 (65 cases) and January 1, 2008 to December 31, 2015 (203 cases). Results: The median gestational age (GA) of extremely preterm infants was 27 weeks (23 +3 -27 +6 weeks). The mortality was higher in infants with GA of 25-<26 weeks ( OR= 2.659, 95% CI: 1.211-5.840) and<25 weeks ( OR= 10.029, 95% CI: 3.266-30.792) compared to that in infants with GA> 26 weeks. From January 1, 2008 to December 31, 2015, the number of extremely preterm infants was increased significantly compared to the previous 9 years, while the mortality decreased significantly ( OR= 0.490, 95% CI: 0.272-0.884). Multivariate unconditional Logistic regression analysis showed that GA below 25 weeks ( OR= 6.033, 95% CI: 1.393-26.133), lower birth weight ( OR= 0.997, 95% CI: 0.995-1.000), stage Ⅲ necrotizing enterocolitis (NEC) ( OR= 15.907, 95% CI: 3.613-70.033), grade Ⅰ and Ⅱ intraventricular hemorrhage (IVH) ( OR= 0.260, 95% CI: 0.117-0.575) and dependence on invasive mechanical ventilation ( OR= 3.630, 95% CI: 1.111-11.867) were predictive factors of mortality in extremely preterm infants. Conclusions: GA below 25 weeks, lower birth weight, stage Ⅲ NEC and dependence on invasive mechanical ventilation are risk factors of mortality in extremely preterm infants. But grade ⅠandⅡ IVH is protective factor.

Usefulness of Glycemic Gap to Predict ICU Mortality in Critically Ill Patients With Diabetes.

PubMed

Liao, Wen-I; Wang, Jen-Chun; Chang, Wei-Chou; Hsu, Chin-Wang; Chu, Chi-Ming; Tsai, Shih-Hung

2015-09-01

Stress-induced hyperglycemia (SIH) has been independently associated with an increased risk of mortality in critically ill patients without diabetes. However, it is also necessary to consider preexisting hyperglycemia when investigating the relationship between SIH and mortality in patients with diabetes. We therefore assessed whether the gap between admission glucose and A1C-derived average glucose (ADAG) levels could be a predictor of mortality in critically ill patients with diabetes.We retrospectively reviewed the Acute Physiology and Chronic Health Evaluation II (APACHE-II) scores and clinical outcomes of patients with diabetes admitted to our medical intensive care unit (ICU) between 2011 and 2014. The glycosylated hemoglobin (HbA1c) levels were converted to the ADAG by the equation, ADAG = [(28.7 × HbA1c) - 46.7]. We also used receiver operating characteristic (ROC) curves to determine the optimal cut-off value for the glycemic gap when predicting ICU mortality and used the net reclassification improvement (NRI) to measure the improvement in prediction performance gained by adding the glycemic gap to the APACHE-II score.We enrolled 518 patients, of which 87 (17.0%) died during their ICU stay. Nonsurvivors had significantly higher APACHE-II scores and glycemic gaps than survivors (P < 0.001). Critically ill patients with diabetes and a glycemic gap ≥80 mg/dL had significantly higher ICU mortality and adverse outcomes than those with a glycemic gap <80 mg/dL (P < 0.001). Incorporation of the glycemic gap into the APACHE-II score increased the discriminative performance for predicting ICU mortality by increasing the area under the ROC curve from 0.755 to 0.794 (NRI = 13.6%, P = 0.0013).The glycemic gap can be used to assess the severity and prognosis of critically ill patients with diabetes. The addition of the glycemic gap to the APACHE-II score significantly improved its ability to predict ICU mortality.

Biochemical risk indices, including plasma homocysteine, that prospectively predict mortality in older British people: the National Diet and Nutrition Survey of People Aged 65 Years and Over.

PubMed

Bates, Christopher J; Mansoor, Mohammed A; Pentieva, Kristina D; Hamer, Mark; Mishra, Gita D

2010-09-01

Predictive power, for total and vascular mortality, of selected indices measured at baseline in the British National Diet and Nutrition Survey (community-living subset) of People Aged 65 Years and Over was tested. Mortality status and its primary and underlying causes were recorded for 1100 (mean age 76.7 (sd 7.5) years, 50.2% females) respondents from the baseline survey in 1994-5 until September 2008. Follow-up data analyses focussed especially on known predictors of vascular disease risk, together with intakes and status indices of selected nutrients known to affect, or to be affected by, these predictors. Total mortality was significantly predicted by hazard ratios of baseline plasma concentrations (per sd) of total homocysteine (tHcy) (95% CI) 1.19 (1.11, 1.27), pyridoxal phosphate 0.90 (0.81, 1.00), pyridoxic acid 1.10 (1.03, 1.19), alpha1-antichymotrypsin 1.21 (1.13, 1.29), fibrinogen 1.14 (1.05, 1.23), creatinine 1.20 (1.10, 1.31) and glycosylated Hb 1.23 (1.14, 1.32), and by dietary intakes of energy 0.87 (0.80, 0.96) and protein 0.86 (0.77, 0.97). Prediction patterns and significance were similar for primary-cause vascular mortality. The traditional risk predictors plasma total and HDL cholesterol were not significant mortality predictors in this age group, nor were the known tHcy-regulating nutrients, folate and vitamin B12 (intakes and status indices). Model adjustment for known risk predictors resulted in the loss of significance for some of the afore-mentioned indices; however, tHcy 1.34 (1.04, 1.73) remained a significant predictor for vascular mortality. Thus, total and primary vascular mortality is predicted by energy and protein intakes, and by biochemical indices including tHcy, independent of serum folate or vitamin B12.

Comparison of the Full Outline of UnResponsiveness score and the Glasgow Coma Scale in predicting mortality in critically ill patients*.

PubMed

Wijdicks, Eelco F M; Kramer, Andrew A; Rohs, Thomas; Hanna, Susan; Sadaka, Farid; O'Brien, Jacklyn; Bible, Shonna; Dickess, Stacy M; Foss, Michelle

2015-02-01

Impaired consciousness has been incorporated in prediction models that are used in the ICU. The Glasgow Coma Scale has value but is incomplete and cannot be assessed in intubated patients accurately. The Full Outline of UnResponsiveness score may be a better predictor of mortality in critically ill patients. Thirteen ICUs at five U.S. hospitals. One thousand six hundred ninety-five consecutive unselected ICU admissions during a six-month period in 2012. Glasgow Coma Scale and Full Outline of UnResponsiveness score were recorded within 1 hour of admission. Baseline characteristics and physiologic components of the Acute Physiology and Chronic Health Evaluation system, as well as mortality were linked to Glasgow Coma Scale/Full Outline of UnResponsiveness score information. None. We recruited 1,695 critically ill patients, of which 1,645 with complete data could be linked to data in the Acute Physiology and Chronic Health Evaluation system. The area under the receiver operating characteristic curve of predicting ICU mortality using the Glasgow Coma Scale was 0.715 (95% CI, 0.663-0.768) and using the Full Outline of UnResponsiveness score was 0.742 (95% CI, 0.694-0.790), statistically different (p = 0.001). A similar but nonsignificant difference was found for predicting hospital mortality (p = 0.078). The respiratory and brainstem reflex components of the Full Outline of UnResponsiveness score showed a much wider range of mortality than the verbal component of Glasgow Coma Scale. In multivariable models, the Full Outline of UnResponsiveness score was more useful than the Glasgow Coma Scale for predicting mortality. The Full Outline of UnResponsiveness score might be a better prognostic tool of ICU mortality than the Glasgow Coma Scale in critically ill patients, most likely a result of incorporating brainstem reflexes and respiration into the Full Outline of UnResponsiveness score.

Serum peroxiredoxin 4: a marker of oxidative stress associated with mortality in type 2 diabetes (ZODIAC-28).

PubMed

Gerrits, Esther G; Alkhalaf, Alaa; Landman, Gijs W D; van Hateren, Kornelis J J; Groenier, Klaas H; Struck, Joachim; Schulte, Janin; Gans, Reinold O B; Bakker, Stephan J L; Kleefstra, Nanne; Bilo, Henk J G

2014-01-01

Oxidative stress plays an underlying pathophysiologic role in the development of diabetes complications. The aim of this study was to investigate peroxiredoxin 4 (Prx4), a proposed novel biomarker of oxidative stress, and its association with and capability as a biomarker in predicting (cardiovascular) mortality in type 2 diabetes mellitus. Prx4 was assessed in baseline serum samples of 1161 type 2 diabetes patients. Cox proportional hazard models were used to evaluate the relationship between Prx4 and (cardiovascular) mortality. Risk prediction capabilities of Prx4 for (cardiovascular) mortality were assessed with Harrell's C statistic, the integrated discrimination improvement and net reclassification improvement. Mean age was 67 and the median diabetes duration was 4.0 years. After a median follow-up period of 5.8 years, 327 patients died; 137 cardiovascular deaths. Prx4 was associated with (cardiovascular) mortality. The Cox proportional hazard models added the variables: Prx4 (model 1); age and gender (model 2), and BMI, creatinine, smoking, diabetes duration, systolic blood pressure, cholesterol-HDL ratio, history of macrovascular complications, and albuminuria (model 3). Hazard ratios (HR) (95% CI) for cardiovascular mortality were 1.93 (1.57 - 2.38), 1.75 (1.39 - 2.20), and 1.63 (1.28 - 2.09) for models 1, 2 and 3, respectively. HR for all-cause mortality were 1.73 (1.50 - 1.99), 1.50 (1.29 - 1.75), and 1.44 (1.23 - 1.67) for models 1, 2 and 3, respectively. Addition of Prx4 to the traditional risk factors slightly improved risk prediction of (cardiovascular) mortality. Prx4 is independently associated with (cardiovascular) mortality in type 2 diabetes patients. After addition of Prx4 to the traditional risk factors, there was a slightly improvement in risk prediction of (cardiovascular) mortality in this patient group.

Comparison of the predictive performance of the BIG, TRISS, and PS09 score in an adult trauma population derived from multiple international trauma registries

PubMed Central

2013-01-01

Background The BIG score (Admission base deficit (B), International normalized ratio (I), and Glasgow Coma Scale (G)) has been shown to predict mortality on admission in pediatric trauma patients. The objective of this study was to assess its performance in predicting mortality in an adult trauma population, and to compare it with the existing Trauma and Injury Severity Score (TRISS) and probability of survival (PS09) score. Materials and methods A retrospective analysis using data collected between 2005 and 2010 from seven trauma centers and registries in Europe and the United States of America was performed. We compared the BIG score with TRISS and PS09 scores in a population of blunt and penetrating trauma patients. We then assessed the discrimination ability of all scores via receiver operating characteristic (ROC) curves and compared the expected mortality rate (precision) of all scores with the observed mortality rate. Results In total, 12,206 datasets were retrieved to validate the BIG score. The mean ISS was 15 ± 11, and the mean 30-day mortality rate was 4.8%. With an AUROC of 0.892 (95% confidence interval (CI): 0.879 to 0.906), the BIG score performed well in an adult population. TRISS had an area under ROC (AUROC) of 0.922 (0.913 to 0.932) and the PS09 score of 0.825 (0.915 to 0.934). On a penetrating-trauma population, the BIG score had an AUROC result of 0.920 (0.898 to 0.942) compared with the PS09 score (AUROC of 0.921; 0.902 to 0.939) and TRISS (0.929; 0.912 to 0.947). Conclusions The BIG score is a good predictor of mortality in the adult trauma population. It performed well compared with TRISS and the PS09 score, although it has significantly less discriminative ability. In a penetrating-trauma population, the BIG score performed better than in a population with blunt trauma. The BIG score has the advantage of being available shortly after admission and may be used to predict clinical prognosis or as a research tool to risk stratify trauma patients into clinical trials. PMID:23844754

A Multifactorial Approach to Predicting Death Anxiety: Assessing the Role of Religiosity, Susceptibility to Mortality Cues, and Individual Differences.

PubMed

French, Carrie; Greenauer, Nathan; Mello, Catherine

2017-01-01

Death anxiety is not only experienced by individuals receiving end-of-life care, but also by family members, social workers, and other service providers who support these individuals. Thus, identifying predictors of individual differences in experienced death anxiety levels may have both theoretical and clinical ramifications. The present study assessed the relative influence of religiosity, susceptibility to mortality cues, state and trait anxiety, and demographic factors in the experience of death anxiety through an online survey distributed to members of two online communities related to end-of-life care. Results indicated that cognitive and emotional susceptibility to mortality cues, as well as gender, predicted differences in death anxiety. Conversely, religiosity and age did not increase the predictive power of the model. Thus, death anxiety may be a function of emotional, cognitive, and sociocultural factors that interact in complex, but predictable, ways to modulate the response to mortality cues that occur in one's life.

Predictive global trends in the incidence and mortality of pancreatic cancer based on geographic location, socio-economic status, and demographic shift.

PubMed

Are, Chandrakanth; Chowdhury, Sanjib; Ahmad, Humera; Ravipati, Advaitaa; Song, Tianqiang; Shrikandhe, Shailesh; Smith, Lynette

2016-11-01

Pancreatic Cancer (PC) is a lethal malignancy that accounts for about 4% of cancer-related deaths worldwide. The aim of this study is to describe the influence of geography (based on WHO regions), socio-economic development (based on Human Development Index [HDI]) and demographic shift on the temporal trends in global incidence and mortality of PC. Data (2012-2030) relating to the incidence, mortality of PC and demographic shifts based on WHO regions and HDI areas were extracted from GLOBOCAN 2012. Linear regression was used to evaluate trends in total incidence and mortality. We noted a definite association between PC and higher socio-economic status. Advanced age (age ≥65) contributed to the rising burden in all socio-economic regions of the world except in the Low Human Development (LHD) countries where the disease predominantly affected population <65 years of age. The global burden of PC is expected to rise significantly over the next few decades regardless of geographic location, socio-economic development, age and gender. Advance knowledge of this data can help formulate strategies to specifically target countries and populations that promote public health policy to tackle this lethal disease on the global stage. J. Surg. Oncol. 2016;114:736-742. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Echocardiographic predictors of adverse outcomes after continuous left ventricular assist device implantation.

PubMed

Topilsky, Yan; Oh, Jae K; Shah, Dipesh K; Boilson, Barry A; Schirger, John A; Kushwaha, Sudhir S; Pereira, Naveen L; Park, Soon J

2011-03-01

The purpose of the study was to identify echocardiographic predictors of adverse outcome in patients implanted with continuous-flow left ventricular assist devices (LVAD). Continuous flow LVAD have become part of the standard of care for the treatment of advanced heart failure. However, knowledge of echocardiographic predictors of outcome after LVAD are lacking. Overall, 83 patients received continuous-flow LVAD (HeartMate II, Thoratec Corporation, Pleasanton, California) from February 2007 to June 2010. The LVAD database, containing various echocardiographic parameters, was examined to analyze their influence on in-hospital mortality, a compound cardiac event (in-hospital mortality or acute right ventricular [RV] dysfunction), and long-term mortality. Eight patients died before discharge (operative mortality 9.6%), and another 15 patients were considered to have acute RV dysfunction immediately after surgery. Patients with relatively small left ventricular end-diastolic diameters (<63 mm) had significantly higher risk for in-hospital mortality (odds ratio [OR]: 0.9; 95% confidence interval [CI]: 0.83 to 0.99; p = 0.04) or occurrence of the compound cardiac event (OR: 0.89; 95% CI: 0.84 to 0.95; p < 0.001). The most significant predictor of outcome was the decreased timing interval between the onset and the cessation of tricuspid regurgitation flow corrected for heart rate (TRDc), a surrogate for early systolic equalization of RV and right atrial pressure. Short TRDc predicted in-hospital mortality (OR: 0.85; 95% CI: 0.74 to 0.97; p = 0.01) and the compound cardiac event (OR: 0.83; 95% CI: 0.74 to 0.91; p < 0.0001). Multivariate analysis based on a logistic regression model demonstrated that the accuracy of predicting the 30-day compound adverse outcome was improved with the addition of echocardiographic variables when added to the commonly used hemodynamic or clinical scores. TRDc predicted long-term survival, with adjusted risk ratios of 0.89 for death from any cause (95% CI: 0.83 to 0.96; p = 0.003) and 0.88 for cardiac-related death (95% CI: 0.77 to 0.98; p = 0.03). The presence of either a relatively small left ventricle (<63 mm) or early systolic equalization of RV and right atrial pressure (short TRDc) demonstrated by echocardiography is associated with increased 30-day morbidity and mortality. Prediction of early adverse outcomes by echocardiographic parameters is additive to laboratory or hemodynamic variables. Copyright © 2011 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Predictive factors of mortality within 30 days in patients with nonvariceal upper gastrointestinal bleeding.

PubMed

Lee, Yoo Jin; Min, Bo Ram; Kim, Eun Soo; Park, Kyung Sik; Cho, Kwang Bum; Jang, Byoung Kuk; Chung, Woo Jin; Hwang, Jae Seok; Jeon, Seong Woo

2016-01-01

Nonvariceal upper gastrointestinal bleeding (NVUGIB) is a common medical emergency that can be life threatening. This study evaluated predictive factors of 30-day mortality in patients with this condition. A prospective observational study was conducted at a single hospital between April 2010 and November 2012, and 336 patients with symptoms and signs of gastrointestinal bleeding were consecutively enrolled. Clinical characteristics and endoscopic findings were reviewed to identify potential factors associated with 30-day mortality. Overall, 184 patients were included in the study (men, 79.3%; mean age, 59.81 years), and 16 patients died within 30 days (8.7%). Multivariate analyses revealed that comorbidity of diabetes mellitus (DM) or metastatic malignancy, age ≥ 65 years, and hypotension (systolic pressure < 90 mmHg) during hospitalization were significant predictive factors of 30-day mortality. Comorbidity of DM or metastatic malignancy, age ≥ 65 years, and hemodynamic instability during hospitalization were predictors of 30-day mortality in patients with NVUGIB. These results will help guide the management of patients with this condition.

Performance of Simplified Acute Physiology Score 3 In Predicting Hospital Mortality In Emergency Intensive Care Unit.

PubMed

Ma, Qing-Bian; Fu, Yuan-Wei; Feng, Lu; Zhai, Qiang-Rong; Liang, Yang; Wu, Meng; Zheng, Ya-An

2017-07-05

Since the 1980s, severity of illness scoring systems has gained increasing popularity in Intensive Care Units (ICUs). Physicians used them for predicting mortality and assessing illness severity in clinical trials. The objective of this study was to assess the performance of Simplified Acute Physiology Score 3 (SAPS 3) and its customized equation for Australasia (Australasia SAPS 3, SAPS 3 [AUS]) in predicting clinical prognosis and hospital mortality in emergency ICU (EICU). A retrospective analysis of the EICU including 463 patients was conducted between January 2013 and December 2015 in the EICU of Peking University Third Hospital. The worst physiological data of enrolled patients were collected within 24 h after admission to calculate SAPS 3 score and predicted mortality by regression equation. Discrimination between survivals and deaths was assessed by the area under the receiver operator characteristic curve (AUC). Calibration was evaluated by Hosmer-Lemeshow goodness-of-fit test through calculating the ratio of observed-to-expected numbers of deaths which is known as the standardized mortality ratio (SMR). A total of 463 patients were enrolled in the study, and the observed hospital mortality was 26.1% (121/463). The patients enrolled were divided into survivors and nonsurvivors. Age, SAPS 3 score, Acute Physiology and Chronic Health Evaluation Score II (APACHE II), and predicted mortality were significantly higher in nonsurvivors than survivors (P < 0.05 or P < 0.01). The AUC (95% confidence intervals [CI s]) for SAPS 3 score was 0.836 (0.796-0.876). The maximum of Youden's index, cutoff, sensitivity, and specificity of SAPS 3 score were 0.526%, 70.5 points, 66.9%, and 85.7%, respectively. The Hosmer-Lemeshow goodness-of-fit test for SAPS 3 demonstrated a Chi-square test score of 10.25, P = 0.33, SMR (95% CI) = 0.63 (0.52-0.76). The Hosmer-Lemeshow goodness-of-fit test for SAPS 3 (AUS) demonstrated a Chi-square test score of 9.55, P = 0.38, SMR (95% CI) = 0.68 (0.57-0.81). Univariate and multivariate analyses were conducted for biochemical variables that were probably correlated to prognosis. Eventually, blood urea nitrogen (BUN), albumin,lactate and free triiodothyronine (FT3) were selected as independent risk factors for predicting prognosis. The SAPS 3 score system exhibited satisfactory performance even superior to APACHE II in discrimination. In predicting hospital mortality, SAPS 3 did not exhibit good calibration and overestimated hospital mortality, which demonstrated that SAPS 3 needs improvement in the future.

Performance of the European System for Cardiac Operative Risk Evaluation II: a meta-analysis of 22 studies involving 145,592 cardiac surgery procedures.

PubMed

Guida, Pietro; Mastro, Florinda; Scrascia, Giuseppe; Whitlock, Richard; Paparella, Domenico

2014-12-01

A systematic review of the European System for Cardiac Operative Risk Evaluation (euroSCORE) II performance for prediction of operative mortality after cardiac surgery has not been performed. We conducted a meta-analysis of studies based on the predictive accuracy of the euroSCORE II. We searched the Embase and PubMed databases for all English-only articles reporting performance characteristics of the euroSCORE II. The area under the receiver operating characteristic curve, the observed/expected mortality ratio, and observed-expected mortality difference with their 95% confidence intervals were analyzed. Twenty-two articles were selected, including 145,592 procedures. Operative mortality occurred in 4293 (2.95%), whereas the expected events according to euroSCORE II were 4802 (3.30%). Meta-analysis of these studies provided an area under the receiver operating characteristic curve of 0.792 (95% confidence interval, 0.773-0.811), an estimated observed/expected ratio of 1.019 (95% confidence interval, 0.899-1.139), and observed-expected difference of 0.125 (95% confidence interval, -0.269 to 0.519). Statistical heterogeneity was detected among retrospective studies including less recent procedures. Subgroups analysis confirmed the robustness of combined estimates for isolated valve procedures and those combined with revascularization surgery. A significant overestimation of the euroSCORE II with an observed/expected ratio of 0.829 (95% confidence interval, 0.677-0.982) was observed in isolated coronary artery bypass grafting and a slight underestimation of predictions in high-risk patients (observed/expected ratio 1.253 and observed-expected difference 1.859). Despite the heterogeneity, the results from this meta-analysis show a good overall performance of the euroSCORE II in terms of discrimination and accuracy of model predictions for operative mortality. Validation of the euroSCORE II in prospective populations needs to be further studied for a continuous improvement of patients' risk stratification before cardiac surgery. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Clinical algorithms for the diagnosis and prognosis of interstitial lung disease in systemic sclerosis.

PubMed

Hax, Vanessa; Bredemeier, Markus; Didonet Moro, Ana Laura; Pavan, Thaís Rohde; Vieira, Marcelo Vasconcellos; Pitrez, Eduardo Hennemann; da Silva Chakr, Rafael Mendonça; Xavier, Ricardo Machado

2017-10-01

Interstitial lung disease (ILD) is currently the primary cause of death in systemic sclerosis (SSc). Thoracic high-resolution computed tomography (HRCT) is considered the gold standard for diagnosis. Recent studies have proposed several clinical algorithms to predict the diagnosis and prognosis of SSc-ILD. To test the clinical algorithms to predict the presence and prognosis of SSc-ILD and to evaluate the association of extent of ILD with mortality in a cohort of SSc patients. Retrospective cohort study, including 177 SSc patients assessed by clinical evaluation, laboratory tests, pulmonary function tests, and HRCT. Three clinical algorithms, combining lung auscultation, chest radiography, and percentage predicted forced vital capacity (FVC), were applied for the diagnosis of different extents of ILD on HRCT. Univariate and multivariate Cox proportional models were used to analyze the association of algorithms and the extent of ILD on HRCT with the risk of death using hazard ratios (HR). The prevalence of ILD on HRCT was 57.1% and 79 patients died (44.6%) in a median follow-up of 11.1 years. For identification of ILD with extent ≥10% and ≥20% on HRCT, all algorithms presented a high sensitivity (>89%) and a very low negative likelihood ratio (<0.16). For prognosis, survival was decreased for all algorithms, especially the algorithm C (HR = 3.47, 95% CI: 1.62-7.42), which identified the presence of ILD based on crackles on lung auscultation, findings on chest X-ray, or FVC <80%. Extensive disease as proposed by Goh et al. (extent of ILD > 20% on HRCT or, in indeterminate cases, FVC < 70%) had a significantly higher risk of death (HR = 3.42, 95% CI: 2.12-5.52). Survival was not different between patients with extent of 10% or 20% of ILD on HRCT, and analysis of 10-year mortality suggested that a threshold of 10% may also have a good predictive value for mortality. However, there is no clear cutoff above which mortality is sharply increased. Clinical algorithms had a good diagnostic performance for extents of SSc-ILD on HRCT with clinical and prognostic relevance (≥10% and ≥20%), and were also strongly related to mortality. Non-HRCT-based algorithms could be useful when HRCT is not available. This is the first study to replicate the prognostic algorithm proposed by Goh et al. in a developing country. Copyright © 2017 Elsevier Inc. All rights reserved.

Mechanisms of plant survival and mortality during drought: Why do some plants survive while others succumb to drought?

USGS Publications Warehouse

McDowell, Nate G.; Pockman, William T.; Allen, Craig D.; Breshears, David D.; Cobb, Neil; Kolb, Thomas; Plaut, Jennifer; Sperry, John; West, Adam; Williams, David G.; Yepez, Enrico A.

2008-01-01

Severe droughts have been associated with regional-scale forest mortality worldwide. Climate change is expected to exacerbate regional mortality events; however, prediction remains difficult because the physiological mechanisms underlying drought survival and mortality are poorly understood. We developed a hydraulically based theory considering carbon balance and insect resistance that allowed development and examination of hypotheses regarding survival and mortality. Multiple mechanisms may cause mortality during drought. A common mechanism for plants with isohydric regulation of water status results from avoidance of drought-induced hydraulic failure via stomatal closure, resulting in carbon starvation and a cascade of downstream effects such as reduced resistance to biotic agents. Mortality by hydraulic failure per se may occur for isohydric seedlings or trees near their maximum height. Although anisohydric plants are relatively drought-tolerant, they are predisposed to hydraulic failure because they operate with narrower hydraulic safety margins during drought. Elevated temperatures should exacerbate carbon starvation and hydraulic failure. Biotic agents may amplify and be amplified by drought-induced plant stress. Wet multidecadal climate oscillations may increase plant susceptibility to drought-induced mortality by stimulating shifts in hydraulic architecture, effectively predisposing plants to water stress. Climate warming and increased frequency of extreme events will probably cause increased regional mortality episodes. Isohydric and anisohydric water potential regulation may partition species between survival and mortality, and, as such, incorporating this hydraulic framework may be effective for modeling plant survival and mortality under future climate conditions.

Simulations of forest mortality in Colorado River basin

NASA Astrophysics Data System (ADS)

Wei, L.; Xu, C.; Johnson, D. J.; Zhou, H.; McDowell, N.

2017-12-01

The Colorado River Basin (CRB) had experienced multiple severe forest mortality events under the recent changing climate. Such forest mortality events may have great impacts on ecosystem services and water budget of the watershed. It is hence important to estimate and predict the forest mortality in the CRB with climate change. We simulated forest mortality in the CRB with a model of plant hydraulics within the FATES (the Functionally Assembled Terrestrial Ecosystem Simulator) coupled to the DOE Earth System model (ACME: Accelerated Climate Model of Energy) at a 0.5 x 0.5 degree resolution. Moreover, we incorporated a stable carbon isotope (δ13C) module to ACME(FATE) and used it as a new predictor of forest mortality. The δ13C values of plants with C3 photosynthetic pathway (almost all trees are C3 plants) can indicate the water stress plants experiencing (the more intensive stress, the less negative δ13C value). We set a δ13C threshold in model simulation, above which forest mortality initiates. We validate the mortality simulations with field data based on Forest Inventory and Analysis (FIA) data, which were aggregated into the same spatial resolution as the model simulations. Different mortality schemes in the model (carbon starvation, hydraulic failure, and δ13C) were tested and compared. Each scheme demonstrated its strength and the plant hydraulics module provided more reliable simulations of forest mortality than the earlier ACME(FATE) version. Further testing is required for better forest mortality modelling.

Detecting early warning signals of tree mortality using multi-scale satellite data: a case study in boreal North Americ

NASA Astrophysics Data System (ADS)

Rogers, B. M.; Hogg, E. H.; Solvik, K.; Ju, J.; Masek, J. G.; Michaelian, M.; Berner, L. T.; Goetz, S. J.

2017-12-01

Tree mortality from drought and biotic infestations represents a fundamental transition for forests at the level of an individual tree, forest stand, and even landscape. Tree mortality precipitates a cascade of ecosystem impacts and has been increasing across the continents, including in the boreal zone where climate changes and feedbacks to the Earth system are relatively large. Despite the importance for science and management communities, our ability to forecast tree mortality at landscape to continental scales is limited. However, two independent information streams have the potential to inform and significantly improve mortality forecasts. Tree-level productivity dynamics are known to precede mortality in predictable ways years to decades before death. Plot-level productivity, in turn, has been related to satellite-based indices such as the Normalized Difference Vegetation Index (NDVI). Here we link these two data sources to show that early warning signals of mortality are evident in several NDVI-based metrics up to 20 years before death. We focus on two repeat forest inventories and three NDVI products across western boreal North America where productivity and mortality dynamics are influenced by periodic drought. These data sources capture a range in forest conditions and spatial resolution to highlight the sensitivity and limitations of our approach. Overall, results indicate potential to use satellite NDVI for early warning signals of mortality. Relationships are broadly consistent across inventories, species, and spatial resolutions, although coarse-scale imagery in the heterogeneous aspen parkland was of limited utility. Longer-term NDVI data and annually re-measured sites with high mortality levels generate the strongest signals, although we still found robust relationships at sites re-measured at a typical five-year frequency. The approach and relationships developed here can be used as a basis for improving forest mortality models and monitoring systems.