Science.gov

Sample records for factor-15 predicts mortality

  1. Growth Differentiation Factor 15 Predicts Chronic Liver Disease Severity

    PubMed Central

    Lee, Eaum Seok; Kim, Seok Hyun; Kim, Hyun Jin; Kim, Kyung Hee; Lee, Byung Seok; Ku, Bon Jeong

    2017-01-01

    Background/Aims Growth differentiation factor 15 (GDF-15) belongs to the transforming growth factor-β superfamily. GDF-15 is emerging as a biomarker for several diseases. The aim of this study was to determine the clinical performances of GDF-15 for the prediction of liver fibrosis and severity in chronic liver disease. Methods The serum GDF-15 levels were examined via enzyme immunoassay in 145 patients with chronic liver disease and 101 healthy individuals. The patients with chronic liver disease consisted of 54 patients with chronic hepatitis, 44 patients with compensated liver cirrhosis, and 47 patients with decompensated liver cirrhosis. Results Of the patients with chronic liver diseases, the decompensated liver cirrhosis patients had an increased serum GDF-15 (3,483 ng/L) level compared with the patients with compensated liver cirrhosis (1,861 ng/L) and chronic hepatitis (1,232 ng/L). The overall diagnostic accuracies of GDF-15, as determined by the area under the receiver operating characteristic curves, were as follows: chronic hepatitis=0.656 (>574 ng/L, sensitivity, 53.7%; specificity, 79.2%), compensated liver cirrhosis=0.886 (>760 ng/L, sensitivity, 75.6%; specificity, 92.1%), and decompensated liver cirrhosis=0.984 (>869 ng/L, sensitivity, 97.9%; specificity, 94.1%). Conclusions This investigation represents the first study to demonstrate the availability of GDF-15 in chronic liver disease. GDF-15 comprised a useful biomarker for the prediction of liver fibrosis and severity in chronic liver disease. PMID:27728964

  2. Growth-differentiation factor 15 as a predictor of mortality in patients with heart failure: a meta-analysis.

    PubMed

    Zeng, Xiaocong; Li, Lang; Wen, Hong; Bi, Qi

    2017-02-01

    Measurement of the biomarker growth-differentiation factor 15 (GDF-15) in patients with heart failure may help in risk stratification. We assessed the relationship between GDF-15 and mortality in patients with heart failure by conducting a meta-analysis. PubMed, Embase, ISI Web of Science, SCOPUS, and Cochrane Library databases were searched for studies that reported data on the baseline GDF-15 levels and all-cause or cardiovascular mortality. Pooled hazard ratios for mortality were calculated and presented with 95% confidence intervals (CIs). Potential sources of heterogeneity were assessed by meta-regression, subgroup, and sensitivity analyses. Eight studies with a total of 4126 heart failure patients were included. Pooled results showed that overexpression of GDF-15 was associated with poor survival in heart failure patients (log unit GDF-15: hazard ratio = 1.86, 95% CI = 1.37-2.52). Subgroup analyses revealed similar results. However, there was evidence of heterogeneity and publication bias. The association disappeared after correction using the trim-and-fill method (log unit GDF-15: hazard ratio 1.07, 95% CI 0.80-1.42). The results of this meta-analysis indicate an association of elevated GDF-15 levels with increased risk of mortality in patients with heart failure. However, the results should be interpreted with caution due to substantial heterogeneity and publication bias among the studies included in the meta-analysis.

  3. Predicting mortality in stroke.

    PubMed

    Bhalla, A; Gupta, O P; Gupta, S B

    2002-09-01

    Physicians are faced with the task of predicting the immediate and long term outcome in stroke patients. It is also important to efficiently and optimally utilize resources. We used APACHE III scoring system or predicting in hospital outcome in patients with stroke. We found it to be sensitive (>90%) and resonably specific (73%) in predicting short term, in-hospital mortality, in our study group.

  4. Plasma growth differentiation factor 15 is associated with weight loss and mortality in cancer patients

    PubMed Central

    Lerner, Lorena; Hayes, Teresa G; Tao, Nianjun; Krieger, Brian; Feng, Bin; Wu, Zhenhua; Nicoletti, Richard; Chiu, M Isabel; Gyuris, Jeno; Garcia, Jose M

    2015-01-01

    Background Cancer-related weight loss is associated with increased inflammation and decreased survival. The novel inflammatory mediator growth differentiation factor (GDF)15 is associated with poor prognosis in cancer but its role in cancer-related weight loss (C-WL) remains unclear. Our objective was to measure GDF15 in plasma samples of cancer subjects and controls and establish its association with other inflammatory markers and clinical outcomes. Methods We measured body weight, appetite, plasma GDF15, and other inflammatory markers in men with cancer-related weight loss (C-WL, n = 58), weight stable patients with cancer (C-WS, n = 72), and non-cancer controls (Co, n = 59) matched by age and pre-illness body mass index. In a subset of patients we also measured handgrip strength, appendicular lean body mass (aLBM), Eastern Cooperative Oncology Group (ECOG), and Karnofsky performance scores. Results GDF15, interleukin (IL)-6 and IL-8 were increased in C-WL versus other groups. IL-1 receptor antagonist, IL-4, interferon–gamma, tumour necrosis factor alpha, and vascular endothelial growth factor A were increased in C-WL versus C-WS, and Activin A was significantly downregulated in Co versus other groups. C-WL patients had lower handgrip strength, aLBM, and fat mass, and Eastern Cooperative Oncology Group and Karnofsky performance scores were lower in both cancer groups. GDF15, IL-6, and IL-8 significantly correlated with weight loss; GDF15 negatively correlated with aLBM, handgrip strength, and fat mass. IL-8 and Activin A negatively correlated with aLBM and fat mass. GDF15 and IL-8 predicted survival adjusting for stage and weight change (Cox regression P < 0.001 for both). Conclusion GDF15 and other inflammatory markers are associated with weight loss, decreased aLBM and strength, and poor survival in patients with cancer. GDF15 may serve as a prognostic indicator in cancer patients and is being evaluated as a potential therapeutic target for

  5. Diabetes mellitus related biomarker: The predictive role of growth-differentiation factor-15.

    PubMed

    Berezin, Alexander E

    2016-01-01

    Growth differentiation factor-15 (GDF-15) is a stress-responsive cytokine, which belongs to super family of the transforming growth factor beta. GDF-15 is widely presented in the various cells (macrophages, vascular smooth muscle cells, adipocytes, cardiomyocytes, endothelial cells, fibroblasts), tissues (adipose tissue, vessels, tissues of central and peripheral nervous system) and organs (heart, brain, liver, placenta) and it plays an important role in the regulation of the inflammatory response, growth and cell differentiation. Elevated GDF-15 was found in patients with established CV diseases including hypertension, stable coronary artery disease, acute coronary syndrome, myocardial infarction, ischemic and none ischemic-induced cardiomyopathies, heart failure, atrial fibrillation, as well as stroke, type two diabetes mellitus (T2DM), chronic kidney disease, infection, liver cirrhosis, malignancy. Therefore, aging, smoking, and various environmental factors, i.e. chemical pollutants are other risk factors that might increase serum GDF-15 level. Although GDF-15 has been reported to be involved in energy homoeostasis and weight loss, to have anti-inflammatory properties, and to predict CV diseases and CV events in general or established CV disease population, there is no large of body of evidence regarding predictive role of elevated GDF-15 in T2DM subjects. The mini review is clarified the role of GDF-15 in T2DM subjects.

  6. Association of Growth Differentiation Factor-15 with Coronary Atherosclerosis and Mortality in a Young, Multiethnic Population: Observations from the Dallas Heart Study

    PubMed Central

    Rohatgi, Anand; Patel, Parag; Das, Sandeep R.; Ayers, Colby R.; Khera, Amit; Martinez-Rumayor, Abelardo; Berry, Jarett D.; McGuire, Darren K.; de Lemos, James A.

    2013-01-01

    Background Growth differentiation factor 15 (GDF-15) is produced by cardiomyocytes and atherosclerotic lesions under stress conditions. Although higher circulating GDF-15 concentrations are associated with mortality across a spectrum of cardiovascular conditions, the relationship of GDF-15 with atherosclerosis and mortality in the general population remains undefined. Methods We measured plasma GDF-15 in 3219 participants of the Dallas Heart Study, a population sample of adults ages 30–65 years (55% women, 49% black). GDF-15 was analyzed in prespecified categories (<1200; 1200–1799; and ≥1800 ng/L) and continuously. End points included prevalent coronary artery calcium (CAC >10 Agatston units), increased CAC (CAC ≥100 Agatston units) by electron beam computed tomography, and mortality through a median 7.3 years of follow-up (120 deaths, 48 cardiovascular deaths). Results Increasing GDF-15 associated with older age, black race, hypertension, diabetes, smoking, left ventricular (LV) mass/body surface area, and worse renal function (P < 0.0001 for each). In multivariable models adjusted for traditional risk factors, renal function, and LV mass/body surface area, GDF-15 ≥1800 ng/L was associated with CAC >10 (odds ratio 2.1; 95% CI 1.2–3.7; P = 0.01), CAC ≥100 (odds ratio 2.6; 95% CI 1.4–4.9; P = 0.002), all-cause mortality (hazard ratio 3.5; 95% CI 2.1–5.9, P < 0.0001), and cardiovascular mortality (hazard ratio 2.5; 95% CI 1.1–5.8, P = 0.03). Adding log GDF-15 to fully adjusted models modestly improved the c statistic (P = 0.025), the integrated discrimination index (0.028; P < 0.0001) and the category-less net reclassification index (0.42; P = 0.002). These findings remained significant with further adjustment for high-sensitivity C-reactive protein, N-terminal pro–B-type natriuretic peptide, and cardiac troponin T. Conclusions GDF-15 is independently associated with subclinical coronary atherosclerosis and mortality, and its potential role for

  7. Association of growth differentiation factor-15 with coronary atherosclerosis and mortality in a young, multiethnic population: observations from the Dallas Heart Study.

    PubMed

    Rohatgi, Anand; Patel, Parag; Das, Sandeep R; Ayers, Colby R; Khera, Amit; Martinez-Rumayor, Abelardo; Berry, Jarett D; McGuire, Darren K; de Lemos, James A

    2012-01-01

    Growth differentiation factor 15 (GDF-15) is produced by cardiomyocytes and atherosclerotic lesions under stress conditions. Although higher circulating GDF-15 concentrations are associated with mortality across a spectrum of cardiovascular conditions, the relationship of GDF-15 with atherosclerosis and mortality in the general population remains undefined. We measured plasma GDF-15 in 3219 participants of the Dallas Heart Study, a population sample of adults ages 30-65 years (55% women, 49% black). GDF-15 was analyzed in prespecified categories (<1200; 1200-1799; and ≥1800 ng/L) and continuously. End points included prevalent coronary artery calcium (CAC>10 Agatston units), increased CAC (CAC≥100 Agatston units) by electron beam computed tomography, and mortality through a median 7.3 years of follow-up (120 deaths, 48 cardiovascular deaths). Increasing GDF-15 associated with older age, black race, hypertension, diabetes, smoking, left ventricular (LV) mass/body surface area, and worse renal function (P<0.0001 for each). In multivariable models adjusted for traditional risk factors, renal function, and LV mass/body surface area, GDF-15≥1800 ng/L was associated with CAC>10 (odds ratio 2.1; 95% CI 1.2-3.7; P=0.01), CAC≥100 (odds ratio 2.6; 95% CI 1.4-4.9; P=0.002), all-cause mortality (hazard ratio 3.5; 95% CI 2.1-5.9, P<0.0001), and cardiovascular mortality (hazard ratio 2.5; 95% CI 1.1-5.8, P=0.03). Adding log GDF-15 to fully adjusted models modestly improved the c statistic (P=0.025), the integrated discrimination index (0.028; P<0.0001) and the category-less net reclassification index (0.42; P=0.002). These findings remained significant with further adjustment for high-sensitivity C-reactive protein, N-terminal pro-B-type natriuretic peptide, and cardiac troponin T. GDF-15 is independently associated with subclinical coronary atherosclerosis and mortality, and its potential role for risk stratification in the general population merits further evaluation.

  8. Growth differentiation factor 15 predicts advanced fibrosis in biopsy-proven non-alcoholic fatty liver disease.

    PubMed

    Koo, Bo Kyung; Um, Sung Hee; Seo, Dong Soo; Joo, Sae Kyung; Bae, Jeong Mo; Park, Jeong Hwan; Chang, Mee Soo; Kim, Jung Ho; Lee, Jieun; Jeong, Won-Il; Kim, Won

    2017-09-12

    We explored whether growth differentiation factor 15 (GDF15) affects the histological severity of non-alcoholic fatty liver disease (NAFLD) independent of insulin resistance. In a biopsy-proven NAFLD cohort, we measured serum GDF15 levels using enzyme-linked immunosorbent assays. Among 190 subjects (mean age, 53±14 years; men, 52.1%), 72 (men, 65.3%) and 78 (men, 44.9%) were diagnosed with biopsy-proven non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH), respectively. GDF15 levels were significantly higher in NASH patients than in controls (P = 0.010) or NAFL patients (P = 0.001). Subjects with advanced fibrosis (≥F3) also showed higher GDF15 levels compared to the others (F0-2; P <0.001). Among NAFLD patients, the highest quartile of GDF15 levels was significantly associated with a risk of advanced fibrosis even after adjustment for age, gender, body mass index, smoking status, hypertension, diabetes, aspartate aminotransferase, platelet, albumin, insulin resistance, and low skeletal muscle mass (odds ratio, 4.27; 95% confidence interval, 1.04-17.63), but not with NASH risk. GDF15 levels showed a significant positive correlation with liver stiffness (Spearman's ρ, 0.525; P < 0.001). Palmitate treatment increased the GDF15 mRNA expression level significantly in Kupffer cells, but not in hepatocytes. In LX-2 cells, GDF15 treatment resulted in enhanced expression of α-smooth muscle actin and collagen I, as well as phosphorylation of SMAD2 and SMAD3. Our findings suggest that GDF15 may serve as a novel biomarker of advanced fibrosis in NAFLD, thereby indicating the need for urgent anti-fibrotic pharmacotherapy. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

  9. Predicting tree mortality following gypsy moth defoliation

    Treesearch

    D.E. Fosbroke; R.R. Hicks; K.W. Gottschalk

    1991-01-01

    Appropriate application of gypsy moth control strategies requires an accurate prediction of the distribution and intensity of tree mortality prior to defoliation. This prior information is necessary to better target investments in control activities where they are needed. This poster lays the groundwork for developing hazard-rating systems for forests of the...

  10. Change in Growth Differentiation Factor 15, but Not C-Reactive Protein, Independently Predicts Major Cardiac Events in Patients with Non-ST Elevation Acute Coronary Syndrome

    PubMed Central

    Hernandez-Baldomero, Idaira F.; Bosa-Ojeda, Francisco

    2014-01-01

    Among the numerous emerging biomarkers, high-sensitivity C-reactive protein (hsCRP) and growth-differentiation factor-15 (GDF-15) have received widespread interest, with their potential role as predictors of cardiovascular risk. The concentrations of inflammatory biomarkers, however, are influenced, among others, by physiological variations, which are the natural, within-individual variation occurring over time. The aims of our study are: (a) to describe the changes in hsCRP and GDF-15 levels over a period of time and after an episode of non-ST-segment elevation acute coronary syndrome (NSTE-ACS) and (b) to examine whether the rate of change in hsCRP and GDF-15 after the acute event is associated with long-term major cardiovascular adverse events (MACE). Two hundred and Fifty five NSTE-ACS patients were included in the study. We measured hsCRP and GDF-15 concentrations, at admission and again 36 months after admission (end of the follow-up period). The present study shows that the change of hsCRP levels, measured after 36 months, does not predict MACE in NSTEACS-patients. However, the level of GDF-15 measured, after 36 months, was a stronger predictor of MACE, in comparison to the acute unstable phase. PMID:24839357

  11. Personalizing Mortality Prediction With Psychosocial Questionnaire Data

    PubMed Central

    Chapman, Benjamin P.; Weiss, Alexander; Fiscella, Kevin; Muennig, Peter; Kawachi, Ichiro; Duberstein, Paul

    2015-01-01

    Background Predicting risk of premature death is one of the most basic tasks in medicine and public health, but has proven difficult over the long term even with the best prognostic models. One popular strategy has been to improve prognostic models with candidate genes and other novel biomarkers. However, the gains in predictive power have been modest and the costs have been high, leading to a demand for cost-effective alternatives. We conducted a proof-of-principle investigation to examine whether simple, cheap, and non-invasive paper-and-pencil measures of social class and personality phenotype could improve the performance of one of the most widely used prediction models for all-cause mortality, the Charlson Comorbidity Index (CCI). Methods We used data from baseline and 25-year mortality follow-up of the UK Health and Lifestyle Study cohort. In a subset of the cohort, we first identified five psychosocial factors highly predictive of mortality: income, education, Type A personality, communalism (preference for the company of others), and “lie” scale (a measure of denial, putatively associated with ill-health). We then examined the predictive performance of the Charlson CCI with and without these measures in a validation subsample. Results Across 5, 10, 15, 20, and 25-year time horizons, the psychosocially augmented CCI showed substantially better discrimination (AUCs (95% CI) from .83 (.81, .85) to .84 (.83 .86)) than the CCI (AUCs from .74 (.71, .76) to .77 (.76 to .79)). These translated into net reclassification improvements from 27% (23%, 31%) to 35% (32%, 38%) of survivors and from 23% (17%, 30%) to 34% (17%, 30%) of decedents; and 23%–42% reductions in the Number Needed to Screen. Calibration improved at all time horizons except 25 years, where it was decreased. Conclusion Widespread attempts to improve prognostic models might consider not only novel biomarkers, but also psychosocial questionnaire measures. PMID:26421372

  12. Copeptin Predicts Mortality in Critically Ill Patients

    PubMed Central

    Krychtiuk, Konstantin A.; Honeder, Maria C.; Lenz, Max; Maurer, Gerald; Wojta, Johann; Heinz, Gottfried; Huber, Kurt; Speidl, Walter S.

    2017-01-01

    Background Critically ill patients admitted to a medical intensive care unit exhibit a high mortality rate irrespective of the cause of admission. Besides its role in fluid and electrolyte balance, vasopressin has been described as a stress hormone. Copeptin, the C-terminal portion of provasopressin mirrors vasopressin levels and has been described as a reliable biomarker for the individual’s stress level and was associated with outcome in various disease entities. The aim of this study was to analyze whether circulating levels of copeptin at ICU admission are associated with 30-day mortality. Methods In this single-center prospective observational study including 225 consecutive patients admitted to a tertiary medical ICU at a university hospital, blood was taken at ICU admission and copeptin levels were measured using a commercially available automated sandwich immunofluorescent assay. Results Median acute physiology and chronic health evaluation II score was 20 and 30-day mortality was 25%. Median copeptin admission levels were significantly higher in non-survivors as compared with survivors (77.6 IQR 30.7–179.3 pmol/L versus 45.6 IQR 19.6–109.6 pmol/L; p = 0.025). Patients with serum levels of copeptin in the third tertile at admission had a 2.4-fold (95% CI 1.2–4.6; p = 0.01) increased mortality risk as compared to patients in the first tertile. When analyzing patients according to cause of admission, copeptin was only predictive of 30-day mortality in patients admitted due to medical causes as opposed to those admitted after cardiac surgery, as medical patients with levels of copeptin in the highest tertile had a 3.3-fold (95% CI 1.66.8, p = 0.002) risk of dying independent from APACHE II score, primary diagnosis, vasopressor use and need for mechanical ventilation. Conclusion Circulating levels of copeptin at ICU admission independently predict 30-day mortality in patients admitted to a medical ICU. PMID:28118414

  13. 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.

  14. Adrenomedullin optimises mortality prediction in COPD patients.

    PubMed

    Brusse-Keizer, Marjolein; Zuur-Telgen, Maaike; van der Palen, Job; VanderValk, Paul; Kerstjens, Huib; Boersma, Wim; Blasi, Francesco; Kostikas, Konstantinos; Milenkovic, Branislava; Tamm, Michael; Stolz, Daiana

    2015-06-01

    Current multicomponent scores that predict mortality in COPD patients might underestimate the systemic component of COPD. Therefore, we evaluated the accuracy of circulating levels of proadrenomedullin (MR-proADM) alone or combined with the ADO (Age, Dyspnoea, airflow Obstruction), updated ADO or BOD (Body mass index, airflow Obstruction, Dyspnoea) index to predict all-cause mortality in stable COPD patients. This study pooled data of 1285 patients from the COMIC and PROMISE-COPD study. Patients with high MR-proADM levels (≥0.87 nmol/l) had a 2.1 fold higher risk of dying than those with lower levels (p < 0.001). Based on the C-statistic, the ADOA index (ADO plus MR-proADM) (C = 0.72) was the most accurate predictor followed by the BODA (BOD plus MR-proADM) (C = 0.71) and the updated ADOA index (updated ADO plus MR-proADM) (C = 0.70). Adding MR-proADM to ADO and BOD was superior in forecasting 1- and 2-year mortality. The net percentages of persons with events correctly reclassified (NRI+) within respectively 1-year and 2-year was 31% and 20% for ADO, 31% and 20% for updated ADO and 25% and 19% for BOD. The net percentages of persons without events correctly reclassified (NRI-) within respectively 1-year and 2-year was 26% and 27% for ADO, 27% and 28% for updated ADO and 34% and 34% for BOD. Adding MR-proADM increased the predictive power of BOD, ADO and updated ADO index. Copyright © 2015 Elsevier Ltd. All rights reserved.

  15. Mapping and predicting mortality from systemic sclerosis.

    PubMed

    Elhai, Muriel; Meune, Christophe; Boubaya, Marouane; Avouac, Jérôme; Hachulla, Eric; Balbir-Gurman, Alexandra; Riemekasten, Gabriela; Airò, Paolo; Joven, Beatriz; Vettori, Serena; Cozzi, Franco; Ullman, Susanne; Czirják, László; Tikly, Mohammed; Müller-Ladner, Ulf; Caramaschi, Paola; Distler, Oliver; Iannone, Florenzo; Ananieva, Lidia P; Hesselstrand, Roger; Becvar, Radim; Gabrielli, Armando; Damjanov, Nemanja; Salvador, Maria J; Riccieri, Valeria; Mihai, Carina; Szücs, Gabriella; Walker, Ulrich A; Hunzelmann, Nicolas; Martinovic, Duska; Smith, Vanessa; Müller, Carolina de Souza; Montecucco, Carlo Maurizio; Opris, Daniela; Ingegnoli, Francesca; Vlachoyiannopoulos, Panayiotis G; Stamenkovic, Bojana; Rosato, Edoardo; Heitmann, Stefan; Distler, Jörg H W; Zenone, Thierry; Seidel, Matthias; Vacca, Alessandra; Langhe, Ellen De; Novak, Srdan; Cutolo, Maurizio; Mouthon, Luc; Henes, Jörg; Chizzolini, Carlo; Mühlen, Carlos Alberto von; Solanki, Kamal; Rednic, Simona; Stamp, Lisa; Anic, Branimir; Santamaria, Vera Ortiz; Santis, Maria De; Yavuz, Sule; Sifuentes-Giraldo, Walter Alberto; Chatelus, Emmanuel; Stork, Jiri; Laar, Jacob van; Loyo, Esthela; García de la Peña Lefebvre, Paloma; Eyerich, Kilian; Cosentino, Vanesa; Alegre-Sancho, Juan Jose; Kowal-Bielecka, Otylia; Rey, Grégoire; Matucci-Cerinic, Marco; Allanore, Yannick

    2017-11-01

    To determine the causes of death and risk factors in systemic sclerosis (SSc). Between 2000 and 2011, we examined the death certificates of all French patients with SSc to determine causes of death. Then we examined causes of death and developed a score associated with all-cause mortality from the international European Scleroderma Trials and Research (EUSTAR) database. Candidate prognostic factors were tested by Cox proportional hazards regression model by single variable analysis, followed by a multiple variable model stratified by centres. The bootstrapping technique was used for internal validation. We identified 2719 French certificates of deaths related to SSc, mainly from cardiac (31%) and respiratory (18%) causes, and an increase in SSc-specific mortality over time. Over a median follow-up of 2.3 years, 1072 (9.6%) of 11 193 patients from the EUSTAR sample died, from cardiac disease in 27% and respiratory causes in 17%. By multiple variable analysis, a risk score was developed, which accurately predicted the 3-year mortality, with an area under the curve of 0.82. The 3-year survival of patients in the upper quartile was 53%, in contrast with 98% in the first quartile. Combining two complementary and detailed databases enabled the collection of an unprecedented 3700 deaths, revealing the major contribution of the cardiopulmonary system to SSc mortality. We also developed a robust score to risk-stratify these patients and estimate their 3-year survival. With the emergence of new therapies, these important observations should help caregivers plan and refine the monitoring and management to prolong these patients' survival. © 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.

  16. Prediction of Mortality Based on Facial Characteristics

    PubMed Central

    Delorme, Arnaud; Pierce, Alan; Michel, Leena; Radin, Dean

    2016-01-01

    Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person’s photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 s. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential (ERP) at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance warrants further investigation. PMID:27242466

  17. Predicting mortality based on body composition analysis.

    PubMed Central

    Tellado, J M; Garcia-Sabrido, J L; Hanley, J A; Shizgal, H M; Christou, N V

    1989-01-01

    The role of the Nae/Ke ratio (the ratio of exchangeable sodium to exchangeable potassium) was examined as a nutritional marker in surgical patients in relation to anthropometrical and biochemical indexes by its ability to identify patients at risk for mortality after hospitalization. In 73 patients with sepsis and malnutrition (Training Group, Madrid) the following were determined: percentage of recent weight loss, triceps skin fold, midarm muscle circumference, serum albumin, serum transferrin, delayed hypersensitivity skin test response, total lymphocytes, and Nae/Ke ratio by multiple isotope dilution. The predictive power of Nae/Ke ratio was so strong (F = 105.1; p less than 0.00001) that it displaced anthropometric, biochemical, and immunologic variables from the linear equation derived from stepwise discriminant analysis using hospital mortality as the dependent variable. A theoretical curve of expected deaths was developed, based on an equation obtained by logistic regression analysis: Pr/death/ = 1/(1 + e[11.8-5.2 Nae/Ke]). Pre- and post-test probabilities on that curve allowed us to determine two cut-off values, Nae/Ke ratios of 1.5 and 2.5, which were markers for nonrisk and mortality, respectively. The model was tested in a heterogeneous data base of surgical patients (n = 417) in another hospital (Validation Group, Montreal). For patients exhibiting an abnormal Nae/Ke ratio (greater than 1.2) and a greater than 10% of probability of death, 54 deaths were expected and 53 observed (X2 = 1.8 NS). Two tests confirmed the basic agreement between the model and its performance, a G statistic of -0.704 and the area beneath the "receiver-operating-characteristic" (ROC) curve (Az = 0.904 + 0.0516 for the Madrid group vs. Az = 0.915 + 0.0349 for the Montreal group, NS). It was concluded from this analysis that, compared with the usual anthropometric measurements, the Nae/Ke ratio, if available, is the best method for identifying malnourished patients at risk of

  18. Consistent Predictions of Future Forest Mortality

    NASA Astrophysics Data System (ADS)

    McDowell, N. G.

    2014-12-01

    We examined empirical and model based estimates of current and future forest mortality of conifers in the northern hemisphere. Consistent water potential thresholds were found that resulted in mortality of our case study species, pinon pine and one-seed juniper. Extending these results with IPCC climate scenarios suggests that most existing trees in this region (SW USA) will be dead by 2050. Further, independent estimates of future mortality for the entire coniferous biome suggest widespread mortality by 2100. The validity and assumptions and implications of these results are discussed.

  19. 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.

  20. Prediction of mortality rates in the presence of missing values

    NASA Astrophysics Data System (ADS)

    Tan, Chon Sern; Pooi, Ah Hin

    2015-12-01

    A time series model based on multivariate power-normal distribution has been applied in the past literature on the United States (US) mortality data from the years 1933 to 2000 to forecast the future age-specific mortality rates of the years 2001 to 2010. In this paper, we show that the method based on multivariate power-normal distribution can still be used for an incomplete US mortality dataset that contains some missing values. The prediction intervals based on this incomplete training data are found to still have good ability of covering the observed future mortality rates although the interval lengths may become wider for long-range prediction.

  1. 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.

  2. Tree mortality predicted from drought-induced vascular damage

    NASA Astrophysics Data System (ADS)

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

    2015-05-01

    The projected responses of forest ecosystems to warming and drying associated with twenty-first-century climate change vary widely from resiliency to widespread tree mortality. Current vegetation models lack the ability to account for mortality of overstorey trees during extreme drought owing to uncertainties in mechanisms and thresholds causing mortality. 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.

  3. 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.

  4. Interpretable Topic Features for Post-ICU Mortality Prediction

    PubMed Central

    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. PMID:28269879

  5. Brain natriuretic peptide predicts mortality in the elderly.

    PubMed Central

    Wallén, T.; Landahl, S.; Hedner, T.; Nakao, K.; Saito, Y.

    1997-01-01

    OBJECTIVE: To study whether prospective measurements of circulating concentrations of brain natriuretic peptide (BNP) could predict mortality in the general elderly population. DESIGN AND SETTING: Circulating BNP was measured in a cohort of 85 year olds from the general population who were followed up prospectively for five years as part of a longitudinal population study, "70 year old people in Gothenburg, Sweden". PATIENTS: 541 subjects from the 85 year old population in Gothenburg. All subjects were investigated for the presence or absence of cardiovascular disorder such as congestive heart failure, ischaemic heart disease, hypertension, and atrial fibrillation. Venous plasma samples were obtained for BNP analysis. MAIN OUTCOME MEASURE: Overall mortality during the prospective follow up period. RESULTS: Circulating concentrations of BNP predicted five-year mortality in the total population (P < 0.001). In subjects with a known cardiovascular disorder, five-year mortality was correlated with increased BNP concentrations (P < 0.01). Increased BNP concentrations predicted five-year mortality in subjects without a defined cardiovascular disorder (P < 0.05). CONCLUSIONS: In an elderly population, measurements of BNP may add valuable prognostic information and may be used to predict mortality in the total population as well as in patients with known cardiovascular disorders. In subjects without any known cardiovascular disorder, BNP was a strong and independent predictor of total mortality. PMID:9093047

  6. Global trends and predictions in hepatocellular carcinoma mortality.

    PubMed

    Bertuccio, Paola; Turati, Federica; Carioli, Greta; Rodriguez, Teresa; La Vecchia, Carlo; Malvezzi, Matteo; Negri, Eva

    2017-08-01

    Trends in hepatocellular carcinoma (HCC) mortality rates have increased over recent decades in most countries. It is also the third cause of cancer death worldwide. The aim of this study is to update global trends in HCC mortality to 2014, and predict trends in rates in the EU, USA and Japan to 2020. Death certification data for HCC over the 1990-2014 period from the World Health Organization database were analyzed. Sixteen European, five American countries, and six other countries worldwide were included, as well as the EU as a whole. In European men, mortality rates were stable during the last decade (3.5/100,000). HCC mortality increased in Northern and Central Europe, and decreased in Southern Europe. In the USA, HCC mortality increased by 35% between 2002 and 2012, reaching 3.1/100,000 men in 2012; it is predicted to remain stable to 2020. Reduced mortality rates were observed in East Asia, although they remained around 10-24/100,000 men. In Japan, HCC mortality is predicted to decrease (5.4/100,000 men in 2020). Trends were favorable in the young, but unfavorable in middle aged, except in East Asia. Mortality rates were 3- to 5-fold lower in women than men in most regions, but trends were similar. Control of hepatitis B (HBV) and hepatitis C virus (HCV) infections has contributed to the decrease in HCC-related mortality in East Asia and Southern Europe. Unfavorable trends in other regions can be attributed to HCV (and HBV) epidemics in the 1960s and 1980s, alcohol consumption, increased overweight/obesity, and diabetes. Better management of cirrhosis, HCC diagnosis and treatment are also influencing the mortality trends worldwide. Mortality rates due to HCC have increased in many countries over recent decades. In this study, we updated worldwide mortality trends for HCC from 1990 to 2014, and predicted trends for some countries to 2020. We observed unfavorable trends in Northern and Central Europe, North and Latin America. East Asia showed an improvement

  7. Forearm bone mass predicts mortality in chronic hemodialysis patients.

    PubMed

    Orlic, Lidija; Mikolasevic, Ivana; Crncevic-Orlic, Zeljka; Jakopcic, Ivan; Josipovic, Josipa; Pavlovic, Drasko

    2016-07-27

    We aim to determine the relationship between bone mineral density (BMD), measured by T- and Z-score, and mortality risk in hemodialysis (HD) patients. We also investigate which are the most suitable skeletal sites for predicting mortality rate. We analyzed the survival of 102 patients who had been treated with chronic HD according to BMD. Patients with a T-score ≤2.5 at the middle, ultradistal and proximal part of the forearm had a higher mortality risk than those with a T-score of -2.5 or higher. Furthermore, no statistically significant association was found between loss of bone mass at other measuring points-lumbar spine (anteroposterior orientation from L1-L4) and hip (neck, trochanter, intertrochanter, total and Ward's triangle)-and mortality risk. We were also interested in exploring the relationship between Z-score at different skeletal regions and mortality risk. We found that patients with a Z-score of -1 or lower at all three parts of the forearm had a greater mortality risk. It is also worth noting that the Z-score at all three parts of the forearm was a more apparent predictor of mortality, compared to the T-score at the same skeletal regions. This empirical analysis showed that BMD assessments should be obtained at the forearm, due to the good predictability of this skeletal site regarding mortality of HD patients. Moreover, data concerning bone density should be reported as Z-scores.

  8. Adolescent-onset substance use disorders predict young adult mortality

    PubMed Central

    Clark, Duncan B.; Martin, Christopher S.; Cornelius, Jack R.

    2009-01-01

    This study determined whether adolescent-onset substance use disorders (SUDs) prospectively predicted early mortality. Among 870 adolescents, 21 young adulthood deaths were observed. Adolescent SUDs, as well as gender, ethnic group, hazardous substance use, and drug trafficking, predicted these deaths. Among African American males with SUDs, 23% died by age 25. PMID:18486875

  9. Towards more accurate vegetation mortality predictions

    DOE PAGES

    Sevanto, Sanna Annika; Xu, Chonggang

    2016-09-26

    Predicting the fate of vegetation under changing climate is one of the major challenges of the climate modeling community. Here, terrestrial vegetation dominates the carbon and water cycles over land areas, and dramatic changes in vegetation cover resulting from stressful environmental conditions such as drought feed directly back to local and regional climate, potentially leading to a vicious cycle where vegetation recovery after a disturbance is delayed or impossible.

  10. Towards more accurate vegetation mortality predictions

    SciTech Connect

    Sevanto, Sanna Annika; Xu, Chonggang

    2016-09-26

    Predicting the fate of vegetation under changing climate is one of the major challenges of the climate modeling community. Here, terrestrial vegetation dominates the carbon and water cycles over land areas, and dramatic changes in vegetation cover resulting from stressful environmental conditions such as drought feed directly back to local and regional climate, potentially leading to a vicious cycle where vegetation recovery after a disturbance is delayed or impossible.

  11. Cancer mortality predictions for 2017 in Latin America.

    PubMed

    Carioli, G; La Vecchia, C; Bertuccio, P; Rodriguez, T; Levi, F; Boffetta, P; Negri, E; Malvezzi, M

    2017-09-01

    From most recent available data, we predicted cancer mortality statistics in selected Latin American countries for the year 2017, with focus on lung cancer. We obtained death certification data from the World Health Organization and population data from the Pan American Health Organization database for all neoplasms and selected cancer sites. We derived figures for Argentina, Brazil, Chile, Colombia, Cuba, Mexico and Venezuela. Using a logarithmic Poisson count data joinpoint model, we estimated number of deaths and age-standardized (world population) mortality rates in 2017. Total cancer mortality rates are predicted to decline in all countries. The highest mortality rates for 2017 are in Cuba, i.e. 132.3/100 000 men and 93.3/100 000 women. Mexico had the lowest predicted rates, 64.7/100 000 men and 60.6/100 000 women. In contrast, the total number of cancer deaths is expected to rise due to population ageing and growth. Men showed declines in lung cancer trends in all countries and age groups considered, while only Colombian and Mexican women had downward trends. Stomach and (cervix) uteri rates are predicted to continue their declines, though mortality from these neoplasms remains comparatively high. Colorectal, breast and prostate cancer rates were predicted to decline moderately, as well as leukaemias. There was no clear pattern for pancreatic cancer. Between 1990 and 2017 about 420 000 cancer deaths were avoided in 5 of the 7 countries, no progress was observed in Brazil and Cuba. Cancer mortality rates for 2017 in seven selected Latin American countries are predicted to decline, though there was appreciable variability across countries. Mortality from major cancers-including lung and prostate-and all cancers remains comparatively high in Cuba, indicating the need for improved prevention and management.

  12. Prediction of mortality rates using a model with stochastic parameters

    NASA Astrophysics Data System (ADS)

    Tan, Chon Sern; Pooi, Ah Hin

    2016-10-01

    Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths.

  13. Predicting 15 year chronic bronchitis mortality in the Whitehall Study.

    PubMed Central

    Ebi-Kryston, K L

    1989-01-01

    Fifteen year chronic bronchitis mortality was investigated among 17,717 male civil servants aged 40-64 years participating in the Whitehall Study. Associations were assessed between mortality and Medical Research Council standardised questions about chronic phlegm production and breathlessness, and a measure of lung function. Low FEV1 was the most powerful single predictor of mortality; controlling for age, smoking habits and employment grade, the relative hazards ratio (RHR) was 20. Using mortality rates standardised for age and smoking, the proportion of mortality in the total population statistically attributable to low FEV1 (population excess fraction) was 57%. Breathlessness while walking on the level was the best predictor among the questions and combinations of questions; the relative hazards ratio was 12 and the population excess fraction, 39%. A Medical Research Council definition of chronic bronchitis including chronic phlegm production and breathlessness was also strongly associated with chronic bronchitis mortality (RHR = 13); however, the population excess fraction was only 20%. This definition identified only 30% of the 64 deaths, and added almost nothing to prediction by FEV1 alone. The results suggest that although the combination of chronic phlegm production and chronic airflow limitation is strongly associated with mortality from chronic bronchitis, the presence of chronic phlegm production alone is not associated with mortality. PMID:2592906

  14. Using liver enzymes as screening tests to predict mortality risk.

    PubMed

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

    2008-01-01

    Determine the relationship between liver function test results (GGT, alkaline phosphatase, AST, and ALT) and all-cause mortality in life insurance applicants. By use of the Social Security Master Death File, mortality was examined in 1,905,664 insurance applicants for whom blood samples were submitted to the Clinical Reference Laboratory. There were 50,174 deaths observed in this study population. Results were stratified by 3 age/sex groups: females, age <60; males, age <60; and all, age 60+. Liver function test values were grouped using percentiles of their distribution in these 3 age/sex groups, as well as ranges of actual values. Using the risk of the middle 50% of the population by distribution as a reference, relative mortality observed for GGT and alkaline phosphatase was linear with a steep slope from very low to relatively high values. Relative mortality was increased at lower values for both AST and ALT. ALT did not predict mortality for values above the middle 50% of its distribution. GGT and alkaline phosphatase are significant predictors of mortality risk for all values. ALT is still useful for triggering further testing for hepatitis, but AST should be used instead to assess mortality risk linked with transaminases.

  15. Predicting postoperative mortality after colorectal surgery: a novel clinical model.

    PubMed

    van der Sluis, F J; Espin, E; Vallribera, F; de Bock, G H; Hoekstra, H J; van Leeuwen, B L; Engel, A F

    2014-08-01

    The aim of this study was to develop and externally validate a clinically, practical and discriminative prediction model designed to estimate in-hospital mortality of patients undergoing colorectal surgery. All consecutive patients who underwent elective or emergency colorectal surgery from 1990 to 2005, at the Zaandam Medical Centre, The Netherlands, were included in this study. Multivariate logistic regression analysis was performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs) linking the explanatory variables to the outcome variable in-hospital mortality, and a simplified Identification of Risk in Colorectal Surgery (IRCS) score was constructed. The model was validated in a population of patients who underwent colorectal surgery from 2005 to 2011 in Barcelona, Spain. Predictive performance was estimated by calculating the area under the receiver operating characteristic curve. The strongest predictors of in-hospital mortality were emergency surgery (OR = 6.7, 95% CI 4.7-9.5), tumour stage (OR = 3.2, 95% CI 2.8-4.6), age (OR = 13.1, 95% CI 6.6-26.0), pulmonary failure (OR = 4.9, 95% CI 3.3-7.1) and cardiac failure (OR = 3.7, 95% CI 2.6-5.3). These parameters were included in the prediction model and simplified scoring system. The IRCS model predicted in-hospital mortality and demonstrated a predictive performance of 0.83 (95% CI 0.79-0.87) in the validation population. In this population the predictive performance of the CR-POSSUM score was 0.76 (95% CI 0.71-0.81). The results of this study have shown that the IRCS score is a good predictor of in-hospital mortality after colorectal surgery despite the relatively low number of model parameters. Colorectal Disease © 2014 The Association of Coloproctology of Great Britain and Ireland.

  16. 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...

  17. Predicting mortality for five California conifers following wildfire

    Treesearch

    Sharon M. Hood; Sheri L. Smith; Daniel R. Cluck

    2010-01-01

    Fire injury was characterized and survival monitored for 5677 trees >25cm DBH from five wildfires in California that occurred between 2000 and 2004. Logistic regression models for predicting the probability of mortality 5-years after fire were developed for incense cedar (Calocedrus decurrens (Torr.) Florin), white fir (Abies concolor (Gord. & Glend.) Lindl. ex...

  18. Predicting Discharge Mortality after Acute Ischemic Stroke Using Balanced Data

    PubMed Central

    Ho, King Chung; Speier, William; El-Saden, Suzie; Liebeskind, David S.; Saver, Jeffery L.; Bui, Alex A. T.; Arnold, Corey W.

    2014-01-01

    Several models have been developed to predict stroke outcomes (e.g., stroke mortality, patient dependence, etc.) in recent decades. However, there is little discussion regarding the problem of between-class imbalance in stroke datasets, which leads to prediction bias and decreased performance. In this paper, we demonstrate the use of the Synthetic Minority Over-sampling Technique to overcome such problems. We also compare state of the art machine learning methods and construct a six-variable support vector machine (SVM) model to predict stroke mortality at discharge. Finally, we discuss how the identification of a reduced feature set allowed us to identify additional cases in our research database for validation testing. Our classifier achieved a c-statistic of 0.865 on the cross-validated dataset, demonstrating good classification performance using a reduced set of variables. PMID:25954451

  19. Diagnosis trajectories of prior multi-morbidity predict sepsis mortality

    PubMed Central

    Beck, Mette K.; Jensen, Anders Boeck; Nielsen, Annelaura Bach; Perner, Anders; Moseley, Pope L.; Brunak, Søren

    2016-01-01

    Sepsis affects millions of people every year, many of whom will die. In contrast to current survival prediction models for sepsis patients that primarily are based on data from within-admission clinical measurements (e.g. vital parameters and blood values), we aim for using the full disease history to predict sepsis mortality. We benefit from data in electronic medical records covering all hospital encounters in Denmark from 1996 to 2014. This data set included 6.6 million patients of whom almost 120,000 were diagnosed with the ICD-10 code: A41 ‘Other sepsis’. Interestingly, patients following recurrent trajectories of time-ordered co-morbidities had significantly increased sepsis mortality compared to those who did not follow a trajectory. We identified trajectories which significantly altered sepsis mortality, and found three major starting points in a combined temporal sepsis network: Alcohol abuse, Diabetes and Cardio-vascular diagnoses. Many cancers also increased sepsis mortality. Using the trajectory based stratification model we explain contradictory reports in relation to diabetes that recently have appeared in the literature. Finally, we compared the predictive power using 18.5 years of disease history to scoring based on within-admission clinical measurements emphasizing the value of long term data in novel patient scores that combine the two types of data. PMID:27812043

  20. 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.

  1. Depressed sympathovagal balance predicts mortality in patients with subarachnoid hemorrhage.

    PubMed

    Chiu, Te-Fa; Huang, Chien-Cheng; Chen, Jiann-Hwa; Chen, Wei-Lung

    2012-06-01

    The objective of this study is to investigate the role of sympathovagal balance in predicting inhospital mortality by assessing power spectral analysis of heart rate variability (HRV) among patients with nontraumatic subarachnoid hemorrhage (SAH) in an emergency department (ED). A cohort of 132 adult patients with spontaneous SAH in an ED was prospectively enrolled. A continuous 10-minute electrocardiography for off-line power spectral analysis of the HRV was recorded. Using the inhospital mortality, the patients were classified into 2 groups: nonsurvivors (n=38) and survivors (n=94). The HRV measures were compared between these 2 groups of patients. Having compared the various measurements, the very low-frequency component, low-frequency component, normalized low-frequency component (LF%), and low-/high-frequency component ratio (LF/HF) were significantly lower, whereas the normalized high-frequency component was significantly higher among the nonsurvivors than among the survivors. A multiple logistic regression model identified LF/HF (odds ratio, 2.16; 95% confidence interval [CI], 1.18-3.97; P=.013) and LF% (odds ratio, 0.78; 95% CI, 0.69-0.88; P<.001) as independent variables that were able to predict inhospital mortality for patients with SAH in an ED. The receiver operating characteristic area for LF/HF in predicting inhospital mortality was 0.957 (95% CI, 0.914-1.000; P<.001), and the best cutoff points was 0.8 (sensitivity, 92.1%; specificity, 90.4%). Power spectral analysis of the HRV is able to predict inhospital mortality for patients after SAH in an ED. A tilt in the sympathovagal balance toward depressed sympathovagal balance, as indicated by HRV analysis, might contribute to the poor outcome among these patients. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Predicting Mortality in Low-Income Country ICUs: The Rwanda Mortality Probability Model (R-MPM)

    PubMed Central

    Kiviri, Willy; Fowler, Robert A.; Mueller, Ariel; Novack, Victor; Banner-Goodspeed, Valerie M.; Weinkauf, Julia L.; Talmor, Daniel S.; Twagirumugabe, Theogene

    2016-01-01

    Introduction Intensive Care Unit (ICU) risk prediction models are used to compare outcomes for quality improvement initiatives, benchmarking, and research. While such models provide robust tools in high-income countries, an ICU risk prediction model has not been validated in a low-income country where ICU population characteristics are different from those in high-income countries, and where laboratory-based patient data are often unavailable. We sought to validate the Mortality Probability Admission Model, version III (MPM0-III) in two public ICUs in Rwanda and to develop a new Rwanda Mortality Probability Model (R-MPM) for use in low-income countries. Methods We prospectively collected data on all adult patients admitted to Rwanda’s two public ICUs between August 19, 2013 and October 6, 2014. We described demographic and presenting characteristics and outcomes. We assessed the discrimination and calibration of the MPM0-III model. Using stepwise selection, we developed a new logistic model for risk prediction, the R-MPM, and used bootstrapping techniques to test for optimism in the model. Results Among 427 consecutive adults, the median age was 34 (IQR 25–47) years and mortality was 48.7%. Mechanical ventilation was initiated for 85.3%, and 41.9% received vasopressors. The MPM0-III predicted mortality with area under the receiver operating characteristic curve of 0.72 and Hosmer-Lemeshow chi-square statistic p = 0.024. We developed a new model using five variables: age, suspected or confirmed infection within 24 hours of ICU admission, hypotension or shock as a reason for ICU admission, Glasgow Coma Scale score at ICU admission, and heart rate at ICU admission. Using these five variables, the R-MPM predicted outcomes with area under the ROC curve of 0.81 with 95% confidence interval of (0.77, 0.86), and Hosmer-Lemeshow chi-square statistic p = 0.154. Conclusions The MPM0-III has modest ability to predict mortality in a population of Rwandan ICU patients. The R

  3. Admission serum lactate predicts mortality in aneurysmal subarachnoid hemorrhage.

    PubMed

    Aisiku, Imo P; Chen, Peng Roc; Truong, Hanh; Monsivais, Daniel R; Edlow, Jonathan

    2016-04-01

    Aneurysmal subarachnoid hemorrhage (SAH) is the most devastating form of hemorrhagic stroke. Primary predictors of mortality are based on initial clinical presentation. Initial serum lactic acid levels have been shown to predict mortality and disease severity. Initial serum lactate may be an objective predictor or mortality. Retrospective review of aneurysmal SAH in a large academic center over a 42-month period. Data collected included demographics, clinical data, serum, and clinical outcomes data. Epidemiologic data were collected at baseline, and patients were followed up through their inpatient stay. We compared data in the group of patients who were deceased (group A) vs survivors (group B). There were a total of 249 patients. Mortality was 21.5%. Mean age was the same for both groups: 57 years (group A) and 55 years (group B). Mean admission serum lactate level was 3.5 ± 2.5 (group A) and 2.2 ± 1.6 (group B; P <. 0001). The range was 0.01 to 14.7. Multivariable analysis controlling for Hunt and Hess grades showed lactic acid levels to be an independent predictor of mortality with a P value of .0018. In aneurysmal SAH, elevated serum lactate levels on admission may have a predictive role for mortality and represent a marker of disease severity. Currently, lactic acid levels are not ordered on all patients with SAH but perhaps should be part of the routine initial blood work and may serve as an additional prognostic marker. Copyright © 2016 Elsevier Inc. All rights reserved.

  4. Olfactory Dysfunction Predicts 5-Year Mortality in Older Adults

    PubMed Central

    Pinto, Jayant M.; Wroblewski, Kristen E.; Kern, David W.; Schumm, L. Philip; McClintock, Martha K.

    2014-01-01

    Prediction of mortality has focused on disease and frailty, although antecedent biomarkers may herald broad physiological decline. Olfaction, an ancestral chemical system, is a strong candidate biomarker because it is linked to diverse physiological processes. We sought to determine if olfactory dysfunction is a harbinger of 5-year mortality in the National Social Life, Health and Aging Project [NSHAP], a nationally representative sample of older U.S. adults. 3,005 community-dwelling adults aged 57–85 were studied in 2005–6 (Wave 1) and their mortality determined in 2010–11 (Wave 2). Olfactory dysfunction, determined objectively at Wave 1, was used to estimate the odds of 5-year, all cause mortality via logistic regression, controlling for demographics and health factors. Mortality for anosmic older adults was four times that of normosmic individuals while hyposmic individuals had intermediate mortality (p<0.001), a “dose-dependent” effect present across the age range. In a comprehensive model that included potential confounding factors, anosmic older adults had over three times the odds of death compared to normosmic individuals (OR, 3.37 [95%CI 2.04, 5.57]), higher than and independent of known leading causes of death, and did not result from the following mechanisms: nutrition, cognitive function, mental health, smoking and alcohol abuse or frailty. Olfactory function is thus one of the strongest predictors of 5-year mortality and may serve as a bellwether for slowed cellular regeneration or as a marker of cumulative toxic environmental exposures. This finding provides clues for pinpointing an underlying mechanism related to a fundamental component of the aging process. PMID:25271633

  5. Olfactory dysfunction predicts 5-year mortality in older adults.

    PubMed

    Pinto, Jayant M; Wroblewski, Kristen E; Kern, David W; Schumm, L Philip; McClintock, Martha K

    2014-01-01

    Prediction of mortality has focused on disease and frailty, although antecedent biomarkers may herald broad physiological decline. Olfaction, an ancestral chemical system, is a strong candidate biomarker because it is linked to diverse physiological processes. We sought to determine if olfactory dysfunction is a harbinger of 5-year mortality in the National Social Life, Health and Aging Project [NSHAP], a nationally representative sample of older U.S. adults. 3,005 community-dwelling adults aged 57-85 were studied in 2005-6 (Wave 1) and their mortality determined in 2010-11 (Wave 2). Olfactory dysfunction, determined objectively at Wave 1, was used to estimate the odds of 5-year, all cause mortality via logistic regression, controlling for demographics and health factors. Mortality for anosmic older adults was four times that of normosmic individuals while hyposmic individuals had intermediate mortality (p<0.001), a "dose-dependent" effect present across the age range. In a comprehensive model that included potential confounding factors, anosmic older adults had over three times the odds of death compared to normosmic individuals (OR, 3.37 [95%CI 2.04, 5.57]), higher than and independent of known leading causes of death, and did not result from the following mechanisms: nutrition, cognitive function, mental health, smoking and alcohol abuse or frailty. Olfactory function is thus one of the strongest predictors of 5-year mortality and may serve as a bellwether for slowed cellular regeneration or as a marker of cumulative toxic environmental exposures. This finding provides clues for pinpointing an underlying mechanism related to a fundamental component of the aging process.

  6. Skin autofluorescence predicts cardiovascular mortality in patients on chronic hemodialysis.

    PubMed

    Kimura, Hiroshi; Tanaka, Kenichi; Kanno, Makoto; Watanabe, Kimio; Hayashi, Yoshimitsu; Asahi, Koichi; Suzuki, Hodaka; Sato, Keiji; Sakaue, Michiaki; Terawaki, Hiroyuki; Nakayama, Masaaki; Miyata, Toshio; Watanabe, Tsuyoshi

    2014-10-01

    Tissue accumulation of advanced glycation end products (AGE) is thought to contribute to the progression of cardiovascular disease (CVD). Skin autofluorescence, a non-invasive measure of AGE accumulation using autofluorescence of the skin under ultraviolet light, has been reported to be an independent predictor of mortality associated with CVD in Caucasian patients on chronic hemodialysis. The aim of this study was to assess the predictive value of skin autofluorescence on all-cause and cardiovascular mortality in non-Caucasian (Japanese) patients on chronic hemodialysis. Baseline skin autofluorescence was measured with an autofluorescence reader in 128 non-Caucasian (Japanese) patients on chronic hemodialysis. All-cause and cardiovascular mortality was monitored prospectively during a period of 6 years. During the follow-up period, 42 of the 128 patients died; 19 of those patients died of CVD. Skin autofluorescence did not have a significant effect on all-cause mortality. However, age, carotid artery intima-media thickness (IMT), serum albumin, high-sensitivity C-reactive protein (hsCRP), skin autofluorescence and pre-existing CVD were significantly correlated with cardiovascular mortality. Multivariate Cox regression analysis showed skin autofluorescence (adjusted hazard ratio [HR] 3.97; 95% confidence interval [CI]1.67-9.43), serum albumin (adjusted HR 0.05; 95% CI 0.01-0.32), and hsCRP (adjusted HR 1.55; 95% CI 1.18-2.05) to be independent predictors of cardiovascular mortality. The present study suggests that skin autofluorescence is an independent predictor of cardiovascular mortality in non-Caucasian (Japanese) patients on chronic hemodialysis.

  7. Vitamin D Status Predicts 30 Day Mortality in Hospitalised Cats

    PubMed Central

    Titmarsh, Helen; Kilpatrick, Scott; Sinclair, Jennifer; Boag, Alisdair; Bode, Elizabeth F.; Lalor, Stephanie M.; Gaylor, Donna; Berry, Jacqueline; Bommer, Nicholas X.; Gunn-Moore, Danielle; Reed, Nikki; Handel, Ian; Mellanby, Richard J.

    2015-01-01

    Vitamin D insufficiency, defined as low serum concentrations of the major circulating form of vitamin D, 25 hydroxyvitamin D (25(OH)D), has been associated with the development of numerous infectious, inflammatory, and neoplastic disorders in humans. In addition, vitamin D insufficiency has been found to be predictive of mortality for many disorders. However, interpretation of human studies is difficult since vitamin D status is influenced by many factors, including diet, season, latitude, and exposure to UV radiation. In contrast, domesticated cats do not produce vitamin D cutaneously, and most cats are fed a commercial diet containing a relatively standard amount of vitamin D. Consequently, domesticated cats are an attractive model system in which to examine the relationship between serum 25(OH)D and health outcomes. The hypothesis of this study was that vitamin D status would predict short term, all-cause mortality in domesticated cats. Serum concentrations of 25(OH)D, together with a wide range of other clinical, hematological, and biochemical parameters, were measured in 99 consecutively hospitalised cats. Cats which died within 30 days of initial assessment had significantly lower serum 25(OH)D concentrations than cats which survived. In a linear regression model including 12 clinical variables, serum 25(OH)D concentration in the lower tertile was significantly predictive of mortality. The odds ratio of mortality within 30 days was 8.27 (95% confidence interval 2.54-31.52) for cats with a serum 25(OH)D concentration in the lower tertile. In conclusion, this study demonstrates that low serum 25(OH)D concentration status is an independent predictor of short term mortality in cats. PMID:25970442

  8. Predicting early mortality following hip fracture surgery: the Hip fracture Estimator of Mortality Amsterdam (HEMA).

    PubMed

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

    2017-09-11

    Early mortality following hip fracture surgery is high and pre-operative 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 following 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 following hip fracture surgery for the individual patient. Prognostic Level II.

  9. Serum Irisin Predicts Mortality Risk in Acute Heart Failure Patients.

    PubMed

    Shen, Shutong; Gao, Rongrong; Bei, Yihua; Li, Jin; Zhang, Haifeng; Zhou, Yanli; Yao, Wenming; Xu, Dongjie; Zhou, Fang; Jin, Mengchao; Wei, Siqi; Wang, Kai; Xu, Xuejuan; Li, Yongqin; Xiao, Junjie; Li, Xinli

    2017-01-01

    Irisin is a peptide hormone cleaved from a plasma membrane protein fibronectin type III domain containing protein 5 (FNDC5). Emerging studies have indicated association between serum irisin and many major chronic diseases including cardiovascular diseases. However, the role of serum irisin as a predictor for mortality risk in acute heart failure (AHF) patients is not clear. AHF patients were enrolled and serum was collected at the admission and all patients were followed up for 1 year. Enzyme-linked immunosorbent assay was used to measure serum irisin levels. To explore predictors for AHF mortality, the univariate and multivariate logistic regression analysis, and receiver-operator characteristic (ROC) curve analysis were used. To determine the role of serum irisin levels in predicting survival, Kaplan-Meier survival analysis was used. In this study, 161 AHF patients were enrolled and serum irisin level was found to be significantly higher in patients deceased in 1-year follow-up. The univariate logistic regression analysis identified 18 variables associated with all-cause mortality in AHF patients, while the multivariate logistic regression analysis identified 2 variables namely blood urea nitrogen and serum irisin. ROC curve analysis indicated that blood urea nitrogen and the most commonly used biomarker, NT-pro-BNP, displayed poor prognostic value for AHF (AUCs ≤ 0.700) compared to serum irisin (AUC = 0.753). Kaplan-Meier survival analysis demonstrated that AHF patients with higher serum irisin had significantly higher mortality (P<0.001). Collectively, our study identified serum irisin as a predictive biomarker for 1-year all-cause mortality in AHF patients though large multicenter studies are highly needed. © 2017 The Author(s). Published by S. Karger AG, Basel.

  10. Prediction of the mortality dose-response relationship in man

    SciTech Connect

    Morris, M.D.; Jones, T.D.

    1987-01-01

    Based upon an extensive data base including 100 separate animal studies, an estimate of the mortality dose-response relationship due to continuous photon radiation is predicted for 70 kg man. The model used in this prediction exercise includes fixed terms accounting for effects of body weight and dose rate, and random terms accounting for inter- and intra-species variation and experimental error. Point predictions and 95% prediction intervals are given for the LD/sub 05/, LD/sub 10/, LD/sub 25/, LD/sub 50/, LD/sub 75/, LD/sub 90/, and LD/sub 95/, for dose rates ranging from 1 to 50 R/min. 6 refs., 5 tabs.

  11. Life-Space Mobility Change Predicts 6-Month Mortality.

    PubMed

    Kennedy, Richard E; Sawyer, Patricia; Williams, Courtney P; Lo, Alexander X; Ritchie, Christine S; Roth, David L; Allman, Richard M; Brown, Cynthia J

    2017-04-01

    To examine 6-month change in life-space mobility as a predictor of subsequent 6-month mortality in community-dwelling older adults. Prospective cohort study. Community-dwelling older adults from five Alabama counties in the University of Alabama at Birmingham (UAB) Study of Aging. A random sample of 1,000 Medicare beneficiaries, stratified according to sex, race, and rural or urban residence, recruited between November 1999 and February 2001, followed by a telephone interview every 6 months for the subsequent 8.5 years. Mortality data were determined from informant contacts and confirmed using the National Death Index and Social Security Death Index. Life-space was measured at each interview using the UAB Life-Space Assessment, a validated instrument for assessing community mobility. Eleven thousand eight hundred seventeen 6-month life-space change scores were calculated over 8.5 years of follow-up. Generalized linear mixed models were used to test predictors of mortality at subsequent 6-month intervals. Three hundred fifty-four deaths occurred within 6 months of two sequential life-space assessments. Controlling for age, sex, race, rural or urban residence, and comorbidity, life-space score and life-space decline over the preceding 6-month interval predicted mortality. A 10-point decrease in life-space resulted in a 72% increase in odds of dying over the subsequent 6 months (odds ratio = 1.723, P < .001). Life-space score at the beginning of a 6-month interval and change in life-space over 6 months were each associated with significant differences in subsequent 6-month mortality. Life-space assessment may assist clinicians in identifying older adults at risk of short-term mortality. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  12. The interaction between stress and positive affect in predicting mortality.

    PubMed

    Okely, Judith A; Weiss, Alexander; Gale, Catharine R

    2017-09-01

    Positive affect is associated with longevity; according to the stress-buffering hypothesis, this is because positive affect reduces the health harming effects of psychological stress. If this mechanism plays a role, then the association between positive affect and mortality risk should be most apparent among individuals who report higher stress. Here, we test this hypothesis. The sample consisted of 8542 participants aged 32-86 from the National Health and Nutrition Examination Survey (NHANES I) Epidemiological Follow-up Study (NHEFS). We used Cox's proportional hazards regression to test for the main effects of and the interaction between positive affect and perceived stress in predicting mortality risk over a 10year follow up period. Greater positive affect was associated with lower mortality risk. We found a significant interaction between positive affect and perceived stress such that the association between positive affect and mortality risk was stronger in people reporting higher stress. In the fully adjusted model, a standard deviation increase in positive affect was associated with a 16% (HR=0.84; 95% CI=0.75, 0.95) reduction in mortality risk among participants who reported high levels of stress. The association between positive affect and mortality risk was weaker and not significant among participants who reported low levels of stress (HR=0.98; 95% CI=0.89, 1.08). Our results support the stress-buffering model and illustrate that the association between positive affect and reduced risk may be strongest under challenging circumstances. Copyright © 2017. Published by Elsevier Inc.

  13. Blood Epigenetic Age may Predict Cancer Incidence and Mortality.

    PubMed

    Zheng, Yinan; Joyce, Brian T; Colicino, Elena; Liu, Lei; Zhang, Wei; Dai, Qi; Shrubsole, Martha J; Kibbe, Warren A; Gao, Tao; Zhang, Zhou; Jafari, Nadereh; Vokonas, Pantel; Schwartz, Joel; Baccarelli, Andrea A; Hou, Lifang

    2016-03-01

    Biological measures of aging are important for understanding the health of an aging population, with epigenetics particularly promising. Previous studies found that tumor tissue is epigenetically older than its donors are chronologically. We examined whether blood Δage (the discrepancy between epigenetic and chronological ages) can predict cancer incidence or mortality, thus assessing its potential as a cancer biomarker. In a prospective cohort, Δage and its rate of change over time were calculated in 834 blood leukocyte samples collected from 442 participants free of cancer at blood draw. About 3-5 years before cancer onset or death, Δage was associated with cancer risks in a dose-responsive manner (P = 0.02) and a one-year increase in Δage was associated with cancer incidence (HR: 1.06, 95% CI: 1.02-1.10) and mortality (HR: 1.17, 95% CI: 1.07-1.28). Participants with smaller Δage and decelerated epigenetic aging over time had the lowest risks of cancer incidence (P = 0.003) and mortality (P = 0.02). Δage was associated with cancer incidence in a 'J-shaped' manner for subjects examined pre-2003, and with cancer mortality in a time-varying manner. We conclude that blood epigenetic age may mirror epigenetic abnormalities related to cancer development, potentially serving as a minimally invasive biomarker for cancer early detection.

  14. Predictive factors of septic shock and mortality in neutropenic patients.

    PubMed

    Ramzi, Jeddi; Mohamed, Zarrouk; Yosr, Benabdennebi; Karima, Kacem; Raihane, Benlakhal; Lamia, Aissaoui; Hela, Ben Abid; Zaher, Belhadjali; Balkis, Meddeb

    2007-12-01

    Neutropenia is a major risk factor for developing a serious infection. Bacteremia still causes significant mortality among neutropenic patients with cancer. The purpose of this study was to identify risk factors for septic shock and for mortality in neutropenic patients with leukemia and bacteremia. Consecutive samples from 20 patients with acute myeloid leukemia and bacteremia were studied during a 1 year period (January-December 2003). All patients received empirical antibiotic therapies for febrile episodes using ceftazidime plus amikacin. About 110 neutropenic febrile episodes were noted: clinically documented 14.54%, microbiologically documented 16.36% and fever of unknown origin 69.09%. Gram-negative organism caused eight febrile episodes: Pseudomonas (5), Klebsiella (3). Gram-positive organism caused 10 episodes: Staphylococcus (6), Streptococci (2), Enterococci (2). Pulmonary infection accounted for 25% of clinically documented infections. About 14 of the 110 febrile episodes were associated with septic shock causing mortality in 7 patients. In a univariate analysis variables associated with septic shock were: pulmonary infection (OR = 17, p = 0.001), serum bicarbonate < 17 mmol/l (OR = 68, p < 0.001) and serum lactate >3 mmol/l (OR = 62, p < 0.001). Variables associated with mortality were: pulmonary infection (OR = 83, p < 0.001) and serum bicarbonate < 17 mmol/l (OR = 61, p < 0.001). In a multivariate analysis two variables were associated with septic shock: pulmonary infection (OR = 5, p = 0.043) and serum lactate >3 mmol/l (OR = 10, p = 0.003). An elevated serum lactate (>3 mmol/l) and low serum bicarbonate ( < 17 mmol/l) at the onset of bacteremia are useful biomarkers in predicting septic shock and mortality in neutropenic patients.

  15. Readmission after Colectomy for Cancer Predicts One-Year Mortality

    PubMed Central

    Greenblatt, David Yu; Weber, Sharon M.; O’Connor, Erin S.; LoConte, Noelle K.; Liou, Jinn-Ing; Smith, Maureen A.

    2010-01-01

    Objectives Early hospital readmission is a common and costly problem in the Medicare population. In 2009, the Centers for Medicaid and Medicare Services began mandating hospital reporting of disease-specific readmission rates. We sought to determine the rate and predictors of readmission after colectomy for cancer, as well as the association between readmission and mortality. Methods Medicare beneficiaries who underwent colectomy for stage I-III colon adenocarcinoma from 1992–2002 were identified from the SEER-Medicare database. Multivariate logistic regression identified predictors of early readmission and one-year mortality. Odds ratios were adjusted for multiple factors, including measures of comorbidity, socioeconomic status, and disease severity. Results Of 42,348 patients who were discharged, 4,662 (11.0%) were readmitted within 30 days. The most common causes of rehospitalization were ileus/obstruction and infection. Significant predictors of readmission included male gender, comorbidity, emergent admission, prolonged hospital stay, blood transfusion, ostomy, and discharge to nursing home. Readmission was inversely associated with hospital procedure volume, but not surgeon volume. After adjusting for potential confounding variables, the predicted probability of one-year mortality was 16% for readmitted patients, compared to 7% for those not readmitted. This difference in mortality was significant for all stages of cancer. Conclusions Early readmission after colectomy for cancer is common and due in part to modifiable factors. There is a remarkable association between readmission and one-year mortality. Early readmission is therefore an important quality-of-care indicator for colon cancer surgery. These findings may facilitate the development of targeted interventions that will decrease readmissions and improve patient outcomes. PMID:20224370

  16. Circulating cell-free DNA in hemodialysis patients predicts mortality.

    PubMed

    Tovbin, David; Novack, Victor; Wiessman, Maya Paryente; Abd Elkadir, Amir; Zlotnik, Moshe; Douvdevani, Amos

    2012-10-01

    Circulating cell-free DNA (CFD) appears following cell damage and DNA release, and increases in hemodialysis (HD) patients particularly following HD. We hypothesized that CFD is an integrative marker of tissue damage and can be an independent predictor for all-cause mortality in HD patients. In a prospective study, CFD levels before and after HD were evaluated in 31 chronic HD patients with no acute disease, using the reported rapid non-cumbersome inexpensive fluorometric assay developed in our laboratory. Follow-up levels were assessed at 18 months in 22 patients. All-cause mortality was a primary endpoint. During 42 months of follow-up, 13 of the 31 (41.9%) patients died. The decedents were older than the survivors (mean age 69.9 versus 61.5 years, P = 0.06), but did not differ in end-stage renal disease (ESRD) duration, gender, albumin and hemoglobin, diabetes mellitus and weight. Post-dialysis CFD levels were significantly lower in survivors (median 688 versus 880 ng/mL, P = 0.01). The sensitivity and specificity of CFD levels of 850 ng/mL to predict 42 months (3.5 years) mortality were 73 and 75%, respectively, and the area under the receiver-operating characteristic curve was 0.77 [95% confidence interval (CI) 0.60-0.94]. The Cox proportional hazard regression model showed that CFD higher than 850 ng/mL adjusted for age, ESRD duration, weight and creatinine (stepwise model) was highly predictive of all-cause death with a hazard ratio of 8.0 (95% CI 2.3-28.5, P = 0.001). Post-dialysis CFD level is an independent predictor of all-cause mortality in patients undergoing HD. We propose that CFD detection is an inexpensive applicable tool for identifying patients at risk and their follow-up.

  17. 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.

  18. Quantifying the Value of Biomarkers for Predicting Mortality

    PubMed Central

    Goldman, Noreen; Glei, Dana A.

    2015-01-01

    Purpose In light of widespread interest in the prognostic value of biomarkers, we apply three discrimination measures to evaluate the incremental value of biomarkers –beyond self-reported measures – for predicting all-cause mortality. We assess whether all three measures –AUC, NRI(>0), and IDI – lead to the same conclusions. Methods We use longitudinal data from a nationally representative sample of older Taiwanese (n = 639, aged 54+ in 2000, examined in 2000 and 2006, with mortality follow-up through 2011). We estimate age-specific mortality using a Gompertz hazard model. Results The broad conclusions are consistent across the three discrimination measures and support the inclusion of biomarkers, particularly inflammatory markers, in household surveys. Although the rank ordering of individual biomarkers varies across discrimination measures, the following is true for all three: interleukin-6 is the strongest predictor, the other three inflammatory markers make the top 10, and homocysteine ranks second or third. Conclusions The consistency of most of our findings across metrics should provide comfort to researchers using discrimination measures to evaluate the prognostic value of biomarkers. However, because the degree of consistency varies with the level of detail inherent in the research question, we recommend that researchers confirm results with multiple discrimination measures. PMID:26419291

  19. Pediatric trauma BIG score: Predicting mortality in polytraumatized pediatric patients.

    PubMed

    El-Gamasy, Mohamed Abd El-Aziz; Elezz, Ahmed Abd El Basset Abo; Basuni, Ahmed Sobhy Mohamed; Elrazek, Mohamed El Sayed Ali Abd

    2016-11-01

    Trauma is a worldwide health problem and the major cause of death and disability, particularly affecting the young population. It is important to remember that pediatric trauma care has made a significant improvement in the outcomes of these injured children. This study aimed at evaluation of pediatric trauma BIG score in comparison with New Injury Severity Score (NISS) and Pediatric Trauma Score (PTS) in Tanta University Emergency Hospital. The study was conducted in Tanta University Emergency Hospital to all multiple trauma pediatric patients attended to the Emergency Department for 1 year. Pediatric trauma BIG score, PTS, and NISS scores were calculated and results compared to each other and to observed mortality. BIG score ≥12.7 has sensitivity 86.7% and specificity 71.4%, whereas PTS at value ≤3.5 has sensitivity 63.3% and specificity 68.6% and NISS at value ≥39.5 has sensitivity 53.3% and specificity 54.3%. There was a significant positive correlation between BIG score value and mortality rate. The pediatric BIG score is a reliable mortality-prediction score for children with traumatic injuries; it uses international normalization ratio (INR), Base Excess (BE), and Glasgow Coma Scale (GCS) values that can be measured within a few minutes of sampling, so it can be readily applied in the Pediatric Emergency Department, but it cannot be applied on patients with chronic diseases that affect INR, BE, or GCS.

  20. Pediatric trauma BIG score: Predicting mortality in polytraumatized pediatric patients

    PubMed Central

    El-Gamasy, Mohamed Abd El-Aziz; Elezz, Ahmed Abd El Basset Abo; Basuni, Ahmed Sobhy Mohamed; Elrazek, Mohamed El Sayed Ali Abd

    2016-01-01

    Background: Trauma is a worldwide health problem and the major cause of death and disability, particularly affecting the young population. It is important to remember that pediatric trauma care has made a significant improvement in the outcomes of these injured children. Aim of the Work: This study aimed at evaluation of pediatric trauma BIG score in comparison with New Injury Severity Score (NISS) and Pediatric Trauma Score (PTS) in Tanta University Emergency Hospital. Materials and Methods: The study was conducted in Tanta University Emergency Hospital to all multiple trauma pediatric patients attended to the Emergency Department for 1 year. Pediatric trauma BIG score, PTS, and NISS scores were calculated and results compared to each other and to observed mortality. Results: BIG score ≥12.7 has sensitivity 86.7% and specificity 71.4%, whereas PTS at value ≤3.5 has sensitivity 63.3% and specificity 68.6% and NISS at value ≥39.5 has sensitivity 53.3% and specificity 54.3%. There was a significant positive correlation between BIG score value and mortality rate. Conclusion: The pediatric BIG score is a reliable mortality-prediction score for children with traumatic injuries; it uses international normalization ratio (INR), Base Excess (BE), and Glasgow Coma Scale (GCS) values that can be measured within a few minutes of sampling, so it can be readily applied in the Pediatric Emergency Department, but it cannot be applied on patients with chronic diseases that affect INR, BE, or GCS. PMID:27994378

  1. Predicting mortality in the intensive care unit: a comparison of the University Health Consortium expected probability of mortality and the Mortality Prediction Model III.

    PubMed

    Lipshutz, Angela K M; Feiner, John R; Grimes, Barbara; Gropper, Michael A

    2016-01-01

    Quality benchmarks are increasingly being used to compare the delivery of healthcare, and may affect reimbursement in the future. The University Health Consortium (UHC) expected probability of mortality (EPM) is one such quality benchmark. Although the UHC EPM is used to compare quality across UHC members, it has not been prospectively validated in the critically ill. We aimed to define the performance characteristics of the UHC EPM in the critically ill and compare its ability to predict mortality with the Mortality Prediction Model III (MPM-III). The first 100 consecutive adult patients discharged from the hospital (including deaths) each quarter from January 1, 2009 until September 30, 2011 that had an intensive care unit (ICU) stay were included. We assessed model discrimination, calibration, and overall performance, and compared the two models using Bland-Altman plots. Eight hundred ninety-one patients were included. Both the UHC EPM and the MPM-III had excellent performance (Brier score 0.05 and 0.06, respectively). The area under the curve was good for both models (UHC 0.90, MPM-III 0.87, p = 0.28). Goodness of fit was statistically significant for both models (UHC p = 0.002, MPM-III p = 0.0003), but improved with logit transformation (UHC p = 0.41; MPM-III p = 0.07). The Bland-Altman plot showed good agreement at extremes of mortality, but agreement diverged as mortality approached 50 %. The UHC EPM exhibited excellent overall performance, calibration, and discrimination, and performed similarly to the MPM-III. Correlation between the two models was poor due to divergence when mortality was maximally uncertain.

  2. Lower serum uric acid level predicts mortality in dialysis patients

    PubMed Central

    Bae, Eunjin; Cho, Hyun-Jeong; Shin, Nara; Kim, Sun Moon; Yang, Seung Hee; Kim, Dong Ki; Kim, Yong-Lim; Kang, Shin-Wook; Yang, Chul Woo; Kim, Nam Ho; Kim, Yon Su; Lee, Hajeong

    2016-01-01

    Abstract We evaluated the impact of serum uric acid (SUA) on mortality in patients with chronic dialysis. A total of 4132 adult patients on dialysis were enrolled prospectively between August 2008 and September 2014. Among them, we included 1738 patients who maintained dialysis for at least 3 months and had available SUA in the database. We categorized the time averaged-SUA (TA-SUA) into 5 groups: <5.5, 5.5–6.4, 6.5–7.4, 7.5–8.4, and ≥8.5 mg/dL. Cox regression analysis was used to calculate the hazard ratio (HR) of all-cause mortality according to SUA group. The mean TA-SUA level was slightly higher in men than in women. Patients with lower TA-SUA level tended to have lower body mass index (BMI), phosphorus, serum albumin level, higher proportion of diabetes mellitus (DM), and higher proportion of malnourishment on the subjective global assessment (SGA). During a median follow-up of 43.9 months, 206 patients died. Patients with the highest SUA had a similar risk to the middle 3 TA-SUA groups, but the lowest TA-SUA group had a significantly elevated HR for mortality. The lowest TA-SUA group was significantly associated with increased all-cause mortality (adjusted HR, 1.720; 95% confidence interval, 1.007–2.937; P = 0.047) even after adjusting for demographic, comorbid, nutritional covariables, and medication use that could affect SUA levels. This association was prominent in patients with well nourishment on the SGA, a preserved serum albumin level, a higher BMI, and concomitant DM although these parameters had no significant interaction in the TA-SUA-mortality relationship except DM. In conclusion, a lower TA-SUA level <5.5 mg/dL predicted all-cause mortality in patients with chronic dialysis. PMID:27310949

  3. Global trends and predictions in ovarian cancer mortality.

    PubMed

    Malvezzi, M; Carioli, G; Rodriguez, T; Negri, E; La Vecchia, C

    2016-11-01

    Over the last two decades, ovarian cancer mortality rates have levelled or declined. There are, however, persisting and substantial differences in ovarian cancer patterns and trends. We updated global trends in ovarian cancer mortality to 2012, and predicted trends in rates to 2020 using data from the World Health Organization database. In the EU, age-adjusted ovarian cancer mortality rates decreased 10% between 2002 and 2012, to 5.2/100 000. The decline was ∼16% in the USA, to 4.9/100 000 in 2012. Latin American countries had lower rates, and declines were observed in Argentina and Chile. Likewise, modest declines (-2.1%) were observed in Japan, whose rate remained low (3.2/100 000 in 2012). Australia had a rate of 4.3/100 000 in 2012, and a 12% decline. The falls were larger in young women, than in middle or old age. Recent rates at age 20-49 were higher in Japan than in the EU and the USA. Predictions to 2020 indicate a further 15% decline in the USA and 10% in the EU and Japan. The main reason for the favourable trends is the use of oral contraceptives (OCs), particularly, in the USA and countries of the EU where OCs were introduced earlier. Declines in menopausal hormone use may also have played a favourable role in elderly women, as well as improved diagnosis, management and treatment. © The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  4. Hemoglobin Variability Does Not Predict Mortality in European Hemodialysis Patients

    PubMed Central

    Kim, Joseph; Kronenberg, Florian; Aljama, Pedro; Anker, Stefan D.; Canaud, Bernard; Molemans, Bart; Stenvinkel, Peter; Schernthaner, Guntram; Ireland, Elizabeth; Fouqueray, Bruno; Macdougall, Iain C.

    2010-01-01

    Patients with CKD exhibit significant within-patient hemoglobin (Hb) level variability, especially with the use of erythropoiesis stimulating agents (ESAs) and iron. Analyses of dialysis cohorts in the United States produced conflicting results regarding the association of Hb variability with patient outcomes. Here, we determined Hb variability in 5037 European hemodialysis (HD) patients treated over 2 years to identify predictors of high variability and to evaluate its association with all-cause and cardiovascular disease (CVD) mortality. We assessed Hb variability with various methods using SD, residual SD, time-in-target (11.0 to 12.5 g/dl), fluctuation across thresholds, and area under the curve (AUC). Hb variability was significantly greater among incident patients than prevalent patients. Compared with previously described cohorts in the United States, residual SD was similar but fluctuations above target were less frequent. Using logistic regression, age, body mass index, CVD history, dialysis vintage, serum albumin, Hb, angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) use, ESA use, dialysis access type, dialysis access change, and hospitalizations were significant predictors of high variability. Multivariable adjusted Cox regression showed that SD, residual SD, time-in-target, and AUC did not predict all-cause or CVD mortality during a median follow-up of 12.4 months (IQR: 7.7 to 17.4). However, patients with consistently low levels of Hb (<11 g/dl) and those who fluctuated between the target range and <11 g/dl had increased risks for death (RR 2.34; 95% CI: 1.24 to 4.41 and RR 1.74; 95% CI: 1.00 to 3.04, respectively). In conclusion, although Hb variability is common in European HD patients, it does not independently predict mortality. PMID:20798262

  5. Darcy's law predicts widespread forest mortality under climate warming

    NASA Astrophysics Data System (ADS)

    McDowell, Nathan G.; Allen, Craig D.

    2015-07-01

    Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

  6. Persistent lymphopenia after diagnosis of sepsis predicts mortality.

    PubMed

    Drewry, Anne M; Samra, Navdeep; Skrupky, Lee P; Fuller, Brian M; Compton, Stephanie M; Hotchkiss, Richard S

    2014-11-01

    The objective of this study was to determine whether persistent lymphopenia on the fourth day following the diagnosis of sepsis predicts mortality. This was a single-center, retrospective cohort study of 335 adult patients with bacteremia and sepsis admitted to a large university-affiliated tertiary care hospital between January 1, 2010, and July 31, 2012. All complete blood cell count profiles during the first 4 days following the diagnosis of sepsis were recorded. The primary outcome was 28-day mortality. Secondary outcomes included development of secondary infections, 1-year mortality, and hospital and intensive care unit lengths of stay. Seventy-six patients (22.7%) died within 28 days. Lymphopenia was present in 28-day survivors (median, 0.7 × 10 cells/μL; interquartile range [IQR], 0.4-1.1 × 10 cells/μL) and nonsurvivors (median, 0.6 × 10 cells/μL; IQR, 0.4-1.1 × 10 cells/μL) at the onset of sepsis and was not significantly different between the groups (P = 0.35). By day 4, the median absolute lymphocyte count was significantly higher in survivors compared with nonsurvivors (1.1 × 10 cells/μL [IQR, 0.7-1.5 × 10 cells/μL] vs. 0.7 × 10 cells/μL [IQR, 0.5-1.0 × 10 cells/μL]; P < 0.0001). Using logistic regression to account for potentially confounding factors (including age, Acute Physiology and Chronic Health Evaluation II score, comorbidities, surgical procedure during the study period, and time until appropriate antibiotic administration), day 4 absolute lymphocyte count was found to be independently associated with 28-day survival (adjusted odds ratio, 0.68 [95% confidence interval, 0.51-0.91]) and 1-year survival (adjusted odds ratio, 0.74 [95% confidence interval, 0.59-0.93]). Severe persistent lymphopenia (defined as an absolute lymphocyte count of 0.6 × 10 cells/μL or less on the fourth day after sepsis diagnosis) was associated with increased development of secondary infections (P = 0.04). Persistent lymphopenia on the fourth day

  7. 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.

  8. 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

  9. Lung function indices for predicting mortality in COPD

    PubMed Central

    Boutou, Afroditi K.; Shrikrishna, Dinesh; Tanner, Rebecca J.; Smith, Cayley; Kelly, Julia L.; Ward, Simon P.; Polkey, Michael I.; Hopkinson, Nicholas S.

    2013-01-01

    Chronic obstructive pulmonary disease (COPD) is characterised by high morbidity and mortality. It remains unknown which aspect of lung function carries the most prognostic information and if simple spirometry is sufficient. Survival was assessed in COPD outpatients whose data had been added prospectively to a clinical audit database from the point of first full lung function testing including spirometry, lung volumes, gas transfer and arterial blood gases. Variables univariately associated with survival were entered into a multivariate Cox proportional hazard model. 604 patients were included (mean±sd age 61.9±9.7 years; forced expiratory volume in 1 s 37±18.1% predicted; 62.9% males); 229 (37.9%) died during a median follow-up of 83 months. Median survival was 91.9 (95% CI 80.8–103) months with survival rates at 3 and 5 years 0.83 and 0.66, respectively. Carbon monoxide transfer factor % pred quartiles (best quartile (>51%): HR 0.33, 95% CI 0.172–0.639; and second quartile (51–37.3%): HR 0.52, 95% CI 0.322–0.825; versus lowest quartile (<27.9%)), age (HR 1.04, 95% CI 1.02–1.06) and arterial oxygen partial pressure (HR 0.85, 95% CI 0.77–0.94) were the only parameters independently associated with mortality. Measurement of gas transfer provides additional prognostic information compared to spirometry in patients under hospital follow-up and could be considered routinely. PMID:23349449

  10. Early warning score predicts acute mortality in stroke patients.

    PubMed

    Liljehult, J; Christensen, T

    2016-04-01

    Clinical deterioration and death among patients with acute stroke are often preceded by detrimental changes in physiological parameters. Systematic and effective tools to identify patients at risk of deterioration early enough to intervene are therefore needed. The aim of the study was to investigate whether the aggregate weighted track and trigger system early warning score (EWS) can be used as a simple observational tool to identify patients at risk and predict mortality in a population of patients with acute stroke. Patients admitted with acute stroke at the Copenhagen University Hospital, Nordsjaellands Hospital, Denmark, from May to September 2012 were enrolled in a retrospective cohort study (n = 274). Vital signs were measured immediately after admission and consistently during the hospitalization period. Based on the vital signs, a single composite EWS was calculated. Death within 30 days was used as outcome. Area under the receiver operating characteristics curve (AUROC) and a Kaplan-Meier curve were computed to examine the prognostic validity of EWS. A total of 24 patients (8.8%) died within 30 days. The prognostic performance was high for both the EWS at admission (AUROC 0.856; 95% CI 0.760-0.951; P-value < 0.001) and the maximal EWS measured (AUROC 0.949; 95% CI 0.919-0.980; P-value < 0.001). Mortality rates were lowest for admission EWS 0-1 (2%) and highest for admission EWS ≥ 5 (63%). Early warning score is a simple and valid tool for identifying patients at risk of dying after acute stroke. Readily available physiological parameters are converted to a single score, which can guide both nurses and physicians in clinical decision making and resource allocation. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  11. The effects of deep network topology on mortality prediction.

    PubMed

    Hao Du; Ghassemi, Mohammad M; Mengling Feng

    2016-08-01

    Deep learning has achieved remarkable results in the areas of computer vision, speech recognition, natural language processing and most recently, even playing Go. The application of deep-learning to problems in healthcare, however, has gained attention only in recent years, and it's ultimate place at the bedside remains a topic of skeptical discussion. While there is a growing academic interest in the application of Machine Learning (ML) techniques to clinical problems, many in the clinical community see little incentive to upgrade from simpler methods, such as logistic regression, to deep learning. Logistic regression, after all, provides odds ratios, p-values and confidence intervals that allow for ease of interpretation, while deep nets are often seen as `black-boxes' which are difficult to understand and, as of yet, have not demonstrated performance levels far exceeding their simpler counterparts. If deep learning is to ever take a place at the bedside, it will require studies which (1) showcase the performance of deep-learning methods relative to other approaches and (2) interpret the relationships between network structure, model performance, features and outcomes. We have chosen these two requirements as the goal of this study. In our investigation, we utilized a publicly available EMR dataset of over 32,000 intensive care unit patients and trained a Deep Belief Network (DBN) to predict patient mortality at discharge. Utilizing an evolutionary algorithm, we demonstrate automated topology selection for DBNs. We demonstrate that with the correct topology selection, DBNs can achieve better prediction performance compared to several bench-marking methods.

  12. Hemoglobin Screening Independently Predicts All-Cause Mortality.

    PubMed

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

    2015-01-01

    Objective .- Determine if the addition of hemoglobin testing improves risk prediction for life insurance applicants. Method .- Hemoglobin results for insurance applicants tested from 1993 to 2007, with vital status determined by Social Security Death Master File follow-up in 2011, were analyzed by age and sex with and without accounting for the contribution of other test results. Results .- Hemoglobin values ≤12.0 g/dL (and possibly ≤13.0 g/dL) in females age 50+ (but not age <50) and hemoglobin values ≤13.0 g/dL in all males are associated with progressively increasing mortality risk independent of the contribution of other test values. Increased risk is also noted for hemoglobin values >15.0 g/dL (and possibly >14.0 g/dL) for all females and for hemoglobin values >16.0 g/dL for males. Conclusion .- Hemoglobin testing can add additional independent risk assessment to that obtained from other laboratory testing, BP and build in this relatively healthy insurance applicant population. Multiple studies support this finding at older ages, but data (and the prevalence of diseases impacting hemoglobin levels) are limited at younger ages.

  13. Pulse pressure can predict mortality in advanced heart failure.

    PubMed

    Ferreira, Ana Rita; Mendes, Sofia; Leite, Luís; Monteiro, Sílvia; Pego, Mariano

    2016-04-01

    Pulse pressure (PP) is the difference between systolic and diastolic blood pressure (BP). PP rises markedly after the fifth decade of life. High PP is a risk factor for the development of coronary heart disease and heart failure. The aim of this study was to assess whether PP can be used as a prognostic marker in advanced heart failure. We retrospectively studied patients in NYHA class III-IV who were hospitalized in a single heart failure unit between January 2003 and August 2012. Demographic characteristics, laboratory tests, and cardiovascular risk factors were recorded. PP was calculated as the difference between systolic and diastolic BP at admission, and the patients were divided into two groups (group 1: PP >40 mmHg and group 2: PP ≤40 mmHg). Median follow-up was 666 ± 50 days for the occurrence of cardiovascular death and heart transplantation. During follow-up 914 patients in NYHA class III-IV were hospitalized, 520 in group 1 and 394 in group 2. The most important difference between the groups was in left ventricular dysfunction, which was greater in patients with lower PP. On Kaplan-Meier analysis, group 2 had higher mortality (38 vs. 24 patients, log-rank p=0.002). PP is easily calculated, and enables prediction of cardiovascular death in patients with advanced heart failure. Copyright © 2016 Sociedade Portuguesa de Cardiologia. Published by Elsevier España. All rights reserved.

  14. Trends and predictions for gastric cancer mortality in Brazil

    PubMed Central

    de Souza Giusti, Angela Carolina Brandão; de Oliveira Salvador, Pétala Tuani Candido; dos Santos, Juliano; Meira, Karina Cardoso; Camacho, Amanda Rodrigues; Guimarães, Raphael Mendonça; Souza, Dyego L B

    2016-01-01

    AIM: To analyze the effect of age-period and birth cohort on gastric cancer mortality, in Brazil and across its five geographic regions, by sex, in the population over 20 years of age, as well as make projections for the period 2010-2029. METHODS: An ecological study is presented herein, which distributed gastric cancer-related deaths in Brazil and its geographic regions. The effects of age-period and birth cohort were calculated by the Poisson regression model and projections were made with the age-period-cohort model in the statistical program R. RESULTS: Progressive reduction of mortality rates was observed in the 1980’s, and then higher and lower mortality rates were verified in the 2000’s, for both sexes, in Brazil and for the South, Southeast and Midwest regions. A progressive decrease in mortality rates was observed for the Northeast (both sexes) and North (men only) regions within the period 1995-1999, followed by rising rates. CONCLUSION: Regional differences were demonstrated in the mortality rates for gastric cancer in Brazil, and the least developed regions of the country will present increases in projected mortality rates. PMID:27605887

  15. Trends and predictions for gastric cancer mortality in Brazil.

    PubMed

    de Souza Giusti, Angela Carolina Brandão; de Oliveira Salvador, Pétala Tuani Candido; Dos Santos, Juliano; Meira, Karina Cardoso; Camacho, Amanda Rodrigues; Guimarães, Raphael Mendonça; Souza, Dyego L B

    2016-07-28

    To analyze the effect of age-period and birth cohort on gastric cancer mortality, in Brazil and across its five geographic regions, by sex, in the population over 20 years of age, as well as make projections for the period 2010-2029. An ecological study is presented herein, which distributed gastric cancer-related deaths in Brazil and its geographic regions. The effects of age-period and birth cohort were calculated by the Poisson regression model and projections were made with the age-period-cohort model in the statistical program R. Progressive reduction of mortality rates was observed in the 1980's, and then higher and lower mortality rates were verified in the 2000's, for both sexes, in Brazil and for the South, Southeast and Midwest regions. A progressive decrease in mortality rates was observed for the Northeast (both sexes) and North (men only) regions within the period 1995-1999, followed by rising rates. Regional differences were demonstrated in the mortality rates for gastric cancer in Brazil, and the least developed regions of the country will present increases in projected mortality rates.

  16. Global Trends in Pancreatic Cancer Mortality From 1980 Through 2013 and Predictions for 2017.

    PubMed

    Lucas, Aimee L; Malvezzi, Matteo; Carioli, Greta; Negri, Eva; La Vecchia, Carlo; Boffetta, Paolo; Bosetti, Cristina

    2016-10-01

    Pancreatic cancer is a leading cause of cancer mortality, and its mortality has not decreased in recent years. We sought to determine global trends in pancreatic cancer mortality. We derived data on deaths from pancreatic cancer from the World Health Organization database for 59 countries from 1980 through 2013. Age-standardized mortalities were computed for persons of all ages and for persons 35-64 years old; for selected countries, they were computed for persons 25-49 years old. Joinpoint regression models were used to identify significant changes in mortality. For selected larger countries, we predicted number of deaths and mortality for 2017. Between 1980 and 2013, overall pancreatic cancer mortality in men increased in the European Union (EU) as well as in Southern and Eastern Europe, Brazil, Japan, and Republic of Korea. Overall pancreatic cancer mortality decreased in most Northern European countries, Australia, Canada, Mexico, and the United States (US). In women, mortality increased in the EU, Brazil, US, Japan, and Republic of Korea but decreased in Canada and Mexico. In 2012, Eastern Europe and Japan had the highest pancreatic cancer mortality for both sexes. In men 25-49 years old, mortality decreased in the EU, US, Japan, and most large European countries. On the basis of our data, we predict overall pancreatic cancer mortality in 2017 to level off in men in the EU and US but increase in Japan. In women, mortality will continue to increase in most countries except the US; the greatest increase is predicted to occur in Japan. Mortality from pancreatic cancer has not decreased as it has for other cancers in recent years. A notable exception is a decrease in mortality in men 25-49 years old, which could indicate a reversal in the current increasing global trends. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

  17. The Prediction Predicament: Rethinking Necrotizing Soft Tissue Infections Mortality

    PubMed Central

    Moore, Samantha A.; Levy, Brandon H.; Prematilake, Chalani

    2015-01-01

    Abstract Background: Our study sought to identify independent risk factors predisposing patients with necrotizing soft tissue infections (NSTIs) to mortality from among laboratory values, demographic data, and microbiologic findings in a small population. To this end, a retrospective review was conducted of the medical records of all patients with NSTI who had been treated at our institution from 2003 to 2012 (n=134). Methods: Baseline demographics and comorbidities, clinical and laboratory values, hospital course, and the microbiologic characteristics of surgical incision cultures were recorded. Each variable was tested for association with survival status and all associated variables with p<0.15 were included in a logistic regression model to seek factors associated independently with mortality. Results: Surprisingly, no demographic or pre-existing condition proved to be a predictor of mortality. Two laboratory values had an inverse correlation to mortality: High C-reactive protein (CRP) and highest recorded CRP. Of surgical incisions that grew bacteria in culture, 33.6% were polymicrobial. Mortality rates were highest with Enterococcus-containing polymicrobial infections (50%), followed by those containing Pseudomonas (40%), and Streptococcus spp. (27%). Understanding why so many studies across the literature, now including our own, find such disparate results for correlation of NSTI mortality with patient data may lie in the fundamentally dynamic nature of the organisms involved. Conclusions: This study suggests that no single factor present on admission is a robust predictor of outcome; it is likely that survival in NSTI is predicated upon a complex interaction of multiple host and microbial factors that do not lend themselves to reduction into a simple formula. It is also abundantly clear that the well-established principles of NSTI surgery should continue to be followed in all cases, with an emphasis on early debridement, irrespective of apparent severity of

  18. Monitoring of the newborn dog and prediction of neonatal mortality.

    PubMed

    Mila, Hanna; Grellet, Aurélien; Delebarre, Marine; Mariani, Claire; Feugier, Alexandre; Chastant-Maillard, Sylvie

    2017-08-01

    Despite the high neonatal mortality rate in puppies, pertinent criteria for health evaluation of the newborns are not defined. This study was thus designed to measure and to characterize factors of variation of six health parameters in dog neonates, and to evaluate their value as predictors of neonatal mortality. A total of 347 purebred puppies under identical conditions of housing and management were examined within the first 8h after birth and then at Day 1. The first health evaluation included Apgar score, weight, blood glucose, lactate and β-hydroxybutyrate concentration, rectal temperature and urine specific gravity (SG). The second evaluation at Day 1 included the same parameters, excluding Apgar score and weight. The mortality rate over the first 24h and over 21days of age was recorded. The early predictors of neonatal mortality in the dog were determined with generalized linear mixed models and receiver operating characteristic curves analyses. An Apgar score at or below 6 evaluated within the first 8h after birth was found associated with a higher risk of death during the first 24h. A reduced glucose concentration (≤92mg/dl) at Day 1 was found to be associated with higher mortality between 1 and 21days of age. Low-birth-weight puppies were characterized by both low viability (low Apgar score) and low blood glucose concentration, and thus were found indirectly at higher risk of neonatal mortality. This study promotes two low cost easy-to-use tests for health evaluation in puppies, i.e. Apgar scoring and blood glucose assay. Further investigation is necessary to establish if the strong relationship between blood glucose and neonatal survival reflects high energy requirements or other benefits from colostrum intake. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

  19. Predicting drought-induced tree mortality in the western United States

    NASA Astrophysics Data System (ADS)

    Anderegg, W.; Wolf, A.; Shevliakova, E.; Pacala, S. W.

    2015-12-01

    Projected responses of forest ecosystems to warming and drying associated with 21st century climate change vary widely from resiliency to widespread dieback. A major shortcoming of current vegetation models is the inability to account for mortality of overstory trees during extreme drought due to uncertainties in mechanisms and thresholds. In this talk, I discuss two modeling efforts to predict drought-induced tree mortality in the western United States. In the first, we identify a lethal drought threshold in the loss of vascular transport capacity from xylem cavitation, which provides insight into what initiates mortality, in Populus tremuloides in the southwestern United States. We then use the hydraulic-based threshold to produce a hindcast of a drought-induced forest dieback and compare predictions against three independent regional mortality datasets. The hydraulic threshold predicted major regional patterns of tree mortality with high accuracy based on field plots and mortality maps derived from Landsat imagery. Climate model simulations project increasing drought stress in this region that exceeds the observed mortality threshold in the high emissions scenario by the 2050s, likely triggering further widespread diebacks. In the second approach, we build a dynamic plant hydraulic model into a land-surface model and compare predictions against observed mortality patterns across multiple species. These methods provide powerful and tractable approaches for incorporating tree mortality into vegetation models to resolve uncertainty over the fate of forest ecosystems in a changing climate.

  20. Prediction of Cancer Incidence and Mortality in Korea, 2017.

    PubMed

    Jung, Kyu-Won; Won, Young-Joo; Oh, Chang-Mo; Kong, Hyun-Joo; Lee, Duk Hyoung; Lee, Kang Hyun

    2017-04-01

    This study aimed to report on cancer incidence and mortality for the year 2017 in Korea in order to estimate the nation's current cancer burden. Cancer incidence data from 1999 to 2014 were obtained from the Korea National Cancer Incidence Database, and cancer mortality data from 1993 to 2015 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observe age-specific cancer rates against observed years, and then multiplying the projected age-specific rates by the age-specific population. The Joinpoint regression model was used to determine at which year the linear trend changed significantly; we only used data of the latest trend. A total of 221,143 new cancer cases and 80,268 cancer deaths are expected to occur in Korea in 2017. The most common cancer sites are the colorectum, stomach, lung, thyroid, and breast. These five cancers represent half of the overall burden of cancer in Korea. For mortality, the most common sites are the lung, liver, colorectal, stomach, and pancreas. The incidence rate of all cancers in Korea appears to have decreased mainly because of a decrease in thyroid cancer. These up-to-date estimates of the cancer burden in Korea could be an important resource for planning and evaluation of cancer-control programs.

  1. Prediction of Cancer Incidence and Mortality in Korea, 2017

    PubMed Central

    Jung, Kyu-Won; Won, Young-Joo; Oh, Chang-Mo; Kong, Hyun-Joo; Lee, Duk Hyoung; Lee, Kang Hyun

    2017-01-01

    Purpose This study aimed to report on cancer incidence and mortality for the year 2017 in Korea in order to estimate the nation’s current cancer burden. Materials and Methods Cancer incidence data from 1999 to 2014 were obtained from the Korea National Cancer Incidence Database, and cancer mortality data from 1993 to 2015 were acquired from Statistics Korea. Cancer incidence and mortality were projected by fitting a linear regression model to observe age-specific cancer rates against observed years, and then multiplying the projected age-specific rates by the age-specific population. The Joinpoint regression model was used to determine at which year the linear trend changed significantly; we only used data of the latest trend. Results A total of 221,143 new cancer cases and 80,268 cancer deaths are expected to occur in Korea in 2017. The most common cancer sites are the colorectum, stomach, lung, thyroid, and breast. These five cancers represent half of the overall burden of cancer in Korea. For mortality, the most common sites are the lung, liver, colorectal, stomach, and pancreas. Conclusion The incidence rate of all cancers in Korea appears to have decreased mainly because of a decrease in thyroid cancer. These up-to-date estimates of the cancer burden in Korea could be an important resource for planning and evaluation of cancer-control programs. PMID:28301926

  2. 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.

  3. Motor functioning differentially predicts mortality in men and women.

    PubMed

    Bravell, Marie Ernsth; Finkel, Deborah; Dahl Aslan, Anna; Reynolds, Chandra A; Hallgren, Jenny; Pedersen, Nancy L

    2017-09-01

    Research indicates gender differences in functional performance at advanced ages, but little is known about their impact on longevity for men and women. To derive a set of motor function factors from a battery of functional performance measures and examine their associations with mortality, incorporating possible gender interactions. Analyses were performed on the longitudinal Swedish Adoption/Twin Study of Aging (SATSA) including twenty-four assessments of motor function up to six times over a 19-year period. Three motor factors were derived from several factor analyses; fine motor, balance/upper strength, and flexibility. A latent growth curve model was used to capture longitudinal age changes in the motor factors and generated estimates of intercept at age 70 (I), rates of change before (S1) and after age 70 (S2) for each factor. Cox regression models were used to determine how gender in interaction with the motor factors was related to mortality. Females demonstrated lower functional performance in all motor functions relative to men. Cox regression survival analyses demonstrated that both balance/upper strength, and fine motor function were significantly related to mortality. Gender specific analyses revealed that this was true for women only. For men, none of the motor factors were related to mortality. Women demonstrated more difficulties in all functioning facets, and only among women were motor functioning (balance/upper strength and fine motor function) associated with mortality. These results provide evidence for the importance of considering motor functioning, and foremost observed gender differences when planning for individualized treatment and rehabilitation. Copyright © 2017 Elsevier B.V. All rights reserved.

  4. Smell Loss Predicts Mortality Risk Regardless of Dementia Conversion.

    PubMed

    Ekström, Ingrid; Sjölund, Sara; Nordin, Steven; Nordin Adolfsson, Annelie; Adolfsson, Rolf; Nilsson, Lars-Göran; Larsson, Maria; Olofsson, Jonas K

    2017-06-01

    To determine whether dementia could explain the association between poor olfactory performance and mortality risk within a decade-long follow-up period. Prospective cohort study. Betula Study, Umeå, Sweden. A population-based sample of adult participants without dementia at baseline aged 40 to 90 (N = 1,774). Olfactory performance using the Scandinavian Odor-Identification Test (SOIT) and self-reported olfactory function; several social, cognitive, and medical risk factors at baseline; and incident dementia during the following decade. Within the 10-year follow-up, 411 of 1,774 (23.2%) participants had died. In a Cox model, the association between higher SOIT score and lower mortality was significant (hazard ratio (HR) = 0.74 per point interval, 95% confidence interval (CI) = 0.71-0.77, P < .001). The effect was attenuated, but remained significant, after controlling for age, sex, education, and health-related and cognitive variables (HR = 0.92, 95% CI = 0.87-0.97, P = .001). The association between SOIT score and mortality was retained after controlling for dementia conversion before death (HR = 0.92, 95% CI = 0.87-0.97, P = .001). Similar results were obtained for self-reported olfactory dysfunction. Poor odor identification and poor self-reported olfactory function are associated with greater likelihood of future mortality. Dementia does not attenuate the association between olfactory loss and mortality, suggesting that olfactory loss might mark deteriorating health, irrespective of dementia. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  5. Acute Kidney Injury Predicts Mortality after Charcoal Burning Suicide

    PubMed Central

    Chen, Yu-Chin; Tseng, Yi-Chia; Huang, Wen-Hung; Hsu, Ching-Wei; Weng, Cheng-Hao; Liu, Shou-Hsuan; Yang, Huang-Yu; Chen, Kuan-Hsin; Chen, Hui-Ling; Fu, Jen-Fen; Lin, Wey-Ran; Wang, I-Kuan; Yen, Tzung-Hai

    2016-01-01

    A paucity of literature exists on risk factors for mortality in charcoal burning suicide. In this observational study, we analyzed the data of 126 patients with charcoal burning suicide that seen between 2002 and 2013. Patients were grouped according to status of renal damage as acute kidney injury (N = 49) or non-acute kidney injury (N = 77). It was found that patients with acute kidney injury suffered severer complications such as respiratory failure (P = 0.002), myocardial injury (P = 0.049), hepatic injury (P < 0.001), rhabdomyolysis (P = 0.045) and out-of-hospital cardiac arrest (P = 0.028) than patients without acute kidney injury. Moreover, patients with acute kidney injury suffered longer hospitalization duration (16.9 ± 18.3 versus 10.7 ± 10.9, P = 0.002) and had higher mortality rate (8.2% versus 0%, P = 0.011) than patients without injury. In a multivariate Cox regression model, it was demonstrated that serum creatinine level (P = 0.019) and heart rate (P = 0.022) were significant risk factors for mortality. Finally, Kaplan-Meier analysis revealed that patients with acute kidney injury suffered lower cumulative survival than without injury (P = 0.016). In summary, the overall mortality rate of charcoal burning suicide population was 3.2%, and acute kidney injury was a powerful predictor of mortality. Further studies are warranted. PMID:27430168

  6. 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.

  7. 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...

  8. Plasma Lactate Dehydrogenase Levels Predict Mortality in Acute Aortic Syndromes

    PubMed Central

    Morello, Fulvio; Ravetti, Anna; Nazerian, Peiman; Liedl, Giovanni; Veglio, Maria Grazia; Battista, Stefania; Vanni, Simone; Pivetta, Emanuele; Montrucchio, Giuseppe; Mengozzi, Giulio; Rinaldi, Mauro; Moiraghi, Corrado; Lupia, Enrico

    2016-01-01

    Abstract In acute aortic syndromes (AAS), organ malperfusion represents a key event impacting both on diagnosis and outcome. Increased levels of plasma lactate dehydrogenase (LDH), a biomarker of malperfusion, have been reported in AAS, but the performance of LDH for the diagnosis of AAS and the relation of LDH with outcome in AAS have not been evaluated so far. This was a bi-centric prospective diagnostic accuracy study and a cohort outcome study. From 2008 to 2014, patients from 2 Emergency Departments suspected of having AAS underwent LDH assay at presentation. A final diagnosis was obtained by aortic imaging. Patients diagnosed with AAS were followed-up for in-hospital mortality. One thousand five hundred seventy-eight consecutive patients were clinically eligible, and 999 patients were included in the study. The final diagnosis was AAS in 201 (20.1%) patients. Median LDH was 424 U/L (interquartile range [IQR] 367–557) in patients with AAS and 383 U/L (IQR 331–460) in patients with alternative diagnoses (P < 0.001). Using a cutoff of 450 U/L, the sensitivity of LDH for AAS was 44% (95% confidence interval [CI] 37–51) and the specificity was 73% (95% CI 69–76). Overall in-hospital mortality for AAS was 23.8%. Mortality was 32.6% in patients with LDH ≥ 450 U/L and 16.8% in patients with LDH < 450 U/L (P = 0.006). Following stratification according to LDH quartiles, in-hospital mortality was 12% in the first (lowest) quartile, 18.4% in the second quartile, 23.5% in the third quartile, and 38% in the fourth (highest) quartile (P = 0.01). LDH ≥ 450 U/L was further identified as an independent predictor of death in AAS both in univariate and in stepwise logistic regression analyses (odds ratio 2.28, 95% CI 1.11–4.66; P = 0.025), in addition to well-established risk markers such as advanced age and hypotension. Subgroup analysis showed excess mortality in association with LDH ≥ 450 U/L in elderly, hemodynamically stable

  9. A biological approach to the interspecies prediction of radiation-induced mortality risk

    SciTech Connect

    Carnes, B.A.; Grahn, D.; Olshansky, S.J.

    1997-08-01

    Evolutionary explanations for why sexually reproducing organisms grow old suggest that the forces of natural selection affect the ages when diseases occur that are subject to a genetic influence (referred to here as intrinsic diseases). When extended to the population level for a species, this logic leads to the general prediction that age-specific death rates from intrinsic causes should begin to rise as the force of selection wanes once the characteristic age of sexual maturity is attained. Results consistent with these predictions have been found for laboratory mice, beagles, and humans where, after adjusting for differences in life span, it was demonstrated that these species share a common age pattern of mortality for intrinsic causes of death. In quantitative models used to predict radiation-induced mortality, risks are often expressed as multiples of those observed in a control population. A control population, however, is an aging population. As such, mortality risks related to exposure must be interpreted relative to the age-specific risk of death associated with aging. Given the previous success in making interspecies predictions of age-related mortality, the purpose of this study was to determine whether radiation-induced mortality observed in one species could also be predicted quantitatively from a model used to describe the mortality consequences of exposure to radiation in a different species. Mortality data for B6CF{sub 1} mice and beagles exposed to {sup 60}Co {gamma}-rays for the duration of life were used for analysis.

  10. Preoperative hypernatremia predicts increased perioperative morbidity and mortality.

    PubMed

    Leung, Alexander A; McAlister, Finlay A; Finlayson, Samuel R G; Bates, David W

    2013-10-01

    The prognostic implications of preoperative hypernatremia are unknown. We sought to determine whether preoperative hypernatremia is a predictor of 30-day perioperative morbidity and mortality. We conducted a cohort study using the American College of Surgeons-National Surgical Quality Improvement Program and identified 908,869 adult patients undergoing major surgery from approximately 300 hospitals from the years 2005 to 2010. We followed the patients for 30-day perioperative outcomes, which included death, major coronary events, wound infections, pneumonia, and venous thromboembolism. Multivariable logistic regression was used to estimate the odds of 30-day perioperative outcomes. The 20,029 patients (2.2%) with preoperative hypernatremia (>144 mmol/L) were compared with the 888,840 patients with a normal baseline sodium (135-144 mmol/L). Hypernatremia was associated with a higher odds for 30-day mortality (5.2% vs 1.3%; adjusted odds ratio [aOR], 1.44; 95% confidence interval [CI], 1.33-1.56), and this finding was consistent in all subgroups. The odds increased according to the severity of hypernatremia (P < .001 for pairwise comparison for mild [145-148 mmol/L] vs severe [>148 mmol/L] categories). Furthermore, hypernatremia was associated with a greater odds for perioperative major coronary events (1.6% vs 0.7%; aOR, 1.16; 95% CI, 1.03-1.32), pneumonia (3.4% vs 1.5%; aOR, 1.23; 95% CI, 1.13-1.34), and venous thromboembolism (1.8% vs 0.9%; OR, 1.28; 95% CI, 1.14-1.42). Preoperative hypernatremia is associated with increased perioperative 30-day morbidity and mortality. Copyright © 2013 Elsevier Inc. All rights reserved.

  11. Right and left heart dysfunction predict mortality in pulmonary hypertension.

    PubMed

    Henein, Michael Y; Grönlund, Christer; Tossavainen, Erik; Söderberg, Stefan; Gonzalez, Manuel; Lindqvist, Per

    2017-01-01

    In pulmonary hypertension (PH), the right heart dysfunction is a strong predictor of adverse clinical outcome, while the role of the left heart is not fully determined. The aim of this study was to identify predictors of mortality in precapillary PH including measures of both right and left heart function. We studied 34 patients (mean age 64 ± 13, range 31-82 years, 24 females) with precapillary PH, all of whom underwent detailed Doppler echocardiographic examination of the right and left heart function using conventional and speckle-tracking echocardiography. Patients were followed up for up to 8 years (mean 4·2 ± 1·9 years). At follow-up, 16 patients survived. Left ventricular (LV) filling time (P = 0·007), pulmonary artery acceleration time (P = 0·009), right atrial pressure (RAP) (P<0·001) and tricuspid regurgitation (TR) severity (P = 0·007) were worse in the deceased group. RV global longitudinal strain (GLS) (P = 0·001), RAP (P≤0·001), LV filling time (P<0·001) and TR severity (P<0·001) were the most accurate predictors, having the largest AUC (>0·65) and carried the highest risk for mortality (P<0·001 for all). The strongest predictors of mortality in precapillary PH indirectly reflect both left and right heart dysfunction including atrial structure and function disturbances. While an interaction pattern is observed, it needs to be confirmed in a larger cohort. © 2015 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

  12. Short-Term Mortality Prediction for Acute Lung Injury Patients: External Validation of the ARDSNet Prediction Model

    PubMed Central

    Damluji, Abdulla; Colantuoni, Elizabeth; Mendez-Tellez, Pedro A.; Sevransky, Jonathan E.; Fan, Eddy; Shanholtz, Carl; Wojnar, Margaret; Pronovost, Peter J.; Needham, Dale M.

    2011-01-01

    Objective An independent cohort of acute lung injury (ALI) patients was used to evaluate the external validity of a simple prediction model for short-term mortality previously developed using data from ARDS Network (ARDSNet) trials. Design, Setting, and Patients Data for external validation were obtained from a prospective cohort study of ALI patients from 13 ICUs at four teaching hospitals in Baltimore, Maryland. Measurements and Main Results Of the 508 non-trauma, ALI patients eligible for this analysis, 234 (46%) died in-hospital. Discrimination of the ARDSNet prediction model for inhospital mortality, evaluated by the area under the receiver operator characteristics curves (AUC), was 0.67 for our external validation dataset versus 0.70 and 0.68 using APACHE II and the ARDSNet validation dataset, respectively. In evaluating calibration of the model, predicted versus observed in-hospital mortality for the external validation dataset was similar for both low risk (ARDSNet model score = 0) and high risk (score = 3 or 4+) patient strata. However, for intermediate risk (score = 1 or 2) patients, observed in-hospital mortality was substantially higher than predicted mortality (25.3% vs. 16.5% and 40.6% vs. 31.0% for score = 1 and 2, respectively). Sensitivity analyses limiting our external validation data set to only those patients meeting the ARDSNet trial eligibility criteria and to those who received mechanical ventilation in compliance with the ARDSNet ventilation protocol, did not substantially change the model’s discrimination or improve its calibration. Conclusions Evaluation of the ARDSNet prediction model using an external ALI cohort demonstrated similar discrimination of the model as was observed with the ARDSNet validation dataset. However, there were substantial differences in observed versus predicted mortality among intermediate risk ALI patients. The ARDSNet model provided reasonable, but imprecise, estimates of predicted mortality when applied to our

  13. Mortality of Inshore Marine Mammals in Eastern Australia Is Predicted by Freshwater Discharge and Air Temperature

    PubMed Central

    Meager, Justin J.; Limpus, Colin

    2014-01-01

    Understanding environmental and climatic drivers of natural mortality of marine mammals is critical for managing populations effectively and for predicting responses to climate change. Here we use a 17-year dataset to demonstrate a clear relationship between environmental forcing and natural mortality of inshore marine mammals across a subtropical-tropical coastline spanning a latitudinal gradient of 13° (>2000 km of coastline). Peak mortality of inshore dolphins and dugongs followed sustained periods of elevated freshwater discharge (9 months) and low air temperature (3 months). At a regional scale, these results translated into a strong relationship between annual mortality and an index of El Niño-Southern Oscillation. The number of cyclones crossing the coastline had a comparatively weak effect on inshore marine mammal mortality, and only in the tropics. Natural mortality of offshore/migratory cetaceans was not predicted by freshwater discharge, but was related to lagged air temperature. These results represent the first quantitative link between environmental forcing and marine mammal mortality in the tropics, and form the basis of a predictive tool for managers to prepare responses to periods of elevated marine mammal mortality. PMID:24740149

  14. Mortality of inshore marine mammals in eastern Australia is predicted by freshwater discharge and air temperature.

    PubMed

    Meager, Justin J; Limpus, Colin

    2014-01-01

    Understanding environmental and climatic drivers of natural mortality of marine mammals is critical for managing populations effectively and for predicting responses to climate change. Here we use a 17-year dataset to demonstrate a clear relationship between environmental forcing and natural mortality of inshore marine mammals across a subtropical-tropical coastline spanning a latitudinal gradient of 13° (>2000 km of coastline). Peak mortality of inshore dolphins and dugongs followed sustained periods of elevated freshwater discharge (9 months) and low air temperature (3 months). At a regional scale, these results translated into a strong relationship between annual mortality and an index of El Niño-Southern Oscillation. The number of cyclones crossing the coastline had a comparatively weak effect on inshore marine mammal mortality, and only in the tropics. Natural mortality of offshore/migratory cetaceans was not predicted by freshwater discharge, but was related to lagged air temperature. These results represent the first quantitative link between environmental forcing and marine mammal mortality in the tropics, and form the basis of a predictive tool for managers to prepare responses to periods of elevated marine mammal mortality.

  15. Amiodarone-Induced Cirrhosis of Liver: What Predicts Mortality?

    PubMed Central

    Hussain, Nasir

    2013-01-01

    Introduction. Amiodarone has been used for more than 5 decades for the treatment of various tachyarrhythmias and previously for the treatment of refractory angina. There are multiple well-established side effects of amiodarone. However, amiodarone-induced cirrhosis (AIC) of liver is an underrecognized complication. Methods. A systematic search of Medline from January 1970 to November 2012 by using the following terms, amiodarone and cirrhosis, identified 37 reported cases of which 30 were used in this analysis. Patients were divided into 2 subsets, survivors versus nonsurvivors, at 5 months. Results. Aspartate aminotransferase was significantly lower (P = 0.03) in patients who survived at 5-months (mean 103.33 IU/L) compared to nonsurvivors (mean 216.88 IU/L). There was no statistical difference in the levels of prothrombin time, total bilirubin, alanine aminotransferase, alkaline phosphatase, gamma-glutamyl transpeptidase, cumulative dose, and latency period between the two groups. The prevalence of DM, HTN, HLD, CAD, and CHF was similar in the two groups. None of the above-mentioned variables could be identified as a predictor of survival at 5 months. Conclusion. AIC carries a mortality risk of 60% at 5 months once the diagnosis is established. Further prospective studies are needed to identify predictors of AIC and of mortality or survival in cases of AIC. PMID:23577267

  16. Predicting mortality in hospitalized patients with 2009 H1N1 influenza pneumonia.

    PubMed

    Riquelme, R; Jiménez, P; Videla, A J; Lopez, H; Chalmers, J; Singanayagam, A; Riquelme, M; Peyrani, P; Wiemken, T; Arbo, G; Benchetrit, G; Rioseco, M L; Ayesu, K; Klotchko, A; Marzoratti, L; Raya, M; Figueroa, S; Saavedra, F; Pryluka, D; Inzunza, C; Torres, A; Alvare, P; Fernandez, P; Barros, M; Gomez, Y; Contreras, C; Rello, J; Bordon, J; Feldman, C; Arnold, F; Nakamatsu, R; Riquelme, J; Blasi, F; Aliberti, S; Cosentini, R; Lopardo, G; Gnoni, M; Welte, T; Saad, M; Guardiola, J; Ramirez, J

    2011-04-01

    Community-acquired pneumonia (CAP) severity scores can identify patients at low risk for mortality who may be suitable for ambulatory care. Here, we follow the clinical course of hospitalized patients with CAP due to 2009 H1N1 influenza. To evaluate the role of CAP severity scores as predictors of mortality. This was a secondary data analysis of patients hospitalized with CAP due to 2009 H1N1 influenza confirmed by reverse transcriptase polymerase chain reaction enrolled in the CAPO (Community-Acquired Pneumonia Organization) international cohort study. CAP severity scores PSI (Pneumonia Severity Index), CURB-65 (confusion, urea, respiratory rate, blood pressure, age ≥ 65 years) and CRB-65 (confusion, respiratory rate, blood pressure, age ≥ 65 years) were calculated. Actual and predicted mortality rates were compared. A total of 37 predictor variables were evaluated to define those associated with mortality. Data from 250 patients with CAP due to 2009 H1N1 influenza were analyzed. Patients with low predicted mortality rates (0-1.5%) had actual mortality rates ranging from 2.6% to 17.5%. Obesity and wheezing were the only novel variables associated with mortality. The decision to hospitalize a patient with CAP due to 2009 H1N1 influenza should not be based on current CAP severity scores, as they underestimate mortality rates in a significant number of patients. Patients with obesity or wheezing should be considered at an increased risk for mortality.

  17. Hearing, mobility, and pain predict mortality: a longitudinal population-based study

    PubMed Central

    Feeny, David; Huguet, Nathalie; McFarland, Bentson H.; Kaplan, Mark S.; Orpana, Heather; Eckstrom, Elizabeth

    2012-01-01

    Objective Measures of health-related quality of life (HRQL), including the Health Utilities Index Mark 3 (HUI3) are predictive of mortality. HUI3 includes eight attributes, vision, hearing, speech, ambulation, dexterity, cognition, emotion, and pain and discomfort, with five or six levels per attribute that vary from no to severe disability. This study examined associations between individual HUI3 attributes and mortality. Study Design and Setting Baseline data and 12 years of follow-up data from a closed longitudinal cohort study, the 1994/95 Canadian National Population Health Survey, consisting of 12,375 women and men aged 18 and older. A priori hypotheses were that ambulation, cognition, emotion, and pain would predict mortality. Cox proportional hazards regression models were applied controlling for standard determinants of health and risk factors. Results Single-attribute utility scores for ambulation (hazard ratio [HR] = 0.10; 0.04–0.22), hearing (HR = 0.18; 0.06–0.57), and pain (HR = 0.53; 0.29–0.96) were statistically significantly associated with an increased risk of mortality; ambulation and hearing were predictive for the 60+ cohort. Conclusion Few studies have identified hearing or pain as risk factors for mortality. This study is innovative because it identifies specific components of HRQL that predict mortality. Further research is needed to understand better the mechanisms through which deficits in hearing and pain affect mortality risks. PMID:22521576

  18. A 6-Point TACS Score Predicts In-Hospital Mortality Following Total Anterior Circulation Stroke

    PubMed Central

    Wood, Adrian D; Gollop, Nicholas D; Bettencourt-Silva, Joao H; Clark, Allan B; Metcalf, Anthony K; Bowles, Kristian M; Flather, Marcus D; Potter, John F

    2016-01-01

    Background and Purpose Little is known about the factors associated with in-hospital mortality following total anterior circulation stroke (TACS). We examined the characteristics and comorbidity data for TACS patients in relation to in-hospital mortality with the aim of developing a simple clinical rule for predicting the acute mortality outcome in TACS. Methods A routine data registry of one regional hospital in the UK was analyzed. The subjects were 2,971 stroke patients with TACS (82% ischemic; median age=81 years, interquartile age range=74–86 years) admitted between 1996 and 2012. Uni- and multivariate regression models were used to estimate in-hospital mortality odds ratios for the study covariates. A 6-point TACS scoring system was developed from regression analyses to predict in-hospital mortality as the outcome. Results Factors associated with in-hospital mortality of TACS were male sex [adjusted odds ratio (AOR)=1.19], age (AOR=4.96 for ≥85 years vs. <65 years), hemorrhagic subtype (AOR=1.70), nonlateralization (AOR=1.75), prestroke disability (AOR=1.73 for moderate disability vs. no symptoms), and congestive heart failure (CHF) (AOR=1.61). Risk stratification using the 6-point TACS Score [T=type (hemorrhage=1 point) and territory (nonlateralization=1 point), A=age (65–84 years=1 point, ≥85 years=2 points), C=CHF (if present=1 point), S=status before stroke (prestroke modified Rankin Scale score of 4 or 5=1 point)] reliably predicted a mortality outcome: score=0, 29.4% mortality; score=1, 46.2% mortality [negative predictive value (NPV)=70.6%, positive predictive value (PPV)=46.2%]; score=2, 64.1% mortality (NPV=70.6, PPV=64.1%); score=3, 73.7% mortality (NPV=70.6%, PPV=73.7%); and score=4 or 5, 81.2% mortality (NPV=70.6%, PPV=81.2%). Conclusions We have identified the key determinants of in-hospital mortality following TACS and derived a 6-point TACS Score that can be used to predict the prognosis of particular patients. PMID:27819414

  19. Prediction of All-Cause Mortality Based on the Direct Measurement of Intrathoracic Impedance.

    PubMed

    Zile, Michael R; Sharma, Vinod; Johnson, James W; Warman, Eduardo N; Baicu, Catalin F; Bennett, Tom D

    2016-01-01

    Intrathoracic impedance-derived OptiVol fluid index calculated using implanted devices has been shown to predict mortality; direct measurements of impedance have not been examined. We hypothesized that baseline measured impedance predicts all-cause mortality; changes in measured impedance result in a change in the predicted mortality; and the prognostic value of measured impedance is additive to the calculated OptiVol fluid index. A retrospective analysis of 146,238 patients within the Medtronic CareLink database with implanted devices was performed. Baseline measured impedance was determined using daily values averaged from month 6 to 9 after implant and were used to divide patients into tertiles: group L = low impedance, ≤ 65 ohms; group M = medium impedance, 66 to 72 ohms; group H = high impedance, ≥ 73 ohms. Change in measured impedance was determined from values averaged from month 9 to 12 post implant compared with the 6- to 9-month values. OptiVol fluid index was calculated using published methods. All-cause mortality was assessed beginning 9 months post implant; changes in mortality was assessed beginning 12 months post implant. Baseline measured impedance predicted all-cause mortality; 5-year mortality for group L was 41%, M was 29%, and H was 25%, P < 0.001 among all groups. Changes in measured impedance resulted in a change in the predicted mortality; the prognostic value of measured impedance was additive to the OptiVol fluid index. Direct measurements of intrathoracic impedance using an implanted device can be used to stratify patients at varying mortality risk. © 2015 American Heart Association, Inc.

  20. Prediction of All-Cause Mortality Based on the Direct Measurement of Intrathoracic Impedance

    PubMed Central

    Zile, Michael R.; Sharma, Vinod; Johnson, James W.; Warman, Eduardo N.; Baicu, Catalin F.; Bennett, Tom D.

    2015-01-01

    Background Intrathoracic impedance-derived OptiVol fluid index calculated using implanted devices has been shown to predict mortality; direct measurements of impedance have not been examined. We hypothesized that baseline measured impedance predicts all-cause mortality; changes in measured impedance result in a change in the predicted mortality; and the prognostic value of measured impedance is additive to the calculated OptiVol fluid index. Methods and Results A retrospective analysis of 146,238 patients within the Medtronic CareLink data base with implanted devices was performed. Baseline measured impedance was determined using daily values averaged from month 6 to 9 post implant and were used to divide patients into tertiles; Group L= Low Impedance: ≤ 65 ohms, M= Medium Impedance: 66–72 ohms, H= High Impedance: ≥ 73 ohms. Change in measured impedance was determined from values averaged from month 9 to 12 post implant compared to the 6 to 9 month values. OptiVol fluid index was calculated using published methods. All-cause mortality was assessed beginning 9 months post implant; changes in mortality beginning 12 months post implant. Baseline measured impedance predicted all-cause mortality; 5 year mortality for group L was 41%, M was 29%, H was 25%, p < 0.001 among all groups. Changes in measured impedance resulted in a change in the predicted mortality; the prognostic value of measured impedance was additive to the OptiVol fluid index. Conclusions Direct measurements of intrathoracic impedance using an implanted device can be used to stratify patients at varying mortality risk. PMID:26699393

  1. 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.

  2. Development and validation of the Neonatal Mortality Score-9 Mexico to predict mortality in critically ill neonates.

    PubMed

    Márquez-González, Horacio; Jiménez-Báez, María Valeria; Muñoz-Ramírez, C Mireya; Yáñez-Gutiérrez, Lucelli; Huelgas-Plaza, Ana C; Almeida-Gutiérrez, Eduardo; Villa-Romero, Antonio Rafael

    2015-06-01

    Prognostic scales or scores are useful for physicians who work in neonatal intensive care units. There are several validated neonatal scores but they are mostly applicable to low birth weight infants. The aim of this study was to develop and validate a mortality prognostic score in newborn infants, that would include new prognostic outcome measures. The study was conducted in a mother and child hospital in the city of Mexico, part of the Instituto Mexicano del Seguro Social (Mexican Institute of Social Security). In the first phase of the study, a nested case-control study was designed (newborn infants admitted on the basis of severity criteria during the first day of life), in which a scale was identified and developed with gradual parameters of cumulative score consisting of nine independent outcome measures to predict death, as follows: weight, metabolic acidemia, lactate, PaO2/FiO2, p(A-a) O2, A/a, platelets and serum glucose.Validation was performed in a matched prospective cohort, using 7-day mortality as an endpoint. The initial cohort consisted of 424 newborn infants. Twenty-two cases and 132 controls were selected; and 9 outcome measures were identified, making up the scale named neonatal mortality score-9 Mexico. The validation cohort consisted of 227 newborn infants. Forty-four (19%) deaths were recorded, with an area under the curve (AUC) of 0.92. With a score between 16 and 18, an 85 (11-102) hazard ratio, 99% specificity, 71% positive predictive value and 90% negative predictive value were reported. Conclusions .The proposed scale is a reliable tool to predict severity in newborn infants.

  3. A simple score for predicting mortality in patients with pneumatosis intestinalis.

    PubMed

    Lee, Ho-Su; Cho, Young-Whan; Kim, Kyung-Jo; Lee, Jong Seok; Lee, Seung Soo; Yang, Suk-Kyun

    2014-04-01

    This study was conducted to identify simple computerized tomography (CT) and clinical predictors of mortality in patients with pneumatosis intestinalis (PI). Thus, the clinical characteristics and outcomes of PI were assessed and the predictors of mortality were identified. The medical records of 123 patients with PI were reviewed retrospectively. Multivariate logistic regression models were constructed to determine independent predictors of mortality. These data were used to develop a simple score that would predict mortality on the first and seventh day after diagnosis. The median age at diagnosis was 62 (range, 20-91) years. The most common cause of PI was mesenteric vascular ischemia (n=43, 35.0%). Twenty-nine (23.6%) disease-related deaths occurred during the index admission. Both signs of peritoneal irritation on physical examination and decreased or absent enhancement of the bowel wall were associated with increased mortality. If both factors were absent, the in-hospital mortalities on both the first and seventh days after the diagnosis of PI were less than 5%. However, if both factors were present, the in-hospital mortality was 57% on the first day and 59% on the seventh day. A simple and novel risk score that predicts mortality in patients with PI was proposed. Patients with both peritoneal irritation and decreased or absent enhancement of bowel wall on CT should be observed vigilantly and early intervention should be instituted. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  4. Predicting 30-day mortality of aortic valve replacement by the AVR score.

    PubMed

    Swinkels, B M; Vermeulen, F E E; Kelder, J C; van Boven, W J; Plokker, H W M; Ten Berg, J M

    2011-06-01

    The objective of this study is to develop a simple risk score to predict 30-day mortality of aortic valve replacement (AVR). In a development set of 673 consecutive patients who underwent AVR between 1990 and 1993, four independent predictors for 30-day mortality were identified: body mass index (BMI) ≥30, BMI <20, previous coronary artery bypass grafting (CABG) and recent myocardial infarction. Based on these predictors, a 30-day mortality risk score-the AVR score-was developed. The AVR score was validated on a validation set of 673 consecutive patients who underwent AVR almost two decennia later in the same hospital. Thirty-day mortality in the development set was ≤2% in the absence of any predictor (class I, low risk), 2-5% in the solitary presence of BMI ≥30 (class II, mild risk), 5-15% in the solitary presence of previous CABG or recent myocardial infarction (class III, moderate risk), and >15% in the solitary presence of BMI <20, or any combination of BMI ≥30, previous CABG or recent myocardial infarction (class IV, high risk). The AVR score correctly predicted 30-day mortality in the validation set: observed 30-day mortality in the validation set was 2.3% in 487 class I patients, 4.4% in 137 class II patients, 13.3% in 30 class III patients and 15.8% in 19 class IV patients. The AVR score is a simple risk score validated to predict 30-day mortality of AVR.

  5. 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.

  6. 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.

  7. 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

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

    PubMed Central

    2013-01-01

    Background 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. Methods 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. Results 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. Conclusion 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. PMID:24195451

  9. Broadly applicable risk stratification system for predicting duration of hospitalization and mortality.

    PubMed

    Sessler, Daniel I; Sigl, Jeffrey C; Manberg, Paul J; Kelley, Scott D; Schubert, Armin; Chamoun, Nassib G

    2010-11-01

    Hospitals are increasingly required to publicly report outcomes, yet performance is best interpreted in the context of population and procedural risk. We sought to develop a risk-adjustment method using administrative claims data to assess both national-level and hospital-specific performance. A total of 35,179,507 patient stay records from 2001-2006 Medicare Provider Analysis and Review (MEDPAR) files were randomly divided into development and validation sets. Risk stratification indices (RSIs) for length of stay and mortality endpoints were derived from aggregate risk associated with individual diagnostic and procedure codes. Performance of RSIs were tested prospectively on the validation database, as well as a single institution registry of 103,324 adult surgical patients, and compared with the Charlson comorbidity index, which was designed to predict 1-yr mortality. The primary outcome was the C statistic indicating the discriminatory power of alternative risk-adjustment methods for prediction of outcome measures. A single risk-stratification model predicted 30-day and 1-yr postdischarge mortality; separate risk-stratification models predicted length of stay and in-hospital mortality. The RSIs performed well on the national dataset (C statistics for median length of stay and 30-day mortality were 0.86 and 0.84). They performed significantly better than the Charlson comorbidity index on the Cleveland Clinic registry for all outcomes. The C statistics for the RSIs and Charlson comorbidity index were 0.89 versus 0.60 for median length of stay, 0.98 versus 0.65 for in-hospital mortality, 0.85 versus 0.76 for 30-day mortality, and 0.83 versus 0.77 for 1-yr mortality. Addition of demographic information only slightly improved performance of the RSI. RSI is a broadly applicable and robust system for assessing hospital length of stay and mortality for groups of surgical patients based solely on administrative data.

  10. A Satellite Mortality Study to Support Space Systems Lifetime Prediction

    NASA Technical Reports Server (NTRS)

    Fox, George; Salazar, Ronald; Habib-Agahi, Hamid; Dubos, Gregory

    2013-01-01

    Estimating the operational lifetime of satellites and spacecraft is a complex process. Operational lifetime can differ from mission design lifetime for a variety of reasons. Unexpected mortality can occur due to human errors in design and fabrication, to human errors in launch and operations, to random anomalies of hardware and software or even satellite function degradation or technology change, leading to unrealized economic or mission return. This study focuses on data collection of public information using, for the first time, a large, publically available dataset, and preliminary analysis of satellite lifetimes, both operational lifetime and design lifetime. The objective of this study is the illustration of the relationship of design life to actual lifetime for some representative classes of satellites and spacecraft. First, a Weibull and Exponential lifetime analysis comparison is performed on the ratio of mission operating lifetime to design life, accounting for terminated and ongoing missions. Next a Kaplan-Meier survivor function, standard practice for clinical trials analysis, is estimated from operating lifetime. Bootstrap resampling is used to provide uncertainty estimates of selected survival probabilities. This study highlights the need for more detailed databases and engineering reliability models of satellite lifetime that include satellite systems and subsystems, operations procedures and environmental characteristics to support the design of complex, multi-generation, long-lived space systems in Earth orbit.

  11. A Satellite Mortality Study to Support Space Systems Lifetime Prediction

    NASA Technical Reports Server (NTRS)

    Fox, George; Salazar, Ronald; Habib-Agahi, Hamid; Dubos, Gregory

    2013-01-01

    Estimating the operational lifetime of satellites and spacecraft is a complex process. Operational lifetime can differ from mission design lifetime for a variety of reasons. Unexpected mortality can occur due to human errors in design and fabrication, to human errors in launch and operations, to random anomalies of hardware and software or even satellite function degradation or technology change, leading to unrealized economic or mission return. This study focuses on data collection of public information using, for the first time, a large, publically available dataset, and preliminary analysis of satellite lifetimes, both operational lifetime and design lifetime. The objective of this study is the illustration of the relationship of design life to actual lifetime for some representative classes of satellites and spacecraft. First, a Weibull and Exponential lifetime analysis comparison is performed on the ratio of mission operating lifetime to design life, accounting for terminated and ongoing missions. Next a Kaplan-Meier survivor function, standard practice for clinical trials analysis, is estimated from operating lifetime. Bootstrap resampling is used to provide uncertainty estimates of selected survival probabilities. This study highlights the need for more detailed databases and engineering reliability models of satellite lifetime that include satellite systems and subsystems, operations procedures and environmental characteristics to support the design of complex, multi-generation, long-lived space systems in Earth orbit.

  12. A satellite mortality study to support space systems lifetime prediction

    NASA Astrophysics Data System (ADS)

    Fox, George; Salazar, Ronald; Habib-Agahi, Hamid; Dubos, Gregory F.

    Estimating the operational lifetime of satellites and spacecraft is a complex process. Operational lifetime can differ from mission design lifetime for a variety of reasons. Unexpected mortality can occur due to human errors in design and fabrication, to human errors in launch and operations, to random anomalies of hardware and software or even satellite function degradation or technology change, leading to unrealized economic or mission return. This study focuses on data collection of public information using, for the first time, a large, publically available dataset, and preliminary analysis of satellite lifetimes, both operational lifetime and design lifetime. The objective of this study is the illustration of the relationship of design life to actual lifetime for some representative classes of satellites and spacecraft. First, a Weibull and Exponential lifetime analysis comparison is performed on the ratio of mission operating lifetime to design life, accounting for terminated and ongoing missions. Next a Kaplan-Meier survivor function, standard practice for clinical trials analysis, is estimated from operating lifetime. Bootstrap resampling is used to provide uncertainty estimates of selected survival probabilities. This study highlights the need for more detailed databases and engineering reliability models of satellite lifetime that include satellite systems and subsystems, operations procedures and environmental characteristics to support the design of complex, multi-generation, long-lived space systems in Earth orbit.

  13. 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...

  14. 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...

  15. 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.

  16. 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. &...

  17. 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, S.; 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 forests1, 2and their associated climatic feedbacks3, 4. Our ability to accurately simulate drought-induced forest impacts remains highly uncertain5, 6 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.

  18. 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.

  19. Prediction of cardiovascular and all-cause mortality at 10 years in the hypertensive aged population.

    PubMed

    Huynh, Quan L; Reid, Christopher M; Chowdhury, Enayet K; Huq, Molla M; Billah, Baki; Wing, Lindon M H; Tonkin, Andrew M; Simons, Leon A; Nelson, Mark R

    2015-05-01

    We have previously developed a score for predicting cardiovascular events in the intermediate term in an elderly hypertensive population. In this study, we aimed to extend this work to predict 10-year cardiovascular and all-cause mortality in the hypertensive aged population. Ten-year follow-up data of 5,378 hypertensive participants in the Second Australian National Blood Pressure study who were aged 65-84 years at baseline (1995-2001) and without prior cardiovascular events were analyzed. By using bootstrap resampling variable selection methods and comparing the Akaike and Bayesian information criterion and C-indices of the potential models, optimal and parsimonious multivariable Cox proportional hazards models were developed to predict 10-year cardiovascular and all-cause mortality. The models were validated using bootstrap validation method internally and using the Dubbo Study dataset externally. The final model for cardiovascular mortality included detrimental (age, smoking, diabetes, waist-hip ratio, and disadvantaged socioeconomic status) and protective factors (female sex, alcohol consumption, and physical activity). The final model for all-cause mortality also included detrimental (age, smoking, random blood glucose, and disadvantaged socioeconomic status) and protective factors (female sex, alcohol consumption, body mass index, and statin use). Blood pressure did not appear in either model in this patient group. The C-statistics for internal validation were 0.707 (cardiovascular mortality) and 0.678 (all-cause mortality), and for external validation were 0.729 (cardiovascular mortality) and 0.772 (all-cause mortality). These algorithms allow reliable estimation of 10-year risk of cardiovascular and all-cause mortality for hypertensive aged individuals. © American Journal of Hypertension, Ltd 2014. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  20. Cytokine activation is predictive of mortality in Zambian patients with AIDS-related diarrhoea.

    PubMed

    Zulu, Isaac; Hassan, Ghaniah; Njobvu R N, Lungowe; Dhaliwal, Winnie; Sianongo, Sandie; Kelly, Paul

    2008-11-13

    Mortality in Zambian AIDS patients is high, especially in patients with diarrhoea, and there is still unacceptably high mortality in Zambian patients just starting anti-retroviral therapy. We set out to determine if high concentrations of serum cytokines correlate with mortality. Serum samples from 30 healthy controls (HIV seropositive and seronegative) and 50 patients with diarrhoea (20 of whom died within 6 weeks) were analysed. Concentrations of tumour necrosis factor receptor p55 (TNFR p55), macrophage migration inhibitory factor (MIF), interleukin (IL)-6, IL-12, interferon (IFN)-gamma and C-reactive protein (CRP) were measured by ELISA, and correlated with mortality after 6 weeks follow-up. Apart from IL-12, concentrations of all cytokines, TNFR p55 and CRP increased with worsening severity of disease, showing highly statistically significant trends. In a multivariable analysis high TNFR p55, IFN-gamma, CRP and low CD4 count (CD4 count <100) were predictive of mortality. Although nutritional status (assessed by body mass index, BMI) was predictive in univariate analysis, it was not an independent predictor in multivariate analysis. High serum concentrations of TNFR p55, IFN-gamma, CRP and low CD4 count correlated with disease severity and short-term mortality in HIV-infected Zambian adults with diarrhoea. These factors were better predictors of survival than BMI. Understanding the cause of TNFR p55, IFN-gamma and CRP elevation may be useful in development of interventions to reduce mortality in AIDS patients with chronic diarrhoea in Africa.

  1. Automated prediction of early blood transfusion and mortality in trauma patients.

    PubMed

    Mackenzie, Colin F; Wang, Yulei; Hu, Peter F; Chen, Shih-Yu; Chen, Hegang H; Hagegeorge, George; Stansbury, Lynn G; Shackelford, Stacy

    2014-06-01

    Prediction of blood transfusion needs and mortality for trauma patients in near real time is an unrealized goal. We hypothesized that analysis of pulse oximeter signals could predict blood transfusion and mortality as accurately as conventional vital signs (VSs). Continuous VS data were recorded for direct admission trauma patients with abnormal prehospital shock index (SI = heart rate [HR] / systolic blood pressure) greater than 0.62. Predictions of transfusion during the first 24 hours and in-hospital mortality using logistical regression models were compared with DeLong's method for areas under receiver operating characteristic curves (AUROCs) to determine the optimal combinations of prehospital SI and HR, continuous photoplethysmographic (PPG), oxygen saturation (SpO2), and HR-related features. We enrolled 556 patients; 37 received blood within 24 hours; 7 received more than 4 U of red blood cells in less than 4 hours or "massive transfusion" (MT); and 9 died. The first 15 minutes of VS signals, including prehospital HR plus continuous PPG, and SpO2 HR signal analysis best predicted transfusion at 1 hour to 3 hours, MT, and mortality (AUROC, 0.83; p < 0.03) and no differently (p = 0.32) from a model including blood pressure. Predictions of transfusion based on the first 15 minutes of data were no different using 30 minutes to 60 minutes of data collection. SI plus PPG and SpO2 signal analysis (AUROC, 0.82) predicted 1-hour to 3-hour transfusion, MT, and mortality no differently from pulse oximeter signals alone. Pulse oximeter features collected in the first 15 minutes of our trauma patient resuscitation cohort, without user input, predicted early MT and mortality in the critical first hours of care better than the currently used VS such as combinations of HR and systolic blood pressure or prehospital SI alone. Therapeutic/prognostic study, level II.

  2. Predicting mortality for paediatric inpatients where malaria is uncommon

    PubMed Central

    Clifton, Dana C; Ramadhani, Habib O; Msuya, Levina J; Njau, Boniface N; Kinabo, Grace D; Buchanan, Ann M; Crump, John A

    2012-01-01

    Objective As the proportion of children living low malaria transmission areas in sub-Saharan Africa increases, approaches for identifying non-malarial severe illness need to be evaluated to improve child outcomes. Design As a prospective cohort study, we identified febrile paediatric inpatients, recorded data using Integrated Management of Childhood Illness (IMCI) criteria, and collected diagnostic specimens. Setting Tertiary referral centre, northern Tanzania. Results Of 466 participants with known outcome, median age was 1.4 years (range 2 months–13.0 years), 200 (42.9%) were female, 11 (2.4%) had malaria and 34 (7.3%) died. Inpatient death was associated with: Capillary refill >3 s (OR 9.0, 95% CI 3.0 to 26.7), inability to breastfeed or drink (OR 8.9, 95% CI 4.0 to 19.6), stiff neck (OR 7.0, 95% CI 2.8 to 17.6), lethargy (OR 5.2, 95% CI 2.5 to 10.6), skin pinch >2 s (OR 4.8, 95% CI 1.9 to 12.3), respiratory difficulty (OR 4.0, 95% CI 1.9 to 8.2), generalised lymphadenopathy (OR 3.6, 95% CI 1.6 to 8.3) and oral candidiasis (OR 3.4, 95% CI 1.4 to 8.3). BCS <5 (OR 27.2, p<0.001) and severe wasting (OR 6.9, p<0.001) were independently associated with inpatient death. Conclusions In a low malaria transmission setting, IMCI criteria performed well for predicting inpatient death from non-malarial illness. Laboratory results were not as useful in predicting death, underscoring the importance of clinical examination in assessing prognosis. Healthcare workers should consider local malaria epidemiology as malaria over-diagnosis in children may delay potentially life-saving interventions in areas where malaria is uncommon. PMID:22872067

  3. A predictive model relating daily fluctuations in summer temperatures and mortality rates.

    PubMed

    Fouillet, Anne; Rey, Grégoire; Jougla, Eric; Frayssinet, Philippe; Bessemoulin, Pierre; Hémon, Denis

    2007-06-19

    In the context of climate change, an efficient alert system to prevent the risk associated with summer heat is necessary. The authors' objective was to describe the temperature-mortality relationship in France over a 29-year period and to define and validate a combination of temperature factors enabling optimum prediction of the daily fluctuations in summer mortality. The study addressed the daily mortality rates of subjects aged over 55 years, in France as a whole, from 1975 to 2003. The daily minimum and maximum temperatures consisted in the average values recorded by 97 meteorological stations. For each day, a cumulative variable for the maximum temperature over the preceding 10 days was defined. The mortality rate was modelled using a Poisson regression with over-dispersion and a first-order autoregressive structure and with control for long-term and within-summer seasonal trends. The lag effects of temperature were accounted for by including the preceding 5 days. A "backward" method was used to select the most significant climatic variables. The predictive performance of the model was assessed by comparing the observed and predicted daily mortality rates on a validation period (summer 2003), which was distinct from the calibration period (1975-2002) used to estimate the model. The temperature indicators explained 76% of the total over-dispersion. The greater part of the daily fluctuations in mortality was explained by the interaction between minimum and maximum temperatures, for a day t and the day preceding it. The prediction of mortality during extreme events was greatly improved by including the cumulative variables for maximum temperature, in interaction with the maximum temperatures. The correlation between the observed and estimated mortality ratios was 0.88 in the final model. Although France is a large country with geographic heterogeneity in both mortality and temperatures, a strong correlation between the daily fluctuations in mortality and the

  4. The MDS Mortality Risk Index: The evolution of a method for predicting 6-month mortality in nursing home residents

    PubMed Central

    2010-01-01

    Background Accurate prognosis is vital to the initiation of advance care planning particularly in a vulnerable, at risk population such as care home residents. The aim of this paper is to report on the revision and simplification of the MDS Mortality Rating Index (MMRI) for use in clinical practice to predict the probability of death in six months for care home residents. Methods The design was a secondary analysis of a US Minimum Data Set (MDS) for long term care residents using regression analysis to identify predictors of mortality within six months. Results Using twelve easy to collect items, the probability of mortality within six months was accurately predicted within the MDS database. The items are: admission to the care home within three months; lost weight unintentionally in past three months; renal failure; chronic heart failure; poor appetite; male; dehydrated; short of breath; active cancer diagnosis; age; deteriorated cognitive skills in past three months; activities of daily living score. Conclusion A lack of recognition of the proximity of death is often blamed for inappropriate admission to hospital at the end of an older person's life. An accurate prognosis for older adults living in a residential or nursing home can facilitate end of life decision making and planning for preferred place of care at the end of life. The original MMRI was derived and validated from a large database of long term care residents in the USA. However, this simplification of the revised index (MMRI-R) may provide a means for facilitating prognostication and end of life discussions for application outside the USA where the MDS is not in use. Prospective testing is needed to further test the accuracy of the MMRI-R and its application in the UK and other non-MDS settings. PMID:20637076

  5. Pulmonary Congestion Predicts Cardiac Events and Mortality in ESRD

    PubMed Central

    Torino, Claudia; Tripepi, Rocco; Tripepi, Giovanni; D’Arrigo, Graziella; Postorino, Maurizio; Gargani, Luna; Sicari, Rosa; Picano, Eugenio; Mallamaci, Francesca

    2013-01-01

    Pulmonary congestion is highly prevalent and often asymptomatic among patients with ESRD treated with hemodialysis, but whether its presence predicts clinical outcomes is unknown. Here, we tested the prognostic value of extravascular lung water measured by a simple, well validated ultrasound B-lines score (BL-US) in a multicenter study that enrolled 392 hemodialysis patients. We detected moderate-to-severe lung congestion in 45% and very severe congestion in 14% of the patients. Among those patients with moderate-to-severe lung congestion, 71% were asymptomatic or presented slight symptoms of heart failure. Compared with those patients having mild or no congestion, patients with very severe congestion had a 4.2-fold risk of death (HR=4.20, 95% CI=2.45–7.23) and a 3.2-fold risk of cardiac events (HR=3.20, 95% CI=1.75–5.88) adjusted for NYHA class and other risk factors. Including the degree of pulmonary congestion in the model significantly improved the risk reclassification for cardiac events by 10% (P<0.015). In summary, lung ultrasound can detect asymptomatic pulmonary congestion in hemodialysis patients, and the resulting BL-US score is a strong, independent predictor of death and cardiac events in this population. PMID:23449536

  6. Systematic review of mortality risk prediction models in the era of endovascular abdominal aortic aneurysm surgery.

    PubMed

    Lijftogt, N; Luijnenburg, T W F; Vahl, A C; Wilschut, E D; Leijdekkers, V J; Fiocco, M F; Wouters, M W J M; Hamming, J F

    2017-07-01

    The introduction of endovascular aneurysm repair (EVAR) has reduced perioperative mortality after abdominal aortic aneurysm (AAA) surgery. The objective of this systematic review was to assess existing mortality risk prediction models, and identify which are most useful for patients undergoing AAA repair by either EVAR or open surgical repair. A systematic search of the literature was conducted for perioperative mortality risk prediction models for patients with AAA published since 2006. PRISMA guidelines were used; quality was appraised, and data were extracted and interpreted following the CHARMS guidelines. Some 3903 studies were identified, of which 27 were selected. A total of 13 risk prediction models have been developed and directly validated. Most models were based on a UK or US population. The best performing models regarding both applicability and discrimination were the perioperative British Aneurysm Repair score (C-statistic 0·83) and the preoperative Vascular Biochemistry and Haematology Outcome Model (C-statistic 0·85), but both lacked substantial external validation. Mortality risk prediction in AAA surgery has been modelled extensively, but many of these models are weak methodologically and have highly variable performance across different populations. New models are unlikely to be helpful; instead case-mix correction should be modelled and adapted to the population of interest using the relevant mortality predictors. © 2017 BJS Society Ltd Published by John Wiley & Sons Ltd.

  7. Intensive Care Unit Admission Parameters Improve the Accuracy of Operative Mortality Predictive Models in Cardiac Surgery

    PubMed Central

    Ranucci, Marco; Ballotta, Andrea; Castelvecchio, Serenella; Baryshnikova, Ekaterina; Brozzi, Simonetta; Boncilli, Alessandra

    2010-01-01

    Background Operative mortality risk in cardiac surgery is usually assessed using preoperative risk models. However, intraoperative factors may change the risk profile of the patients, and parameters at the admission in the intensive care unit may be relevant in determining the operative mortality. This study investigates the association between a number of parameters at the admission in the intensive care unit and the operative mortality, and verifies the hypothesis that including these parameters into the preoperative risk models may increase the accuracy of prediction of the operative mortality. Methodology 929 adult patients who underwent cardiac surgery were admitted to the study. The preoperative risk profile was assessed using the logistic EuroSCORE and the ACEF score. A number of parameters recorded at the admission in the intensive care unit were explored for univariate and multivariable association with the operative mortality. Principal Findings A heart rate higher than 120 beats per minute and a blood lactate value higher than 4 mmol/L at the admission in the intensive care unit were independent predictors of operative mortality, with odds ratio of 6.7 and 13.4 respectively. Including these parameters into the logistic EuroSCORE and the ACEF score increased their accuracy (area under the curve 0.85 to 0.88 for the logistic EuroSCORE and 0.81 to 0.86 for the ACEF score). Conclusions A double-stage assessment of operative mortality risk provides a higher accuracy of the prediction. Elevated blood lactates and tachycardia reflect a condition of inadequate cardiac output. Their inclusion in the assessment of the severity of the clinical conditions after cardiac surgery may offer a useful tool to introduce more sophisticated hemodynamic monitoring techniques. Comparison between the predicted operative mortality risk before and after the operation may offer an assessment of the operative performance. PMID:21042411

  8. Preoperative risk score predicting 90-day mortality after liver resection in a population-based study.

    PubMed

    Chang, Chun-Ming; Yin, Wen-Yao; Su, Yu-Chieh; Wei, Chang-Kao; Lee, Cheng-Hung; Juang, Shiun-Yang; Chen, Yi-Ting; Chen, Jin-Cherng; Lee, Ching-Chih

    2014-09-01

    The impact of important preexisting comorbidities, such as liver and renal disease, on the outcome of liver resection remains unclear. Identification of patients at risk of mortality will aid in improving preoperative preparations. The purpose of this study is to develop and validate a population-based score based on available preoperative and predictable parameters predicting 90-day mortality after liver resection using data from a hepatitis endemic country.We identified 13,159 patients who underwent liver resection between 2002 and 2006 in the Taiwan National Health Insurance Research Database. In a randomly selected half of the total patients, multivariate logistic regression analysis was used to develop a prediction score for estimating the risk of 90-day mortality by patient demographics, preoperative liver disease and comorbidities, indication for surgery, and procedure type. The score was validated with the remaining half of the patients.Overall 90-day mortality was 3.9%. Predictive characteristics included in the model were age, preexisting cirrhosis-related complications, ischemic heart disease, heart failure, cerebrovascular disease, renal disease, malignancy, and procedure type. Four risk groups were stratified by mortality scores of 1.1%, 2.2%, 7.7%, and 15%. Preexisting renal disease and cirrhosis-related complications were the strongest predictors. The score discriminated well in both the derivation and validation sets with c-statistics of 0.75 and 0.75, respectively.This population-based score could identify patients at risk of 90-day mortality before liver resection. Preexisting renal disease and cirrhosis-related complications had the strongest influence on mortality. This score enables preoperative risk stratification, decision-making, quality assessment, and counseling for individual patients.

  9. Urinary cadmium levels predict mortality of patients with acute heart failure

    PubMed Central

    Hsu, Ching-Wei; Weng, Cheng-Hao; Lee, Cheng-Chia; Lin-Tan, Dan-Tzu; Chu, Pao-Hsien; Chen, Kuan-Hsing; Yen, Tzung-Hai; Huang, Wen-Hung

    2017-01-01

    Background Acute heart failure (AHF) is a serious condition that is associated with increased mortality in critically ill patients. Previous studies indicated that environmental exposure to cadmium increases mortality of general populations. However, the relationship of cadmium exposure and mortality is unclear for AHF patients. Materials and methods A total of 153 patients with AHF in intensive care units (ICUs) met the inclusion criteria and were followed up for 6 months. Demographic data, AHF etiology, hematological and biochemical data, and hospital mortality were recorded. The scores of two predictive systems (Sequential Organ Failure Assessment [SOFA], Acute Physiology and Chronic Health Evaluation II [APACHE II]) for mortality in critically ill patients were calculated, and urinary cadmium levels were recorded. Results At the end of the follow-up period, the mortality rate was 24.8%. The survivors (n=115) had higher urinary cadmium levels on day 1 (D1UCd) of ICU admission than non-survivors (n=38). A multiple linear regression analysis revealed a positive correlation between D1UCd and acute kidney injury, but a negative correlation between D1UCd and the level of serum albumin. A multivariate Cox analysis indicated that D1UCd was an independent predictor of mortality in AHF patients. For each increment of 1 μg of D1UCd, the hazard ratio for ICU mortality was 1.20 (95% confidence interval [CI]: 1.09–1.32, P<0.001). The area under the receiver operating characteristic curve for D1UCd was 0.84 (95% CI: 0.78–0.91), better than the values for the SOFA and APACHE II systems. Conclusion The D1UCd may serve as a single predictor of hospital mortality for AHF patients in the ICU. Because of the high mortality and smaller sample size, more investigations are required to confirm these observations and elucidate the underlying mechanisms. PMID:28392700

  10. Assessment of Euroscore and SAPS III as hospital mortality predicted in cardiac surgery.

    PubMed

    Mateos-Pañero, B; Sánchez-Casado, M; Castaño-Moreira, B; Paredes-Astillero, I; López-Almodóvar, L F; Bustos-Molina, F

    2017-05-01

    To perform an external validation of Euroscore I, Euroscore II and SAPS III. Retrospective cohort study over three years on all adult patients who underwent cardiac surgery. We reviewed the clinical data, following the patient until outcome or discharge from hospital (dead, alive). We computed the predicted mortality by Euroscore I (EI), II (EII) and SAPS III. The model validation was assessed by discrimination: area under curve ROC; and calibration (Hosmer-Lemeshow test). 866 patients were included. 62.5% of them male, with a median age of 69 years, 6.1% died during hospitalization. Predicted mortality: E I 7.94%, E II 3.54, SAPS III 12.1%. Area under curve (95% IC): E I 0.862 (0.812-0.912); E II 0.861 (0.806-0.915); SAPS III 0.692 (0.601-0.784). Hosmer-Lemeshow test: E I 14.0046 (P=.08164); E II 33.67 (P=.00004660); SAPS III 11.57 (P=.171). EII had good discrimination, but the calibration was not good with predicted mortality lower than the real mortality. E I showed the best discrimination with good calibration and a tendency to overestimate the mortality. SAPS III showed poor discrimination with good calibration and a tendency to greatly overestimate the predicted mortality. We saw no improvement in the predictive performance of EII over I and we reject the use of SAPS III in this kind of patient. Copyright © 2017 Sociedad Española de Anestesiología, Reanimación y Terapéutica del Dolor. Publicado por Elsevier España, S.L.U. All rights reserved.

  11. Mortality risk prediction models for coronary artery bypass graft surgery: current scenario and future direction.

    PubMed

    Karim, Mohammed N; Reid, Christopher M; Cochrane, Andrew; Tran, Lavinia; Alramadan, Mohammed; Hossain, Mohammed N; Billah, Baki

    2017-12-01

    Many risk prediction models are currently in use for predicting short-term mortality following coronary artery bypass graft (CABG) surgery. This review critically appraised the methods that were used for developing these models to assess their applicability in current practice setting as well as for the necessity of up-gradation. Medline via Ovid was searched for articles published between 1946 and 2016 and EMBASE via Ovid between 1974 and 2016 to identify risk prediction models for CABG. Article selection and data extraction was conducted using the CHARMS checklist for review of prediction model studies. Association between model development methods and model's discrimination was assessed using Kruskal-Wallis one-way analysis of variance and Mann-Whitney U-test. A total of 53 risk prediction models for short-term mortality following CABG were identified. The review found a wide variation in development methodology of risk prediction models in the field. Ambiguous predictor and outcome definition, sub-optimum sample size, inappropriate handling of missing data and inefficient predictor selection technique are major issues identified in the review. Quantitative synthesis in the review showed "missing value imputation" and "adopting machine learning algorithms" may result in better discrimination power of the models. There are aspects in current risk modeling, where there is room for improvement to reflect current clinical practice. Future risk modelling needs to adopt a standardized approach to defining both outcome and predictor variables, rational treatment of missing data and robust statistical techniques to enhance performance of the mortality risk prediction.

  12. Predicting all-cause mortality from basic physiology in the Framingham Heart Study.

    PubMed

    Zhang, William B; Pincus, Zachary

    2016-02-01

    Using longitudinal data from a cohort of 1349 participants in the Framingham Heart Study, we show that as early as 28-38 years of age, almost 10% of variation in future lifespan can be predicted from simple clinical parameters. Specifically, we found diastolic and systolic blood pressure, blood glucose, weight, and body mass index (BMI) to be relevant to lifespan. These and similar parameters have been well-characterized as risk factors in the relatively narrow context of cardiovascular disease and mortality in middle to old age. In contrast, we demonstrate here that such measures can be used to predict all-cause mortality from mid-adulthood onward. Further, we find that different clinical measurements are predictive of lifespan in different age regimes. Specifically, blood pressure and BMI are predictive of all-cause mortality from ages 35 to 60, while blood glucose is predictive from ages 57 to 73. Moreover, we find that several of these parameters are best considered as measures of a rate of 'damage accrual', such that total historical exposure, rather than current measurement values, is the most relevant risk factor (as with pack-years of cigarette smoking). In short, we show that simple physiological measurements have broader lifespan-predictive value than indicated by previous work and that incorporating information from multiple time points can significantly increase that predictive capacity. In general, our results apply equally to both men and women, although some differences exist.

  13. Predicting in-hospital mortality after hip fracture in elderly patients.

    PubMed

    Incalzi, R A; Capparella, O; Gemma, A; Camaioni, D; Sanguinetti, C; Carbonin, P U

    1994-01-01

    Ninety-seven patients aged 88 +/- 4 years (range, 80-97 years) (study group), and 74 aged 75 +/- 3 years (range, 70-79 years) (control group), were prospectively studied to investigate whether basic medical variables can predict in-hospital mortality in very old patients undergoing hip surgery because of femoral fracture. Mortality was 16.5% and 6.7% in the study and control groups, respectively (p = 0.054). In the study group, mortality was significantly correlated with age (p < 0.01), venous disorders (p < 0.05), malnutrition (p < 0.0001), duration of surgery (p < 0.006), and postoperative noninfectious complications (p < 0.005). In the control group, age was the only significant correlate of mortality (p < 0.005). After exclusion of surgery-related variables, the logistic regression analysis confirmed the predictive role of venous disorders (odds ratio = 2.04, confidence limits = 1.09-3.79) and malnutrition (odds ratio = 6.01, confidence limits = 1.85-19.47) but not of age in the study group. However, the goodness-of-fit test showed that the statistical model did not fit the data adequately. We conclude that in-hospital mortality after hip surgery in the very old cannot be predicted on the basis of underlying medical conditions alone.

  14. A combined comorbidity score predicted mortality in elderly patients better than existing scores

    PubMed Central

    Glynn, Robert J.; Avorn, Jerry; Levin, Raisa; Schneeweiss, Sebastian

    2010-01-01

    OBJECTIVE To develop and validate a single numeric comorbidity score for predicting short-and long-term mortality, by combining conditions in the Charlson and Elixhauser measures. STUDY DESIGN AND SETTING In a cohort of 120,679 Pennsylvania Medicare enrollees with drug coverage through a pharmacy assistance program, we developed a single numeric comorbidity score for predicting 1-year mortality, by combining the conditions in the Charlson and Elixhauser measures. We externally validated the combined score in a cohort of New Jersey Medicare enrollees, by comparing its performance to that of both component scores in predicting 1-year mortality, as well as 180-, 90-, and 30-day mortality. RESULTS C-statistics from logistic regression models including the combined score were higher than corresponding c-statistics from models including either the Romano implementation of the Charlson Index or the single numeric version of the Elixhauser system; c-statistics were 0.860 (95% confidence interval [CI]: 0.854, 0.866), 0.839 (95% CI: 0.836, 0.849), and 0.836 (95% CI: 0.834, 0.847), respectively, for the 30-day mortality outcome. The combined comorbidity score also yielded positive values for two recently proposed measures of reclassification. CONCLUSION In similar populations and data settings, the combined score may offer improvements in comorbidity summarization over existing scores. PMID:21208778

  15. 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.

  16. Developing a simple preinterventional score to predict hospital mortality in adult venovenous extracorporeal membrane oxygenation

    PubMed Central

    Cheng, Yu-Ting; Wu, Meng-Yu; Chang, Yu-Sheng; Huang, Chung-Chi; Lin, Pyng-Jing

    2016-01-01

    Abstract Despite gaining popularity, venovenous extracorporeal membrane oxygenation (VV-ECMO) remains a controversial therapy for acute respiratory failure (ARF) in adult patients due to its equivocal survival benefits. The study was aimed at identifying the preinterventional prognostic predictors of hospital mortality in adult VV-ECMO patients and developing a practical mortality prediction score to facilitate clinical decision-making. This retrospective study included 116 adult patients who received VV-ECMO for severe ARF in a tertiary referral center, from 2007 to 2015. The definition of severe ARF was PaO2/ FiO2 ratio < 70 mm Hg under advanced mechanical ventilation (MV). Preinterventional variables including demographic characteristics, ventilatory parameters, and severity of organ dysfunction were collected for analysis. The prognostic predictors of hospital mortality were generated with multivariate logistic regression and transformed into a scoring system. The discriminative power on hospital mortality of the scoring system was presented as the area under receiver operating characteristic curve (AUROC). The overall hospital mortality rate was 47% (n = 54). Pre-ECMO MV day > 4 (OR: 4.71; 95% CI: 1.98–11.23; P < 0.001), pre-ECMO sequential organ failure assessment (SOFA) score >9 (OR: 3.16; 95% CI: 1.36–7.36; P = 0.01), and immunocompromised status (OR: 2.91; 95% CI: 1.07–7.89; P = 0.04) were independent predictors of hospital mortality of adult VV-ECMO. A mortality prediction score comprising of the 3 binary predictors was developed and named VV-ECMO mortality score. The total score was estimated as follows: VV-ECMO mortality score = 2 × (Pre-ECMO MV day > 4) + 1 × (Pre-ECMO SOFA score >9) + 1 × (immunocompromised status). The AUROC of VV-ECMO mortality score was 0.76 (95% CI: 0.67–0.85; P < 0.001). The corresponding hospital mortality rates to VV-ECMO mortality scores were 18% (Score 0), 35% (Score 1), 56

  17. A Risk Model to Predict 90-Day Mortality among Patients Undergoing Hepatic Resection

    PubMed Central

    Hyder, Omar; Pulitano, Carlo; Firoozmand, Amin; Dodson, Rebecca; Wolfgang, Christopher L; Choti, Michael A; Aldrighetti, Luca; Pawlik, Timothy M

    2014-01-01

    BACKGROUND Reliable criteria to predict mortality after hepatectomy remain poorly defined. We sought to identify factors associated with 90-day mortality, as well as validate the “50-50” and peak bilirubin of >7 mg/dL prediction rules for mortality after liver resection. In addition, we propose a novel integer-based score for 90-day mortality using a large cohort of patients. STUDY DESIGN Data from 2,056 patients who underwent liver resection at 2 major hepatobiliary centers between 1990 and 2011 were identified. Perioperative laboratory data, as well as surgical and postoperative details, were analyzed to identify factors associated with liver-related 90-day death. RESULTS Indications for liver resection included colorectal metastasis (39%), hepatocellular carcinoma (19%), benign mass (17%), or noncolorectal metastasis (14%). Most patients had normal underlying liver parenchyma (71%) and resection involved ≥3 segments (36%). Overall morbidity and mortality were 19% and 2%, respectively. Only 1 patient fulfilled the 50-50 criteria; this patient survived and was discharged on day 8. Twenty patients had a peak bilirubin concentration >7 mg/dL and 5 died within 90 days; the sensitivity and spec-ificity of the >7-mg/dL rule were 25% and 99.3%, respectively, but overall accuracy was poor (area under the curve 0.574). Factors associated with 90-day mortality included international normalized ratio (odds ratio = 11.87), bilirubin (odds ratio = 1.16), and serum creatinine (odds ratio = 1.87) on postoperative day 3, as well as grade of postoperative complications (odds ratio = 5.08; all p < 0.05). Integer values were assigned to each factor to develop a model that predicted 90-day mortality (area under the curve 0.89). A score of ≥11 points had a sensitivity and specificity of 83.3% and 98.8%, respectively. CONCLUSIONS The 50-50 and bilirubin >7-mg/dL rules were not accurate in predicting 90-day mortality. Rather, a composite integer-based risk score based on

  18. A preoperative risk prediction model for 30-day mortality following cardiac surgery in an Australian cohort.

    PubMed

    Billah, Baki; Reid, Christopher Michael; Shardey, Gilbert C; Smith, Julian A

    2010-05-01

    Population-specific risk models are required to build consumer and provider confidence in clinical service delivery, particularly when the risks may be life-threatening. Cardiac surgery carries such risks. Currently, there is no model developed on the Australian cardiac surgery population and this article presents a novel risk prediction model for the Australian cohort with the aim to provide a guide for the surgeons and patients in assessing preoperative risk factors for cardiac surgery. This study aims to identify preoperative risk factors associated with 30-day mortality following cardiac surgery for an Australian population and to develop a preoperative model for risk prediction. All patients (23016) undergoing cardiac surgery between July 2001 and June 2008 recorded in the Australian Society of Cardiac and Thoracic Surgeons (ASCTS) database were included in this analysis. The data were divided randomly into model creation (13810, 60%) and model validation (9206, 40%) sets. The model was developed on the creation set and then validated on the validation set. The bootstrap sampling and automated variable selection methods were used to develop several candidate models. The final model was selected from this group of candidate models by using prediction mean square error (MSE) and Bayesian Information Criteria (BIC). Using a multifold validation, the average receiver operating characteristic (ROC), p-value for Hosmer-Lemeshow chi-squared test and MSE were obtained. Risk thresholds for low-, moderate- and high-risk patients were defined. The expected and observed mortality for various risk groups were compared. The multicollinearity and first-order interaction effect between clinically meaningful risk factors were investigated. A total of 23016 patients underwent cardiac surgery and the 30-day mortality rate was 3.2% (728 patients). Independent predictors of mortality in the model were: age, sex, the New York Heart Association (NYHA) class, urgency of procedure

  19. The Aristotle Comprehensive Complexity score predicts mortality and morbidity after congenital heart surgery.

    PubMed

    Bojan, Mirela; Gerelli, Sébastien; Gioanni, Simone; Pouard, Philippe; Vouhé, Pascal

    2011-04-01

    The Aristotle Comprehensive Complexity (ACC) score has been proposed for complexity adjustment in the analysis of outcome after congenital heart surgery. The score is the sum of the Aristotle Basic Complexity score, largely used but poorly related to mortality and morbidity, and of the Comprehensive Complexity items accounting for comorbidities and procedure-specific and anatomic variability. This study aims to demonstrate the ability of the ACC score to predict 30-day mortality and morbidity assessed by the length of the intensive care unit (ICU) stay. We retrospectively enrolled patients undergoing congenital heart surgery in our institution. We modeled the ACC score as a continuous variable, mortality as a binary variable, and length of ICU stay as a censored variable. For each mortality and morbidity model we performed internal validation by bootstrapping and assessed overall performance by R(2), calibration by the calibration slope, and discrimination by the c index. Among all 1,454 patients enrolled, 30-day mortality rate was 3.4% and median length of ICU stay was 3 days. The ACC score strongly related to mortality, but related to length of ICU stay only during the first postoperative week. For the mortality model, R(2) = 0.24, calibration slope = 0.98, c index = 0.86, and 95% confidence interval was 0.82 to 0.91. For the morbidity model, R(2) = 0.094, calibration slope = 0.94, c index = 0.64, and 95% confidence interval was 0.62 to 0.66. The ACC score predicts 30-day mortality and length of ICU stay during the first postoperative week. The score is an adequate tool for complexity adjustment in the analysis of outcome after congenital heart surgery. Copyright © 2011 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  20. Validated Risk Score for Predicting 6-Month Mortality in Infective Endocarditis.

    PubMed

    Park, Lawrence P; Chu, Vivian H; Peterson, Gail; Skoutelis, Athanasios; Lejko-Zupa, Tatjana; Bouza, Emilio; Tattevin, Pierre; Habib, Gilbert; Tan, Ren; Gonzalez, Javier; Altclas, Javier; Edathodu, Jameela; Fortes, Claudio Querido; Siciliano, Rinaldo Focaccia; Pachirat, Orathai; Kanj, Souha; Wang, Andrew

    2016-04-18

    Host factors and complications have been associated with higher mortality in infective endocarditis (IE). We sought to develop and validate a model of clinical characteristics to predict 6-month mortality in IE. Using a large multinational prospective registry of definite IE (International Collaboration on Endocarditis [ICE]-Prospective Cohort Study [PCS], 2000-2006, n=4049), a model to predict 6-month survival was developed by Cox proportional hazards modeling with inverse probability weighting for surgery treatment and was internally validated by the bootstrapping method. This model was externally validated in an independent prospective registry (ICE-PLUS, 2008-2012, n=1197). The 6-month mortality was 971 of 4049 (24.0%) in the ICE-PCS cohort and 342 of 1197 (28.6%) in the ICE-PLUS cohort. Surgery during the index hospitalization was performed in 48.1% and 54.0% of the cohorts, respectively. In the derivation model, variables related to host factors (age, dialysis), IE characteristics (prosthetic or nosocomial IE, causative organism, left-sided valve vegetation), and IE complications (severe heart failure, stroke, paravalvular complication, and persistent bacteremia) were independently associated with 6-month mortality, and surgery was associated with a lower risk of mortality (Harrell's C statistic 0.715). In the validation model, these variables had similar hazard ratios (Harrell's C statistic 0.682), with a similar, independent benefit of surgery (hazard ratio 0.74, 95% CI 0.62-0.89). A simplified risk model was developed by weight adjustment of these variables. Six-month mortality after IE is ≈25% and is predicted by host factors, IE characteristics, and IE complications. Surgery during the index hospitalization is associated with lower mortality but is performed less frequently in the highest risk patients. A simplified risk model may be used to identify specific risk subgroups in IE. © 2016 The Authors. Published on behalf of the American Heart

  1. Clinical characteristics and mortality risk prediction in critically ill children in Malaysian Borneo.

    PubMed

    Ganesan, Indra; Thomas, Terrence; Ng, Fon En; Soo, Thian Lian

    2014-05-01

    Mortality risk prediction scores are important for benchmarking quality of care in paediatric intensive care units (PICUs). We aimed to benchmark PICU outcomes at our hospital against the Pediatric Index of Mortality 2 (PIM2) mortality risk prediction score, and evaluate differences in diagnosis on admission and outcomes between Malaysian and immigrant children. We prospectively collected demographic and clinical data on paediatric medical patients admitted to the PICU of Sabah Women's and Children's Hospital in Kota Kinabalu, Sabah, Malaysia. The PIM2 risk score for mortality was tabulated. Of the 131 patients who met the inclusion criteria, data was available for 115 patients. The mean age of the patients was 2.6 ± 3.8 years, with 79% of the cohort aged less than five years. Patients were mainly of Kadazan (38%) and Bajau (30%) descent, and 26% of patients were non-citizens. Leading diagnoses on admission were respiratory (37%), neurological (18%) and infectious (17%) disorders. Out of the 29 patients who died, 23 (79%) were Malaysians and the main mortality diagnostic categories were respiratory disorder (22%), septicaemia (22%), haemato-oncological disease (17%) and neurological disorder (13%). Calculated standardised mortality ratios (SMRs) were not significantly > 1 for any patient category for variables such as age and admission diagnosis. However, infants less than two years old with comorbidities were significantly worse (SMR 2.61, 95% confidence interval 1.02-6.66). The patient profile at our centre was similar to that reported from other PICUs in Asia. The PIM2 score is a useful mortality risk prediction model for our population.

  2. 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.

  3. Gut Epithelial Barrier Dysfunction and Innate Immune Activation Predict Mortality in Treated HIV Infection

    PubMed Central

    Hunt, Peter W.; Sinclair, Elizabeth; Rodriguez, Benigno; Shive, Carey; Clagett, Brian; Funderburg, Nicholas; Robinson, Janet; Huang, Yong; Epling, Lorrie; Martin, Jeffrey N.; Deeks, Steven G.; Meinert, Curtis L.; Van Natta, Mark L.; Jabs, Douglas A.; Lederman, Michael M.

    2014-01-01

    Background. While inflammation predicts mortality in treated human immunodeficiency virus (HIV) infection, the prognostic significance of gut barrier dysfunction and phenotypic T-cell markers remains unclear. Methods. We assessed immunologic predictors of mortality in a case-control study within the Longitudinal Study of the Ocular Complications of AIDS (LSOCA), using conditional logistic regression. Sixty-four case patients who died within 12 months of treatment-mediated viral suppression were each matched to 2 control individuals (total number of controls, 128) by duration of antiretroviral therapy–mediated viral suppression, nadir CD4+ T-cell count, age, sex, and prior cytomegalovirus (CMV) retinitis. A similar secondary analysis was conducted in the SCOPE cohort, which had participants with less advanced immunodeficiency. Results. Plasma gut epithelial barrier integrity markers (intestinal fatty acid binding protein and zonulin-1 levels), soluble CD14 level, kynurenine/tryptophan ratio, soluble tumor necrosis factor receptor 1 level, high-sensitivity C-reactive protein level, and D-dimer level all strongly predicted mortality, even after adjustment for proximal CD4+ T-cell count (all P ≤ .001). A higher percentage of CD38+HLA-DR+ cells in the CD8+ T-cell population was a predictor of mortality before (P = .031) but not after (P = .10) adjustment for proximal CD4+ T-cell count. Frequencies of senescent (defined as CD28−CD57+ cells), exhausted (defined as PD1+ cells), naive, and CMV-specific T cells did not predict mortality. Conclusions. Gut epithelial barrier dysfunction, innate immune activation, inflammation, and coagulation—but not T-cell activation, senescence, and exhaustion—independently predict mortality in individuals with treated HIV infection with a history of AIDS and are viable targets for interventions. PMID:24755434

  4. 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.

  5. Predicting postfire Douglas-fir beetle attacks and tree mortality in the northern Rocky Mountains

    Treesearch

    Sharon Hood; Barbara Bentz

    2007-01-01

    Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) were monitored for 4 years following three wildfires. Logistic regression analyses were used to develop models predicting the probability of attack by Douglas-fir beetle (Dendroctonus pseudotsugae Hopkins, 1905) and the probability of Douglas-fir mortality within 4 years following...

  6. Prediction of growth and mortality of Oregon White Oak in the Pacific Northwest.

    Treesearch

    Peter J. Gould; David D. Marshall; Constance A. Harrington

    2008-01-01

    We developed new equations to predict Oregon white oak (Quercus garryana Dougl. ex Hook.) development with ORGANON, a stand-development model that is widely used in the Pacific Northwest. Tree size, competitive status, crown ratio, and site productivity were statistically significant predictors of growth and mortality. Three scenarios were...

  7. Osteoprotegerin independently predicts mortality in patients with stable coronary artery disease: the CLARICOR trial.

    PubMed

    Bjerre, Mette; Hilden, Jørgen; Kastrup, Jens; Skoog, Maria; Hansen, Jørgen F; Kolmos, Hans J; Jensen, Gorm B; Kjøller, Erik; Winkel, Per; Flyvbjerg, Allan; Gluud, Christian

    2014-11-01

    To elucidate the prognostic power of serum osteoprotegerin (OPG) in patients with stable coronary artery disease (CAD). Serum OPG levels were measured in the CLARICOR trial cohort of 4063 patients with stable CAD on blood samples drawn at randomization. The follow-up was 2.6 years for detailed cardiovascular events and 6 years for all-cause mortality. OPG levels were significantly increased in non-survivors (21%) compared to survivors (median [quartiles] 2092 ng/L [1636; 2800] compared to 1695 ng/L [1322; 2193, p < 0.0001]). The 2.6-year follow-up showed that OPG adds to the prediction of both cardiovascular and all-cause mortality in combination with clinical risk factors (HR [one log10 unit increase] 6.1 [95% CI 2.4-15.6, p = 0.0001]) and HR 6.5 [95% CI 3.4-12.5, p < 0.0001], respectively). Similar, in the 6-year follow-up, OPG was found to be a strong predictor for all-cause mortality. Importantly, OPG remained an independent predictor of mortality even after adjustment for both clinical and conventional cardiovascular risk markers (HR 2.5 [95% CI 1.6-3.9, p < 0.0001]). Serum OPG has a long-lasting independent predictive power as to all-cause mortality and cardiovascular death in patients with stable CAD.

  8. Coronary flow reserve assessed by myocardial contrast echocardiography predicts mortality in patients with heart failure.

    PubMed

    Anantharam, Brijesh; Janardhanan, Raj; Hayat, Sajad; Hickman, Michael; Chahal, Navtej; Bassett, Paul; Senior, Roxy

    2011-01-01

    the aim of the study was to assess whether myocardial contrast echocardiography (MCE) can predict mortality in patients with heart failure. Myocardial viability, ischaemia, and coronary flow reserve (CFR) are predictors of mortality in patients with heart failure. MCE can assess myocardial viability, ischaemia, and CFR at the bedside. However, its prognostic value is unknown in patients with heart failure. eighty-seven patients (age: 68 ± 10 years, 62% male) with heart failure [left ventricular ejection fraction (LVEF): 35% ± 13] underwent low-power intermittent MCE at rest and 2 min after dipyridamole infusion. Resting and stress perfusion score index were derived qualitatively. CFR (MBF at stress/MBF at rest) was calculated by a quantitative method. All patients underwent coronary arteriography. Patients were followed up for mortality. Of the 87 patients, 43 (49%) patients had coronary artery disease. There were 28 (32%) deaths during a mean follow-up of 4.1 ± 1.7 years. Type 2 diabetes [P = 0.02, hazard ratios (HR) 2.43, confidence interval (CI) 1.13-5.22] and CFR (P = 0.001, HR 0.15, CI 0.05-0.45) were independent predictors of mortality. A CFR ≤ 1.5 had a significantly (P < 0.0001) higher mortality of 49 vs. 10% in patients with CFR > 1.5 over the 4 year follow-up period. CFR determined by MCE is a powerful predictor of mortality in patients with heart failure.

  9. Nutritional risk screening 2002 and ASA score predict mortality after elective liver resection for malignancy

    PubMed Central

    Ferreira, Nelio

    2017-01-01

    Introduction The aim of the study was to evaluate whether Nutritional risk screening 2002 (NRS 2002) at hospital admission may predict postoperative mortality and complications within 90 days after elective liver resection for malignancy. Material and methods A retrospective cohort study of a prospective database was performed. Two-hundred and three patients with elective liver resection for malignancy between 9 November 2007 and 27 May 2014 were included. Clinical data, NRS 2002, surgical procedures and histology were recorded. The primary endpoint was 90-day mortality. Complications were registered within 90 days postoperatively according to the Clavien-Dindo classification. Results The 90-day mortality was 5.9% and the overall complication rate was 59.1%. Multivariate analysis identified NRS 2002 score ≥ 4 (odds ratio (OR) = 9.24; p = 0.005) and American Society of Anesthesiologists (ASA) score ≥ 3 (OR = 6.20; p = 0.009) as predictors of 90-day mortality. The 90-day mortality was 27.6% (8/29) for patients with both risk factors (NRS 2002 score ≥ 4 and ASA score ≥ 3) vs. 2.3% (4/174) for patients without or with only one risk factor (p < 0.001). Conclusions In the present study NRS 2002 score ≥ 4 and ASA score ≥ 3 were predictors of 90-day mortality after elective liver resection for malignancy. PMID:28261289

  10. Nutritional risk screening 2002 and ASA score predict mortality after elective liver resection for malignancy.

    PubMed

    Zacharias, Thomas; Ferreira, Nelio

    2017-03-01

    The aim of the study was to evaluate whether Nutritional risk screening 2002 (NRS 2002) at hospital admission may predict postoperative mortality and complications within 90 days after elective liver resection for malignancy. A retrospective cohort study of a prospective database was performed. Two-hundred and three patients with elective liver resection for malignancy between 9 November 2007 and 27 May 2014 were included. Clinical data, NRS 2002, surgical procedures and histology were recorded. The primary endpoint was 90-day mortality. Complications were registered within 90 days postoperatively according to the Clavien-Dindo classification. The 90-day mortality was 5.9% and the overall complication rate was 59.1%. Multivariate analysis identified NRS 2002 score ≥ 4 (odds ratio (OR) = 9.24; p = 0.005) and American Society of Anesthesiologists (ASA) score ≥ 3 (OR = 6.20; p = 0.009) as predictors of 90-day mortality. The 90-day mortality was 27.6% (8/29) for patients with both risk factors (NRS 2002 score ≥ 4 and ASA score ≥ 3) vs. 2.3% (4/174) for patients without or with only one risk factor (p < 0.001). In the present study NRS 2002 score ≥ 4 and ASA score ≥ 3 were predictors of 90-day mortality after elective liver resection for malignancy.

  11. Growth rate predicts mortality of Abies concolor in both burned and unburned stands

    USGS Publications Warehouse

    van Mantgem, Phillip J.; Stephenson, Nathan L.; Mutch, Linda S.; Johnson, Veronica G.; Esperanza, Annie M.; Parsons, David J.

    2003-01-01

    Tree mortality is often the result of both long-term and short-term stress. Growth rate, an indicator of long-term stress, is often used to estimate probability of death in unburned stands. In contrast, probability of death in burned stands is modeled as a function of short-term disturbance severity. We sought to narrow this conceptual gap by determining (i) whether growth rate, in addition to crown scorch, is a predictor of mortality in burned stands and (ii) whether a single, simple model could predict tree death in both burned and unburned stands. Observations of 2622 unburned and 688 burned Abies concolor (Gord. & Glend.) Lindl. (white fir) in the Sierra Nevada of California, U.S.A., indicated that growth rate was a significant predictor of mortality in the unburned stands, while both crown scorch and radial growth were significant predictors of mortality in the burned stands. Applying the burned stand model to unburned stands resulted in an overestimation of the unburned stand mortality rate. While failing to create a general model of tree death for A. concolor, our findings underscore the idea that similar processes may affect mortality in disturbed and undisturbed stands.

  12. Morbidity and mortality predictivity of nutritional assessment tools in the postoperative care unit.

    PubMed

    Özbilgin, Şule; Hanc, Volkan; Ömür, Dilek; Özbilgin, Mücahit; Tosun, Mine; Yurtlu, Serhan; Küçükgüçlü, Semih; Arkan, Atalay

    2016-10-01

    The aim was to evaluate the nutritional situation of patients admitted to the Postoperative Acute Care Unit using classic methods of objective anthropometry, systemic evaluation methods, and Nutrition Risk in Critically Ill (NUTRIC) score, and to compare them as a predictor of morbidity and mortality.At admission to the postoperative care unit, patients undergoing various surgeries were assessed for the following items: Subjective Global Assessment (SGA), Nutritional Risk Index (NRI), Nutritional Risk Screening (NRS)-2002, Mini Nutritional Assessment (MNA), Charlson comorbidity index (CCI), and NUTRIC score, anthropometric measurements, serum total protein, serum albumin, and lymphocyte count. Patients were monitored for postoperative complications until death or discharge. Correlation of complications with these parameters was also analyzed.A total of 152 patients were included in the study. In this study a positive correlation was determined between mortality and NRS-2002, SGA, CCI, Acute Physiology and Chronic Health Evaluation , Sepsis-related Organ Failure Assessment, and NUTRIC score, whereas a negative correlation was determined between mortality and NRI. There was a correlation between NUTRIC score and pneumonia, development of atrial fibrillation, delirium, renal failure, inotrope use, and duration of mechanical ventilation. In our study group of postoperative patients, MNA had no predictive properties for any complication, whereas SGA had no predictive properties for any complications other than duration of hospital stay and mortality.The NUTRIC score is an important indicator of mortality and morbidity in postoperative surgical patients. NRI correlated with many postoperative complications, and though SGA and NRS were correlated with mortality, they were not correlated with the majority of complications. MNA was determined not to have any correlation with any complication, mortality, and duration of hospital stay in our patient group.

  13. Cardiac Biomarkers Predict 1-Year Mortality in Elderly Patients Undergoing Hip Fracture Surgery.

    PubMed

    Katsanos, Spyridon; Mavrogenis, Andreas F; Kafkas, Nikolaos; Sardu, Celestino; Kamperidis, Vasileios; Katsanou, Panagiota; Farmakis, Dimitrios; Parissis, John

    2017-05-01

    This prospective study included 152 elderly patients (mean age, 80 years; range, 72-88 years) with a hip fracture treated surgically. Comorbidities were evaluated, and B-type natriuretic peptide was measured at baseline and at postoperative days 4 and 5 in addition to troponin I. Major cardiac events were recorded, and 1-year mortality was assessed. Comorbidity models with the important multivariate predictors of 1-year mortality were analyzed. Overall, 9 patients (6%) experienced major cardiac events postoperatively during their hospitalization. Three patients (2%) died postoperatively, at days 5, 7, and 10, from autopsy-confirmed myocardial infarction. Three patients (2%) experienced a nonfatal myocardial infarction, and 3 patients (2%) experienced acute heart failure. At 1-year follow-up, 37 patients (24%) had died. Age older than 80 years (P=.000), renal failure (P=.016), cardiovascular disease (P=.003), respiratory disease (P=.010), Parkinson disease (P=.024), and dementia (P=.000) were univariate predictors of 1-year mortality. However, in the multivariate model, only age older than 80 years (P=.000) and dementia (P=.024) were important predictors of 1-year mortality. In all comorbidity models, age older than 80 years and dementia were important predictors of 1-year mortality. Postoperative increase in B-type natriuretic peptide was the most important predictor of 1-year mortality. Receiver operating characteristic curve analysis showed a threshold of 90 ng/mL of preoperative B-type natriuretic peptide (area under the curve=0.773, 95% confidence interval, 0.691-0.855, P<.001) had 82% sensitivity and 62% specificity to predict 1-year mortality. Similarly, a threshold of 190 ng/mL of postoperative B-type natriuretic peptide (area under the curve=0.753, 95% confidence interval, 0.662-0.844, P<.001) had 70% sensitivity and 77% specificity to predict the study endpoint. [Orthopedics. 2017; 40(3):e417-e424.]. Copyright 2017, SLACK Incorporated.

  14. A multiparameter model predicting in-hospital mortality in malignant cerebral infarction.

    PubMed

    Chen, Chien-Fu; Lin, Ruey-Tay; Lin, Hsiu-Fen; Chao, A-Ching

    2017-07-01

    The early identification of patients with large hemisphere infarctions (LHIs) at risk of fatal brain edema may result in better outcomes. A quantitative model using parameters obtained at admission may be a predictor of in-hospital mortality from LHI.This prospective study enrolled all patients with LHI involving >50% of the middle cerebral artery (MCA) admitted to our neurological intensive care unit within 48 hours of symptom onset. Early clinical and radiographic parameters and the baseline CHADS2 score (congestive heart failure, hypertension, age ≥ 75 years, diabetes mellitus, stroke [double weight]) were analyzed regarding their ability to predict patient outcomes.Seventy-seven patients with LHIs were identified, 33 (42.9%) with complete MCA infarction (CMCA), and 44 (57.1%) with incomplete MCA infarction (IMCA). The predictors of CMCA score included: >1/3 early hypodensity in computed tomography findings, hyperdense MCA sign, brain edema, initial National Institutes of Health Stroke Scale (NIHSS) score ≥17, and stroke in progression during the 1st 5 days of admission. The cutoff CMCA score was 2, with a sensitivity of 81.8% and specificity of 70.5%. Mortality score 1, used for predicting in-hospital mortality from LHI, included CMCA and CHADS2 scores ≥4 (sensitivity 100.0%, specificity 57.4%), and mortality score 2 included CMCA and CHADS2 scores ≥4, and NIHSS score ≥26, during the 1st 5 days (sensitivity 100.0%, specificity 91.7%).Patients qualifying for a mortality score of 2 were at high-risk of in-hospital mortality from LHI. These findings may aid in identifying patients who may benefit from invasive therapeutic strategies, and in better describing the characteristics of those at risk of mortality.

  15. 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.

  16. Morbidity and mortality predictivity of nutritional assessment tools in the postoperative care unit

    PubMed Central

    Özbilgin, Şule; Hancı, Volkan; Ömür, Dilek; Özbilgin, Mücahit; Tosun, Mine; Yurtlu, Serhan; Küçükgüçlü, Semih; Arkan, Atalay

    2016-01-01

    Abstract The aim was to evaluate the nutritional situation of patients admitted to the Postoperative Acute Care Unit using classic methods of objective anthropometry, systemic evaluation methods, and Nutrition Risk in Critically Ill (NUTRIC) score, and to compare them as a predictor of morbidity and mortality. At admission to the postoperative care unit, patients undergoing various surgeries were assessed for the following items: Subjective Global Assessment (SGA), Nutritional Risk Index (NRI), Nutritional Risk Screening (NRS)-2002, Mini Nutritional Assessment (MNA), Charlson comorbidity index (CCI), and NUTRIC score, anthropometric measurements, serum total protein, serum albumin, and lymphocyte count. Patients were monitored for postoperative complications until death or discharge. Correlation of complications with these parameters was also analyzed. A total of 152 patients were included in the study. In this study a positive correlation was determined between mortality and NRS-2002, SGA, CCI, Acute Physiology and Chronic Health Evaluation , Sepsis-related Organ Failure Assessment, and NUTRIC score, whereas a negative correlation was determined between mortality and NRI. There was a correlation between NUTRIC score and pneumonia, development of atrial fibrillation, delirium, renal failure, inotrope use, and duration of mechanical ventilation. In our study group of postoperative patients, MNA had no predictive properties for any complication, whereas SGA had no predictive properties for any complications other than duration of hospital stay and mortality. The NUTRIC score is an important indicator of mortality and morbidity in postoperative surgical patients. NRI correlated with many postoperative complications, and though SGA and NRS were correlated with mortality, they were not correlated with the majority of complications. MNA was determined not to have any correlation with any complication, mortality, and duration of hospital stay in our patient group. PMID

  17. Body fat distribution is more predictive of all-cause mortality than overall adiposity.

    PubMed

    Lee, Sung Woo; Son, Jee Young; Kim, Jeong Min; Hwang, Seung-Sik; Han, Jin Suk; Heo, Nam Ju

    2017-07-03

    The relationship between directly measured body fat and all-cause mortality has been rarely studied. The aim of this study was to evaluate the predictive significance of computed tomography (CT)-measured body fat, including both visceral fat area (VFA) and subcutaneous fat area (SFA), for mortality. The study included 36 656 participants who underwent abdominal CT as part of a health check-up at a single university-affiliated healthcare center in 2007 to 2015. Of those, 32 593 participants with data regarding vital status as of May 2016 were included in the final analysis. The main factors evaluated were VFA, SFA and visceral-to-subcutaneous fat area ratio (VSR), and the primary outcome was all-cause mortality. There were 253 deaths during a mean follow-up of 5.7 years. Increased SFA was associated with decreased all-cause mortality, whereas an increased VFA and VSR were related to increased all-cause mortality. Compared with the predictive power of body mass index (BMI), SFA and VSR showed a larger area under the curve than did BMI. In Kaplan-Meier survival curve analysis, increased SFA and VSR were associated with decreased and increased hazard of all-cause death, respectively. However, in multivariate Cox proportional hazard regression analysis, only VSR was independently associated with all-cause mortality. Moreover, this relationship was paralleled by the harmful impact of increased VSR on metabolic profiles. Increased VSR was an independent predictor of all-cause mortality. This suggests that the location of fat deposits may be more important than the actual amount of body fat. © 2017 John Wiley & Sons Ltd.

  18. Does life satisfaction predict five-year mortality in community-living older adults?

    PubMed

    St John, Philip D; Mackenzie, Corey; Menec, Verena

    2015-01-01

    Depression and depressive symptoms predict death, but it is less clear if more general measures of life satisfaction (LS) predict death. Our objectives were to determine: (1) if LS predicts mortality over a five-year period in community-living older adults; and (2) which aspects of LS predict death. 1751 adults over the age of 65 who were living in the community were sampled from a representative population sampling frame in 1991/1992 and followed five years later. Age, gender, and education were self-reported. An index of multimorbidity and the Older American Resource Survey measured health and functional status, and the Terrible-Delightful Scale assessed overall LS as well as satisfaction with: health, finances, family, friends, housing, recreation, self-esteem, religion, and transportation. Cox proportional hazards models examined the influence of LS on time to death. 417 participants died during the five-year study period. Overall LS and all aspects of LS except finances, religion, and self-esteem predicted death in unadjusted analyses. In fully adjusted analyses, LS with health, housing, and recreation predicted death. Other aspects of LS did not predict death after accounting for functional status and multimorbidity. LS predicted death, but certain aspects of LS are more strongly associated with death. The effect of LS is complex and may be mediated or confounded by health and functional status. It is important to consider different domains of LS when considering the impact of this important emotional indicator on mortality among older adults.

  19. Life span decrements in fluid intelligence and processing speed predict mortality risk.

    PubMed

    Aichele, Stephen; Rabbitt, Patrick; Ghisletta, Paolo

    2015-09-01

    We examined life span changes in 5 domains of cognitive performance as predictive of mortality risk. Data came from the Manchester Longitudinal Study of Cognition, a 20-plus-year investigation of 6,203 individuals ages 42-97 years. Cognitive domains were general crystallized intelligence, general fluid intelligence, verbal memory, visuospatial memory, and processing speed. Life span decrements were evident across these domains, controlling for baseline performance at age 70 and adjusting for retest effects. Survival analyses stratified by sex and conducted independently by cognitive domain showed that lower baseline performance levels in all domains-and larger life span decrements in general fluid intelligence and processing speed-were predictive of increased mortality risk for both women and men. Critically, analyses of the combined predictive power of cognitive performance variables showed that baseline levels of processing speed (in women) and general fluid intelligence (in men), and decrements in processing speed (in women and in men) and general fluid intelligence (in women), accounted for most of the explained variation in mortality risk. In light of recent evidence from brain-imaging studies, we speculate that cognitive abilities closely linked to cerebral white matter integrity (such as processing speed and general fluid intelligence) may represent particularly sensitive markers of mortality risk. In addition, we presume that greater complexity in cognition-survival associations observed in women (in analyses incorporating all cognitive predictors) may be a consequence of longer and more variable cognitive declines in women relative to men.

  20. QRS fragmentation is superior to QRS duration in predicting mortality in adults with tetralogy of Fallot.

    PubMed

    Bokma, Jouke P; Winter, Michiel M; Vehmeijer, Jim T; Vliegen, Hubert W; van Dijk, Arie P; van Melle, Joost P; Meijboom, Folkert J; Post, Martijn C; Zwinderman, Aeilko H; Mulder, Barbara J M; Bouma, Berto J

    2017-05-01

    Although QRS duration >180 ms has prognostic value in adults with tetralogy of Fallot (TOF), its sensitivity to predict mortality is low. Fragmented QRS complexes, a simple measurement on ECG, are related to myocardial fibrosis and dysfunction in patients with TOF. Our objective was to determine whether QRS fragmentation predicts major outcomes in TOF. This multicentre study included adult patients with TOF from a prospective registry. Notches in the QRS complex in ≥2 contiguous leads on a 12-lead ECG, not related to bundle branch block, were defined as QRS fragmentation, which was classified as none, moderate (≤4 leads) or severe (≥5 leads). The primary and secondary outcomes were all-cause mortality and clinical ventricular arrhythmia, respectively. A total of 794 adult patients with TOF (median age 27 years, 55% male; 52% no QRS fragmentation, 32% moderate, 16% severe) were included. During long-term (median 10.4 years) follow-up, 46 (6%) patients died and 35 (4%) patients had ventricular arrhythmias. Overall, 10-year survival was 98% in patients without fragmented QRS complexes, 93% in patients with moderate QRS fragmentation and 81% in patients with severe QRS fragmentation. In multivariable Cox hazards regression analysis, extent of QRS fragmentation (HR: 2.24/class, 95% CI 1.48 to 3.40, p<0.001) remained independently predictive for mortality, whereas QRS duration was not predictive (p=0.85). The extent of QRS fragmentation was also independently predictive for ventricular arrhythmia (HR: 2.00/class, 95% CI 1.26 to 3.16, p=0.003). The extent of QRS fragmentation is superior to QRS duration in predicting mortality in adult patients with TOF and may be used in risk stratification. 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/.

  1. 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.

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

    PubMed Central

    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. PMID:27414408

  3. A Severe Sepsis Mortality Prediction Model and Score for Use With Administrative Data.

    PubMed

    Ford, Dee W; Goodwin, Andrew J; Simpson, Annie N; Johnson, Emily; Nadig, Nandita; Simpson, Kit N

    2016-02-01

    Administrative data are used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score. Retrospective cohort study using 2012 administrative data from five U.S. states. Three cohorts of patients with severe sepsis were created: 1) International Classification of Diseases, 9th Revision, Clinical Modification codes for severe sepsis/septic shock, 2) Martin approach, and 3) Angus approach. The model was developed and internally validated in International Classification of Diseases, 9th Revision, Clinical Modification, cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score. Acute care, nonfederal hospitals in New York, Maryland, Florida, Michigan, and Washington. Patients in one of three severe sepsis cohorts: 1) explicitly coded (n = 108,448), 2) Martin cohort (n = 139,094), and 3) Angus cohort (n = 523,637) INTERVENTIONS: None. Maximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit and C-statistics, respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. Goodness-of-fit demonstrated p value of more than 0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort), suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile. Our sepsis severity model and score is a tool that provides reliable risk adjustment for

  4. Poor physical health predicts time to additional breast cancer events and mortality in breast cancer survivors.

    PubMed

    Saquib, Nazmus; Pierce, John P; Saquib, Juliann; Flatt, Shirley W; Natarajan, Loki; Bardwell, Wayne A; Patterson, Ruth E; Stefanick, Marcia L; Thomson, Cynthia A; Rock, Cheryl L; Jones, Lovell A; Gold, Ellen B; Karanja, Njeri; Parker, Barbara A

    2011-03-01

    Health-related quality of life has been hypothesized to predict time to additional breast cancer events and all-cause mortality in breast cancer survivors. Women with early-stage breast cancer (n=2967) completed the SF-36 (mental and physical health-related quality of life) and standardized psychosocial questionnaires to assess social support, optimism, hostility, and depression prior to randomization into a dietary trial. Cox regression was performed to assess whether these measures of quality of life and psychosocial functioning predicted time to additional breast cancer events and all-cause mortality; hazard ratios were the measure of association. There were 492 additional breast cancer events and 301 deaths occurred over a median 7.3 years (range: 0.01-10.8 years) of follow-up. In multivariate models, poorer physical health was associated with both decreased time to additional breast cancer events and all-cause mortality (p trend=0.005 and 0.004, respectively), while greater hostility predicted additional breast cancer events only (p trend=0.03). None of the other psychosocial variables predicted either outcome. The hazard ratios comparing persons with poor (bottom two quintiles) to better (top three quintiles) physical health were 1.42 (95% CI: 1.16, 1.75) for decreased time to additional breast cancer events and 1.37 (95% CI: 1.08, 1.74) for all-cause mortality. Potentially modifiable factors associated with poor physical health included higher body mass index, lower physical activity, lower alcohol consumption, and more insomnia (p<0.05 for all). Interventions to improve physical health should be tested as a means to increase time to additional breast cancer events and mortality among breast cancer survivors. Copyright © 2010 John Wiley & Sons, Ltd.

  5. 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.

  6. European cancer mortality predictions for the year 2017, with focus on lung cancer.

    PubMed

    Malvezzi, M; Carioli, G; Bertuccio, P; Boffetta, P; Levi, F; La Vecchia, C; Negri, E

    2017-05-01

    We predicted cancer mortality figures in the European Union (EU) for the year 2017 using most recent available data, with a focus on lung cancer. We retrieved cancer death certification data and population figures from the World Health Organisation and Eurostat databases. Age-standardized (world standard population) rates were computed for France, Germany, Italy, Poland, Spain, the UK and the EU overall in 1970-2012. We obtained estimates for 2017 by implementing a joinpoint regression model. The predicted number of cancer deaths for 2017 in the EU is 1 373 500, compared with 1 333 400 in 2012 (+3%). Cancer mortality rates are predicted to decline in both sexes, reaching 131.8/100 000 men (-8.2% when compared with 2012) and 84.5/100 000 women (-3.6%). Mortality rates for all selected cancer sites are predicted to decline, except pancreatic cancer in both sexes and lung cancer in women. In men, pancreatic cancer rate is stable, in women it increases by 3.5%. Lung cancer mortality rate in women is predicted to rise to 14.6/100 000 in 2017 (+5.1% since 2012, corresponding to 92 300 predicted deaths), compared with 14.0/100 000 for breast cancer, corresponding to 92 600 predicted deaths. Only younger (25-44) women have favourable lung cancer trends, and rates at this age group are predicted to be similar in women (1.4/100 000) and men (1.2/100 000). In men lung cancer rates are predicted to decline by 10.7% since 2012, and falls are observed in all age groups. European cancer mortality projections for 2017 confirm the overall downward trend in rates, with a stronger pattern in men. This is mainly due to different smoking prevalence trends in different generations of men and women. Lung cancer rates in young European women are comparable to those in men, confirming that smoking has the same impact on lung cancer in the two sexes.

  7. 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.

  8. Should We Use the Model for End-Stage Liver Disease (MELD) to Predict Mortality After Colorectal Surgery?

    PubMed

    Pantel, Haddon Jacob; Stensland, Kristian D; Nelson, Jason; Francone, Todd D; Roberts, Patricia L; Marcello, Peter W; Read, Thomas; Ricciardi, Rocco

    2016-08-01

    We sought to determine the accuracy of the Model for End-Stage Liver Disease and the Mayo Clinic Postoperative Mortality Risk in Patients with Cirrhosis Calculator in patients with ascites who underwent colorectal surgery. The National Surgical Quality Improvement Program database was queried for patients with ascites who underwent a major colorectal operation. Predicted 90-day mortality rate based on the Model for End-Stage Liver Disease and 30-day mortality based on the Mayo Clinic Postoperative Mortality Risk in Patients with Cirrhosis Calculator were compared with observed 30-day mortality. The cohort contained 3137 patients with ascites who underwent a colorectal operation. The Model for End-Stage Liver Disease predicted that 252 (8 %) of patients with ascites undergoing colorectal operations would die within 90 days postoperatively, yet we observed 821 deaths (26 % mortality) within 30 days after surgery (p < 0.001). The Mayo Clinic Postoperative Mortality Risk in Patients with Cirrhosis Calculator predicted that 491 (16.6 % mortality) of patients with ascites undergoing colorectal operations would die within 30 days postoperatively, yet we observed 707 (23.9 % mortality) at 30 days (p < 0.01). We concluded that the current risk prediction models significantly under predict mortality in patients with ascites who underwent colorectal surgery.

  9. 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...

  10. 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.

  11. 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

  12. Prediction of mortality after radical cystectomy for bladder cancer by machine learning techniques.

    PubMed

    Wang, Guanjin; Lam, Kin-Man; Deng, Zhaohong; Choi, Kup-Sze

    2015-08-01

    Bladder cancer is a common cancer in genitourinary malignancy. For muscle invasive bladder cancer, surgical removal of the bladder, i.e. radical cystectomy, is in general the definitive treatment which, unfortunately, carries significant morbidities and mortalities. Accurate prediction of the mortality of radical cystectomy is therefore needed. Statistical methods have conventionally been used for this purpose, despite the complex interactions of high-dimensional medical data. Machine learning has emerged as a promising technique for handling high-dimensional data, with increasing application in clinical decision support, e.g. cancer prediction and prognosis. Its ability to reveal the hidden nonlinear interactions and interpretable rules between dependent and independent variables is favorable for constructing models of effective generalization performance. In this paper, seven machine learning methods are utilized to predict the 5-year mortality of radical cystectomy, including back-propagation neural network (BPN), radial basis function (RBFN), extreme learning machine (ELM), regularized ELM (RELM), support vector machine (SVM), naive Bayes (NB) classifier and k-nearest neighbour (KNN), on a clinicopathological dataset of 117 patients of the urology unit of a hospital in Hong Kong. The experimental results indicate that RELM achieved the highest average prediction accuracy of 0.8 at a fast learning speed. The research findings demonstrate the potential of applying machine learning techniques to support clinical decision making.

  13. [Predictive value of early lactate area for mortality in elderly patients with septic shock].

    PubMed

    Zhang, J X; Yin, M; Chen, X M; Li, C; Wu, D W; Ding, S F; Du, B F; Guo, H P; Qin, W D; Yang, H N; Wang, H

    2016-09-06

    Objective: To investigate the predictive value of early lactate area for mortality in elderly patients with septic shock. Methods: From January 2012 to December 2013, a prospective study was conducted in the Department of Critical Care Medicine, Qilu Hospital of Shandong University. A total of 115 septic shock patients with age ≥65 years were included in the study. Serum lactate was measured every 6 hours, the lactate indicators, including early lactate area, APACHE Ⅱ score etc were recorded. Results: The overall 28-day mortality rate was 67.0%. The top three primary infection sources were lung, abdominal cavity and bloodstream. When compared to survivors, non-survivors had significantly elevated early lactate area and APACHE Ⅱ score and lowered lactate clearance[(27.4±7.6) vs ( 20.3±6.5)], they were significantly more likely to have undergone mechanical ventilation, renal replacement therapy and inotropic or vasopressor support for ≥3 d, and more frequently displayed signs of cardiovascular, respiratory, and renal and hepatic dysfunction (all P<0.05) .Receiver Operating Characteristic curves indicated the lactate area score displayed a strong predictive power for 28 day mortality as indicated by an AUC of 0.758 (P<0.01) and had significantly greater predictive power when compared to the initial lactate or lactate clearance (all P<0.05). Conclusions: In geriatric patients with septic shock, the early lactate area is a useful predictor for early death and showed better predictive value than other lactate indicators.

  14. Inflammation biomarkers and mortality prediction in patients with type 2 diabetes (ZODIAC-27).

    PubMed

    Landman, Gijs W D; Kleefstra, Nanne; Groenier, Klaas H; Bakker, Stephan J L; Groeneveld, Geert H; Bilo, Henk J G; van Hateren, Kornelis J J

    2016-07-01

    C-reactive protein (CRP), procalcitonin (PCT) and pro-adrenomedullin (MR-proADM) are inflammation markers associated with long-term mortality risk. We compared the associations and predictive capacities of CRP, PCT and MR-proADM with cardiovascular and all-cause mortality in patients with type 2 diabetes. This study included primary care treated patients with type 2 diabetes participating in the ZODIAC cohort study. A total of 1005 out of 1688 patients (60%) had complete baseline variables. Baseline CRP, PCT and MR-proADM were assessed in relation to cardiovascular and all-cause mortality with Cox proportional hazard analyses. Hazard Ratios (HR) were adjusted for age, gender, BMI, smoking, systolic blood pressure, cholesterol-HDL ratio, duration of diabetes, HbA1c, history of cardiovascular diseases, albumin-creatinine ratio and creatinine. Risk prediction capabilities were assessed with Harrell's C statistics and proportion of explained variance (R(2)). After a median follow-up of 11 years, 472 (47%) of 1005 patients had died. The likelihood ratio test showed that CRP and MR-proADM significantly improved prediction in cardiovascular mortality [HRs 1.20 (95%CI 1.09-1.33) and 1.56 (95%CI 1.06-2.30)] and in all-cause mortality [HRs 1.10 (95%CI: 1.03-1.18) and 1.31 (95%CI 1.02-1.69)]. Harrell's C values and R(2) measures showed slightly improved discrimination for cardiovascular mortality in patients without macrovascular disease (C: 0.80 to 0.81; R(2): 0.50 to 0.52) and MR-proADM (C: 0.80 to 0.82; R(2): 0.50 to 0.52). CRP and MR-proADM, but not PCT, were independently associated with cardiovascular and all-cause mortality. In patients without macrovascular diseases, CRP and MR-proADM slightly improved discrimination, in absolute sense, of patients at risk for cardiovascular mortality. Copyright © 2016. Published by Elsevier Ireland Ltd.

  15. Nutritional Risk Index predicts mortality in hospitalized advanced heart failure patients.

    PubMed

    Adejumo, Oluwayemisi L; Koelling, Todd M; Hummel, Scott L

    2015-11-01

    Hospitalized advanced heart failure (HF) patients are at high risk for malnutrition and death. The Nutritional Risk Index (NRI) is a simple, well-validated tool for identifying patients at risk for nutrition-related complications. We hypothesized that, in advanced HF patients from the ESCAPE (Evaluation Study of Congestive Heart Failure and Pulmonary Artery Catheterization Effectiveness) trial, the NRI would improve risk discrimination for 6-month all-cause mortality. We analyzed the 160 ESCAPE index admission survivors with complete follow-up and NRI data, calculated as follows: NRI = (1.519 × discharge serum albumin [in g/dl]) + (41.7 × discharge weight [in kg] / ideal body weight [in kg]); as in previous studies, if discharge weight is greater than ideal body weight (IBW), this ratio was set to 1. The previously developed ESCAPE mortality model includes: age; 6-minute walk distance; cardiopulmonary resuscitation/mechanical ventilation; discharge β-blocker prescription and diuretic dose; and discharge serum sodium, blood urea nitrogen and brain natriuretic peptide levels. We used Cox proportional hazards modeling for the outcome of 6-month all-cause mortality. Thirty of 160 patients died within 6 months of hospital discharge. The median NRI was 96 (IQR 91 to 102), reflecting mild-to-moderate nutritional risk. The NRI independently predicted 6-month mortality, with adjusted HR 0.60 (95% CI 0.39 to 0.93, p = 0.02) per 10 units, and increased Harrell's c-index from 0.74 to 0.76 when added to the ESCAPE model. Body mass index and NRI at hospital admission did not predict 6-month mortality. The discharge NRI was most helpful in patients with high (≥ 20%) predicted mortality by the ESCAPE model, where observed 6-month mortality was 38% in patients with NRI < 100 and 14% in those with NRI > 100 (p = 0.04). The NRI is a simple tool that can improve mortality risk stratification at hospital discharge in hospitalized patients with advanced HF. Published by Elsevier

  16. Predictive factors for mortality in Fournier' gangrene: a series of 59 cases.

    PubMed

    García Marín, Andrés; Turégano Fuentes, Fernando; Cuadrado Ayuso, Marta; Andueza Lillo, Juan Antonio; Cano Ballesteros, Juan Carlos; Pérez López, Mercedes

    2015-01-01

    Fournier's gangrene (FG) is the necrotizing fasciitis of the perineum and genital area and presents a high mortality rate. The aim was to assess prognostic factors for mortality, create a new mortality predictive scale and compare it with previously published scales in patients diagnosed with FG in our Emergency Department. Retrospective analysis study between 1998 and 2012. Of the 59 patients, 44 survived (74%) (S) and 15 died (26%) (D). Significant differences were found in peripheral vasculopathy (S 5 [11%]; D 6 [40%]; P=.023), hemoglobin (S 13; D 11; P=.014), hematocrit (S 37; D 31.4; P=.009), white blood cells (S 17,400; D 23,800; P=.023), serum urea (S 58; D 102; P<.001), creatinine (S 1.1; D 1.9; P=.032), potassium (S 3.7; D 4.4; P=.012) and alkaline phosphatase (S 92; D 133; P=.014). Predictive scores: Charlson index (S 1; D 4; P=.013), severe sepsis criteria (S 16 [36%]; D 13 [86%]; P=.001), Fournier's gangrene severity index score (FGSIS) (S 4; D 7; P=.002) and Uludag Fournier's Gangrene Severity Index (UFGSI) (S 9; D 13; P=.004). Independent predictive factors were peripheral vasculopathy, serum potassium and severe sepsis criteria, and a model was created with an area under the ROC curve of 0.850 (0.760-0.973), higher than FGSIS (0.746 [0.601-0.981]) and UFGSI (0.760 [0.617-0.904]). FG showed a high mortality rate. Independent predictive factors were peripheral vasculopathy, potassium and severe sepsis criteria creating a predictive model that performed better than those previously described. Copyright © 2014 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

  17. Saddle Pulmonary Embolism: Laboratory and Computed Tomographic Pulmonary Angiographic Findings to Predict Short-term Mortality.

    PubMed

    Liu, Min; Miao, Ran; Guo, Xiaojuan; Zhu, Li; Zhang, Hongxia; Hou, Qing; Guo, Youmin; Yang, Yuanhua

    2017-02-01

    Saddle pulmonary embolism (SPE) is rare type of acute pulmonary embolism and there is debate about its treatment and prognosis. Our aim is to assess laboratory and computed tomographic pulmonary angiographic (CTPA) findings to predict short-term mortality in patients with SPE. This was a five-centre, retrospective study. The clinical information, laboratory and CTPA findings of 88 consecutive patients with SPE were collected. One-month mortality after diagnosis of SPE was the primary end-point. The correlation of laboratory and CTPA findings with one-month mortality was analysed with area under curve (AUC) of receiver operating characteristic (ROC) curves and logistic regression analysis. Eighteen patients with SPE died within one month. Receiver operating characteristic curves revealed that the cutoff values for the right and left atrial diameter ratio, the right ventricular area and left ventricular area ratio (RVa/LVa ratio), Mastora score, septal angle, N-terminal pro-brain natriuretic peptide and cardiac troponin I (cTnI) for detecting early mortality were 2.15, 2.13, 69%, 57°, 3036 pg/mL and 0.18ng/mL, respectively. Using logistic regression analysis of laboratory and CTPA findings with regard to one-month mortality of SPE, RVa/LVa ratio and cTnI were shown to be independently associated with early death. A combination of cTnI and RVa/LVa ratio revealed an increase in the AUC value, but the difference did not reach significance compared with RVa/LVa or cTnI, alone (P>0.05). In patients with SPE, both the RVa/LVa ratio on CTPA and cTnI appear valuable for the prediction of short-term mortality. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

  18. The Predictive Role of Red Cell Distribution Width in Mortality among Chronic Kidney Disease Patients

    PubMed Central

    Hsieh, Yao-Peng; Chang, Chia-Chu; Kor, Chew-Teng; Yang, Yu; Wen, Yao-Ko; Chiu, Ping-Fang

    2016-01-01

    Background Recently, accumulating evidence has demonstrated that RDW independently predicts clinically important outcomes in many populations. However, the role of RDW has not been elucidated in chronic kidney disease (CKD) patients. We conducted the present study with the aim to evaluate the predictive value of RDW in CKD patients. Methods A retrospective observational cohort study of 1075 stage 3–5 CKD patients was conducted in a medical center. The patients’ baseline information included demographic data, laboratory values, medications, and comorbid conditions. The upper limit of normal RDW value (14.9%) was used to divide the whole population. Multivariate Cox regression analysis was used to determine the independent predictors of mortality. Results Of the 1075 participants, 158 patients (14.7%) died over a mean follow-up of approximately 2.35 years. The crude mortality rate was significantly higher in the high RDW group (high RDW group, 22.4%; low RDW group 11%, p <0.001). From the adjusted model, the high RDW group was correlated with a hazard ratio of 2.19 for overall mortality as compared with the low RDW group (95% CI = 1.53–3.09, p<0.001). In addition, the high RDW group was also associated with an increased risk for cardiovascular disease (HR = 2.28, 95% CI = 1.14–4.25, p = 0.019) and infection (HR = 1.9, 95% CI = 1.15–3.14, p = 0.012)) related mortality in comparison with the low RDW group. Conclusions In stage 3–5 CKD patients, RDW was associated with patient mortality of all-cause, cardiovascular disease and infection. RDW should be considered as a clinical predictor for mortality when providing healthcare to CKD patients. PMID:27906969

  19. The utility of 6-minute walk distance in predicting waitlist mortality for lung transplant candidates

    PubMed Central

    Castleberry, Anthony; Mulvihill, Michael S.; Yerokun, Babatunde A.; Gulack, Brian C.; Englum, Brian; Snyder, Laurie; Worni, Mathias; Osho, Asishana; Palmer, Scott; Davis, R. Duane; Hartwig, Matthew G.

    2017-01-01

    BACKGROUND The lung allocation score (LAS) has led to improved organ allocation for transplant candidates. At present, the 6-minute walk distance (6MWD) is treated as a binary categorical variable of whether or not a candidate can walk more than 150 feet in 6 minutes. In this study, we tested the hypothesis that 6MWD is presently under-utilized with respect to discriminatory power, and that, as a continuous variable, could better prognosticate risk of waitlist mortality. METHODS A retrospective cohort analysis was performed using the Organ Procurement and Transplantation Network/United Network for Organ Sharing (OPTN/UNOS) transplant database. Candidates listed for isolated lung transplant between May 2005 and December 2011 were included. The population was stratified by 6MWD quartiles and unadjusted survival rates were estimated. Multivariable Cox proportional hazards modeling was used to assess the effect of 6MWD on risk of death. The Scientific Registry of Transplant Recipients (SRTR) Waitlist Risk Model was used to adjust for confounders. The optimal 6MWD for discriminative accuracy in predicting waitlist mortality was assessed by receiver-operating characteristic (ROC) curves. RESULTS Analysis was performed on 12,298 recipients. Recipients were segregated into quartiles by distance walked. Waitlist mortality decreased as 6MWD increased. In the multivariable model, significant variables included 6MWD, male gender, non-white ethnicity and restrictive lung diseases. ROC curves discriminated 6-month mortality was best at 655 feet. CONCLUSIONS The 6MWD is a significant predictor of waitlist mortality. A cut-off of 150 feet suboptimally identifies candidates with increased risk of mortality. A cut-off between 550 and 655 feet is more optimal if 6MWD is to be treated as a dichotomous variable. Utilization of the LAS as a continuous variable could further enhance predictive capabilities. PMID:28131666

  20. The utility of 6-minute walk distance in predicting waitlist mortality for lung transplant candidates.

    PubMed

    Castleberry, Anthony; Mulvihill, Michael S; Yerokun, Babatunde A; Gulack, Brian C; Englum, Brian; Snyder, Laurie; Worni, Mathias; Osho, Asishana; Palmer, Scott; Davis, R Duane; Hartwig, Matthew G

    2017-07-01

    The lung allocation score (LAS) has led to improved organ allocation for transplant candidates. At present, the 6-minute walk distance (6MWD) is treated as a binary categorical variable of whether or not a candidate can walk more than 150 feet in 6 minutes. In this study, we tested the hypothesis that 6MWD is presently under-utilized with respect to discriminatory power, and that, as a continuous variable, could better prognosticate risk of waitlist mortality. A retrospective cohort analysis was performed using the Organ Procurement and Transplantation Network/United Network for Organ Sharing (OPTN/UNOS) transplant database. Candidates listed for isolated lung transplant between May 2005 and December 2011 were included. The population was stratified by 6MWD quartiles and unadjusted survival rates were estimated. Multivariable Cox proportional hazards modeling was used to assess the effect of 6MWD on risk of death. The Scientific Registry of Transplant Recipients (SRTR) Waitlist Risk Model was used to adjust for confounders. The optimal 6MWD for discriminative accuracy in predicting waitlist mortality was assessed by receiver-operating characteristic (ROC) curves. Analysis was performed on 12,298 recipients. Recipients were segregated into quartiles by distance walked. Waitlist mortality decreased as 6MWD increased. In the multivariable model, significant variables included 6MWD, male gender, non-white ethnicity and restrictive lung diseases. ROC curves discriminated 6-month mortality was best at 655 feet. The 6MWD is a significant predictor of waitlist mortality. A cut-off of 150 feet sub-optimally identifies candidates with increased risk of mortality. A cut-off between 550 and 655 feet is more optimal if 6MWD is to be treated as a dichotomous variable. Utilization of the LAS as a continuous variable could further enhance predictive capabilities. Copyright © 2017 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights

  1. New consensus definition for acute kidney injury accurately predicts 30-day mortality in cirrhosis with infection

    PubMed Central

    Wong, Florence; O’Leary, Jacqueline G; Reddy, K Rajender; Patton, Heather; Kamath, Patrick S; Fallon, Michael B; Garcia-Tsao, Guadalupe; Subramanian, Ram M.; Malik, Raza; Maliakkal, Benedict; Thacker, Leroy R; Bajaj, Jasmohan S

    2015-01-01

    Background & Aims A consensus conference proposed that cirrhosis-associated acute kidney injury (AKI) be defined as an increase in serum creatinine by >50% from the stable baseline value in <6 months or by ≥0.3mg/dL in <48 hrs. We prospectively evaluated the ability of these criteria to predict mortality within 30 days among hospitalized patients with cirrhosis and infection. Methods 337 patients with cirrhosis admitted with or developed an infection in hospital (56% men; 56±10 y old; model for end-stage liver disease score, 20±8) were followed. We compared data on 30-day mortality, hospital length-of-stay, and organ failure between patients with and without AKI. Results 166 (49%) developed AKI during hospitalization, based on the consensus criteria. Patients who developed AKI had higher admission Child-Pugh (11.0±2.1 vs 9.6±2.1; P<.0001), and MELD scores (23±8 vs17±7; P<.0001), and lower mean arterial pressure (81±16mmHg vs 85±15mmHg; P<.01) than those who did not. Also higher amongst patients with AKI were mortality in ≤30 days (34% vs 7%), intensive care unit transfer (46% vs 20%), ventilation requirement (27% vs 6%), and shock (31% vs 8%); AKI patients also had longer hospital stays (17.8±19.8 days vs 13.3±31.8 days) (all P<.001). 56% of AKI episodes were transient, 28% persistent, and 16% resulted in dialysis. Mortality was 80% among those without renal recovery, higher compared to partial (40%) or complete recovery (15%), or AKI-free patients (7%; P<.0001). Conclusions 30-day mortality is 10-fold higher among infected hospitalized cirrhotic patients with irreversible AKI than those without AKI. The consensus definition of AKI accurately predicts 30-day mortality, length of hospital stay, and organ failure. PMID:23999172

  2. Poor self-rated health predicts mortality in patients with stable chronic heart failure.

    PubMed

    Inkrot, Simone; Lainscak, Mitja; Edelmann, Frank; Loncar, Goran; Stankovic, Ivan; Celic, Vera; Apostolovic, Svetlana; Tahirovic, Elvis; Trippel, Tobias; Herrmann-Lingen, Christoph; Gelbrich, Götz; Düngen, Hans-Dirk

    2016-12-01

    In heart failure, a holistic approach incorporating the patient's perspective is vital for prognosis and treatment. Self-rated health has strong associations with adverse events and short-term mortality risk, but long-term data are limited. We investigated the predictive value of two consecutive self-rated health assessments with regard to long-term mortality in a large, well characterised sample of elderly patients with stable chronic heart failure. We measured self-rated health by asking 'In general, would you say your health is: 1, excellent; 2, very good; 3, good; 4, fair; 5, poor?' twice: at baseline and the end of a 12-week beta-blocker up-titration period in the CIBIS-ELD trial. Mortality was assessed in an observational follow-up after 2-4 years. A total of 720 patients (mean left ventricular ejection fraction 45±12%, mean age 73±5 years, 36% women) rated their health at both time points. During long-term follow-up, 144 patients died (all-cause mortality 20%). Fair/poor self-rated health in at least one of the two reports was associated with increased mortality (hazard ratio 1.42 per level; 95% confidence interval 1.16-1.75; P<0.001). It remained independently significant in multiple Cox regression analysis, adjusted for N-terminal pro B-type natriuretic peptide (NTproBNP), heart rate and other risk prediction covariates. Self-rated health by one level worse was as predictive for mortality as a 1.9-fold increase in NTproBNP. Poor self-rated health predicts mortality in our long-term follow-up of patients with stable chronic heart failure, even after adjustment for established risk predictors. We encourage clinicians to capture patient-reported self-rated health routinely as an easy to assess, clinically meaningful measure and pay extra attention when self-rated health is poor. © The European Society of Cardiology 2015.

  3. Claudication, in contrast to angina pectoris, independently predicts mortality risk in the general population.

    PubMed

    Kieback, Arne G; Lorbeer, Roberto; Wallaschofski, Henri; Ittermann, Till; Völzke, Henry; Felix, Stephan; Dörr, Marcus

    2012-03-01

    The aim of our analyses was to investigate whether claudication and angina pectoris, each defined and based on the answer to a single question, are predictive of future mortality. The study population consisted of 3995 subjects selected from the population-based Study of Health In Pomerania (SHIP). Kaplan-Meier analysis and multivariable Cox proportional hazards regression analysis were used to analyze the association of angina pectoris and claudication with all-cause and cardiovascular mortality adjusted for major cardiovascular risk factors. At baseline, 417 individuals had symptoms of angina pectoris, and 323 had symptoms of claudication. During a median follow-up of 8.5 years, 277 individuals died. Individuals with claudication had a higher fully-adjusted all-cause mortality rate (Hazard Ratio (HR) 1.79; 95 % CI 1.34, 2.39, p < 0.001) and a higher sex- and age-adjusted cardiovascular mortality rate (HR 1.76; 95 % CI 1.03, 2.99, p = 0.038) compared to subjects without claudication. In contrast, subjects with angina pectoris had neither an elevated fully-adjusted all-cause mortality rate (HR 1.15; 95 % CI 0.82, 1.61, p = 0.413) nor sex- and age-adjusted cardiovascular mortality rate (HR 0.71; 95 % CI 0.34, 1.48, p = 0.363) compared to those without this symptom. Claudication, in contrast to angina pectoris, is a strong, independent predictor of all-cause mortality.

  4. Symmetrical dimethylarginine predicts mortality in the general population: observations from the Dallas heart study.

    PubMed

    Gore, M Odette; Lüneburg, Nicole; Schwedhelm, Edzard; Ayers, Colby R; Anderssohn, Maike; Khera, Amit; Atzler, Dorothee; de Lemos, James A; Grant, Peter J; McGuire, Darren K; Böger, Rainer H

    2013-11-01

    Increased asymmetrical dimethylarginine (ADMA), a NO synthase inhibitor, and its congener symmetrical dimethylarginine (SDMA), predict cardiovascular and all-cause mortality in at-risk populations. Their prognostic value in the general population remains uncertain. We investigated the correlations of SDMA and ADMA with atherosclerosis and cardiovascular/all-cause mortality in the Dallas Heart Study, a multiethnic probability-based cohort aged 30 to 65 years. SDMA and ADMA were measured by liquid chromatography-tandem mass-spectrometry (n=3523), coronary artery calcium by electron-beam computed tomography, and abdominal aortic wall thickness by MRI. In unadjusted analyses, categories of increasing SDMA and ADMA were associated with higher prevalence of cardiovascular risk factors, increased risk markers, and all-cause and cardiovascular mortality (median follow-up, 7.4 years). After adjustment for age, sex, and race, traditional cardiovascular risk factors, and renal function, SDMA and ADMA analyzed as continuous variables were associated with coronary artery calcium >10, but only SDMA was associated with abdominal aortic wall thickness. SDMA, but not ADMA, was associated with cardiovascular mortality (hazard ratio per log unit change, 3.36 [95% confidence interval, 1.49-7.59]; P=0.004). SDMA and ADMA were both associated with all-cause mortality, but after further adjustment for N-terminal pro-brain-type natriuretic peptide, high-sensitivity C-reactive protein, and high-sensitivity cardiac troponin T, only SDMA was associated with all-cause mortality (hazard ratio per log unit change, 1.86 [95% confidence interval, 1.04-3.30]; P=0.01). SDMA, but not ADMA, was an independent predictor of all-cause and cardiovascular mortality in a large multiethnic population-based cohort.

  5. Comparison of mental status scales for predicting mortality on the general wards

    PubMed Central

    Zadravecz, Frank J.; Tien, Linda; Robertson-Dick, Brian J.; Yuen, Trevor C.; Twu, Nicole M.; Churpek, Matthew M.; Edelson, Dana P.

    2016-01-01

    Background Altered mental status is a significant predictor of mortality in inpatients. Several scales exist to characterize mental status, including the AVPU (Alert, responds to Voice, responds to Pain, Unresponsive) scale, which is used in many early warning scores in the general ward setting. The use of the Glasgow Coma Scale (GCS) and Richmond Agitation Sedation Scale (RASS) is not well established in this population. Objective To compare the accuracies of AVPU, GCS, and RASS for predicting inpatient mortality Design Retrospective cohort study Setting Single urban academic medical center Participants Adult inpatients on the general wards Measurements Nurses recorded GCS and RASS on consecutive adult hospitalizations. AVPU was extracted from the eye subscale of the GCS. We compared the accuracies of each scale for predicting in-hospital mortality within 24 hours of a mental status observation using area under the receiver operating characteristic curves (AUC). Results 295,974 paired observations of GCS and RASS were obtained from 26,873 admissions; 417 (1.6%) resulted in in-hospital death. GCS and RASS more accurately predicted mortality than AVPU (AUC 0.80 and 0.82, respectively vs. 0.73; p<0.001 for both comparisons). Simultaneous use of GCS and RASS produced an AUC of 0.85 (95% CI: 0.82-0.87; p<0.001 when compared to all three scales). Conclusions In ward patients, both GCS and RASS were significantly more accurate predictors of mortality than AVPU. In addition, combining GCS and RASS was more accurate than any scale alone. Routine tracking of GCS and/or RASS on general wards may improve accuracy of detecting clinical deterioration. PMID:26374471

  6. Cholesterol esterification in plasma as a biomarker for liver function and prediction of mortality.

    PubMed

    Kaiser, Thorsten; Kinny-Köster, Benedict; Bartels, Michael; Berg, Thomas; Scholz, Markus; Engelmann, Cornelius; Seehofer, Daniel; Becker, Susen; Ceglarek, Uta; Thiery, Joachim

    2017-04-20

    Advanced stages of liver cirrhosis lead to a dramatically increased mortality. For valid identification of these patients suitable biomarkers are essential. The most important biomarkers for liver function are bilirubin and prothrombin time expressed as International Normalized Ratio (INR). However, the influence of several anticoagulants on the prothrombin time limits its diagnostic value. Aim of this study was the evaluation of cholesterol esterification (CE) fraction (esterified cholesterol vs. total cholesterol) as an alternative biomarker for liver synthesis and mortality prediction. Under physiological conditions the CE fraction in blood is closely regulated by lecithin-cholesterol acyltransferase (LCAT) which is produced in the liver. One hundred forty-two patients with liver disease clinically considered for orthotopic liver transplant for different indications were enrolled in the study. One patient was excluded because of the intake of a direct oral factor Xa inhibitor which has a strong impact on prothrombin time. Results of CE fraction were in good agreement with INR (R(2) = 0.73; p < 0.001). In patients who died or survived within three months mean CE fraction was 56% vs. 74% (p < 0.001) and mean INR was 2.0 vs. 1.3 (p < 0.001), respectively. The predictive value of CE fraction for three-month mortality risk was higher compared to INR (p = 0.04). Results for one-year mortality were comparable. The cholesterol esterification fraction is a valid biomarker for liver synthesis and allows reliable prediction of mortality. In contrast to INR, it is independent of anticoagulation and other analytical limitations of coagulation tests.

  7. The effect of adding functional classification to ASA status for predicting 30-day mortality.

    PubMed

    Visnjevac, Ognjen; Davari-Farid, Sina; Lee, Jun; Pourafkari, Leili; Arora, Pradeep; Dosluoglu, Hasan H; Nader, Nader D

    2015-07-01

    curve the receiver operator characteristic curve was 0.811 ± 0.010 for traditional ASA classification in predicting death within 30 days, which improved 4.7% to 0.848 ± 0.008 using the modified ASA classification, P < 0.00001. Functional capacity was an independent predictor of mortality within each ASA class, indicating that it should be considered for incorporation into the routine preoperative evaluation. Functional dependence may be an indication for increasing a patient's ASA class by 1 class-point to better reflect his or her perioperative risk, but prospective validation of these findings is recommended, as this is a preliminary study.

  8. Cystatin C at Admission in the Intensive Care Unit Predicts Mortality among Elderly Patients.

    PubMed

    Dalboni, Maria Aparecida; Beraldo, Daniel de Oliveira; Quinto, Beata Marie Redublo; Blaya, Rosângela; Narciso, Roberto; Oliveira, Moacir; Monte, Júlio César Martins; Durão, Marcelino de Souza; Cendoroglo, Miguel; Pavão, Oscar Fernando; Batista, Marcelo Costa

    2013-01-01

    Introduction. Cystatin C has been used in the critical care setting to evaluate renal function. Nevertheless, it has also been found to correlate with mortality, but it is not clear whether this association is due to acute kidney injury (AKI) or to other mechanism. Objective. To evaluate whether serum cystatin C at intensive care unit (ICU) entry predicts AKI and mortality in elderly patients. Materials and Methods. It was a prospective study of ICU elderly patients without AKI at admission. We evaluated 400 patients based on normality for serum cystatin C at ICU entry, of whom 234 (58%) were selected and 45 (19%) developed AKI. Results. We observed that higher serum levels of cystatin C did not predict AKI (1.05 ± 0.48 versus 0.94 ± 0.36 mg/L; P = 0.1). However, it was an independent predictor of mortality, H.R. = 6.16 (95% CI 1.46-26.00; P = 0.01), in contrast with AKI, which was not associated with death. In the ROC curves, cystatin C also provided a moderate and significant area (0.67; P = 0.03) compared to AKI (0.47; P = 0.6) to detect death. Conclusion. We demonstrated that higher cystatin C levels are an independent predictor of mortality in ICU elderly patients and may be used as a marker of poor prognosis.

  9. Cystatin C at Admission in the Intensive Care Unit Predicts Mortality among Elderly Patients

    PubMed Central

    Dalboni, Maria Aparecida; Beraldo, Daniel de Oliveira; Quinto, Beata Marie Redublo; Blaya, Rosângela; Narciso, Roberto; Oliveira, Moacir; Monte, Júlio César Martins; Durão, Marcelino de Souza; Cendoroglo, Miguel; Pavão, Oscar Fernando; Batista, Marcelo Costa

    2013-01-01

    Introduction. Cystatin C has been used in the critical care setting to evaluate renal function. Nevertheless, it has also been found to correlate with mortality, but it is not clear whether this association is due to acute kidney injury (AKI) or to other mechanism. Objective. To evaluate whether serum cystatin C at intensive care unit (ICU) entry predicts AKI and mortality in elderly patients. Materials and Methods. It was a prospective study of ICU elderly patients without AKI at admission. We evaluated 400 patients based on normality for serum cystatin C at ICU entry, of whom 234 (58%) were selected and 45 (19%) developed AKI. Results. We observed that higher serum levels of cystatin C did not predict AKI (1.05 ± 0.48 versus 0.94 ± 0.36 mg/L; P = 0.1). However, it was an independent predictor of mortality, H.R. = 6.16 (95% CI 1.46–26.00; P = 0.01), in contrast with AKI, which was not associated with death. In the ROC curves, cystatin C also provided a moderate and significant area (0.67; P = 0.03) compared to AKI (0.47; P = 0.6) to detect death. Conclusion. We demonstrated that higher cystatin C levels are an independent predictor of mortality in ICU elderly patients and may be used as a marker of poor prognosis. PMID:24967238

  10. Predictive factors of perinatal mortality in transfused fetuses due to maternal alloimmunization: what really matters?

    PubMed

    Osanan, Gabriel Costa; Silveira Reis, Zilma Nogueira; Apocalypse, Isabela Gomes; Lopes, Ana Paula Brum; Pereira, Alamanda Kfoury; da Silva Ribeiro, Orquidea Maria; Vieira Cabral, Antônio Carlos

    2012-08-01

    Alloimmunization is the main cause of fetal anemia. There are not many consistent analyses associating antenatal parameters to perinatal mortality in transfused fetuses due to maternal alloimmunization. The study aimed to determine the prognostic variables related to perinatal death. A cohort study analyzed 128 fetuses treated with intrauterine transfusion (IUT), until the early neonatal period. Perinatal mortality was associated with prognostic conditions related to prematurity, severity of fetal anemia and IUT procedure by univariated logistic regression. Multiple logistic regression was used to compute the odds ratio (OR) for adjusting the hemoglobin deficit at the last IUT, gestational age at birth, complications of IUT, antenatal corticosteroid and hydrops. Perinatal mortality rate found in this study was 18.1%. The hemoglobin deficit at the last IUT (OR: 1.26, 95% CI: 1.04-1.53), gestational age at birth (OR: 0.53, 95% CI: 0.38-0.74) and the presence of transfusional complications (OR: 5.43, 95% CI: 142-20.76) were significant in predicting fetal death. Perinatal mortality prediction in transfused fetuses is not associated only to severity of anemia, but also to the risks of IUT and prematurity.

  11. Modified Glasgow Coma Scale to predict mortality in febrile unconscious children.

    PubMed

    Chaturvedi, P; Kishore, M

    2001-04-01

    A prospective hospital based study was conducted in the Department of Pediatrics of the Kasturba Hospital, Mahatma Gandhi Institute of Medical Sciences, Sevagram, Wardha to predict the mortality in children admitted with fever and unconsciousness using the Modified Glasgow Coma Scale (MGCS) score. Forty eight children were admitted with fever and unconsciousness; cases of febrile convulsions, epilepsy and cerebral palsy were excluded. MGCS scores were assessed on admission and repeated at 12 hours, 24 hours, 48 hours and 72 hours after admission in each case. Diagnosis in each case was confirmed by history, examinations and investigations. All the cases were regularly followed up till death/discharge. The overall mortality was 29.1% (14/48) out of which 85% (12/14) died within the first 24 hours. Mortality was highest in the toddler age group and in patients with pyogenic meningitis. There was a significant association between death and MGCS scores on admission with a post test probability for discharge being only 10% with a score of less than 5 and 99% with a score of more than 10 respectively. MGCS scores on admission can be used to predict mortality in patients hospitalized with fever and unconsciousness. The scale is simple, easy, can be applied at bed side and does not need any investigations. Its application in developing countries with limited investigative and intensive care facilities can help the treating physician decide regarding referral and counseling the parents regarding the probable clinical outcome.

  12. Venovenous extracorporeal membrane oxygenation in adult respiratory failure: Scores for mortality prediction.

    PubMed

    Hsin, Chun-Hsien; Wu, Meng-Yu; Huang, Chung-Chi; Kao, Kuo-Chin; Lin, Pyng-Jing

    2016-06-01

    Despite a potentially effective therapy for adult respiratory failure, a general agreement on venovenous extracorporeal membrane oxygenation (VV-ECMO) has not been reached among institutions due to its invasiveness and high resource usage. To establish consensus on the timing of intervention, large ECMO organizations have published the respiratory extracorporeal membrane oxygenation survival prediction (RESP) score and the ECMOnet score, which allow users to predict hospital mortality for candidates with their pre-ECMO presentations. This study was aimed to test the predictive powers of these published scores in a medium-sized cohort enrolling adults treated with VV-ECMO for acute respiratory failure, and develop an institutional prediction model under the framework of the 3 scores if a superior predictive power could be achieved. This retrospective study included 107 adults who received VV-ECMO for severe acute respiratory failure (a PaO2/FiO2 ratio <70 mm Hg) in a tertiary referral center from 2007 to 2015. Essential demographic and clinical data were collected to calculate the RESP score, the ECMOnet score, and the sequential organ failure assessment (SOFA) score before VV-ECMO. The predictive power of hospital mortality of each score was presented as the area under receiver-operating characteristic curve (AUROC). The multivariate logistic regression was used to develop an institutional prediction model. The surviving to discharge rate was 55% (n = 59). All of the 3 published scores had a real but poor predictive power of hospital mortality in this study. The AUROCs of RESP score, ECMOnet score, and SOFA score were 0.662 (P = 0.004), 0.616 (P = 0.04), and 0.667 (P = 0.003), respectively. An institutional prediction model was established from these score parameters and presented as follows: hospital mortality (Y) = -3.173 + 0.208 × (pre-ECMO SOFA score) + 0.148 × (pre-ECMO mechanical ventilation day) + 1.021

  13. 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 (PEWISRNM) 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 PEWISRNM 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. PEWISRNM and GNRI were identified as independent predictors of death. Addition of PEWISRNM 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 PEWISRNM and GNRI. When lowering the criterion level of BMI per 1 kg/m(2) sequentially, PEWISRNM at BMI <20 kg/m(2) maximized the hazard ratio for mortality. The model including PEWISRNM at BMI <20 kg/m(2) improved NRI compared with the model including GNRI. PEWISRNM 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.

  14. Changes in Albuminuria Predict Mortality and Morbidity in Patients with Vascular Disease

    PubMed Central

    Mann, Johannes F. E.; Schumacher, Helmut; Gao, Peggy; Mancia, Giuseppe; Weber, Michael A.; McQueen, Matthew; Koon, Teo; Yusuf, Salim

    2011-01-01

    The degree of albuminuria predicts cardiovascular and renal outcomes, but it is not known whether changes in albuminuria also predict similar outcomes. In two multicenter, multinational, prospective observational studies, a central laboratory measured albuminuria in 23,480 patients with vascular disease or high-risk diabetes. We quantified the association between a greater than or equal to twofold change in albuminuria in spot urine from baseline to 2 years and the incidence of cardiovascular and renal outcomes and all-cause mortality during the subsequent 32 months. A greater than or equal to twofold increase in albuminuria from baseline to 2 years, observed in 28%, associated with nearly 50% higher mortality (HR 1.48; 95% CI 1.32 to 1.66), and a greater than or equal to twofold decrease in albuminuria, observed in 21%, associated with 15% lower mortality (HR 0.85; 95% CI 0.74 to 0.98) compared with those with lesser changes in albuminuria, after adjustment for baseline albuminuria, BP, and other potential confounders. Increases in albuminuria also significantly associated with cardiovascular death, composite cardiovascular outcomes (cardiovascular death, myocardial infarction, stroke, and hospitalization for heart failure), and renal outcomes including dialysis or doubling of serum creatinine (adjusted HR 1.40; 95% CI 1.11 to 1.78). In conclusion, in patients with vascular disease, changes in albuminuria predict mortality and cardiovascular and renal outcomes, independent of baseline albuminuria. This suggests that monitoring albuminuria is a useful strategy to help predict cardiovascular risk. PMID:21719791

  15. TI-59 programmable calculator program for calculating predicted operative mortality in general surgery.

    PubMed

    Haddad, M; Reiss, R; Lilos, P; Fuchs, C

    1986-01-01

    A program for the TI-59 programmable calculator for calculating predicted postoperative mortality is presented. Input data are based on handy, clinical, non-invasive pre-operative and operative parameters retrieved mostly significant in this respect by former multivariate logistic regression analysis of a broad data-base; their relative weights are incorporated into the program data base as basic coefficients. Considerations employed in its usage are discussed, as well as possible future technical and/or environmental modifications.

  16. Could dysnatremias play a role as independent factors to predict mortality in surgical critically ill patients?

    PubMed Central

    Nicolini, Edson A.; Nunes, Roosevelt S.; Santos, Gabriela V.; da Silva, Silvana Lia; Carreira, Mariana M.; Pellison, Fernanda G.; Menegueti, Mayra G.; Auxiliadora-Martins, Maria; Bellissimo-Rodrigues, Fernando; Feres, Marcus A.; Basile-Filho, Anibal

    2017-01-01

    Abstract Several studies have demonstrated the impact of dysnatremias on mortality of intensive care unit (ICU) patients. The objective of this study was to assess whether dysnatremia is an independent factor to predict mortality in surgical critically ill patients admitted to ICU in postoperative phase. One thousand five hundred and ninety-nine surgical patients (58.8% males; mean age of 60.6 ± 14.4 years) admitted to the ICU in the postoperative period were retrospectively studied. The patients were classified according to their serum sodium levels (mmol/L) at admission as normonatremia (135–145), hyponatremia (<135), and hypernatremia (>145). APACHE II, SAPS III, and SOFA were recorded. The capability of each index to predict mortality of ICU and hospital mortality of patients was analyzed by multiple logistic regression. Hyponatremia did not have an influence on mortality in the ICU with a relative risk (RR) = 0.95 (0.43–2.05) and hospital mortality of RR = 1.40 (0.75–2.59). However, this association was greater in patients with hypernatremia mortality in the ICU (RR = 3.33 [95% confidence interval, CI 1.58–7.0]) and also in hospital mortality (RR = 2.9 [ 95% CI = 1.51–5.55). The pairwise comparison of ROC curves among the different prognostic indexes (APACHE II, SAPS III, SOFA) did not show statistical significance. The comparison of these indexes with serum sodium levels for general population, hyponatremia, and normonatremia was statistically significant (P < .001). For hypernatremia, the AUC and 95% CI for APACHE II, SAPS III, SOFA, and serum sodium level were 0.815 (0.713–0.892), 0.805 (0.702–0.885), 0.885 (0.794–0.945), and 0.663 (0.549–0.764), respectively. The comparison among the prognostic indexes was not statistically significant. Only SOFA score had a statistic difference compared with hypernatremia (P < .02). The serum sodium levels at admission, especially hypernatremia, may be used as an

  17. Does Parsonnet scoring model predict mortality following adult cardiac surgery in India?

    PubMed Central

    Srilata, Moningi; Padhy, Narmada; Padmaja, Durga; Gopinath, Ramachandran

    2015-01-01

    Aims and Objectives: To validate the Parsonnet scoring model to predict mortality following adult cardiac surgery in Indian scenario. Materials and Methods: A total of 889 consecutive patients undergoing adult cardiac surgery between January 2010 and April 2011 were included in the study. The Parsonnet score was determined for each patient and its predictive ability for in-hospital mortality was evaluated. The validation of Parsonnet score was performed for the total data and separately for the sub-groups coronary artery bypass grafting (CABG), valve surgery and combined procedures (CABG with valve surgery). The model calibration was performed using Hosmer–Lemeshow goodness of fit test and receiver operating characteristics (ROC) analysis for discrimination. Independent predictors of mortality were assessed from the variables used in the Parsonnet score by multivariate regression analysis. Results: The overall mortality was 6.3% (56 patients), 7.1% (34 patients) for CABG, 4.3% (16 patients) for valve surgery and 16.2% (6 patients) for combined procedures. The Hosmer–Lemeshow statistic was <0.05 for the total data and also within the sub-groups suggesting that the predicted outcome using Parsonnet score did not match the observed outcome. The area under the ROC curve for the total data was 0.699 (95% confidence interval 0.62–0.77) and when tested separately, it was 0.73 (0.64–0.81) for CABG, 0.79 (0.63–0.92) for valve surgery (good discriminatory ability) and only 0.55 (0.26–0.83) for combined procedures. The independent predictors of mortality determined for the total data were low ejection fraction (odds ratio [OR] - 1.7), preoperative intra-aortic balloon pump (OR - 10.7), combined procedures (OR - 5.1), dialysis dependency (OR - 23.4), and re-operation (OR - 9.4). Conclusions: The Parsonnet score yielded a good predictive value for valve surgeries, moderate predictive value for the total data and for CABG and poor predictive value for combined

  18. Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

    PubMed Central

    de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F. E.

    2012-01-01

    Background Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. Methodology/Principal Findings As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Conclusions Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality. PMID:23152764

  19. Medical comorbidities predict mortality in women with a history of early stage breast cancer.

    PubMed

    Patterson, Ruth E; Flatt, Shirley W; Saquib, Nazmus; Rock, Cheryl L; Caan, Bette J; Parker, Barbara A; Laughlin, Gail A; Erickson, Kirsten; Thomson, Cynthia A; Bardwell, Wayne A; Hajek, Richard A; Pierce, John P

    2010-08-01

    This analysis was conducted to determine whether comorbid medical conditions predict additional breast cancer events and all-cause mortality in women with a history of early stage breast cancer. Women (n = 2,542) participating in a randomized diet trial completed a self-administered questionnaire regarding whether they were currently being treated for a wide variety of diseases (cardiovascular, diabetes, gallbladder, gastrointestinal, arthritis, and osteoporosis) and conditions (high blood pressure, elevated cholesterol level). Height and weight were measured at baseline. Participants were followed for a median of 7.3 years (range 0.8-15.0). Cox regression analysis was performed to assess whether comorbidities predicted disease-free and overall survival; hazard ratio (HR) was the measure of association. Overall, there were 406 additional breast cancer events and 242 deaths. Participants with diabetes had over twofold the risk of additional breast cancer events (HR 2.1, 95% CI: 1.3, 3.4) and mortality (HR 2.5, 95% CI: 1.4, 4.4). The presence of multiple comorbidities did not statistically significantly predict additional breast cancer events. However, compared to no comorbidities, participants with 3 or more comorbidities had a HR of 2.1, 95% CI: 1.3, 3.3 for mortality. In conclusion, type 2 diabetes is associated with poor breast cancer prognosis. Given that 85% of deaths were caused by breast cancer, these findings suggest that multiple comorbidities may reduce the likelihood of surviving additional breast cancer events.

  20. Temperature multiscale entropy analysis: a promising marker for early prediction of mortality in septic patients.

    PubMed

    Papaioannou, V E; Chouvarda, I G; Maglaveras, N K; Baltopoulos, G I; Pneumatikos, I A

    2013-11-01

    A few studies estimating temperature complexity have found decreased Shannon entropy, during severe stress. In this study, we measured both Shannon and Tsallis entropy of temperature signals in a cohort of critically ill patients and compared these measures with the sequential organ failure assessment (SOFA) score, in terms of intensive care unit (ICU) mortality. Skin temperature was recorded in 21 mechanically ventilated patients, who developed sepsis and septic shock during the first 24 h of an ICU-acquired infection. Shannon and Tsallis entropies were calculated in wavelet-based decompositions of the temperature signal. Statistically significant differences of entropy features were tested between survivors and non-survivors and classification models were built, for predicting final outcome. Significantly reduced Tsallis and Shannon entropies were found in non-survivors (seven patients, 33%) as compared to survivors. Wavelet measurements of both entropy metrics were found to predict ICU mortality better than SOFA, according to a combination of area under the curve, sensitivity and specificity values. Both entropies exhibited similar prognostic accuracy. Combination of SOFA and entropy presented improved the outcome of univariate models. We suggest that reduced wavelet Shannon and Tsallis entropies of temperature signals may complement SOFA in mortality prediction, during the first 24 h of an ICU-acquired infection.

  1. Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

    PubMed

    de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E

    2012-01-01

    Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

  2. Fetal MRI for prediction of neonatal mortality following preterm premature rupture of the fetal membranes.

    PubMed

    Messerschmidt, Agnes; Pataraia, Anna; Helmer, Hanns; Kasprian, Gregor; Sauer, Alexandra; Brugger, Peter C; Pollak, Arnold; Weber, Michael; Prayer, Daniela

    2011-11-01

    Lung MRI volumetrics may be valuable for fetal assessment following early preterm premature rupture of the foetal membranes (pPROM). To evaluate the predictive value of MRI lung volumetrics after pPROM. Retrospective cohort study of 40 fetuses after pPROM in a large, tertiary, perinatal referral center. Fetuses underwent MRI lung volumetrics. Estimated lung volume was expressed as percentage of expected lung volume (our own normal references). Primary outcome was neonatal mortality due to respiratory distress before discharge from hospital. Gestational age range was 16-27 weeks. Estimated-to-expected lung volume was 73% in non-survivors and 102% in survivors (P < 0.05). There were no survivors with a lung volume less than 60% of expected. By logistic regression, mortality could be predicted with a sensitivity of 80%, specificity of 86% and accuracy of 85%. Fetal MR lung volumetrics may be useful for predicting mortality due to respiratory distress in children with early gestational pPROM.

  3. 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

  4. Echocardiographic parameters of right ventricular function predict mortality in acute respiratory distress syndrome: a pilot study

    PubMed Central

    Wadia, Subeer K.; Kovach, Julie; Fogg, Louis; Tandon, Rajive

    2016-01-01

    Abstract Right ventricular (RV) dysfunction in acute respiratory distress syndrome (ARDS) contributes to increased mortality. Our aim is to identify reproducible transthoracic echocardiography (TTE) parameters of RV dysfunction that can be used to predict outcomes in ARDS. We performed a retrospective single-center cohort pilot study measuring tricuspid annular plane systolic excursion (TAPSE), Tei index, RV-fractional area change (RV-FAC), pulmonary artery systolic pressure (PASP), and septal shift, reevaluated by an independent blinded cardiologist (JK). Thirty-eight patients were included. Patients were divided on the basis of 30-day survival. Thirty-day mortality was 47%. Survivors were younger than nonsurvivors. Survivors had a higher pH, PaO2∶FiO2 ratio, and TAPSE. Acute Physiology and Chronic Health Evaluation II (APACHE II), Simplified Acute Physiology Score II (SAPS II), and Sequential Organ Failure Assessment (SOFA) scores were lower in survivors. TAPSE has the strongest association with increased 30-day mortality from date of TTE. Accordingly, TAPSE has a strong positive correlation with PaO2∶FiO2 ratios, and Tei index has a strong negative correlation with PaO2∶FiO2 ratios. Septal shift was associated with lower PaO2∶FiO2 ratios. Decrease in TAPSE, increase in Tei index, and septal shift were seen in the severe ARDS group. In multivariate logistic regression models, TAPSE maintained a significant association with mortality independent of age, pH, PaO2∶FiO2 ratios, positive end expiratory pressure, PCO2, serum bicarbonate, plateau pressures, driving pressures, APACHE II, SAPS II, and SOFA scores. In conclusion, TAPSE and other TTE parameters should be used as novel predictive indicators for RV dysfunction in ARDS. These parameters can be used as surrogate noninvasive RV hemodynamic measurements to be manipulated to improve mortality in patients with ARDS and contributory RV dysfunction. PMID:27252840

  5. Predictive Value of Cumulative Blood Pressure for All-Cause Mortality and Cardiovascular Events

    PubMed Central

    Wang, Yan Xiu; Song, Lu; Xing, Ai Jun; Gao, Ming; Zhao, Hai Yan; Li, Chun Hui; Zhao, Hua Ling; Chen, Shuo Hua; Lu, Cheng Zhi; Wu, Shou Ling

    2017-01-01

    The predictive value of cumulative blood pressure (BP) on all-cause mortality and cardiovascular and cerebrovascular events (CCE) has hardly been studied. In this prospective cohort study including 52,385 participants from the Kailuan Group who attended three medical examinations and without CCE, the impact of cumulative systolic BP (cumSBP) and cumulative diastolic BP (cumDBP) on all-cause mortality and CCEs was investigated. For the study population, the mean (standard deviation) age was 48.82 (11.77) years of which 40,141 (76.6%) were male. The follow-up for all-cause mortality and CCEs was 3.96 (0.48) and 2.98 (0.41) years, respectively. Multivariate Cox proportional hazards regression analysis showed that for every 10 mm Hg·year increase in cumSBP and 5 mm Hg·year increase in cumDBP, the hazard ratio for all-cause mortality were 1.013 (1.006, 1.021) and 1.012 (1.006, 1.018); for CCEs, 1.018 (1.010, 1.027) and 1.017 (1.010, 1.024); for stroke, 1.021 (1.011, 1.031) and 1.018 (1.010, 1.026); and for MI, 1.013 (0.996, 1.030) and 1.015 (1.000, 1.029). Using natural spline function analysis, cumSBP and cumDBP showed a J-curve relationship with CCEs; and a U-curve relationship with stroke (ischemic stroke and hemorrhagic stroke). Therefore, increases in cumSBP and cumDBP were predictive for all-cause mortality, CCEs, and stroke. PMID:28167816

  6. Early hospital readmission in decompensated cirrhosis: Incidence, impact on mortality, and predictive factors.

    PubMed

    Morales, Betty P; Planas, Ramon; Bartoli, Ramon; Morillas, Rosa M; Sala, Margarita; Cabré, Eduard; Casas, Irma; Masnou, Helena

    2017-08-01

    The early hospital readmission of patients with decompensated cirrhosis is a current problem. A study is presented on the incidence, the impact on mortality, and the predictive factors of early hospital readmission. On the study included 112 cirrhotic patients, discharged after some decompensation between January 2013 and May 2014. Multivariate analyses were performed to identify predictors of early readmission and mortality. The early readmission rate was 29.5%. The predictive factors were male gender (OR: 2.81; 95% CI: 1.07-7.35), Model for End-Stage Liver Disease-sodium score ≥15 (OR: 3.79; 95% CI 1.48-9.64), and Charlson index ≥7 (OR: 4.34, 95% CI 1.65-11.4). This model enabled patients to be classified into low or high risk of early readmissions (13.6% vs. 52.2%). The mortality rate was significantly higher among patients with early readmission (73% vs. 35%) (p<.0001). After adjusting for the Model for End-Stage Liver Disease-sodium score, Charlson index, dependence in activities of daily living, educational status, and number of medications on discharge, the early readmission was independently associated with mortality. Early hospital readmission is common, and is independently associated with mortality. Male gender, MELD-Na ≥15, and Charlson index ≥7 are predictors of early readmission. These results could be used to develop future strategies to reduce early readmission. Copyright © 2017 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.

  7. High soluble vascular cell adhesion molecule-1 concentrations predict long-term mortality in hemodialysis patients.

    PubMed

    Chang, Jia-Feng; Hsu, Shih-Ping; Pai, Mei-Fen; Yang, Ju-Yeh; Chen, Hung-Yuan; Wu, Hon-Yen; Peng, Yu-Sen

    2013-12-01

    Soluble vascular cell adhesion molecule-1 (sVCAM-1) has a strong association with cardiovascular deaths in patients with coronary artery disease. The aim of this study is to explore the association between sVCAM-1 and cardiovascular mortality in maintenance hemodialysis (MHD) patients. Eighty-three clinically stable MHD patients (mean age of 59.4 ± 13.7 years) at a single hospital-based dialysis facility were included. sVCAM-1, soluble intercellular adhesion molecule-1 (sICAM-1), and soluble E-selectin (sE-selectin) were determined at study baseline. The study cohort was divided into higher and lower concentration groups by the median value. The all-cause and cardiovascular mortality of this cohort were followed for 7 years. The mean concentrations of sVCAM-1, sICAM-1, and sE-selectin were 1,393.08 ± 300.96, 230.16 ± 84.86, and 60.01 ± 42.00 ng/mL, respectively. The higher concentration groups of sVCAM-1 and sICAM-1 had higher all-cause mortality by Kaplan-Meier analysis (p = 0.002 and p = 0.030, respectively). Higher sVCAM-1 concentrations had a higher risk of all-cause and cardiovascular mortality (p = 0.006 p = 0.046, respectively) in Cox proportional hazards model analysis. In MHD patients, higher sVCAM-1 concentrations independently predict all-cause and cardiovascular mortality. This biomarker may be used as a valid surrogate marker for predicting outcomes.

  8. Low platelet activity predicts 30 days mortality in patients undergoing heart surgery.

    PubMed

    Kuliczkowski, Wiktor; Sliwka, Joanna; Kaczmarski, Jacek; Zysko, Dorota; Zembala, Michal; Steter, Dawid; Zembala, Marian; Gierlotka, Marek; Kim, Moo Hyun; Serebruany, Victor

    2016-03-01

    Despite advanced techniques and improved clinical outcomes, patient survival following coronary artery bypass grafting (CABG) is still a major concern. Therefore, predicting future CABG mortality represents an unmet medical need and should be carefully explored. The objective of this study is to assess whether pre-CABG platelet activity corresponds with 30 days mortality post-CABG. Retrospective analyses of platelet biomarkers and death at 30 days in 478 heart surgery patients withdrawn from aspirin or/and clopidogrel. Platelet activity was assessed prior to CABG for aspirin (ASPI-test) with arachidonic acid and clopidogrel (ADP-test) utilizing Multiplate impedance aggregometer. Most patients (n = 198) underwent conventional CABG, off-pump (n = 162), minimally invasive (n = 30), artificial valve implantation (n = 48) or valves in combination with CABG (n = 40). There were 22 deaths at 30 days, including 10 in-hospital fatalities. With the cut-off value set below 407 area under curve (AUC) for the ASPI-test, the 30-day mortality was 5.90% for the lower cohort and 2.66% for patients with significantly higher platelet reactivity (P = 0.038). For the ADP-test with a cut-off at 400AUC, the 30-day mortality was 9.68% for the lower cohort and 3.66% for patients with higher platelet reactivity, representing a borderline significant difference (P = 0.046). Aside from the platelet indices, patients who received red blood cell (RBC) concentrate had a highly significant (P < 0.0001) risk of death at 30 days. Both aspirin and clopidogrel tests were useful in predicting 30 days mortality following heart surgery, suggesting the danger of diminished platelet activity prior to CABG in such high-risk patients. These preliminary evidence supports early discontinuation of antiplatelet therapy for elective CABG and requires adequately powered randomized trials to test the hypothesis and potentially improve survival.

  9. Predictive Value of Cumulative Blood Pressure for All-Cause Mortality and Cardiovascular Events

    NASA Astrophysics Data System (ADS)

    Wang, Yan Xiu; Song, Lu; Xing, Ai Jun; Gao, Ming; Zhao, Hai Yan; Li, Chun Hui; Zhao, Hua Ling; Chen, Shuo Hua; Lu, Cheng Zhi; Wu, Shou Ling

    2017-02-01

    The predictive value of cumulative blood pressure (BP) on all-cause mortality and cardiovascular and cerebrovascular events (CCE) has hardly been studied. In this prospective cohort study including 52,385 participants from the Kailuan Group who attended three medical examinations and without CCE, the impact of cumulative systolic BP (cumSBP) and cumulative diastolic BP (cumDBP) on all-cause mortality and CCEs was investigated. For the study population, the mean (standard deviation) age was 48.82 (11.77) years of which 40,141 (76.6%) were male. The follow-up for all-cause mortality and CCEs was 3.96 (0.48) and 2.98 (0.41) years, respectively. Multivariate Cox proportional hazards regression analysis showed that for every 10 mm Hg·year increase in cumSBP and 5 mm Hg·year increase in cumDBP, the hazard ratio for all-cause mortality were 1.013 (1.006, 1.021) and 1.012 (1.006, 1.018); for CCEs, 1.018 (1.010, 1.027) and 1.017 (1.010, 1.024); for stroke, 1.021 (1.011, 1.031) and 1.018 (1.010, 1.026); and for MI, 1.013 (0.996, 1.030) and 1.015 (1.000, 1.029). Using natural spline function analysis, cumSBP and cumDBP showed a J-curve relationship with CCEs; and a U-curve relationship with stroke (ischemic stroke and hemorrhagic stroke). Therefore, increases in cumSBP and cumDBP were predictive for all-cause mortality, CCEs, and stroke.

  10. Validation of trauma scales: ISS, NISS, RTS and TRISS for predicting mortality in a Colombian population.

    PubMed

    Valderrama-Molina, Carlos Oliver; Giraldo, Nelson; Constain, Alfredo; Puerta, Andres; Restrepo, Camilo; León, Alba; Jaimes, Fabián

    2017-02-01

    Our purpose was to validate the performance of the ISS, NISS, RTS and TRISS scales as predictors of mortality in a population of trauma patients in a Latin American setting. Subjects older than 15 years with diagnosis of trauma, lesions in two or more body areas according to the AIS and whose initial attention was at the hospital in the first 24 h were included. The main outcome was inpatient mortality. Secondary outcomes were admission to the intensive care unit, requirement of mechanical ventilation and length of stay. A logistic regression model for hospital mortality was fitted with each of the scales as an independent variable, and its predictive accuracy was evaluated through discrimination and calibration statistics. Between January 2007 and July 2015, 4085 subjects were enrolled in the study. 84.2% (n = 3442) were male, the mean age was 36 years (SD = 16), and the most common trauma mechanism was blunt type (80.1%; n = 3273). The medians of ISS, NISS, TRISS and RTS were: 14 (IQR = 10-21), 17 (IQR = 11-27), 4.21 (IQR = 2.95-5.05) and 7.84 (IQR = 6.90-7.84), respectively. Mortality was 9.3%, and the discrimination for ISS, NISS, TRISS and RTS was: AUC 0.85, 0.89, 0.86 and 0.92, respectively. No one scale had appropriate calibration. Determining the severity of trauma is an essential tool to guide treatment and establish the necessary resources for attention. In a Colombian population from a capital city, trauma scales have adequate performance for the prediction of mortality in patients with trauma.

  11. Speckle tracking echocardiography detects uremic cardiomyopathy early and predicts cardiovascular mortality in ESRD.

    PubMed

    Kramann, Rafael; Erpenbeck, Johanna; Schneider, Rebekka K; Röhl, Anna B; Hein, Marc; Brandenburg, Vincent M; van Diepen, Merel; Dekker, Friedo; Marx, Nicolaus; Floege, Jürgen; Becker, Michael; Schlieper, Georg

    2014-10-01

    Cardiovascular mortality is high in ESRD, partly driven by sudden cardiac death and recurrent heart failure due to uremic cardiomyopathy. We investigated whether speckle-tracking echocardiography is superior to routine echocardiography in early detection of uremic cardiomyopathy in animal models and whether it predicts cardiovascular mortality in patients undergoing dialysis. Using speckle-tracking echocardiography in two rat models of uremic cardiomyopathy soon (4-6 weeks) after induction of kidney disease, we observed that global radial and circumferential strain parameters decreased significantly in both models compared with controls, whereas standard echocardiographic readouts, including fractional shortening and cardiac output, remained unchanged. Furthermore, strain parameters showed better correlations with histologic hallmarks of uremic cardiomyopathy. We then assessed echocardiographic and clinical characteristics in 171 dialysis patients. During the 2.5-year follow-up period, ejection fraction and various strain parameters were significant risk factors for cardiovascular mortality (primary end point) in a multivariate Cox model (ejection fraction hazard ratio [HR], 0.97 [95% confidence interval (95% CI), 0.95 to 0.99; P=0.012]; peak global longitudinal strain HR, 1.17 [95% CI, 1.07 to 1.28; P<0.001]; peak systolic and late diastolic longitudinal strain rates HRs, 4.7 [95% CI, 1.23 to 17.64; P=0.023] and 0.25 [95% CI, 0.08 to 0.79; P=0.02], respectively). Multivariate Cox regression analysis revealed circumferential early diastolic strain rate, among others, as an independent risk factor for all-cause mortality (secondary end point; HR, 0.43; 95% CI, 0.25 to 0.74; P=0.002). Together, these data support speckle tracking as a postprocessing echocardiographic technique to detect uremic cardiomyopathy and predict cardiovascular mortality in ESRD.

  12. The FOUR score predicts mortality, endotracheal intubation and ICU length of stay after traumatic brain injury.

    PubMed

    Okasha, Ahmed Said; Fayed, Akram Muhammad; Saleh, Ahmad Sabry

    2014-12-01

    The Glasgow Coma Scale (GCS) is the most widely accepted scale for assessing levels of consciousness, clinical status, as well as prognosis of traumatic brain injury (TBI) patients. The Full Outline of UnResponsiveness (FOUR) score is a new coma scale developed addressing the limitations of the GCS. The aim of this prospective cohort study was to compare the performance of the FOUR score vs. the GCS in predicting TBI outcomes. From April to July 2011, 60 consecutive adult patients with TBI admitted to the Alexandria Main University Hospital intensive care units (ICU) were enrolled in the study. GCS and FOUR score were documented on arrival to emergency room. Outcomes were in-hospital mortality, unfavorable outcome [Glasgow outcome scale extended (GOSE) 1-4], endotracheal intubation, and ICU length of stay (LOS). Fifteen (25 %) patients died and 35 (58 %) had unfavorable outcome. When predicting mortality, the FOUR score showed significantly higher area under receiver operating characteristic curve (AUC) than the GCS score (0.850 vs. 0.796, p = 0.025). The FOUR score and the GCS score were not different in predicting unfavorable outcome (AUC 0.813 vs. 0.779, p = 0.136) and endotracheal intubation (AUC 0.961 vs. 0.982, p = 0.06). Both scores were good predictors of ICU LOS (r (2) = 0.40 [FOUR score] vs. 0.41 [GCS score]). The FOUR score was superior to the GCS in predicting in-hospital mortality in TBI patients. There was no difference between both scores in predicting unfavorable outcome, endotracheal intubation, and ICU LOS.

  13. Are Mortality and Acute Morbidity in Patients Presenting With Nonspecific Complaints Predictable Using Routine Variables?

    PubMed

    Jenny, Mirjam A; Hertwig, Ralph; Ackermann, Selina; Messmer, Anna S; Karakoumis, Julia; Nickel, Christian H; Bingisser, Roland

    2015-10-01

    Patients presenting to the emergency department (ED) with nonspecific complaints are difficult to accurately triage, risk stratify, and diagnose. This can delay appropriate treatment. The extent to which key medical outcomes are at all predictable in these patients, and which (if any) predictors are useful, has previously been unclear. To investigate these questions, we tested an array of statistical and machine learning models in a large group of patients and estimated the predictability of mortality (which occurred in 6.6% of our sample of patients), acute morbidity (58%), and presence of acute infectious disease (28.2%). To investigate whether the best available tools can predict the three key outcomes, we fed data from a sample of 1,278 ED patients with nonspecific complaints into 17 state-of-the-art statistical and machine learning models. The patient sample stems from a diagnostic multicenter study with prospective 30-day follow-up conducted in Switzerland. Predictability of the three key medical outcomes was quantified by computing the area under the receiver operating characteristic curve (AUC) for each model. The models performed at different levels but, on average, the predictability of the target outcomes ranged between 0.71 and 0.82. The better models clearly outperformed physicians' intuitive judgments of how ill patients looked (AUC = 0.67 for mortality, 0.65 for morbidity, and 0.60 for infectious disease). Modeling techniques can be used to derive formalized models that, on average, predict the outcomes of mortality, acute morbidity, and acute infectious disease in patients with nonspecific complaints with a level of accuracy far beyond chance. The models also predicted these outcomes more accurately than did physicians' intuitive judgments of how ill the patients look; however, the latter was among the small set of best predictors for mortality and acute morbidity. These results lay the groundwork for further refining triage and risk stratification

  14. BNP, NTproBNP, CMBK, and MMP-2 predict mortality in severe Chagas cardiomyopathy

    PubMed Central

    Sherbuk, Jacqueline E.; Okamoto, Emi E.; Marks, Morgan A.; Fortuny, Enzo; Clark, Eva H.; Galdos-Cardenas, Gerson; Vasquez-Villar, Angel; Fernandez, Antonio B.; Crawford, Thomas C.; Do, Rose Q.; Flores-Franco, Jorge Luis; Colanzi, Rony; Gilman, Robert H.; Bern, Caryn

    2015-01-01

    Background Chagas cardiomyopathy is a chronic sequela of infection by the parasite, Trypanosoma cruzi. Advanced cardiomyopathy is associated with a high mortality rate, and clinical characteristics have been used to predict mortality risk. Though multiple biomarkers have been associated with Chagas cardiomyopathy, it is unknown how these are related to survival. Objectives Our study aimed to identify biomarkers associated with mortality in individuals with severe Chagas cardiomyopathy in an urban Bolivian hospital. Methods The population included individuals with and without T. cruzi infection recruited in an urban hospital in Santa Cruz, Bolivia. Baseline characteristics, ECG findings, medications, and serum cardiac biomarker levels (BNP, NTproBNP, CKMB, troponin I, MMP-2, MMP-9, TIMP-1, TIMP-2, TGFb1, and TGFb2) were ascertained. Echocardiograms were preferentially performed on those with cardiac symptoms or electrocardiogram abnormalities. Participants were contacted by phone approximately 1 year after initial evaluation; deaths were reported by family members. Receiver operating characteristic curves were used to optimize cut-off values for each marker. For markers with area under curve > 0.55, Cox proportional hazards models were performed to determine the hazards ratio (HR) and 95% confidence interval (CI) for the association of each marker with mortality. Results The median follow-up time was 14.1 months (interquartile range 12.5- 16.7 months). Of 254 individuals with complete cardiac data, 220 (87%) had follow-up data. Of 50 patients with severe Chagas cardiomyopathy, 20 (40%) had died. Higher baseline levels of BNP (HR[95% CI]:3.1 [1.2, 8.4]), NTproBNP (4.4[1.8,11.0]), CKMB (3.3[1.3, 8.0]), and MMP-2 (4.2[1.5, 11.8]) were significantly associated with subsequent mortality. Conclusions Severe Chagas cardiomyopathy is associated with high short-term mortality. BNP, NTproBNP, CKMB and MMP2 have added predictive value for mortality, even in the presence of

  15. Does personality predict mortality? Results from the GAZEL French prospective cohort study

    PubMed Central

    Nabi, Hermann; Kivimäki, Mika; Zins, Marie; Elovainio, Marko; Consoli, Silla M.; Cordier, Sylvaine; Ducimetière, Pierre; Goldberg, Marcel; Singh-Manoux, Archana

    2008-01-01

    Background Majority of studies on personality and physical health have focused on one or two isolated personality traits. We aim to test the independent association of 10 personality traits, from three major conceptual models, with all-cause and cause-specific mortality in the French GAZEL cohort. Methods A total of 14,445 participants, aged 39–54 in 1993, completed the personality questionnaires composed of the Bortner Type-A scale, the Buss-Durkee-Hostility-Inventory (for total, neurotic and reactive hostility), and the Grossarth-Maticek-Eysenck-Personality- Stress-Inventory that assesses six personality types (cancer-prone, coronary heart disease (CHD)-prone, ambivalent, healthy, rational, anti-social). The association between personality traits and mortality, during a mean follow-up of 12.7 years, was assessed using the Relative Index of Inequality (RII) in Cox regression. Results In models adjusted for age, sex, marital status and education, all-cause and causespecific mortality were predicted by “total hostility”, its “neurotic hostility” component as well as by “CHD-prone”, “ambivalent” “antisocial”, and “healthy” personality types. After mutually adjusting personality traits for each other, only high “neurotic hostility” remained a robust predictor of excess mortality from all causes (RII=2.62; 95% CI=1.68–4.09) and external causes (RII=3.24; 95% CI=1.03–10.18). “CHD-prone” (RII=2.23; 95% CI=0.72– 6.95) and “anti-social” (RII=2.13; 95% CI 0.61–6.58) personality types were associated with cardiovascular mortality and with mortality from external causes, respectively, but confidence intervals were wider. Adjustment for potential behavioural mediators had only a modest effect on these associations. Conclusions Neurotic hostility, CHD-prone personality and antisocial personality were all predictive of mortality outcomes. Further research is required to determine the precise mechanisms that contribute to these

  16. The predictive value of malnutrition - inflammation score on 1-year mortality in Turkish maintenance hemodialysis patients.

    PubMed

    Kara, Ekrem; Sahutoglu, Tuncay; Ahbap, Elbis; Sakaci, Tamer; Koc, Yener; Basturk, Taner; Sevinc, Mustafa; Akgol, Cuneyt; Unsal, Abdulkadir

    2016-08-01

    The aim of this study was to evaluate the predictive value of malnutrition-inflammation score (MIS) on short-term mortality and to identify the best cut-off point in the Turkish maintenance hemodialysis (MHD) population. A total of 100 patients on MHD were included in this prospective single-center study. Demographic, anthropometric, and biochemical data were obtained from all patients. The study population was followed up as a 12-month prospective cohort to evaluate mortality as the primary outcome. Median (IQR) age and HD vintage of 100 patients (M/F: 52/48) were 53 (39.5 - 67) years and 53.5 (11 - 104.7) months, respectively. Deceased patients (n = 7) had significantly older age (years) (50 (38.5 - 63.5) vs. 70 (62 - 82), respectively, p = 0.001), lower spKt/V (1.60 (1.40 - 1.79) vs. 1.35 (0.90 - 1.50), respectively, p = 0.002), lower triceps skinfold thickness (14 (10 - 19) vs. 9 (7 - 11), respectively, p = 0.021) and higher MIS (5 (4 - 7) vs. 10 (7 - 11), respectively, p = 0.013). In the ROC analysis, we found that the optimal cut-off value of MIS for predicting death was 6.5 with 85.7% sensitivity and 62.4% specificity (positive and negative predictive values were 0.6951 and 0.8136, respectively). Advanced age, low spKt/V, and high MIS were found to be predictors of mortality in multivariate logistic regression analysis. The 1-year mortality rate was significantly higher in MIS > 6.5 group compared to the MIS ≤ 6.5 group (14,3% (6/41) vs. 1.6% (1/59), respectively). Compared to MIS ≤ 6.5 group, 1 year survival time of the patients with MIS > 6.5 was found to be significantly lower (47.8 ± 0.16 vs. 43.6 ± 1.63 weeks, respectively, p (log-rank) = 0.012). MIS is a robust and independent predictor of short-term mortality in MHD patients. Patients with MIS > 6.5 had a significant risk, and additional risk factors associated with short-term mortality were advanced age and low spKt/V.

  17. Combination of biomarkers to predict mortality in elderly patients with myocardial infarction.

    PubMed

    Olivieri, Fabiola; Spazzafumo, Liana; Antonicelli, Roberto; Marchegiani, Francesca; Cardelli, Maurizio; Sirolla, Cristina; Galeazzi, Roberta; Giovagnetti, Simona; Mocchegiani, Eugenio; Franceschi, Claudio

    2008-04-01

    The elderly subjects affected by Acute Myocardial Infarction (AMI) have the highest risk of mortality. Our study was designed to improve the capability of mortality risk stratification in elderly AMI patients through the concurrent evaluations of different biomarkers, including genetic markers. One-year follow-up study was performed in 250 elderly AMI patients. The combination of high total Homocysteine (tHcy), low folate and vitamin B12 plasma levels (18.0+/-9.0 micromol/l; 4.4+/-1.2 ng/ml; 404.2+/-287.5 pg/ml, respectively) and elevated CRP plasma levels (> or =6 mg/dl) identify the highest-risk pathway of heart mortality (RR=4.20, IC 95% 1.62-10.89, P<0.002) with respect to the combination of low total tHcy, high folate and vitamin B12 plasma levels (12.4+/-5.2 micromol/l; 8.9+/-2.5 ng/ml; 546.9+/-379.8 pg/ml, respectively) and low CRP plasma levels (<6 mg/dl). In elderly AMI patients the concomitant elevation of CRP and tHcy, associated with folate and vitamin B12 low levels, could be considered a significant predictive heart mortality risk factor.

  18. Electrocardiographic Left Ventricular Hypertrophy Predicts Cardiovascular Morbidity and Mortality in Hypertensive Patients: The ALLHAT Study.

    PubMed

    Bang, Casper N; Soliman, Elsayed Z; Simpson, Lara M; Davis, Barry R; Devereux, Richard B; Okin, Peter M

    2017-09-01

    Electrocardiographic (ECG) left ventricular hypertrophy (LVH) is a strong predictor of cardiovascular (CV) morbidity and mortality. However, the predictive value of ECG LVH in treated hypertensive patients remains unclear. A total of 33,357 patients (aged ≥ 55 years) with hypertension and at least 1 other coronary heart disease (CHD) risk factor were randomized to chlorthalidone, amlodipine, or lisinopril. The outcome of the present study was all-cause mortality; and secondary endpoints were CHD, nonfatal myocardial infarction (MI), stroke, angina, heart failure (HF), and peripheral arterial disease. Cornell voltage criteria (S in V3 + R in aVL > 28 [men] or >22 mm [women]) defined ECG LVH. ECGs were available at baseline in 26,384 patients. Baseline Cornell voltage LVH was present in 1,741 (7%) patients, who were older (67.4 vs. 66.6 years, P < 0.001), more likely to be female (74 vs. 44%, P < 0001) with a higher systolic blood pressure (151 vs. 146 mm Hg, P < 0.001) than patients without ECG LVH. During 5.0 ± 1.4 years mean follow-up, baseline and in-study ECG LVH was significantly associated with 29 to 98% increased risks of all-cause mortality, MI, CHD, stroke, and HF in multivariable Cox analyses. Baseline Cornell voltage LVH is associated with increased CV morbidity and all-cause mortality in treated hypertensive patients independent of treatment modality and other CV risk factors. Trial Number NCT00000542.

  19. The Feasibility of Measuring Frailty to Predict Disability and Mortality in Older Medical-ICU Survivors

    PubMed Central

    Baldwin, Matthew R.; Reid, M. Cary; Westlake, Amanda A.; Rowe, John W.; Granieri, Evelyn C.; Wunsch, Hannah; Dam, Tien; Rabinowitz, Daniel; Goldstein, Nathan E.; Maurer, Mathew S.; Lederer, David J.

    2014-01-01

    Purpose To determine whether frailty can be measured within 4 days prior to hospital discharge in older ICU survivors of respiratory failure, and whether it is associated with post-discharge disability and mortality. Materials and Methods We performed a single center prospective cohort study of 22 medical-ICU survivors age ≥ 65 years old who had received non-invasive or invasive mechanical ventilation for at least 24 hours. Frailty was defined as a score of ≥ 3 using Fried’s 5-point scale. We measured disability with the Katz Activities of Daily Living. We estimated unadjusted associations between Fried’s frailty score and incident disability at 1-month and 6-month mortality using Cox proportional hazard models. Results The mean (standard deviation) age was 77 (9) years, mean APACHE II score was 27 (9.7), mean frailty score was 3.4 (1.3), and 18 (82%) were frail. Nine subjects (41%) died within 6 months, and all were frail. Each 1-point increase in frailty score was associated with a 90% increased rate of incident disability at 1-month (rate ratio: 1.9, 95% CI 0.7-4.9) and a threefold increase in 6-month mortality (rate ratio: 3.0, 95% CI 1.4-6.3). Conclusions:Frailty can be measured in older ICU survivors near hospital discharge and is associated with 6-month mortality in unadjusted analysis. Larger studies to determine if frailty independently predicts outcomes are warranted. PMID:24559575

  20. Dengue fever mortality score: A novel decision rule to predict death from dengue fever.

    PubMed

    Huang, Chien-Cheng; Hsu, Chien-Chin; Guo, How-Ran; Su, Shih-Bin; Lin, Hung-Jung

    2017-09-27

    Dengue fever (DF) is still a major challenge for public health, especially during massive outbreaks. We developed a novel prediction score to help decision making, which has not been performed till date. We conducted a retrospective case-control study to recruit all the DF patients who visited a medical center during the 2015 DF outbreak. Demographic data, vital signs, symptoms/signs, chronic comorbidities, laboratory data, and 30-day mortality rates were included in the study. Univariate analysis and multivariate logistic regression analysis were used to identify the independent mortality predictors, which further formed the components of a DF mortality (DFM) score. Bootstrapping method was used to validate the DFM score. In total, a sample of 2358 DF patients was included in this study, which also consisted of 34 deaths (1.44%). Five independent mortality predictors were identified: elderly age (≥65 years), hypotension (systolic blood pressure <90 mmHg), hemoptysis, diabetes mellitus, and chronic bedridden. After assigning each predictor a score of "1", we developed a DFM score (range: 0-5), which showed that the mortality risk ratios for scores 0, 1, 2, and ≥3 were 0.2%, 2.3%, 6.0%, and 45.5%, respectively. The area under the curve was 0.849 (95% confidence interval [CI]: 0.785-0.914), and Hosmer-Lemeshow goodness-of-fit was 0.642. Compared with score 0, the odds ratios for mortality were 12.73 (95% CI: 3.58-45.30) for score 1, 34.21 (95% CI: 9.75-119.99) for score 2, and 443.89 (95% CI: 86.06-2289.60) for score ≥3, with significant differences (all p values <0.001). The score ≥1 had a sensitivity of 91.2% for mortality and score ≥3 had a specificity of 99.7% for mortality. DFM score was a simple and easy method to help decision making, especially in the massive outbreak. Further studies in other hospitals or nations are warranted to validate this score. Copyright © 2017. Published by Elsevier Ltd.

  1. Similar support for three different life course socioeconomic models on predicting premature cardiovascular mortality and all-cause mortality

    PubMed Central

    Rosvall, Maria; Chaix, Basile; Lynch, John; Lindström, Martin; Merlo, Juan

    2006-01-01

    Background There are at least three broad conceptual models for the impact of the social environment on adult disease: the critical period, social mobility, and cumulative life course models. Several studies have shown an association between each of these models and mortality. However, few studies have investigated the importance of the different models within the same setting and none has been performed in samples of the whole population. The purpose of the present study was to study the relation between socioeconomic position (SEP) and mortality using different conceptual models in the whole population of Scania. Methods In the present investigation we use socioeconomic information on all men (N = 48,909) and women (N = 47,688) born between 1945 and 1950, alive on January, 1st,1990, and living in the Region of Scania, in Sweden. Focusing on three specific life periods (i.e., ages 10–15, 30–35 and 40–45), we examined the association between SEP and the 12-year risk of premature cardiovascular mortality and all-cause mortality. Results There was a strong relation between SEP and mortality among those inside the workforce, irrespective of the conceptual model used. There was a clear upward trend in the mortality hazard rate ratios (HRR) with accumulated exposure to manual SEP in both men (p for trend < 0.001 for both cardiovascular and all-cause mortality) and women (p for trend = 0.01 for cardiovascular mortality) and (p for trend = 0.003 for all-cause mortality). Inter- and intragenerational downward social mobility was associated with an increased mortality risk. When applying similar conceptual models based on workforce participation, it was shown that mortality was affected by the accumulated exposure to being outside the workforce. Conclusion There was a strong relation between SEP and cardiovascular and all-cause mortality, irrespective of the conceptual model used. The critical period, social mobility, and cumulative life course models, showed the same

  2. Admission Risk Score to Predict Inpatient Pediatric Mortality at Four Public Hospitals in Uganda

    PubMed Central

    Mpimbaza, Arthur; Sears, David; Sserwanga, Asadu; Kigozi, Ruth; Rubahika, Denis; Nadler, Adam; Yeka, Adoke; Dorsey, Grant

    2015-01-01

    Mortality rates among hospitalized children in many government hospitals in sub-Saharan Africa are high. Pediatric emergency services in these hospitals are often sub-optimal. Timely recognition of critically ill children on arrival is key to improving service delivery. We present a simple risk score to predict inpatient mortality among hospitalized children. Between April 2010 and June 2011, the Uganda Malaria Surveillance Project (UMSP), in collaboration with the National Malaria Control Program (NMCP), set up an enhanced sentinel site malaria surveillance program for children hospitalized at four public hospitals in different districts: Tororo, Apac, Jinja and Mubende. Clinical data collected through March 2013, representing 50249 admissions were used to develop a mortality risk score (derivation data set). One year of data collected subsequently from the same hospitals, representing 20406 admissions, were used to prospectively validate the performance of the risk score (validation data set). Using a backward selection approach, 13 out of 25 clinical parameters recognizable on initial presentation, were selected for inclusion in a final logistic regression prediction model. The presence of individual parameters was awarded a score of either 1 or 2 based on regression coefficients. For each individual patient, a composite risk score was generated. The risk score was further categorized into three categories; low, medium, and high. Patient characteristics were comparable in both data sets. Measures of performance for the risk score included the receiver operating characteristics curves and the area under the curve (AUC), both demonstrating good and comparable ability to predict deathusing both the derivation (AUC =0.76) and validation dataset (AUC =0.74). Using the derivation and validation datasets, the mortality rates in each risk category were as follows: low risk (0.8% vs. 0.7%), moderate risk (3.5% vs. 3.2%), and high risk (16.5% vs. 12.6%), respectively. Our

  3. The Aristotle score predicts mortality after surgery of patent ductus arteriosus in preterm infants.

    PubMed

    Chang, Yun Hee; Lee, Jae Young; Kim, Jeong Eun; Kim, Ji-yong; Youn, YoungAh; Lee, Eun-Jung; Moon, Sena; Lee, Ju Young; Sung, In Kyung

    2013-09-01

    Outcomes after surgical ligation of patent ductus arteriosus (PDA) in preterm infants are often complicated by prematurity associated comorbidities. The Aristotle comprehensive complexity score (ACCS) has been proposed as a useful tool for complexity adjustment in the analysis of outcome after congenital heart surgery. The aims of this study were to define preoperative risk factors for mortality and to demonstrate the usefulness of ACCS to predict mortality after surgical ligation of PDA in the preterm. Included were 49 preterm babies (≤35 weeks of gestation) who had surgical ligation of PDA between May 2009 and July 2012. Median gestational age was 27.6 weeks (range, 23 to 35 weeks) and median birth weight was 1,040 g (range, 520 to 2,280 g). Median age at operation was 15 days (range, 4 to 44 days) and median weight was 1,120 g (range, 400 to 2,880 g). Initial oral ibuprofen was ineffective in 24 patients and contraindicated in 25. All surgical ligations were done at bedside in the neonatal intensive care unit. Preoperative clinical and laboratory profiles were reviewed and ACCS was derived. Eight of 49 patients (16.3%) died at a median of 14 days (range, 2 to 73 days) after PDA ligation. Patients who had contraindications for oral ibuprofen (odds ratio [OR] 8.94; p=0.049), coagulopathy (OR 12.13; p=0.025), renal dysfunction (OR 28.88; p=0.003), intraventricular hemorrhage greater than grade II or seizure (OR 34.00; p=0.002), and ACCS points (OR 29.594; p<0.05) were significantly associated with an increased risk for mortality. Among the risk factors, ACCS showed the largest area under curve (0.991) by receiver-operating characteristic curve analysis. Optimal cutoff value of ACCS for mortality were 15 or greater, with sensitivity of 87.5%, specificity of 100%, positive predictive value of 100%, and negative predictive value of 97.6%. The ACCS, especially for procedure-independent complexity factors, is a useful tool to predict mortality after ligation of PDA in

  4. Admission Risk Score to Predict Inpatient Pediatric Mortality at Four Public Hospitals in Uganda.

    PubMed

    Mpimbaza, Arthur; Sears, David; Sserwanga, Asadu; Kigozi, Ruth; Rubahika, Denis; Nadler, Adam; Yeka, Adoke; Dorsey, Grant

    2015-01-01

    Mortality rates among hospitalized children in many government hospitals in sub-Saharan Africa are high. Pediatric emergency services in these hospitals are often sub-optimal. Timely recognition of critically ill children on arrival is key to improving service delivery. We present a simple risk score to predict inpatient mortality among hospitalized children. Between April 2010 and June 2011, the Uganda Malaria Surveillance Project (UMSP), in collaboration with the National Malaria Control Program (NMCP), set up an enhanced sentinel site malaria surveillance program for children hospitalized at four public hospitals in different districts: Tororo, Apac, Jinja and Mubende. Clinical data collected through March 2013, representing 50249 admissions were used to develop a mortality risk score (derivation data set). One year of data collected subsequently from the same hospitals, representing 20406 admissions, were used to prospectively validate the performance of the risk score (validation data set). Using a backward selection approach, 13 out of 25 clinical parameters recognizable on initial presentation, were selected for inclusion in a final logistic regression prediction model. The presence of individual parameters was awarded a score of either 1 or 2 based on regression coefficients. For each individual patient, a composite risk score was generated. The risk score was further categorized into three categories; low, medium, and high. Patient characteristics were comparable in both data sets. Measures of performance for the risk score included the receiver operating characteristics curves and the area under the curve (AUC), both demonstrating good and comparable ability to predict deathusing both the derivation (AUC =0.76) and validation dataset (AUC =0.74). Using the derivation and validation datasets, the mortality rates in each risk category were as follows: low risk (0.8% vs. 0.7%), moderate risk (3.5% vs. 3.2%), and high risk (16.5% vs. 12.6%), respectively. Our

  5. High blood pressure variability predicts 30-day mortality but not 1-year mortality in hospitalized elderly patients.

    PubMed

    Weiss, Avraham; Rudman, Yaron; Beloosesky, Yichayaou; Akirov, Amit; Shochat, Tzippy; Grossman, Alon

    2017-10-01

    The association of blood pressure (BP) variability (BPV) in hospitalized patients, which represents day-to-day variability, with mortality has been extensively reported in patients with stroke, but poorly defined for other medical conditions. To assess the association of day-to-day blood pressure variability in hospitalized patients, 10 BP measurements were obtained in individuals ≥75 years old hospitalized in a geriatric ward. Day-to-day BPV, measured 3 times a day, was calculated in each patient as the coefficient of variation of systolic BP. Patients were stratified by quartiles of coefficient of variation of systolic BP, and 30-day and 1-year mortality data were compared between those in the highest versus the lowest (reference) group. Overall, 469 patients were included in the final analysis. Mean coefficient of variation of systolic BP was 12.1%. 30-day mortality and 1-year mortality occurred in 29/469 (6.2%) and 95/469 (20.2%) individuals respectively. Patients in the highest quartile of BPV were at a significantly higher risk for 30-day mortality (HR =4.12, CI 1.12-15.10) but not for 1-year mortality compared with the lowest BPV quartile (HR =1.61, CI 0.81-3.23). Day-to-day BPV is associated with 30-day, but not with 1-year mortality in hospitalized elderly patients.

  6. Clinical and Genetic Factors Predictive of Mortality in Early Systemic Sclerosis

    PubMed Central

    Assassi, Shervin; del Junco, Deborah; Sutter, Kari; McNearney, Terry A.; Reveille, John D.; Karnavas, Andrew; Gourh, Pravitt; Estrada-Y-Martin, Rosa M.; Fischbach, Michael; Arnett, Frank C.; Mayes, Maureen D.

    2010-01-01

    Objective To investigate the clinical and genetic variables at initial presentation that predict survival in the Genetics versus Environment in Scleroderma Outcome Study (GENISOS) cohort. Methods GENISOS is a prospective, observational study of a multiethnic early systemic sclerosis (SSc) cohort. To date, a total of 250 patients have been enrolled. In addition to clinical and laboratory data, electrocardiograms (EKGs), chest radiographs, and pulmonary function tests have been obtained from each patient. A modified Rodnan skin thickness score, HLA class II genotyping, and a Medsger Damage Index also have been collected. We performed multivariable analyses utilizing the Cox regression following a purposeful model building strategy. Results The study analyzed 122 white, 47 African American, and 71 Hispanic SSc patients with an average disease duration of 2.6 years at enrollment. At the time of analysis, 52 (20.8%) of the 250 patients had died. In the final multivariable model excluding HLA genes, 7 variables emerged as significant predictors of mortality: age ≥65 years at enrollment, forced vital capacity <50% predicted, clinically significant arrhythmia on EKG, absence of anticentromere antibodies, hypertension, chest radiograph suggestive of pulmonary fibrosis, and low body mass index (BMI). In separate modeling that included HLA genes, HLA alleles DRB1*0802 and DQA1*0501 were significant predictors of mortality in addition to the predictors mentioned above. Conclusion A limited number of variables collected at presentation, including BMI, are able to predict mortality in patients with early SSc. In addition, some of the HLA genes associated with SSc susceptibility are useful for predicting SSc outcome. PMID:19790132

  7. A one-year mortality clinical prediction rule for patients with heart failure.

    PubMed

    Escobar, Antonio; García-Pérez, Lidia; Navarro, Gemma; Bilbao, Amaia; Quiros, Raul

    2017-06-19

    To create and validate a clinical prediction rule which is easy to manage, reproducible and that allows classifying patients admitted for heart failure according to their one-year mortality risk. A prospective cohort study carried out with 2565 consecutive patients admitted with heart failure in 13 hospitals in Spain. The derivation cohort was made up of 1283 patients and 1282 formed the validation cohort. In the derivation cohort, we carried out a multivariate logistic model to predict one-year mortality. The performance of the derived predictive risk score was externally validated in the validation cohort, and internally validated by K-fold cross-validation. The risk score was categorized into four risk levels. The mean age was 77.2years, 49.7% were female and there were 611 (23.8%) deaths in the follow-up period. The variables included in the predictive model were: age≥75, systolic blood pressure<135, New York Heart Association class III-IV, heart valve disease, dementia, prior hospitalization, haemoglobin<13, sodium<136, urea≥86, length of stay≥14 and Physical dimension of Minnesota Living with Heart Failure questionnaire. The AUC for the risk score were 0.73 and 0.70 in the derivation and validation cohorts, respectively, and 0.73 in the K-fold cross-validation. The percentage of mortality ranged from 8.08% in the low-risk to 58.20% in the high-risk groups (p<0.0001; AUC, 0.72). This model based on routinely available data, for admitted patients and with a follow-up at one year is a simple and easy-to-use tool for improving management of patients with heart failure. Copyright © 2017 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

  8. Serum creatinine level, a surrogate of muscle mass, predicts mortality in critically ill patients.

    PubMed

    Thongprayoon, Charat; Cheungpasitporn, Wisit; Kashani, Kianoush

    2016-05-01

    Serum creatinine (SCr) has been widely used to estimate glomerular filtration rate (GFR). Creatinine generation could be reduced in the setting of low skeletal muscle mass. Thus, SCr has also been used as a surrogate of muscle mass. Low muscle mass is associated with reduced survival in hospitalized patients, especially in the intensive care unit (ICU) settings. Recently, studies have demonstrated high mortality in ICU patients with low admission SCr levels, reflecting that low muscle mass or malnutrition, are associated with increased mortality. However, SCr levels can also be influenced by multiple GFR- and non-GFR-related factors including age, diet, exercise, stress, pregnancy, and kidney disease. Imaging techniques, such as computed tomography (CT) and ultrasound, have recently been studied for muscle mass assessment and demonstrated promising data. This article aims to present the perspectives of the uses of SCr and other methods for prediction of muscle mass and outcomes of ICU patients.

  9. Variation in GYS1 Interacts with Exercise and Gender to Predict Cardiovascular Mortality

    PubMed Central

    Fredriksson, Jenny; Anevski, Dragi; Almgren, Peter; Sjögren, Marketa; Lyssenko, Valeriya; Carlson, Joyce; Isomaa, Bo; Taskinen, Marja-Riitta; Groop, Leif; Orho-Melander, Marju

    2007-01-01

    Background The muscle glycogen synthase gene (GYS1) has been associated with type 2 diabetes (T2D), the metabolic syndrome (MetS), male myocardial infarction and a defective increase in muscle glycogen synthase protein in response to exercise. We addressed the questions whether polymorphism in GYS1 can predict cardiovascular (CV) mortality in a high-risk population, if this risk is influenced by gender or physical activity, and if the association is independent of genetic variation in nearby apolipoprotein E gene (APOE). Methodology/Principal Findings Polymorphisms in GYS1 (XbaIC>T) and APOE (-219G>T, ε2/ε3/ε4) were genotyped in 4,654 subjects participating in the Botnia T2D-family study and followed for a median of eight years. Mortality analyses were performed using Cox proportional-hazards regression. During the follow-up period, 749 individuals died, 409 due to CV causes. In males the GYS1 XbaI T-allele (hazard ratio (HR) 1.9 [1.2–2.9]), T2D (2.5 [1.7–3.8]), earlier CV events (1.7 [1.2–2.5]), physical inactivity (1.9 [1.2–2.9]) and smoking (1.5 [1.0–2.3]) predicted CV mortality. The GYS1 XbaI T-allele predicted CV mortality particularly in physically active males (HR 1.7 [1.3–2.0]). Association of GYS1 with CV mortality was independent of APOE (219TT/ε4), which by its own exerted an effect on CV mortality risk in females (2.9 [1.9–4.4]). Other independent predictors of CV mortality in females were fasting plasma glucose (1.2 [1.1–1.2]), high body mass index (BMI) (1.0 [1.0–1.1]), hypertension (1.9 [1.2–3.1]), earlier CV events (1.9 [1.3–2.8]) and physical inactivity (1.9 [1.2–2.8]). Conclusions/Significance Polymorphisms in GYS1 and APOE predict CV mortality in T2D families in a gender-specific fashion and independently of each other. Physical exercise seems to unmask the effect associated with the GYS1 polymorphism, rendering carriers of the variant allele less susceptible to the protective effect of exercise on the risk of CV death

  10. In Nonagenarians, Acute Kidney Injury Predicts In-Hospital Mortality, while Heart Failure Predicts Hospital Length of Stay

    PubMed Central

    Chao, Chia-Ter; Lin, Yu-Feng; Tsai, Hung-Bin; Hsu, Nin-Chieh; Tseng, Chia-Lin; Ko, Wen-Je

    2013-01-01

    Background/Aims The elderly constitute an increasing proportion of admitted patients worldwide. We investigate the determinants of hospital length of stay and outcomes in patients aged 90 years and older. Methods We retrospectively analyzed all admitted patients aged >90 years from the general medical wards in a tertiary referral medical center between August 31, 2009 and August 31, 2012. Patients’ clinical characteristics, admission diagnosis, concomitant illnesses at admission, and discharge diagnosis were collected. Each patient was followed until discharge or death. Multivariate logistic regression analysis was utilized to study factors associated with longer hospital length of stay (>7 days) and in-hospital mortality. Results A total of 283 nonagenarian in-patients were recruited, with 118 (41.7%) hospitalized longer than one week. Nonagenarians admitted with pneumonia (p = 0.04) and those with lower Barthel Index (p = 0.012) were more likely to be hospitalized longer than one week. Multivariate logistic regression analysis revealed that patients with lower Barthel Index (odds ratio [OR] 0.98; p = 0.021) and those with heart failure (OR 3.05; p = 0.046) had hospital stays >7 days, while patients with lower Barthel Index (OR 0.93; p = 0.005), main admission nephrologic diagnosis (OR 4.83; p = 0.016) or acute kidney injury (OR 30.7; p = 0.007) had higher in-hospital mortality. Conclusion In nonagenarians, presence of heart failure at admission was associated with longer hospital length of stay, while acute kidney injury at admission predicted higher hospitalization mortality. Poorer functional status was associated with both prolonged admission and higher in-hospital mortality. PMID:24223127

  11. Pretransplant comorbidities predict severity of acute graft-versus-host disease and subsequent mortality

    PubMed Central

    Martin, Paul J.; Storb, Rainer F.; Bhatia, Smita; Maziarz, Richard T.; Pulsipher, Michael A.; Maris, Michael B.; Davis, Christopher; Deeg, H. Joachim; Lee, Stephanie J.; Maloney, David G.; Sandmaier, Brenda M.; Appelbaum, Frederick R.; Gooley, Theodore A.

    2014-01-01

    Whether the hematopoietic cell transplantation comorbidity index (HCT-CI) can provide prognostic information about development of acute graft-versus-host disease (GVHD) and subsequent mortality is unknown. Five institutions contributed information on 2985 patients given human leukocyte antigen-matched grafts to address this question. Proportional hazards models were used to estimate the hazards of acute GVHD and post-GVHD mortality after adjustment for known risk variables. Higher HCT-CI scores predicted increased risk of grades 3 to 4 acute GVHD (P < .0001 and c-statistic of 0.64), and tests of interaction suggested that this association was consistent among different conditioning intensities, donor types, and stem cell sources. Probabilities of grades 3 to 4 GVHD were 13%, 18%, and 24% for HCT-CI risk groups of 0, 1 to 4, and ≥5. The HCT-CI was statistically significantly associated with mortality rates following diagnosis of grade 2 (hazard ratio [HR] = 1.24; P < .0001) or grades 3 to 4 acute GVHD (HR = 1.19; P < .0001). Patients with HCT-CI scores of ≥3 who developed grades 3 to 4 acute GVHD had a 2.63-fold higher risk of mortality than those with scores of 0 to 2 and did not develop acute GVHD. Thus, pretransplant comorbidities are associated with the development and severity of acute GVHD and with post-GVHD mortality. The HCT-CI could be useful in designing trials for GVHD prevention and could inform expectations for GVHD treatment trials. PMID:24797298

  12. Predicting later life health status and mortality using state-level socioeconomic characteristics in early life.

    PubMed

    Hamad, Rita; Rehkopf, David H; Kuan, Kai Y; Cullen, Mark R

    2016-12-01

    Studies extending across multiple life stages promote an understanding of factors influencing health across the life span. Existing work has largely focused on individual-level rather than area-level early life determinants of health. In this study, we linked multiple data sets to examine whether early life state-level characteristics were predictive of health and mortality decades later. The sample included 143,755 U.S. employees, for whom work life claims and administrative data were linked with early life state-of-residence and mortality. We first created a "state health risk score" (SHRS) and "state mortality risk score" (SMRS) by modeling state-level contextual characteristics with health status and mortality in a randomly selected 30% of the sample (the "training set"). We then examined the association of these scores with objective health status and mortality in later life in the remaining 70% of the sample (the "test set") using multivariate linear and Cox regressions, respectively. The association between the SHRS and adult health status was β=0.14 (95%CI: 0.084, 0.20), while the hazard ratio for the SMRS was 0.96 (95%CI: 0.93, 1.00). The association between the SHRS and health was not statistically significant in older age groups at a p-level of 0.05, and there was a statistically significantly different association for health status among movers compared to stayers. This study uses a life course perspective and supports the idea of "sensitive periods" in early life that have enduring impacts on health. It adds to the literature examining populations in the U.S. where large linked data sets are infrequently available.

  13. Can photoperiod predict mortality in the 1918-1920 influenza pandemic?

    PubMed

    Prendergast, Brian J

    2011-08-01

    Amplitude of the seasonal change in day length increases with distance from the equator, and changes in day length markedly alter immune function in diverse nonhuman animal models of infection. Historical records of mortality data, ambient temperature, population density, geography, and economic indicators from 42 countries during 1918-1920 were analyzed to determine relative contributions toward human mortality during the "Spanish" influenza pandemic of 1918-1920. The data identify a strong negative relation between distance from the equator and mortality during the 1918-1920 influenza pandemic, which, in a multiple regression model, manifested independent of major economic, demographic, and temperature variables. Enhanced survival was evident in populations that experienced a winter nadir day length ≤10 h light/day, relative to those that experienced lower amplitude changes in photoperiod. Numerous reports indicate that exposure to short day lengths, typical of those occurring outside the tropics during winter, yields robust and enduring reductions in the magnitude of cytokine, febrile, and behavioral responses to infection. The present results are preliminary but prompt the conjecture that, if similar mechanisms are operant in humans, then they would be predicted to mitigate symptoms of infection in proportion to an individual's distance from the equator. Although limitations and uncertainties accompany regression-based analyses of historical epidemiological data, latitude, per se, may be an underrecognized factor in mortality during the 1918-1920 influenza pandemic. The author proposes that some proportion of the global variance in morbidity and mortality from infectious diseases may be explained by effects of day length on the innate immune response to infection.

  14. The Change in Body Weight During Hospitalization Predicts Mortality in Patients With Acute Decompensated Heart Failure

    PubMed Central

    Komaki, Tomo; Miura, Shin-ichiro; Arimura, Tadaaki; Shiga, Yuhei; Morii, Joji; Kuwano, Takashi; Imaizumi, Satoshi; Kitajima, Ken; Iwata, Atsushi; Morito, Natsumi; Yahiro, Eiji; Fujimi, Kanta; Matsunaga, Akira; Saku, Keijiro

    2017-01-01

    Background In our experience, the change in body weight (BW) during hospitalization varies greatly in patients with acute decompensated heart failure (HF). Since the clinical significance of a change in BW is not clear, we investigated whether a change in BW could predict mortality. Methods We retrospectively enrolled 130 patients (72 males; aged 68 ± 10 years) who were hospitalized due to acute decompensated HF and followed for 2 years after discharge. The change in the BW index during hospitalization (ΔBWI) was calculated as (BW at hospital admission minus BW at hospital discharge)/body surface area at hospital discharge. Results The patients were divided into quartiles according to ΔBWI, and the 2-year mortality rates in the quartiles with the lowest, second, third and highest ΔBWI were 18.8%, 12.1%, 3.1% and 9.1%, respectively. In a multivariate Cox proportional hazards analysis after adjusting for variables with a P value less than 0.05, ΔBWI was independently associated with 2-year mortality (P = 0.0002), and the quartile with the lowest ΔBWI had a higher relative risk (RR) for 2-year mortality than the quartile with the highest ΔBWI (RR: 7.46, 95% confidence interval: 1.03 - 53.99, P = 0.04). Conclusion In conclusion, ΔBWI was significantly associated with 2-year mortality after discharge, which indicates that ΔBWI might be a simple predictor of prognosis in acute decompensated HF. PMID:28179967

  15. Monocyte/high-density lipoprotein ratio predicts the mortality in ischemic stroke patients.

    PubMed

    Bolayir, Asli; Gokce, Seyda Figul; Cigdem, Burhanettin; Bolayir, Hasan Ata; Yildiz, Ozlem Kayim; Bolayir, Ertugrul; Topaktas, Suat Ahmet

    2017-08-24

    The inflammatory process is a very important stage in the development and prognosis of acute ischemic stroke (AIS). The monocyte to high-density lipoprotein (HDL) ratio (MHR) is accepted as a novel marker for demonstrating inflammation. However, the role of MHR as a predictor of mortality in patients with AIS remains unclear. We retrospectively enrolled 466 patients who were referred to our clinic within the first 24hours of symptom presentation and who were diagnosed with AIS between January 2008 and June 2016. Four hundred and eight controls of similar age and gender were also included. The patient group was classified into two groups according to 30-day mortality. The groups were compared in terms of monocyte counts, HDL, and MHR values. The patient group had significantly higher monocyte counts and lower HDL levels; therefore, this group had higher values of MHR compared to controls. Additionally, the monocyte count and MHR value were higher, and the HDL level was lower in non-surviving patients (p<0.001). The MHR value was also observed as a significant independent variable of 30-day mortality in patients with AIS (p<0.001). The optimum cut-off value of MHR in predicting the 30-day mortality for patients with AIS was 17.52 (95% CI 0.95-0.98). Our study demonstrated that a high MHR value is an independent predictor of 30-day mortality in patients with AIS. Copyright © 2017 Polish Neurological Society. Published by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

  16. 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.

  17. A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis.

    PubMed

    Bastos, Helder Novais; Osório, Nuno S; Castro, António Gil; Ramos, Angélica; Carvalho, Teresa; Meira, Leonor; Araújo, David; Almeida, Leonor; Boaventura, Rita; Fragata, Patrícia; Chaves, Catarina; Costa, Patrício; Portela, Miguel; Ferreira, Ivo; Magalhães, Sara Pinto; Rodrigues, Fernando; Sarmento-Castro, Rui; Duarte, Raquel; Guimarães, João Tiago; Saraiva, Margarida

    2016-01-01

    Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8-7.9), age ≥50 years (OR 2.9, 95% CI 1.7-4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4-4.4), ≥1 significant comorbidity-HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease-(OR 2.3, 95% CI 1.3-3.8), and hemoglobin <12 g/dL (OR 1.8, 95% CI 1.1-3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score ≤2), moderate (score 3-5) and high (score ≥6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment.

  18. A Prediction Rule to Stratify Mortality Risk of Patients with Pulmonary Tuberculosis

    PubMed Central

    Osório, Nuno S.; Castro, António Gil; Ramos, Angélica; Carvalho, Teresa; Meira, Leonor; Araújo, David; Almeida, Leonor; Boaventura, Rita; Fragata, Patrícia; Chaves, Catarina; Costa, Patrício; Portela, Miguel; Ferreira, Ivo; Magalhães, Sara Pinto; Rodrigues, Fernando; Sarmento-Castro, Rui; Duarte, Raquel; Guimarães, João Tiago; Saraiva, Margarida

    2016-01-01

    Tuberculosis imposes high human and economic tolls, including in Europe. This study was conducted to develop a severity assessment tool for stratifying mortality risk in pulmonary tuberculosis (PTB) patients. A derivation cohort of 681 PTB cases was retrospectively reviewed to generate a model based on multiple logistic regression analysis of prognostic variables with 6-month mortality as the outcome measure. A clinical scoring system was developed and tested against a validation cohort of 103 patients. Five risk features were selected for the prediction model: hypoxemic respiratory failure (OR 4.7, 95% CI 2.8–7.9), age ≥50 years (OR 2.9, 95% CI 1.7–4.8), bilateral lung involvement (OR 2.5, 95% CI 1.4–4.4), ≥1 significant comorbidity—HIV infection, diabetes mellitus, liver failure or cirrhosis, congestive heart failure and chronic respiratory disease–(OR 2.3, 95% CI 1.3–3.8), and hemoglobin <12 g/dL (OR 1.8, 95% CI 1.1–3.1). A tuberculosis risk assessment tool (TReAT) was developed, stratifying patients with low (score ≤2), moderate (score 3–5) and high (score ≥6) mortality risk. The mortality associated with each group was 2.9%, 22.9% and 53.9%, respectively. The model performed equally well in the validation cohort. We provide a new, easy-to-use clinical scoring system to identify PTB patients with high-mortality risk in settings with good healthcare access, helping clinicians to decide which patients are in need of closer medical care during treatment. PMID:27636095

  19. Serum creatinine level, a surrogate of muscle mass, predicts mortality in peritoneal dialysis patients.

    PubMed

    Park, Jongha; Mehrotra, Rajnish; Rhee, Connie M; Molnar, Miklos Z; Lukowsky, Lilia R; Patel, Sapna S; Nissenson, Allen R; Kopple, Joel D; Kovesdy, Csaba P; Kalantar-Zadeh, Kamyar

    2013-08-01

    In hemodialysis patients, higher serum creatinine (Cr) concentration represents larger muscle mass and predicts greater survival. However, this association remains uncertain in peritoneal dialysis (PD) patients. In a cohort of 10 896 PD patients enrolled from 1 July 2001 to 30 June 2006, the association of baseline serum Cr level and change during the first 3 months after enrollment with all-cause mortality was examined. The cohort mean ± SD age was 55 ± 15 years old and included 52% women, 24% African-Americans and 48% diabetics. Compared with patients with serum Cr levels of 8.0-9.9 mg/dL, patients with serum Cr levels of <4.0 mg/dL and 4.0-5.9 mg/dL had higher risks of death {HR 1.36 [95% confidence interval (95% CI) 1.19-1.55] and 1.19 (1.08-1.31), respectively} whereas patients with serum Cr levels of 10.0-11.9 mg/dL, 12.0-13.9 mg/dL and ≥14.0 mg/dL had lower risks of death (HR 0.88 [95% CI 0.79-0.97], 0.71 [0.62-0.81] and 0.64 [0.55-0.75], respectively) in the fully adjusted model. Decrease in serum Cr level over 1.0 mg/dL during the 3 months predicted an increased risk of death additionally. The serum Cr-mortality association was robust in patients with PD treatment duration of ≥12 months, but was not observed in those with PD duration of <3 months. Muscle mass reflected in serum Cr level may be associated with survival even in PD patients. However, the serum Cr-mortality association is attenuated in the early period of PD treatment, suggesting competing effect of muscle mass versus residual renal function on mortality.

  20. Circulating Biologically Active Adrenomedullin (bio-ADM) Predicts Hemodynamic Support Requirement and Mortality During Sepsis.

    PubMed

    Caironi, Pietro; Latini, Roberto; Struck, Joachim; Hartmann, Oliver; Bergmann, Andreas; Maggio, Giuseppe; Cavana, Marco; Tognoni, Gianni; Pesenti, Antonio; Gattinoni, Luciano; Masson, Serge

    2017-08-01

    The biological role of adrenomedullin (ADM), a hormone involved in hemodynamic homeostasis, is controversial in sepsis because administration of either the peptide or an antibody against it may be beneficial. Plasma biologically active ADM (bio-ADM) was assessed on days 1, 2, and 7 after randomization of 956 patients with sepsis or septic shock to albumin or crystalloids for fluid resuscitation in the multicenter Albumin Italian Outcome Sepsis trial. We tested the association of bio-ADM and its time-dependent variation with fluid therapy, vasopressor administration, organ failures, and mortality. Plasma bio-ADM on day 1 (median [Q1-Q3], 110 [59-198] pg/mL) was higher in patients with septic shock, associated with 90-day mortality, multiple organ failures and the average extent of hemodynamic support therapy (fluids and vasopressors), and serum lactate time course over the first week. Moreover, it predicted incident cardiovascular dysfunction in patients without shock at enrollment (OR [95% CI], 1.9 [1.4-2.5]; P < .0001, for an increase of 1 interquartile range of bio-ADM concentration). bio-ADM trajectory during the first week of treatment clearly predicted 90-day mortality after adjustment for clinically relevant covariates (hazard ratio [95% CI], 1.3 [1.2-1.4]; P < .0001), and its reduction below 110 pg/mL at day 7 was associated with a marked reduction in 90-day mortality. Changes over the first 7 days of bio-ADM concentrations were not dependent on albumin treatment. In patients with sepsis, the circulating, biologically active form of ADM may help individualizing hemodynamic support therapy, while avoiding harmful effects. Its possible pathophysiologic role makes bio-ADM a potential candidate for future targeted therapies. ClinicalTrials.gov; No.: NCT00707122. Copyright © 2017 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

  1. Artificial neural networks accurately predict mortality in patients with nonvariceal upper GI bleeding.

    PubMed

    Rotondano, Gianluca; Cipolletta, Livio; Grossi, Enzo; Koch, Maurizio; Intraligi, Marco; Buscema, Massimo; Marmo, Riccardo

    2011-02-01

    Risk stratification systems that accurately identify patients with a high risk for bleeding through the use of clinical predictors of mortality before endoscopic examination are needed. Computerized (artificial) neural networks (ANNs) are adaptive tools that may improve prognostication. To assess the capability of an ANN to predict mortality in patients with nonvariceal upper GI bleeding and compare the predictive performance of the ANN with that of the Rockall score. Prospective, multicenter study. Academic and community hospitals. This study involved 2380 patients with nonvariceal upper GI bleeding. Upper GI endoscopy. The primary outcome variable was 30-day mortality, defined as any death occurring within 30 days of the index bleeding episode. Other outcome variables were recurrent bleeding and need for surgery. We performed analysis of certified outcomes of 2380 patients with nonvariceal upper GI bleeding. The Rockall score was compared with a supervised ANN (TWIST system, Semeion), adopting the same result validation protocol with random allocation of the sample in training and testing subsets and subsequent crossover. Overall, death occurred in 112 cases (4.70%). Of 68 pre-endoscopic input variables, 17 were selected and used by the ANN versus 16 included in the Rockall score. The sensitivity of the ANN-based model was 83.8% (76.7-90.8) versus 71.4% (62.8-80.0) for the Rockall score. Specificity was 97.5 (96.8-98.2) and 52.0 (49.8 4.2), respectively. Accuracy was 96.8% (96.0-97.5) versus 52.9% (50.8-55.0) (P<.001). The predictive performance of the ANN-based model for prediction of mortality was significantly superior to that of the complete Rockall score (area under the curve 0.95 [0.92-0.98] vs 0.67 [0.65-0.69]; P<.001). External validation on a subsequent independent population is needed, patients with variceal bleeding and obscure GI hemorrhage are excluded. In patients with nonvariceal upper GI bleeding, ANNs are significantly superior to the Rockall

  2. Development of a Risk Index for Prediction of Mortality after Open Aortic Aneurysm Repair

    PubMed Central

    Ramanan, Bala; Gupta, Prateek K; Sundaram, Abhishek; Gupta, Himani; Johanning, Jason M.; Lynch, Thomas G.; MacTaggart, Jason N.; Pipinos, Iraklis I.

    2013-01-01

    Objective Open infrarenal aortic aneurysm (oAAA) repair is associated with significant morbidity and mortality. While there has been a shift towards endovascular repair, many patients continue to undergo an open repair due to anatomical considerations. Tools currently existing for estimation of peri-procedural risk in patients undergoing open aortic surgery have certain limitations. The objective of this study was to develop a risk index to estimate the risk of 30-day perioperative mortality after elective oAAA repair. Methods Patients who underwent elective oAAA repair (n=2845) were identified from the American College of Surgeons’ 2007-09 National Surgical Quality Improvement Program (NSQIP) - a prospective database maintained at multiple centers (>250). Univariable and multivariable analyses were performed to evaluate risk factors associated with 30-day mortality after oAAA repair and a risk index was developed. Results The 30-day mortality after oAAA repair was 3.3%. On multivariable analysis, six preoperative predictors of mortality were identified and a risk index was created by assigning weighted points to each predictor using the beta-coefficients from the regression analysis. The predictors included dyspnea (at rest: 8 points; on moderate exertion: 2 points; none: 0 points), history of peripheral arterial disease requiring revascularization or amputation (3 points), age >65 years (3 points), preoperative creatinine >1.5 mg/dl (2 points), female gender (2 points), and platelets < 150,000/mm3 or >350,000/mm3 (2 points). Patients were classified as low (<7%), intermediate (7-15%), and high (>15%) risk for 30-day mortality, based on a total point score of <8, 8-11, and >11, respectively. There were 2508 (88.2%) patients in the low risk category, while there were 278 (9.8%) patients in the intermediate, and 59 (2.1%) patients in the high risk category. Conclusions This risk index has excellent predictive ability for mortality after oAAA surgery and awaits

  3. European cancer mortality predictions for the year 2016 with focus on leukaemias.

    PubMed

    Malvezzi, M; Carioli, G; Bertuccio, P; Rosso, T; Boffetta, P; Levi, F; La Vecchia, C; Negri, E

    2016-04-01

    Current cancer mortality statistics are important for public health decision-making and resource allocation. Age-standardized rates and numbers of deaths are predicted for 2016 in the European Union (EU). Population and death certification data for stomach, colorectum, pancreas, lung, breast, uterus, prostate, leukaemias and total cancers were obtained from the World Health Organization database and Eurostat. Figures were derived for the EU, France, Germany, Italy, Poland, Spain and the UK. Projected numbers of deaths by age group were obtained for 2016 by linear regression on estimated numbers of deaths over the most recent time period identified by a joinpoint regression model. Projected total cancer mortality trends for 2016 in the EU are favourable in both sexes with rates of 133.5/100 000 men and 85.2/100 000 women (8% and 3% falls since 2011) corresponding to 753 600 and 605 900 deaths in men and women for a total number of 1 359 500 projected cancer deaths (+3% compared with 2011, due to population ageing). In men, lung, colorectal and prostate cancer have fallen 11%, 5% and 8%, respectively, since 2011. Breast and colorectal cancer trends in women are favourable (8% and 7% falls, respectively), but lung and pancreatic cancer rates have risen 5% and 4% since 2011 reaching rates of 14.4 and 5.6/100 000 women. Leukaemias show favourable projected mortality for both sexes and all age groups, with stronger falls in the younger age groups. All ages rates are 4.0/100 000 men and 2.5/100 000 women, with falls of 14% and 12% respectively. The 2016 predictions for EU cancer mortality confirm the favourable trends in rates particularly for men. Lung cancer is likely to be the leading site for female cancer rates. Continuing falls in mortality, larger in children and young adults, are predicted in leukaemias, essentially due to advancements in management and therapy, and their subsequent adoption across Europe. © The Author 2016. Published by Oxford University Press

  4. A Validated Risk Score for Venous Thromboembolism Is Predictive of Cancer Progression and Mortality.

    PubMed

    Kuderer, Nicole M; Culakova, Eva; Lyman, Gary H; Francis, Charles; Falanga, Anna; Khorana, Alok A

    2016-07-01

    Retrospective studies have suggested an association between cancer-associated venous thromboembolism (VTE) and patient survival. We evaluated a previously validated VTE Clinical Risk Score in also predicting early mortality and cancer progression. A large, nationwide, prospective cohort study of adults with solid tumors or lymphoma initiating chemotherapy was conducted from 2002 to 2006 at 115 U.S. practice sites. Survival and cancer progression were estimated by the method of Kaplan and Meier. Multivariate analysis was based on Cox regression analysis adjusted for major prognostic factors including VTE itself. Of 4,405 patients, 134 (3.0%) died and 330 (7.5%) experienced disease progression during the first 4 months of therapy (median follow-up 75 days). Patients deemed high risk (n = 540, 12.3%) by the Clinical Risk Score had a 120-day mortality rate of 12.7% (adjusted hazard ratio [aHR] 3.00, 95% confidence interval [CI] 1.4-6.3), and intermediate-risk patients (n = 2,665, 60.5%) had a mortality rate of 5.9% (aHR 2.3, 95% CI 1.2-4.4) compared with only 1.4% for low-risk patients (n = 1,200, 27.2%). At 120 days of follow-up, cancer progression occurred in 27.2% of high-risk patients (aHR 2.2, 95% CI 1.4-3.5) and 16.4% of intermediate-risk patients (aHR 1.9, 95% CI 1.3-2.7) compared with only 8.5% of low-risk patients (p < .0001). The Clinical Risk Score, originally developed to predict the occurrence of VTE, is also predictive of early mortality and cancer progression during the first four cycles of outpatient chemotherapy, independent from other major prognostic factors including VTE itself. Ongoing and future studies will help determine the impact of VTE prophylaxis on survival. The risk of venous thromboembolism (VTE) is increased in patients receiving cancer chemotherapy. In this article, the authors demonstrate that a popular risk score for VTE in patients with cancer is also associated with the risk of early mortality in this setting. It is important that

  5. An evaluation of machine-learning methods for predicting pneumonia mortality.

    PubMed

    Cooper, G F; Aliferis, C F; Ambrosino, R; Aronis, J; Buchanan, B G; Caruana, R; Fine, M J; Glymour, C; Gordon, G; Hanusa, B H; Janosky, J E; Meek, C; Mitchell, T; Richardson, T; Spirtes, P

    1997-02-01

    This paper describes the application of eight statistical and machine-learning methods to derive computer models for predicting mortality of hospital patients with pneumonia from their findings at initial presentation. The eight models were each constructed based on 9847 patient cases and they were each evaluated on 4352 additional cases. The primary evaluation metric was the error in predicted survival as a function of the fraction of patients predicted to survive. This metric is useful in assessing a model's potential to assist a clinician in deciding whether to treat a given patient in the hospital or at home. We examined the error rates of the models when predicting that a given fraction of patients will survive. We examined survival fractions between 0.1 and 0.6. Over this range, each model's predictive error rate was within 1% of the error rate of every other model. When predicting that approximately 30% of the patients will survive, all the models have an error rate of less than 1.5%. The models are distinguished more by the number of variables and parameters that they contain than by their error rates; these differences suggest which models may be the most amenable to future implementation as paper-based guidelines.

  6. Using Data-Driven Rules to Predict Mortality in Severe Community Acquired Pneumonia

    PubMed Central

    Wu, Chuang; Rosenfeld, Roni; Clermont, Gilles

    2014-01-01

    Prediction of patient-centered outcomes in hospitals is useful for performance benchmarking, resource allocation, and guidance regarding active treatment and withdrawal of care. Yet, their use by clinicians is limited by the complexity of available tools and amount of data required. We propose to use Disjunctive Normal Forms as a novel approach to predict hospital and 90-day mortality from instance-based patient data, comprising demographic, genetic, and physiologic information in a large cohort of patients admitted with severe community acquired pneumonia. We develop two algorithms to efficiently learn Disjunctive Normal Forms, which yield easy-to-interpret rules that explicitly map data to the outcome of interest. Disjunctive Normal Forms achieve higher prediction performance quality compared to a set of state-of-the-art machine learning models, and unveils insights unavailable with standard methods. Disjunctive Normal Forms constitute an intuitive set of prediction rules that could be easily implemented to predict outcomes and guide criteria-based clinical decision making and clinical trial execution, and thus of greater practical usefulness than currently available prediction tools. The Java implementation of the tool JavaDNF will be publicly available. PMID:24699007

  7. Risk stratification scores for predicting mortality in coronary artery bypass surgery.

    PubMed

    Baretti, R; Pannek, N; Knecht, J-P; Krabatsch, T; Hübler, S; Hetzer, R

    2002-08-01

    Four risk-stratification scores (RSSs - Euro, French, CCS/Higgins, Parsonnet) were tested as predictors of mortality in coronary artery bypass grafting (CABG) surgery. From March to April 2000, the perioperative courses of 245 consecutive CABG patients were compared to the predictions according to the RSSs. Sensitivity and specificity were determined with receiver operating characteristics (ROC) curves. CCS/Higgins uses the most easily acquired patient data, and rates emergency conditions as high-risk. Euro focuses on advanced age and septal rupture. French uses the smallest number of patient parameters and rates rare critical situations as high-risk. Parsonnet is partially based on the physician's subjective assessment of a "catastrophic state," making the scoring arbitrary. All RSSs gave similar (not significant) areas under the ROC curves regarding mortality (Euro 0.826 +/- 0.080, French 0.783 +/- 0.094, CCS/Higgins 0.820 +/- 0.060, Parsonnet 0.831 +/- 0.042). Predicted risk levels for the 11 patients who died differed between the RSSs--Higgins placed these patients in 3 of 5 risk levels with ascending distribution. The other RSSs placed these patients in the highest risk level except for one and two patients, respectively, who were placed in the lowest Euro and French risk level. Euro and Parsonnet placed about half of all patients with non-lethal outcome in the highest risk level. All RSSs satisfactorily estimated the group risk for mortality. No RSS expressed sufficient validity to predict individuals with lethal outcome. In clinical use, CCS/Higgins proved the most practicable.

  8. Nurse-led risk assessment/management clinics reduce predicted cardiac morbidity and mortality in claudicants.

    PubMed

    Hatfield, Josephine; Gulati, Sumit; Abdul Rahman, Morhisham N A; Coughlin, Patrick A; Chetter, Ian C

    2008-12-01

    Nurse-led assessment/management of risk factors is effective in many chronic medical conditions. We aimed to evaluate whether this finding was true for patients with intermittent claudication and to analyze its impact on patient-reported quality of life and predicted mortality due to coronary heart disease. We prospectively studied a series of 78 patients (51 men; median age, 65 years [IQR: 56-74 years]), diagnosed with intermittent claudication and referred to a nurse-led risk assessment/management clinic (NLC) from a consultant-led vascular surgical clinic. The NLC used clinical care pathways to manage antiplatelet medication, smoking cessation, hyperlipidemia, hypertension, and diabetes and to provide exercise advice. All patients were reassessed at a 3 months. Medication compliance, smoking status, fasting lipid profiles, blood pressure, and HbA1c were recorded. Disease-specific quality of life was assessed using King's College VascuQoL and predicted cardiac morbidity and mortality were calculated using the PROCAM and Framingham risk scores. We found that NLC enrollment produced an antiplatelet and a statin compliance of 100%, a smoking cessation rate of 17% (9 patients) and significant improvements in total cholesterol (median, 5.2-4.5 mmol/l), LDL (median, 3.1-2.5 mmol/l) and triglyceride (median, 1.7-1.4 mmol/l) levels. Significant disease-specific quality of life improvements and significant reduction in both the PROCAM (14% to 10%) and Framingham (14% to 11%) coronary risk scores were observed. Providing care at NLCs for claudicants is effective in assessing and managing risk factors, improves disease-specific quality of life and reduces predicted morbidity and mortality due to coronary heart disease.

  9. Resistance profiles of coagulase-negative staphylococci contaminating blood cultures predict pathogen resistance and patient mortality.

    PubMed

    Obolski, Uri; Alon, Danny; Hadany, Lilach; Stein, Gideon Y

    2014-09-01

    Blood culture isolates are the cornerstone of adequate antibiotic treatment. However, many blood cultures are contaminated with bacteria residing on the skin, the most common contaminants being coagulase-negative staphylococci (CoNS). Such contaminated cultures are mostly disregarded. In this retrospective study, we show that contaminated cultures contain diagnostic information. We tested the association between resistance profiles of CoNS contaminants and those of the actual infecting bacteria isolated subsequently from the same patient, as well as their association with short-term mortality. We identified all patients in Rabin Medical Center, Israel, with positive blood cultures during 2009-12. Data included patient demographics, hospitalization records, comorbidities, blood culture results and date of death. Our cohort consists of 2518 patients with 5290 blood cultures, where 1124 patients had 1664 blood cultures with CoNS contaminants. High overall CoNS resistance predicted high overall resistance of the subsequent bacterial isolates (P<0.004 and P<0.0006, for Gram-positive and -negative bacteria, respectively). Moreover, the resistance of CoNS contaminants to a specific antibiotic predicted the resistance of the subsequent bacterial isolates to that antibiotic (OR=5.55, 95% CI=3.54-8.66, P<10(-15) and OR=2.47, 95% CI=1.61-3.78, P<3 ×10(-5), for Gram-positive and -negative bacteria, respectively). Finally, highly resistant CoNS isolates were associated with higher short-term mortality (hazard ratio=1.71, 95% CI=1.4-2.11, P<10(-6)). Resistance patterns of CoNS contaminants predict specific and overall resistance of subsequent blood culture isolates and short-term mortality. These results may help predict patient mortality and correct empirical antibiotic therapy if blood cultures yield contaminant bacteria and imply that skin commensals may serve as an additional, non-invasive, diagnostic tool. © The Author 2014. Published by Oxford University Press on

  10. Posthepatectomy portal vein pressure predicts liver failure and mortality after major liver resection on noncirrhotic liver.

    PubMed

    Allard, Marc-Antoine; Adam, René; Bucur, Pétru-Octav; Termos, Salah; Cunha, Antonio Sa; Bismuth, Henri; Castaing, Denis; Vibert, Eric

    2013-11-01

    To evaluate the predictive value of portal vein pressure (PVP) after major liver resection for posthepatectomy liver failure (PLF) and 90-day mortality in patients without cirrhosis. As elevated PVP is associated with liver failure after living donor liver transplantation, we hypothesized that the outcome after major hepatectomy may be influenced by posthepatectomy PVP. All patients without severe fibrosis or cirrhosis who underwent a major liver resection (≥3 segments) with an intraoperative measurement of PVP at the end of the procedure were included. Outcome was analyzed regarding 3 most widely used definitions of PLF: "50-50" criteria, peak of serum bilirubin greater than 120 μmol/L, and grade C PLF proposed by the International Study Group of Liver Surgery (ISGLS). Receiver operating characteristic curves and logistic regression model were used to determine the optimal cutoff of PVP and independent risk factors of PLF. The study population consisted of 277 patients. Posthepatectomy PVP was gradually correlated with the PLF risk. Probability for PLF was nil when PVP was 10 mm Hg or less, ranges from 13% to 16%, depending on PLF definitions, when PVP was 20 mm Hg, and from 24% to 33% when PVP was 30 mm Hg. The optimal value of posthepatectomy PVP to predict PLF was 22 mm Hg when considering the "50-50" criteria and grade C PLF (proposed by the International Study Group of Liver Surgery). A value of 21 mm Hg best predicted PLF defined by peak of serum bilirubin greater than 120 μmol/L and 90-day mortality. At multivariate analysis, posthepatectomy PVP remained an independent predictor of PLF as well as the extent of resection, intraoperative transfusion, and the presence of diabetes. The 90-day mortality was associated with PVP greater than 21 mm Hg, older than 70 years, and intraoperative transfusion. Posthepatectomy PVP is an independent predictive factor of PLF and of 90-day mortality after major liver resection in patients without cirrhosis

  11. Risk stratification simplified: the worst injury predicts mortality for the injured children.

    PubMed

    Tepas, Joseph J; Leaphart, Cynthia L; Celso, Brian G; Tuten, James D; Pieper, Pam; Ramenofsky, Max L

    2008-12-01

    The International Classification Injury Severity Score (ICISS) uses anatomic injury diagnoses to predict probability of survival (Ps) computed as the product of the survival risk ratios (SRR) of the three most severe injuries. SRRs are derived as the proportion of fatalities for every International Classification of Diseases-9th Revision-Clinical Modification diagnosis in a "benchmark" population. Pediatric-specific SRRs were computed from 103,434 entries in the National Pediatric Trauma Registry. We hypothesized that ICISS was a valid pediatric outcome predictor, and that the child's most severe injury; i.e., the lowest SRR, is the major driver of outcome, which can be used alone to predict survival. Receiver operator characteristic analysis was used to assess the predictive validity of ICISS. SRRs derived from 53,235 phase II patients were used as the training set to calculate the Ps for 50,199 phase III children comprising the test set. The survival probability (Ps) computed from the standard three diagnoses was compared with that computed from only the worst injury (lowest SRR). Records with a single diagnosis or Ps of 1, indicating no mortality potential, were excluded from the analysis. Nagelkerke pseudo R2 defined what proportion of the predicted Ps was the effect of the worst injury alone versus the traditional Ps. A total of 25,239 records with at least two diagnoses with SRRs indicating risk of mortality were analyzed. The area under the receiver operator characteristic curve for traditional Ps was 0.935, compared with 0.932 for that calculated using only the lowest SRR. The difference of 0.003 was not significant (z = 1.061, p = 0.2888, NS). Nagelkerke pseudo R2 for the lowest SRR was 0.455 compared with 0.462 for the traditional three diagnosis Ps, which shows that the majority of Ps predictive power is related to the single injury with the lowest SRR. Further analysis demonstrated that this effect was related to frequency of coexistent injuries with no

  12. Pyogenic liver abscess: current status and predictive factors for recurrence and mortality of first episodes.

    PubMed

    Czerwonko, Matías E; Huespe, Pablo; Bertone, Santiago; Pellegrini, Pablo; Mazza, Oscar; Pekolj, Juan; de Santibañes, Eduardo; Hyon, Sung Ho; de Santibañes, Martín

    2016-12-01

    In times of modern surgery, transplantation and percutaneous techniques, pyogenic liver abscess (PLA) has essentially become a problem of biliary or iatrogenic origin. In the current scenario, diagnostic approach, clinical behavior and therapeutic outcomes have not been profoundly studied. This study analyzes the clinical and microbiological features, diagnostic methods, therapeutic management and predictive factors for recurrence and mortality of first episodes of PLA. A retrospective single-center study was conducted including 142 patients admitted to the Hospital Italiano de Buenos Aires, between 2005 and 2015 with first episodes of PLA. Prevailing identifiable causes were biliary diseases (47.9%) followed by non-biliary percutaneous procedures (NBIPLA, 15.5%). Seventeen patients (12%) were liver recipients. Eleven patients (7.8%) died and 18 patients (13.7%) had recurrence in the first year of follow up. The isolation of multiresistant organisms (p = 0.041) and a history of cholangitis (p < 0.001) were independent risk factors for recurrence. Mortality was associated with serum bilirubin >5 mg/dL (p = 0.022) and bilateral involvement (p = 0.014) in the multivariate analysis. NBPLA and PLA after transplantation may be increasing among the population of PLA in referral centers. History of cholangitis is a strong predictor for recurrence. Mortality is associated to hiperbilirrubinemia and anatomical distribution of the lesions. Copyright © 2016 International Hepato-Pancreato-Biliary Association Inc. Published by Elsevier Ltd. All rights reserved.

  13. Young-Burgess classification of pelvic ring fractures: does it predict mortality, transfusion requirements, and non-orthopaedic injuries?

    PubMed

    Manson, Theodore; O'Toole, Robert V; Whitney, Augusta; Duggan, Brian; Sciadini, Marcus; Nascone, Jason

    2010-10-01

    The objectives of this study were to evaluate the ability of the Young-Burgess classification system to predict mortality, transfusion requirements, and nonorthopaedic injuries in patients with pelvic ring fractures and to determine whether mortality rates after pelvic fractures have changed over time. Retrospective review. Level I trauma center. One thousand two hundred forty-eight patients with pelvic fractures during a 7-year period. None. Mortality at index admission, transfusion requirement during first 24 hours, and presence of nonorthopaedic injuries as a function of Young-Burgess pelvic classification type. Mortality compared with historic controls. Despite a relatively large sample size, the ability of the Young-Burgess system to predict mortality only approached statistical significance (P = 0.07, Kruskal-Wallis). The Young-Burgess system differentiated transfusion requirements--lateral compression Type 3 (LC3) and anteroposterior compression Types 2 (APC2) and 3 (APC3) fractures had higher transfusion requirements than did lateral compression Type 1 (LC1), anteroposterior compression Type 1 (APC1), and vertical shear (VS) (P < 0.05)--but was not as useful at predicting head, chest, or abdomen injuries. Dividing fractures into stable and unstable types allowed the system to predict mortality rates, abdomen injury rates, and transfusion requirements. Overall mortality in the study group was 9.1%, unchanged from original Young-Burgess studies 15 years previously (P = 0.3). The Young-Burgess system is useful for predicting transfusion requirements. For the system to predict mortality or nonorthopaedic injuries, fractures must be divided into stable (APC1, LC1) and unstable (APC2, APC3, LC2, LC3, VS, combined mechanism of injury) types. LC1 injuries are very common and not always benign (overall mortality rate, 8.2%).

  14. Admission physiology criteria after injury on the battlefield predict medical resource utilization and patient mortality.

    PubMed

    Eastridge, Brian J; Owsley, Jimmie; Sebesta, James; Beekley, Alec; Wade, Charles; Wildzunas, Robert; Rhee, Peter; Holcomb, John

    2006-10-01

    Medical resources and resource allocation including operating room and blood utilization are of prime importance in the modern combat environment. We hypothesized that easily measurable admission physiologic criteria and injury site as well as injury severity calculated after diagnostic evaluation or surgical intervention, would be strongly correlated with resource utilization and in theater mortality outcomes. We retrospectively reviewed the Joint Theater Trauma Registry for all battlefield casualties presenting to surgical component facilities during Operation Iraqi Freedom from January to July 2004. Data were collected from the composite population of 1,127 battlefield casualty patients with respect to demographics, mechanism, presentation physiology (blood pressure, heart rate, temperature), base deficit, admission hematocrit, Glasgow Coma Score (GCS), Injury Severity Score (ISS), operating room utilization, blood transfusion, and mortality. Univariate and multivariate analyses were conducted to determine the degree to which admission physiology and injury severity correlated with blood utilization, necessity for operation, and acute mortality. Univariate analysis demonstrated a significant (p < 0.05) association between hypothermia (T < 34 degrees C) and the subsequent requirement for operation and mortality. In addition, the outcome variable total blood product utilization was significantly correlated with base deficit (r = 0.61), admission hematocrit (r = 0.51), temperature (r = 0.47), and ISS (r = 0.54). Using multiple logistic regression techniques, blood pressure, GCS, and ISS together demonstrated a significant association (p < 0.05) with mortality (area under ROC curve = 95%). Multiple linear regression established that blood pressure, heart rate, temperature, hematocrit, and ISS had a collective significant effect (p < 0.05) on total blood product utilization explaining 67% of the variance in this outcome variable. Admission physiology and injury

  15. Female sex independently predicts mortality after thoracic endovascular aortic repair for intact descending thoracic aortic aneurysms.

    PubMed

    Deery, Sarah E; Shean, Katie E; Wang, Grace J; Black, James H; Upchurch, Gilbert R; Giles, Kristina A; Patel, Virendra I; Schermerhorn, Marc L

    2017-07-01

    independently predictive of 30-day mortality (odds ratio, 1.5; 95% confidence interval, 1.1-2.1, P < .01) and long-term mortality (hazard ratio, 1.3; 95% confidence interval, 1.03-1.6; P = .02). Even after adjusting for differences in age and comorbidities, female patients have higher perioperative mortality and lower long-term survival after TEVAR. These findings, along with the rupture risk by sex, should be considered by clinicians in determining the timing of intervention. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

  16. Prediction of risk of diabetic retinopathy for all-cause mortality, stroke and heart failure

    PubMed Central

    Zhu, Xiao-Rong; Zhang, Yong-Peng; Bai, Lu; Zhang, Xue-Lian; Zhou, Jian-Bo; Yang, Jin-Kui

    2017-01-01

    Abstract To examine and quantify the potential relation between diabetic retinopathy (DR) and risk of all-cause mortality, stroke and heart failure (HF). The resources of meta-analysis of epidemiological observational studies were from Pub-med, EMBASE, CINAHL, Cochrane Library, conference, and proceedings. Random/fixed effects models were used to calculate pooled subgroup analysis stratified by different grades of DR was performed to explore the potential source of heterogeneity. Statistical manipulations were undertaken using program STATA. Of the included 25 studies, comprising 142,625 participants, 19 studies were concluded to find the relation of DR to all-cause mortality, 5 for stroke, and 3 for HF. Risk ratio (RR) for all-cause mortality with the presence of DR was 2.33 (95% CI 1.92–2.81) compared with diabetic individuals without DR. Evidences showed a higher risk of all-cause mortality associated with DR in patients with T2D or T1D (RR 2.25, 95% CI 1.91–2.65. RR 2.68, 95% CI 1.34–5.36). According to different grades of DR in patients with T2D, RR for all-cause mortality varied, the risk of nonproliferative diabetic retinopathy (NPDR) was 1.38 (1.11–1.70), while the risk of proliferative diabetic retinopathy (PDR) was 2.32 (1.75–3.06). There was no evidence of significant heterogeneity (Cochran Q test P = 0.29 vs 0.26, I2 = 19.6% vs 22.6%, respectively). Data from 5 studies in relation to DR and the risk of stroke showed that DR was significantly associated with increased risk of stroke (RR = 1.74, 95%CI: 1.35–2.24), compared with patients without DR. Furthermore, DR (as compared with individuals without DR) was associated with a marginal increased risk of HF in patients with diabetes mellitus (DM) (n = 3 studies; RR 2.24, 95% CI 0.98–5.14, P = 0.056). Our results showed that DR increased the risk of all-cause mortality, regardless of the different stages, compared with the diabetic individuals without DR. DR predicted

  17. Quick SOFA Scores Predict Mortality in Adult Emergency Department Patients With and Without Suspected Infection.

    PubMed

    Singer, Adam J; Ng, Jennifer; Thode, Henry C; Spiegel, Rory; Weingart, Scott

    2017-04-01

    The Quick Sequential Organ Failure Assessment (qSOFA) score (composed of respiratory rate ≥22 breaths/min, systolic blood pressure ≤100 mm Hg, and altered mental status) may identify patients with infection who are at risk of complications. We determined the association between qSOFA scores and outcomes in adult emergency department (ED) patients with and without suspected infection. We performed a single-site, retrospective review of adult ED patients between January 2014 and March 2015. Patients triaged to fast-track, dentistry, psychiatry, and labor and delivery were excluded. qSOFA scores were calculated with simultaneous vital signs and Modified Early Warning System scores. Patients receiving intravenous antibiotics were presumed to have suspected infection. Univariate and multivariate analyses were performed to explore the association between qSOFA scores and inpatient mortality, admission, and length of stay. Receiver operating characteristics curve analysis and c statistics were also calculated for ICU admission and mortality. We included 22,530 patients. Mean age was 54 years (SD 21 years), 53% were women, 45% were admitted, and mortality rate was 1.6%. qSOFA scores were associated with mortality (0 [0.6%], 1 [2.8%], 2 [12.8%], and 3 [25.0%]), ICU admission (0 [5.1%], 1 [10.5%], 2 [20.8%], and 3 [27.4%]), and hospital length of stay (0 [123 hours], 1 [163 hours], 2 [225 hours], and 3 [237 hours]). Adjusted rates were also associated with qSOFA. The c statistics for mortality in patients with and without suspected infection were similarly high (0.75 [95% confidence interval 0.71 to 0.78) and 0.70 (95% confidence interval 0.65 to 0.74), respectively. qSOFA scores were associated with inpatient mortality, admission, ICU admission, and hospital length of stay in adult ED patients likely to be admitted both with and without suspected infection and may be useful in predicting outcomes. Copyright © 2016 American College of Emergency Physicians. Published by

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

    PubMed

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

    2014-07-01

    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 the 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 as 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 the choice of weather variables in heat epidemiology studies.

  19. 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

  20. Lipoprotein(a) level and MIF gene variant predict incident metabolic syndrome and mortality.

    PubMed

    Onat, Altan; Can, Günay; Çoban, Neslihan; Dönmez, İbrahim; Çakır, Hakan; Ademoğlu, Evin; Erginel-Ünaltuna, Nihan; Yüksel, Hüsniye

    2016-02-01

    Owing to the scarcity of available information, we aimed to assess the association of migration inhibitory factor (MIF)-173 G/C genotypes and serum lipoprotein(Lp)(a) with incident metabolic syndrome (MetS) and all-cause mortality, respectively. In population based, middle-aged adults (n=1297), stratified by gender and presence of MetS, we used Lp(a) quintiles to identify non-linear associations with outcomes using Cox regression models, adjusted for MIF genotype, age, smoking status, high density lipoprotein cholesterol, and systolic blood pressure. After 5.2 years of follow-up, 151 cases of incident MetS and 123 deaths were recorded. For incident MetS, adjusted HRs increased in each gender across four declining quintiles, starting from the highest quintile in men and from quintile 4 in women. The MIF CC-GC genotype appeared to contribute to the risk estimates in men. Similarly adjusted models in the whole sample disclosed that all-cause mortality tended to be inversely associated with Lp(a) quintiles and yielded an HR (2.42 (95% CI 1.03 to 5.81)) in men in quintile 2, whereas the MIF genotype additively predicted mortality (HR 1.79 (95% CI 1.01 to 3.18)) only in men. Excess risk of death was additively conferred on Turkish men by the MIF CC-GC genotype and by apparently reduced circulating Lp(a) assays, supporting the notion that 'low' serum Lp(a), mediating autoimmune activation, is a major determinant of metabolic disease risk and death. Damaged MIF protein and more complex autoimmune activation in women may be responsible from lack of relationship to MetS/mortality.

  1. Predicting mortality from change-over-time in the Charlson Comorbidity Index

    PubMed Central

    Fraccaro, Paolo; Kontopantelis, Evangelos; Sperrin, Matthew; Peek, Niels; Mallen, Christian; Urban, Philip; Buchan, Iain E.; Mamas, Mamas A.

    2016-01-01

    Abstract Multimorbidity is common among older people and presents a major challenge to health systems worldwide. Metrics of multimorbidity are, however, crude: focusing on measuring comorbid conditions at single time-points rather than reflecting the longitudinal and additive nature of chronic conditions. In this paper, we explore longitudinal comorbidity metrics and their value in predicting mortality. Using linked primary and secondary care data, we conducted a retrospective cohort study on adults in Salford, UK from 2005 to 2014 (n = 287,459). We measured multimorbidity with the Charlson Comorbidity Index (CCI) and quantified its changes in various time windows. We used survival models to assess the relationship between CCI changes and mortality, controlling for gender, age, baseline CCI, and time-dependent CCI. Goodness-of-fit was assessed with the Akaike Information Criterion and discrimination with the c-statistic. Overall, 15.9% patients experienced a change in CCI after 10 years, with a mortality rate of 19.8%. The model that included gender and time-dependent age, CCI, and CCI change across consecutive time windows had the best fit to the data but equivalent discrimination to the other time-dependent models. The absolute CCI score gave a constant hazard ratio (HR) of around 1.3 per unit increase, while CCI change afforded greater prognostic impact, particularly when it occurred in shorter time windows (maximum HR value for the 3-month time window, with 1.63 and 95% confidence interval 1.59–1.66). Change over time in comorbidity is an important but overlooked predictor of mortality, which should be considered in research and care quality management. PMID:27787358

  2. Mini Nutritional Assessment predicts gait status and mortality 6 months after hip fracture.

    PubMed

    Gumieiro, David N; Rafacho, Bruna P M; Gonçalves, Andrea F; Tanni, Suzana E; Azevedo, Paula S; Sakane, Daniel T; Carneiro, Carlos A S; Gaspardo, David; Zornoff, Leonardo A M; Pereira, Gilberto J C; Paiva, Sergio A R; Minicucci, Marcos F

    2013-05-01

    The aim of the present study was to evaluate the Mini Nutritional Assessment (MNA), the Nutritional Risk Screening (NRS) 2002 and the American Society of Anesthesiologists Physical Status Score (ASA) as predictors of gait status and mortality 6 months after hip fracture. A total of eighty-eight consecutive patients over the age of 65 years with hip fracture admitted to an orthopaedic unit were prospectively evaluated. Within the first 72 h of admission, each patient's characteristics were recorded, and the MNA, the NRS 2002 and the ASA were performed. Gait status and mortality were evaluated 6 months after hip fracture. Of the total patients, two were excluded because of pathological fractures. The remaining eighty-six patients (aged 80·2 (sd 7·3) years) were studied. Among these patients 76·7 % were female, 69·8 % walked with or without support and 12·8 % died 6 months after the fracture. In a multivariate analysis, only the MNA was associated with gait status 6 months after hip fracture (OR 0·773, 95 % CI 0·663, 0·901; P= 0·001). In the Cox regression model, only the MNA was associated with mortality 6 months after hip fracture (hazard ratio 0·869, 95 % CI 0·757, 0·998; P= 0·04). In conclusion, the MNA best predicts gait status and mortality 6 months after hip fracture. These results suggest that the MNA should be included in the clinical stratification of patients with hip fracture to identify and treat malnutrition in order to improve the outcomes.

  3. Nutritional Status Predicts 10-Year Mortality in Patients with End-Stage Renal Disease on Hemodialysis.

    PubMed

    Kang, Shin Sook; Chang, Jai Won; Park, Yongsoon

    2017-04-18

    Protein-energy wasting (PEW) is associated with mortality in patients with end-stage renal disease (ESRD) on maintenance hemodialysis. The correct diagnosis of PEW is extremely important in order to predict clinical outcomes. However, it is unclear which parameters should be used to diagnose PEW. Therefore, this retrospective observational study investigated the relationship between mortality and nutritional parameters in ESRD patients on maintenance hemodialysis. A total of 144 patients were enrolled. Nutritional parameters, including body mass index, serum albumin, dietary intake, normalized protein catabolic rate (nPCR), and malnutrition inflammation score (MIS), were measured at baseline. Fifty-three patients died during the study. Survivors had significantly higher nPCR (1.10 ± 0.24 g/kg/day vs. 1.01 ± 0.21 g/kg/day; p = 0.048), energy intake (26.7 ± 5.8 kcal/kg vs. 24.3 ± 4.2 kcal/kg; p = 0.009) and protein intake (0.91 ± 0.21 g/kg vs. 0.82 ± 0.24 g/kg; p = 0.020), and lower MIS (5.2 ± 2.3 vs. 6.1 ± 2.1, p = 0.039). In multivariable analysis, energy intake <25 kcal/kg (HR 1.860, 95% CI 1.018-3.399; p = 0.044) and MIS > 5 (HR 2.146, 95% CI 1.173-3.928; p = 0.013) were independent variables associated with all-cause mortality. These results suggest that higher MIS and lower energy intake are harmful to ESRD patients on maintenance hemodialysis. Optimal energy intake could reduce mortality in these patients.

  4. [Predictions of cancer incidence and mortality in Catalonia to 2015 by means of Bayesian models].

    PubMed

    Ribes, J; Clèries, R; Buxó, M; Ameijide, A; Valls, J; Gispert, R

    2008-10-01

    To perform cancer incidence and mortality projections in Catalonia for the period 2005-2019. To assess the projected increase in the incidence in 2015 compared with that in 2005, and to determine whether this increase is attributable to changes in risk or in demographics. Bayesian age-period-cohort models were fitted to age-specific rates for 1985-2004 to obtain the expected number of cases for the 5-year periods 2005-2009, 2010-2014 and 2015- 2019. Annual cases were estimated through a polynomial interpolation model. Incidence and mortality data were obtained from the Tarrragona and Gerona cancer registries, while population pyramids for the period 1985-2019 were obtained from the Catalan Institute of Statistics. In Catalonia, 27,438 cancer cases will be diagnosed among men and 19,986 among women in 2015, representing an increase in the number of cases diagnosed of 31% and 34%, respectively, when compared with those diagnosed in 2005 (20,999 and 14,141, respectively). In men, the increases attributable to risk, aging and demographic changes are 10%, 14% and 7%, respectively, whereas in women these changes are 6%, 13% and 15%. In the next decade, cancer mortality is expected to stabilize in men and to continue to decrease in women. Major increases in cancer incidence and mortality are expected among old age groups. The present study highlights the need to reorganize the resources and infrastructures required for cancer control and care, taking into account the predicted burden of oncology patients.

  5. Exercise heart rate gradient: a novel index to predict all-cause mortality.

    PubMed

    Duarte, Carlos Vieira; Myers, Jonathan; de Araújo, Claudio Gil Soares

    2015-05-01

    Although substantial evidence relates reduced exercise heart rate (HR) reserve and recovery to a higher risk of all-cause mortality, a combined indicator of these variables has not been explored. Our aim was to combine HR reserve and recovery into a single index and to assess its utility to predict all-cause mortality. Retrospective cohort analysis. Participants were 1476 subjects (937 males) aged between 41 and 79 years who completed a maximal cycle cardiopulmonary exercise test while not using medication with negative chronotropic effects or having an implantable cardiac pacemaker. HR reserve (HR maximum - HR resting) and recovery (HR maximum - HR at 1-min post exercise) were calculated and divided into quintiles. Quintile rankings were summed yielding an exercise HR gradient (EHRG) ranging from 2 to 10, reflecting the magnitude of on- and off-HR transients to exercise. Survival analyses were undertaken using EHRG scores and HR reserve and recovery in the lowest quintiles (Q1). During a mean follow up of 7.3 years, 44 participants died (3.1%). There was an inverse trend for EHRG scores and death rate (p < 0.05) that increased from 1.2% to 13.5%, respectively, for scores 10 and 2. An EHRG score of 2 was a better predictor of all-cause mortality than either Q1 for HR reserve (<80 bpm) or HR recovery alone (<27 bpm): age-adjusted hazard ratios: 3.53 (p = 0.011), 2.52 (p < 0.05), and 2.57 (p < 0.05), respectively. EHRG, a novel index combining HR reserve and HR recovery, is a better indicator of mortality risk than either response alone. © The European Society of Cardiology 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  6. What predicts mortality in Parkinson disease?: a prospective population-based long-term study.

    PubMed

    Forsaa, E B; Larsen, J P; Wentzel-Larsen, T; Alves, G

    2010-10-05

    To identify independent risk factors of mortality in a community-based Parkinson disease (PD) cohort during prospective long-term follow-up. A community-based prevalent sample of 230 patients with PD from southwestern Norway was followed prospectively with repetitive assessments of motor and nonmotor symptoms from 1993 to 2005. Information on vital status until October 20, 2009, was obtained from the National Population Register in Norway. Cox proportional hazards models were applied to identify independent predictors of mortality during follow-up. Chronological age, Unified Parkinson's Disease Rating Scale (UPDRS) motor score, levodopa equivalent dose, probable REM sleep behavior disorder, psychotic symptoms, dementia, and use of antipsychotics were included as time-dependent variables, and age at onset (AAO) and sex as time-independent variables. Of 230 patients, 211 (92%) died during the study period. Median survival time from motor onset was 15.8 years (range 2.2-36.6). Independent predictors of mortality during follow-up were AAO (hazard ratio [HR] 1.40 for 10-years increase, p = 0.029), chronological age (HR 1.51 for 10-years increase, p = 0.043), male sex (HR 1.63, p = 0.001), UPDRS motor score (HR 1.18 for 10-point increase, p < 0.001), psychotic symptoms (HR 1.45, p = 0.039), and dementia (HR 1.89, p = 0.001). This population-based long-term study demonstrates that in addition to AAO, chronological age, motor severity, and dementia, psychotic symptoms independently predict increased mortality in PD. In contrast, no significant impact of antipsychotic or antiparkinsonian drugs on survival was observed in our PD cohort. Early prevention of motor progression and development of psychosis and dementia may be the most promising strategies to increase life expectancy in PD.

  7. Central Venous Pressure After Coronary Artery Bypass Surgery: Does it Predict Postoperative Mortality or Renal Failure?

    PubMed Central

    Williams, Judson B.; Peterson, Eric D.; Wojdyla, Daniel; Ferguson, T. Bruce; Smith, Peter K.; Milano, Carmelo A.; Lopes, Renato D.

    2015-01-01

    Background While hemodynamic monitoring is often performed following coronary artery bypass grafting (CABG), the relationship between postoperative central venous pressure (CVP) measurement and clinical outcomes is unknown. Methods Detailed clinical data were analyzed from 2,390 randomly selected patients undergoing high risk CABG or CABG/valve at 55 hospitals participating in the Society of Thoracic Surgeons' National Cardiac Surgery Database from 2004 to 2005. Eligible patients underwent elective/urgent isolated CABG with an ejection fraction < 40%, or elective/urgent CABG at age ≥65 years with diabetes or a glomerular filtration rate 60 mL/min per 1.73 m2. Correlation between post-operative CVP and in-hospital / 30-day mortality and renal failure was assessed as a continuous variable, both unadjusted and after adjusting for important clinical factors using logistic regression modeling. Results Mean age was 72 years, 54% of patients had diabetes mellitus, 49% were urgent procedures, and mean cardiopulmonary bypass time was 105 minutes. Patients’ CVP 6 hours post-operation was strongly associated with in-hospital and 30 day mortality: odds ratio (OR) 1.5 (95% confidence interval [CI] 1.23, 1.87) for every 5 mmHg increase in CVP, p<0.0001. This association remained significant after risk-adjustment for cardiac index: adjusted OR 1.44 (95% CI 1.10, 1.89), p<0.01. A model adjusting for cardiac index also revealed increased incidence of mortality or renal failure: adjusted OR 1.5 (95% CI 1.28, 1.86) for every 5 mmHg increase in CVP, p<0.0001. Conclusion Patients’ central venous pressure at 6 hours following CABG surgery was highly predictive of operative mortality or renal failure, independent of cardiac index and other important clinical variables. Future studies will need to assess whether post-operative CVP can be used to guide intervention and improve outcomes. PMID:25035048

  8. MELD-XI Score Predicts Early Mortality in Patients After Heart Transplantation.

    PubMed

    Grimm, Joshua C; Shah, Ashish S; Magruder, J Trent; Kilic, Arman; Valero, Vicente; Dungan, Samuel P; Tedford, Ryan J; Russell, Stuart D; Whitman, Glenn J R; Sciortino, Christopher M

    2015-11-01

    The aim of this study was to determine the utility of the Model for End-Stage Liver Disease Excluding INR (MELD-XI) in predicting early outcomes (30 days and 1 year) and late outcomes (5 years) in patients after orthotopic heart transplantation (OHT). The United Network for Organ Sharing database was queried for all adult patients (aged ≥ 18 years) undergoing OHT from 2000 to 2012. A MELD-XI was calculated and the population stratified into score quartiles. Early and late survivals were compared among the MELD-XI cohorts. Multivariable Cox proportional hazards models were constructed to determine the capacity of MELD-XI (when modeled both as a categoric and a continuous variable) to predict 30-day, 1-year, and 5-year mortality. Conditional models were also designed to determine the effect of early mortality on long-term survival. A total of 22,597 patients were included for analysis. The MELD-XI cutoff scores were established as follows: low (≤ 10.5), low-intermediate (10.6 to 12.6), intermediate-high (12.7 to 16.4), and high (>16.4). The high MELD-XI cohort experienced statistically worse 30-day, 1-year, and 5-year unconditional survivals when compared with patients with low scores (p < 0.001). Similarly, a high MELD-XI score was also predictive of early and late mortality (p < 0.001) after risk adjustment. There was, however, no difference in 5-year survival between the high score and low score cohorts after accounting for 1-year deaths. Subanalysis of patients bridged to transplant with a continuous-flow left ventricular assist device demonstrated similar findings. This is the first known study to examine the relationship between a high MELD-XI score and outcomes in patients after OHT. Patients with hepatic or renal dysfunction before OHT should be closely monitored and aggressively optimized as early mortality appears to drive long-term outcomes. Copyright © 2015 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  9. Incidence, Mortality and Positive Predictive Value of Type 1 Cardiorenal Syndrome in Acute Coronary Syndrome

    PubMed Central

    Pimienta González, Raquel; Couto Comba, Patricia; Rodríguez Esteban, Marcos; Alemán Sánchez, José Juan; Hernández Afonso, Julio; Rodríguez Pérez, María del Cristo; Marcelino Rodríguez, Itahisa; Brito Díaz, Buenaventura; Elosua, Roberto; Cabrera de León, Antonio

    2016-01-01

    Objectives To determine whether the risk of cardiovascular mortality associated with cardiorenal syndrome subtype 1 (CRS1) in patients who were hospitalized for acute coronary syndrome (ACS) was greater than the expected risk based on the sum of its components, to estimate the predictive value of CRS1, and to determine whether the severity of CRS1 worsens the prognosis. Methods Follow-up study of 1912 incident cases of ACS for 1 year after discharge. Cox regression models were estimated with time to event (in-hospital death, and readmission or death during the first year after discharge) as the dependent variable. Results The incidence of CRS1 was 9.2/1000 person-days of hospitalization (95% CI = 8.1–10.5), but these patients accounted for 56.6% (95% CI = 47.4–65.) of all mortality. The positive predictive value of CRS1 was 29.6% (95% CI = 23.9–36.0) for in-hospital death, and 51.4% (95% CI = 44.8–58.0) for readmission or death after discharge. The risk of in-hospital death from CRS1 (RR = 18.3; 95% CI = 6.3–53.2) was greater than the sum of risks associated with either acute heart failure (RR = 7.6; 95% CI = 1.8–31.8) or acute kidney injury (RR = 2.8; 95% CI = 0.9–8.8). The risk of events associated with CRS1 also increased with syndrome severity, reaching a RR of 10.6 (95% CI = 6.2–18.1) for in-hospital death at the highest severity level. Conclusions The effect of CRS1 on in-hospital mortality is greater than the sum of the effects associated with each of its components, and it increases with the severity of the syndrome. CRS1 accounted for more than half of all mortality, and its positive predictive value approached 30% in-hospital and 50% after discharge. PMID:27907067

  10. 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.

  11. Development and Validation of a Mortality Prediction Model for Patients Receiving 14 Days of Mechanical Ventilation.

    PubMed

    Hough, Catherine L; Caldwell, Ellen S; Cox, Christopher E; Douglas, Ivor S; Kahn, Jeremy M; White, Douglas B; Seeley, Eric J; Bangdiwala, Shrikant I; Rubenfeld, Gordon D; Angus, Derek C; Carson, Shannon S

    2015-11-01

    The existing risk prediction model for patients requiring prolonged mechanical ventilation is not applicable until after 21 days of mechanical ventilation. We sought to develop and validate a mortality prediction model for patients earlier in the ICU course using data from day 14 of mechanical ventilation. Multicenter retrospective cohort study. Forty medical centers across the United States. Adult patients receiving at least 14 days of mechanical ventilation. None. Predictor variables were measured on day 14 of mechanical ventilation in the development cohort and included in a logistic regression model with 1-year mortality as the outcome. Variables were sequentially eliminated to develop the ProVent 14 model. This model was then generated in the validation cohort. A simplified prognostic scoring rule (ProVent 14 Score) using categorical variables was created in the development cohort and then tested in the validation cohort. Model discrimination was assessed by the area under the receiver operator characteristic curve. Four hundred ninety-one patients and 245 patients were included in the development and validation cohorts, respectively. The most parsimonious model included age, platelet count, requirement for vasopressors, requirement for hemodialysis, and nontrauma admission. The area under the receiver operator characteristic curve for the ProVent 14 model using continuous variables was 0.80 (95% CI, 0.76-0.83) in the development cohort and 0.78 (95% CI, 0.72-0.83) in the validation cohort. The ProVent 14 Score categorized age at 50 and 65 years old and platelet count at 100×10(9)/L and had similar discrimination as the ProVent 14 model in both cohorts. Using clinical variables available on day 14 of mechanical ventilation, the ProVent 14 model can identify patients receiving prolonged mechanical ventilation with a high risk of mortality within 1 year.

  12. Macrophage-colony stimulating factor (CSF1) predicts breast cancer progression and mortality.

    PubMed

    Richardsen, Elin; Uglehus, Rebecca Dale; Johnsen, Stein Harald; Busund, Lill-Tove

    2015-02-01

    Macrophage colony-stimulating factor (CSF1), also known as colony-stimulating factor-1 (CSF1), and its receptor CSF1R have been correlated with poor prognosis in many cancer types including breast cancer. Herein, we investigated the prognostic impact of CSF1 and CSF1R expression in tumor epithelial and stromal compartments in primary breast cancer and axillary lymph node metastases. In addition, the density of CD68+ tumor-associated macrophages (TAMs) and CD3+ T-lymphocytes was examined. Tumor tissue was obtained at the time of primary surgery from 68 prior treatment breast cancer patients, 38 with axillary lymph node metastases and 30 patients without metastases. Digital video analysis was performed on immunohistochemically stained slides. The expression of CSF1, CSF1R and the density of TAMs and CD3+ T-lymphocytes were then correlated to metastases and disease-specific mortality. Metastasized primary cancers had higher tumor epithelial and stromal expressions of CSF1 (p<0.001 and p=0.002, respectively) and CSF1R (both p=0.03) compared to non-metastatic cancers. Similar findings were made for the density of CD68+ (p=0.003) and CD3+ cells in the tumor epithelium (p<0.001). In multivariate analysis, a high tumor epithelial expression of CSF1 in primary breast cancer predicted mortality (hazard ratio (HR)=8.6, p=0.039). High expression of CSF1 and CSF1R and high density of TAMs and CD3+ T-lymphocytes were related to breast cancer progression. CSF1 expression in tumor epithelium predicted breast cancer mortality. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

  13. Predicting hospitalization and mortality in patients with heart failure: The BARDICHE-index.

    PubMed

    Uszko-Lencer, Nicole H M K; Frankenstein, Lutz; Spruit, Martijn A; Maeder, Micha T; Gutmann, Marc; Muzzarelli, Stefano; Osswald, Stefan; Pfisterer, Matthias E; Zugck, Christian; Brunner-La Rocca, Hans-Peter

    2017-01-15

    Prediction of events in chronic heart failure (CHF) patients is still difficult and available scores are often complex to calculate. Therefore, we developed and validated a simple-to-use, multidimensional prognostic index for such patients. A theoretical model was developed based on known prognostic factors of CHF that are easily obtainable: Body mass index (B), Age (A), Resting systolic blood pressure (R), Dyspnea (D), N-termInal pro brain natriuretic peptide (NT-proBNP) (I), Cockroft-Gault equation to estimate glomerular filtration rate (C), resting Heart rate (H), and Exercise performance using the 6-min walk test (E) (the BARDICHE-index). Scores were given for all components and added, the sum ranging from 1 (lowest value) to 25 points (maximal value), with estimated risk being highest in patients with highest scores. Scores were categorized into three groups: a low (≤8 points); medium (9-16 points), or high (>16 points) BARDICHE-score. The model was validated in a data set of 1811 patients from two prospective CHF-cohorts (median follow-up 887days). The primary outcome was 5-year all-cause survival. Secondary outcomes were 5-year survival without all-cause hospitalization and 5-year survival without CHF-related hospitalization. There were significant differences between BARDICHE-risk groups for mortality (hazard ratio=3.63 per BARDICHE-group, 95%-CI 3.10-4.25), mortality or all-cause hospitalization (HR=2.00 per BARDICHE-group, 95%-CI 1.83-2.19), and mortality or CHF-related hospitalization (HR=3.43 per BARDICHE-group, 95%-CI 3.01-3.92; all P<10-50). Outcome was predicted independently of left ventricular ejection fraction (LVEF) and gender. The BARDICHE-index is a simple multidimensional prognostic tool for patients with CHF, independently of LVEF. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  14. Bayesian multilevel discrete interval hazard analysis to predict dichlorodiphenyldichloroethylene mortality in Hyalella azteca based on body residues.

    PubMed

    Lee, Jong-Hyeon; Stow, Craig A; Landrum, Peter F

    2009-11-01

    We exposed Hyalella azteca to p,p'-dichlorodiphenyldichloroethylene for intervals of 1 to 4 d and followed mortality out to 10 d. Mortality was determined as the cessation of heartbeat; dead organism body residue was determined daily. To model mortality probability, body residues of the living organisms were estimated using published kinetic data with concentration-dependent rate constants. The estimated residues compared favorably with measured residues in the dead organisms (predicted body residue = 1.302 ± 0.142 measured body residue + 10.351 ± 15.766, r² = 0.64, n = 50). The response data were collected at discrete intervals; thus, it was not possible to determine the exact time of death for organisms. Consequently, we analyzed the mortality data using discrete interval analysis, in a Bayesian hierarchical framework, with body residue as the dose metric. The predicted body residues to produce mortality were similar across the duration of exposure when postexposure mortality was considered. The concentration for 50% mortality was 0.47 μmol/g (148.6 tg/g, range 0.32-0.66 μmol/g), and predictions of response indicted 95% (range 73-99.9%) mortality at 0.79 μmol/g (250 μg/g) and 4% (range 1.2-9.6%) mortality at 0.16 μmol/g (50 μg/g). The lethal residue for 50% mortality based on interval analysis for short-term exposures with postexposure mortality resulted in values similar to long-term continuous exposures for exposure durations of more than 600 h.

  15. Quantitative and Morphological Measures May Predict Growth and Mortality During Prenatal Growth in Japanese Quails

    PubMed Central

    Arora, Kashmiri L.; Vatsalya, Vatsalya

    2014-01-01

    Growth pattern and mortality rate during the embryonic phase of avian species are difficult to recognize and predict. Determination of such measures and associated events may enhance our understanding of characteristics involved in the growth and hatching process. Furthermore, some quantitative measures could validate morphological determinants during the embryonic phase and predict the course of normal growth and alterations. Our aim was to characterize quantitative growth of embryos and to establish baseline embryonic standards for use in comparative and pathological research during the prenatal life of Japanese quail. Day 10 was a landmark timeline for initiation of extensive anatomical changes in growth and transformation. Wet and dry weights were positively correlated with each other and inversely correlated with water content (p = 0.05). Following d10, the water content decreased progressively, whereas, dry and wet weights increased with increasing age. Velocity of growth in wet and dry weights was evident starting d6, spiked at d11 and d15 and then declined before hatching on d16. Organic and inorganic contents of embryos were positively associated with age. Progressive increase in the organic to inorganic ratio with age was evident after d5, spiked on d9, d13 and d16. Accurate determinations of prenatal growth processes could serve as valuable tools in identifying morphological developments and characterization of prenatal growth and mortality, thus enhancing the reproductive efficiency of the breeding colony and the postnatal robustness of the offspring. PMID:25285101

  16. CIBMTR Chronic GVHD Risk Score Predicts Mortality in an Independent Validation Cohort

    PubMed Central

    Arora, Mukta; Hemmer, Michael T.; Ahn, Kwang Woo; Klein, John P.; Cutler, Corey S.; Urbano-Ispizua, Alvaro; Couriel, Daniel R.; Alousi, Amin M.; Gale, Robert Peter; Inamoto, Yoshihiro; Weisdorf, Daniel J.; Li, Peigang; Antin, Joseph H.; Bolwell, Brian J.; Boyiadzis, Michael; Cahn, Jean-Yves; Cairo, Mitchell S.; Isola, Luis M.; Jacobsohn, David A.; Jagasia, Madan; Klumpp, Thomas R.; Petersdorf, Effie W.; Santarone, Stella; Schouten, Harry C.; Wingard, John R.; Spellman, Stephen R.; Pavletic, Steven Z.; Lee, Stephanie J.; Horowitz, Mary M.; Flowers, Mary E.D.

    2015-01-01

    We previously reported a risk score that predicted mortality in patients with chronic graft-versus-host disease (CGVHD) after hematopoietic stem cell transplant (HCT) between 1995–2004 and reported to the Center for International Blood and Marrow Transplant Registry (CIBMTR). We sought to validate this risk score in an independent CIBMTR cohort of 1128 patients with CGVHD transplanted between 2005–2007 using the same inclusion criteria and risk-score calculations. According to the sum of the overall risk score (range 1 to 12), patients were assigned to 4 risk-groups (RGs): RG1 (0–2), RG2 (3–6), RG3 (7–8) and RG4 (9–10). RG3 and 4 were combined as RG4 comprised only 1% of the total cohort. Cumulative incidences of non relapse mortality (NRM) and probability of overall survival (OS) were significantly different between each RG (all p<0.01). NRM and OS at five years after CGVHD for each RG were 17% and 72% in RG1, 26% and 53% in RG2, and 44% and 25% in RG 3, respectively (all p<0.01). Our study validates the prognostic value of the CIBMTR CGVHD RGs for OS and NRM in a contemporary transplant population. The CIBMTR CGVHD RGs can be used to predict major outcomes, tailor treatment planning, and enrollment in clinical trials. PMID:25528390

  17. Validation of a risk stratification index and risk quantification index for predicting patient outcomes: in-hospital mortality, 30-day mortality, 1-year mortality, and length-of-stay.

    PubMed

    Sigakis, Matthew J G; Bittner, Edward A; Wanderer, Jonathan P

    2013-09-01

    External validation of published risk stratification models is essential to determine their generalizability. This study evaluates the performance of the Risk Stratification Indices (RSIs) and 30-day mortality Risk Quantification Index (RQI). 108,423 adult hospital admissions with anesthetics were identified (2006-2011). RSIs for mortality and length-of-stay endpoints were calculated using published methodology. 91,128 adult, noncardiac inpatient surgeries were identified with administrative data required for RQI calculation. RSI in-hospital mortality and RQI 30-day mortality Brier scores were 0.308 and 0.017, respectively. RSI discrimination, by area under the receiver operating curves, was excellent at 0.966 (95% CI, 0.963-0.970) for in-hospital mortality, 0.903 (0.896-0.909) for 30-day mortality, 0.866 (0.861-0.870) for 1-yr mortality, and 0.884 (0.882-0.886) for length-of-stay. RSI calibration, however, was poor overall (17% predicted in-hospital mortality vs. 1.5% observed after inclusion of the regression constant) as demonstrated by calibration plots. Removal of self-fulfilling diagnosis and procedure codes (20,001 of 108,423; 20%) yielded similar results. RQIs were calculated for only 62,640 of 91,128 patients (68.7%) due to unmatched procedure codes. Patients with unmatched codes were younger, had higher American Society of Anesthesiologists physical status and 30-day mortality. The area under the receiver operating curve for 30-day mortality RQI was 0.888 (0.879-0.897). The model also demonstrated good calibration. Performance of a restricted index, Procedure Severity Score + American Society of Anesthesiologists physical status, performed as well as the original RQI model (age + American Society of Anesthesiologists + Procedure Severity Score). Although the RSIs demonstrated excellent discrimination, poor calibration limits their generalizability. The 30-day mortality RQI performed well with age providing a limited contribution.

  18. Personalized Mortality Prediction Driven by Electronic Medical Data and a Patient Similarity Metric

    PubMed Central

    Lee, Joon; Maslove, David M.; Dubin, Joel A.

    2015-01-01

    Background Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. Methods and Findings We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. Conclusions The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our

  19. Personalized mortality prediction driven by electronic medical data and a patient similarity metric.

    PubMed

    Lee, Joon; Maslove, David M; Dubin, Joel A

    2015-01-01

    Clinical outcome prediction normally employs static, one-size-fits-all models that perform well for the average patient but are sub-optimal for individual patients with unique characteristics. In the era of digital healthcare, it is feasible to dynamically personalize decision support by identifying and analyzing similar past patients, in a way that is analogous to personalized product recommendation in e-commerce. Our objectives were: 1) to prove that analyzing only similar patients leads to better outcome prediction performance than analyzing all available patients, and 2) to characterize the trade-off between training data size and the degree of similarity between the training data and the index patient for whom prediction is to be made. We deployed a cosine-similarity-based patient similarity metric (PSM) to an intensive care unit (ICU) database to identify patients that are most similar to each patient and subsequently to custom-build 30-day mortality prediction models. Rich clinical and administrative data from the first day in the ICU from 17,152 adult ICU admissions were analyzed. The results confirmed that using data from only a small subset of most similar patients for training improves predictive performance in comparison with using data from all available patients. The results also showed that when too few similar patients are used for training, predictive performance degrades due to the effects of small sample sizes. Our PSM-based approach outperformed well-known ICU severity of illness scores. Although the improved prediction performance is achieved at the cost of increased computational burden, Big Data technologies can help realize personalized data-driven decision support at the point of care. The present study provides crucial empirical evidence for the promising potential of personalized data-driven decision support systems. With the increasing adoption of electronic medical record (EMR) systems, our novel medical data analytics contributes to

  20. Modification of diet in renal disease and Cockcroft-Gault formulas do not predict mortality (ZODIAC-6).

    PubMed

    Bilo, H J G; Logtenberg, S J J; Joosten, H; Groenier, K H; Ubink-Veltmaat, L J; Kleefstra, N

    2009-05-01

    An inverse relationship between estimates of renal function, with formulas such as the Modification of diet in renal disease (MDRD) study equation or the Cockcroft-Gault formula, and mortality has been suggested. These formulas both contain the variables sex, serum creatinine and age and the latter also contains body weight. We investigated whether these formulas predict mortality better than the variables they contain together in patients with Type 2 diabetes. In 1998, 1143 primary care patients with Type 2 diabetes participated in the Zwolle Outpatient Diabetes project Integrating Available Care (ZODIAC) Study, in the Netherlands. Clinical and laboratory data were collected at baseline. Life status was assessed after 6 years. We used Cox proportional hazard modelling to investigate the association between estimates of renal function (continuous data) and the variables they contain and mortality, adjusting for confounders. Both formulas were compared with models consisting of the variables present in the formulas. Predictability was assessed using Bayesian information criterion (BIC) and Harrell's C statistics. At follow-up, 335 patients had died. All variables, except sex, influenced mortality. Predictive capability, indicated by lower BIC values and higher Harrell's C values, was up to 10% better for models containing the separate variables as compared with Cockcroft-Gault or MDRD. Using estimates of renal function to assess mortality risk decreases predictability as compared with the combination of the risk factors they contain. These formulas, therefore, could be used to estimate renal function; however, they should not be used as a tool to predict mortality risk.

  1. Mortality Risk Prediction by an Insurance Company and Long-Term Follow-Up of 62,000 Men

    PubMed Central

    Sijbrands, Eric J. G.; Tornij, Erik; Homsma, Sietske J.

    2009-01-01

    Background Insurance companies use medical information to classify the mortality risk of applicants. Adding genetic tests to this assessment is currently being debated. This debate would be more meaningful, if results of present-day risk prediction were known. Therefore, we compared the predicted with the observed mortality of men who applied for life insurance, and determined the prognostic value of the risk assessment. Methods Long-term follow-up was available for 62,334 male applicants whose mortality risk was predicted with medical evaluation and they were assigned to five groups with increasing risk from 1 to 5. We calculated all cause standardized mortality ratios relative to the Dutch population and compared groups with Cox's regression. We compared the discriminative ability of risk assessments as indicated by a concordance index (c). Results In 844,815 person years we observed 3,433 deaths. The standardized mortality relative to the Dutch male population was 0.76 (95 percent confidence interval, 0.73 to 0.78). The standardized mortality ratios ranged from 0.54 in risk group 1 to 2.37 in group 5. A large number of risk factors and diseases were significantly associated with increased mortality. The algorithm of prediction was significantly, but only slightly better than summation of the number of disorders and risk factors (c-index, 0.64 versus 0.60, P<0.001). Conclusions Men applying for insurance clearly had better survival relative to the general population. Readily available medical evaluation enabled accurate prediction of the mortality risk of large groups, but the deceased men could not have been identified with the applied prediction method. PMID:19421319

  2. The predictive value of different measures of obesity for incident cardiovascular events and mortality.

    PubMed

    Schneider, Harald J; Friedrich, Nele; Klotsche, Jens; Pieper, Lars; Nauck, Matthias; John, Ulrich; Dörr, Marcus; Felix, Stephan; Lehnert, Hendrik; Pittrow, David; Silber, Sigmund; Völzke, Henry; Stalla, Günter K; Wallaschofski, Henri; Wittchen, Hans-Ulrich

    2010-04-01

    To date, it is unclear which measure of obesity is the most appropriate for risk stratification. The aim of the study was to compare the associations of various measures of obesity with incident cardiovascular events and mortality. We analyzed two German cohort studies, the DETECT study and SHIP, including primary care and general population. A total of 6355 (mean follow-up, 3.3 yr) and 4297 (mean follow-up, 8.5 yr) individuals participated in DETECT and SHIP, respectively. We measured body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and waist-to-hip ratio (WHR) and assessed cardiovascular and all-cause mortality and the composite endpoint of incident stroke, myocardial infarction, or cardiovascular death. In both studies, we found a positive association of the composite endpoint with WHtR but not with BMI. There was no heterogeneity among studies. The relative risks in the highest versus the lowest sex- and age-specific quartile of WHtR, WC, WHR, and BMI after adjustment for multiple confounders were as follows in the pooled data: cardiovascular mortality, 2.75 (95% confidence interval, 1.31-5.77), 1.74 (0.84-3.6), 1.71 (0.91-3.22), and 0.74 (0.35-1.57), respectively; all-cause mortality, 1.86 (1.25-2.76), 1.62 (1.22-2.38), 1.36 (0.93-1.69), and 0.77 (0.53-1.13), respectively; and composite endpoint, 2.16 (1.39-3.35), 1.59 (1.04-2.44), 1.49 (1.07-2.07), and 0.57 (0.37-0.89), respectively. Separate analyses of sex and age groups yielded comparable results. Receiver operating characteristics analysis yielded the highest areas under the curve for WHtR for predicting these endpoints. WHtR represents the best predictor of cardiovascular risk and mortality, followed by WC and WHR. Our results discourage the use of the BMI.

  3. Longitudinal change in the BODE index predicts mortality in severe emphysema.

    PubMed

    Martinez, Fernando J; Han, Meilan K; Andrei, Adin-Cristian; Wise, Robert; Murray, Susan; Curtis, Jeffrey L; Sternberg, Alice; Criner, Gerard; Gay, Steven E; Reilly, John; Make, Barry; Ries, Andrew L; Sciurba, Frank; Weinmann, Gail; Mosenifar, Zab; DeCamp, Malcolm; Fishman, Alfred P; Celli, Bartolome R

    2008-09-01

    The predictive value of longitudinal change in BODE (Body mass index, airflow Obstruction, Dyspnea, and Exercise capacity) index has received limited attention. We hypothesized that decrease in a modified BODE (mBODE) would predict survival in National Emphysema Treatment Trial (NETT) patients. To determine how the mBODE score changes in patients with lung volume reduction surgery versus medical therapy and correlations with survival. Clinical data were recorded using standardized instruments. The mBODE was calculated and patient-specific mBODE trajectories during 6, 12, and 24 months of follow-up were estimated using separate regressions for each patient. Patients were classified as having decreasing, stable, increasing, or missing mBODE based on their absolute change from baseline. The predictive ability of mBODE change on survival was assessed using multivariate Cox regression models. The index of concordance was used to directly compare the predictive ability of mBODE and its separate components. The entire cohort (610 treated medically and 608 treated surgically) was characterized by severe airflow obstruction, moderate breathlessness, and increased mBODE at baseline. A wide distribution of change in mBODE was seen at follow-up. An increase in mBODE of more than 1 point was associated with increased mortality in surgically and medically treated patients. Surgically treated patients were less likely to experience death or an increase greater than 1 in mBODE. Indices of concordance showed that mBODE change predicted survival better than its separate components. The mBODE demonstrates short- and intermediate-term responsiveness to intervention in severe chronic obstructive pulmonary disease. Increase in mBODE of more than 1 point from baseline to 6, 12, and 24 months of follow-up was predictive of subsequent mortality. Change in mBODE may prove a good surrogate measure of survival in therapeutic trials in severe chronic obstructive pulmonary disease. Clinical

  4. IL-6 predicts organ dysfunction and mortality in patients with multiple injuries

    PubMed Central

    Frink, Michael; van Griensven, Martijn; Kobbe, Philipp; Brin, Thomas; Zeckey, Christian; Vaske, Bernhard; Krettek, Christian; Hildebrand, Frank

    2009-01-01

    Background Although therapeutic concepts of patients with major trauma have improved during recent years, organ dysfunction still remains a frequent complication during clinical course in intensive care units. It has previously been shown that cytokines are upregulated under stress conditions such as trauma or sepsis. However, it is still debatable if cytokines are adequate parameters to describe the current state of trauma patients. To elucidate the relevance of cytokines, we investigated if cytokines predict development of multiple organ dysfunction syndrome (MODS) or outcome. Methods A total of 143 patients with an injury severity score ≥ 16, between 16 and 65 years, admitted to the Hannover Medical School Level 1 Trauma Center between January 1997 and December 2001 were prospectively included in this study. Marshall Score for MODS was calculated for at least 14 days and plasma levels of TNF-α, IL-1β, IL-6, IL-8 and IL-10 were measured. To determine the association between cytokine levels and development of MODS the Spearman rank correlation coefficient was calculated and logistic regression and analysis were performed. Results and Discussion Patients with MODS had increased plasma levels of IL-6, IL-8 and IL-10. IL-6 predicted development of MODS with an overall accuracy of 84.7% (specificity: 98.3%, sensitivity: 16.7%). The threshold value for development of MODS was 761.7 pg/ml and 2176.0 pg/ml for mortality during the in patient time. Conclusion We conclude that plasma IL-6 levels predict mortality and that they are a useful tool to identify patients who are at risk for development of MODS. PMID:19781105

  5. Delirium and other clinical factors with Clostridium difficile infection that predict mortality in hospitalized patients.

    PubMed

    Archbald-Pannone, Laurie R; McMurry, Timothy L; Guerrant, Richard L; Warren, Cirle A

    2015-07-01

    Clostridium difficile infection (CDI) severity has increased, especially among hospitalized older adults. We evaluated clinical factors to predict mortality after CDI. We collected data from inpatients diagnosed with CDI at a U.S. academic medical center (HSR-IRB#13630). We evaluated age, Charlson comorbidity index (CCI), whether patients were admitted from a long-term care facility, whether patients were in an intensive care unit (ICU) at the time of diagnosis, white blood cell count (WBC), blood urea nitrogen (BUN), low body mass index, and delirium as possible predictors. A parsimonious predictive model was chosen using the Akaike information criterion (AIC) and a best subsets model selection algorithm. The area under the receiver operating characteristic curve was used to assess the model's comparative, with the AIC as the selection criterion for all subsets to measure fit and control for overfitting. From the 362 subjects, the selected model included CCI, WBC, BUN, ICU, and delirium. The logistic regression coefficients were converted to a points scale and calibrated so that each unit on the CCI contributed 2 points, ICU admission contributed 5 points, each unit of WBC (natural log scale) contributed 3 points, each unit of BUN contributed 5 points, and delirium contributed 11 points.Our model shows substantial ability to predict short-term mortality in patients hospitalized with CDI. Patients who were diagnosed in the ICU and developed delirium are at the highest risk for dying within 30 days of CDI diagnosis. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

  6. 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...

  7. 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...

  8. GRACE Score Validation in Predicting Hospital Mortality: Analysis of the Role of Sex.

    PubMed

    de-Miguel-Balsa, Eva; Latour-Pérez, Jaime; Baeza-Román, Anna; Amorós-Verdú, Cristina; Fernández-Lozano, Juan Antonio

    2017-01-20

    The GRACE (Global Registry of Acute Coronary Events) risk score is recommended for risk stratification in acute coronary syndrome (ACS). It does not include sex, a variable strongly associated with ACS prognosis. The aim of this study was to examine if sex adds prognostic information to the GRACE score in a contemporary population. Analysis of discrimination and calibration of GRACE score in the validation population, derived from the ARIAM-SEMICYUC registry (2012-2015). Outcome was hospital mortality. The uniformity of fit of the score was tested in predefined subpopulations: with and without ST-segment elevation myocardial infarction (STEMI and NSTEMI). A total of 9781 patients were included: 4598 with NSTEMI (28% women) and 5183 with STEMI (23% women). Discriminative capacity of the GRACE score was significantly lower in women with STEMI compared to men (area under the receiver operating characteristic curve [AUC] 0.82, 95% CI 0.78-0.86 vs. AUC 0.90, 95% CI 0.88-0.92, p = 0.0006). In multivariate analysis, female sex predicted hospital mortality independently of GRACE in STEMI (p = 0.019) but not in NSTEMI (p = 0.356) (interaction p = 0.0308). However, neither the AUC nor the net reclassification index (NRI) improved by including female sex in the STEMI subpopulation (NRI 0.0011, 95% CI -0.023 to 0.025; p = 0.928). Although female sex was an independent predictor of hospital mortality in the STEMI subpopulation, it does not substantially improve the discriminative ability of GRACE score.

  9. Real-time Automated Sampling of Electronic Medical Records Predicts Hospital Mortality

    PubMed Central

    Khurana, Hargobind S.; Groves, Robert H.; Simons, Michael P.; Martin, Mary; Stoffer, Brenda; Kou, Sherri; Gerkin, Richard; Reiman, Eric; Parthasarathy, Sairam

    2016-01-01

    Background Real-time automated continuous sampling of electronic medical record data may expeditiously identify patients at risk for death and enable prompt life-saving interventions. We hypothesized that a real-time electronic medical record-based alert could identify hospitalized patients at risk for mortality. Methods An automated alert was developed and implemented to continuously sample electronic medical record data and trigger when at least two of four systemic inflammatory response syndrome criteria plus at least one of 14 acute organ dysfunction parameters was detected. The SIRS/OD alert was applied real-time to 312,214 patients in 24 hospitals and analyzed in two phases: training and validation datasets. Results In the training phase, 29,317 (18.8%) triggered the alert and 5.2% of such patients died whereas only 0.2% without the alert died (unadjusted odds ratio 30.1; 95% confidence interval [95%CI] 26.1, 34.5; P<0.0001). In the validation phase, the sensitivity, specificity, area under curve (AUC), positive and negative likelihood ratios for predicting mortality were 0.86, 0.82, 0.84, 4.9, and 0.16, respectively. Multivariate Cox-proportional hazard regression model revealed greater hospital mortality when the alert was triggered (adjusted Hazards Ratio 4.0; 95%CI 3.3, 4.9; P<0.0001). Triggering the alert was associated with additional hospitalization days (+3.0 days) and ventilator days (+1.6 days; P<0.0001). Conclusion An automated alert system that continuously samples electronic medical record-data can be implemented, has excellent test characteristics, and can assist in the real-time identification of hospitalized patients at risk for death. PMID:27019043

  10. Global Sensory Impairment Predicts Morbidity and Mortality in Older U.S. Adults.

    PubMed

    Pinto, Jayant M; Wroblewski, Kristen E; Huisingh-Scheetz, Megan; Correia, Camil; Lopez, Kevin J; Chen, Rachel C; Kern, David W; Schumm, Philip L; Dale, William; McClintock, Martha K

    2017-09-24

    To evaluate global sensory impairment (GSI, an integrated measure of sensory dysfunction) as a predictor of physical function, cognition, overall health, and mortality. Prospective study. The National Social Life, Health, and Aging Project. A national probability sample of 3,005 home-dwelling older U.S. adults assessed at baseline (2005-06) and 5-year follow-up (2010-11). Gait speed, activity, disability, cognition, overall health, 5-year mortality. At baseline, older adults with worse GSI were slower (Timed Up and Go times: odds ratio (OR) = 1.32, 95% confidence interval (CI) = 1.17-1.50) and had more activity of daily living deficits (≥2: OR = 1.26, 95% CI = 1.10-1.46). Five years later, they were still slower (timed walk: OR = 1.22, 95% CI = 1.05-1.42), had more disabilities (≥2 instrumental activities of daily living; OR = 1.45, 95% CI = 1.23-1.70), were less active (daytime activity according to accelerometry: β = -2.7, 95% CI = -5.2 to -0.2), had worse cognitive function (Montreal Cognitive Assessment; β = -0.64, 95% CI = -0.84 to -0.44), more likely to have poorer overall health (OR = 1.16, 95% CI = 1.03-1.31) and lose weight (>10%: OR = 1.31, 95% CI = 1.04-1.64), and have died (OR = 1.45, 95% CI = 1.19-1.76). All analyses were adjusted for relevant confounders at baseline, including age, sex, race and ethnicity, education, smoking, problem drinking, body mass index, comorbidities, and cognitive function. GSI predicts impaired physical function, cognitive dysfunction, significant weight loss, and mortality 5 years later in older U.S. adults. Multisensory evaluation may identify vulnerable individuals, offering the opportunity for early intervention to mitigate adverse outcomes. © 2017, Copyright the Authors Journal compilation © 2017, The American Geriatrics Society.

  11. Retrospective evaluation of the BIG score to predict mortality in pediatric blunt trauma.

    PubMed

    Grandjean-Blanchet, Charlotte; Emeriaud, Guillaume; Beaudin, Marianne; Gravel, Jocelyn

    2017-08-14

    This study's objective was to measure the criterion validity of the BIG score (a new pediatric trauma score composed of the initial base deficit [BD], international normalized ratio [INR], and Glasgow Coma Scale [GCS]) to predict in-hospital mortality among children admitted to the emergency department with blunt trauma requiring an admission to the intensive care unit, knowing that a score <16 identifies children with a high probability of survival. This was a retrospective cohort study performed in a single tertiary care pediatric hospital between 2008 and 2016. Participants were all children admitted to the emergency department for a blunt trauma requiring intensive care unit admission or who died in the emergency department. The primary analysis was the association between a BIG score ≥16 and in-hospital mortality. Twenty-eight children died among the 336 who met the inclusion criteria. Two hundred eighty-four children had information on the three components of the BIG score, and they were included in the primary analysis. A BIG score ≥16 demonstrated a sensitivity of 0.93 (95% confidence interval [CI]: 0.76-0.98) and specificity of 0.83 (95% CI: 0.78-0.87) to identify mortality. Using receiver operating characteristic curves, the area under the curve was higher for the BIG score (0.97; 95% IC: 0.95-0.99) in comparison to the Injury Severity Score (0.78; 95% IC: 0.71-0.85). In this retrospective cohort, the BIG score was an excellent predictor of survival for children admitted to the emergency department following a blunt trauma.

  12. HBV-DNA levels predict overall mortality in HIV/HBV coinfected individuals.

    PubMed

    Nikolopoulos, Georgios K; Paraskevis, Dimitrios; Psichogiou, Mina; Hatzakis, Angelos

    2016-03-01

    The coinfection of Hepatitis B virus (HBV) and human immunodeficiency virus (HIV) has been associated with increased death rates. However, the relevant research has mostly relied on serologic HBV testing [HBV surface antigen (HBsAg)]. The aim of this work was to explore the relationship of HBV viraemia with overall mortality among HIV/HBV coinfected individuals. The analysis included 1,609 HIV seropositives of a previously described cohort (1984-2003) with limited exposure to tenofovir (12%) and a median follow-up of approximately 5 years. Those with persistent expression of HBsAg were further tested for HBV-DNA. The data were analyzed using Poisson regression models. Totally, 101 participants were chronic carriers of HBsAg (6.28%). Of these, 81 were tested for HBV-DNA. The median HBV-DNA levels were 3.81 log (base-10) International Units (IU)/ml. A third (31%) of those tested for HBV-DNA had received tenofovir. Before developing acquired immune deficiency syndrome (AIDS), the adjusted incidence rate ratio (IRR) for all-cause mortality of coinfected patients with HBV viraemia above the median value versus the HIV monoinfected group was 3.44 [95% confidence interval (CI): 1.05-11.27]. Multivariable regressions in the coinfected group only (n = 81) showed that one log-10 increase in HBV-DNA levels was associated with an elevated risk for death (IRR: 1.24, 95%CI: 1.03-1.49). HBV-DNA levels predict overall mortality in the setting of HIV/HBV coinfection, especially during the period before developing AIDS, and could thus help prioritize needs and determine the frequency of medical monitoring.

  13. CT pulmonary angiography findings that predict 30-day mortality in patients with acute pulmonary embolism.

    PubMed

    Bach, Andreas Gunter; Nansalmaa, Baasai; Kranz, Johanna; Taute, Bettina-Maria; Wienke, Andreas; Schramm, Dominik; Surov, Alexey

    2015-02-01

    Standard computed tomography pulmonary angiography (CTPA) can be used to diagnose acute pulmonary embolism. In addition, multiple findings at CTPA have been proposed as potential tools for risk stratification. Therefore, the aim of the present study is to examine the prognostic value of (I) thrombus distribution, (II) morphometric parameters of right ventricular dysfunction, and (III) contrast reflux in inferior vena cava on 30-day mortality. In a retrospective, single-center study from 06/2005 to 01/2010 365 consecutive patients were included. Inclusion criteria were: presence of acute pulmonary embolism, and availability of 30-day follow-up. A review of patient charts and images was performed. There were no significant differences between the group of 326 survivors and 39 non-survivors in (I) thrombus distribution, and (II) morphometric measurements of right ventricular dysfunction. However, (III) contrast reflux in inferior vena cava was significantly stronger in non-survivors (odds ratio 3.29; p<0.001). Results were independent from comorbidities like heart insufficiency and pulmonary hypertension. Measurement of contrast reflux is a new and robust method for predicting 30-day mortality in patients with acute pulmonary embolism. Obstruction scores and morphometric measurements of right ventricular dysfunction perform poor as risk stratification tools. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  14. New algorithm of mortality risk prediction for cardiovascular patients admitted in intensive care unit

    PubMed Central

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

    2015-01-01

    Objective: Recognizing and managing of admitted patients in intensive care unit (ICU) with high risk of mortality is important for maximizing the patient’s outcomes and minimizing the costs. This study is based on linear and nonlinear analysis of heart rate variability (HRV) to design a classifier for mortality prediction of cardio vascular patients admitted to ICU. Methods: In this study we evaluated 90 cardiovascular ICU patients (45 males and 45 females). Linear and nonlinear features of HRV include SDNN, NN50, low frequency (LF), high frequency (HF), correlation dimension, approximate entropy; detrended fluctuation analysis (DFA) and Poincaré plot were analyzed. Paired sample t-test was used for statistical comparison. Finally, we fed these features to the Multi-Layer Perceptron (MLP) and Support Vector Machines (SVMs) to find a robust classification method to classify the patients with low risk and high risk of death. Results: Almost all HRV features measuring heart rate complexity were significantly decreased in the episode of half-hour before death. The results generated based on SVM and MLP classifiers show that SVM classifier is enable to distinguish high and low risk episodes with the total classification sensitivity, specificity, positive productivity and accuracy rate of 97.3%, 98.1%, 92.5% and 99.3%, respectively. Conclusions: The results of the current study suggest that nonlinear features of the HRV signals could be show nonlinear dynamics. PMID:26309114

  15. Health Literacy Predicts Morbidity and Mortality in Rural Patients With Heart Failure.

    PubMed

    Moser, Debra K; Robinson, Susan; Biddle, Martha J; Pelter, Michele M; Nesbitt, Thomas S; Southard, Jeffery; Cooper, Lawton; Dracup, Kathleen

    2015-08-01

    Patients hospitalized with heart failure are often readmitted. Health literacy may play a substantial role in the high rate of readmissions. The purpose of this study was to examine the association of health literacy with the composite end point of heart failure readmission rates and all-cause mortality in patients with heart failure living in rural areas. Rural adults (n = 575), hospitalized for heart failure within the past 6 months, completed the Short Test of Functional Health Literacy in Adults (STOFHLA) to measure health literacy and were followed for ≥2 years. The percentage of patients with the end point of heart failure readmission or all-cause death was different (P = .001) among the 3 STOFHLA score levels. Unadjusted analysis revealed that patients with inadequate and marginal health literacy were 1.94 (95% confidence interval [CI] 1.43-2.63; P < .001) times, and 1.91 (95% CI 1.36-2.67; P < .001) times, respectively, more likely to experience the outcome. After adjustment for covariates, health literacy remained a predictor of outcomes. Of the other covariates, worse functional class, higher comorbidity burden, and higher depression score predicted worse outcomes. Inadequate or marginal health literacy is a risk factor for heart failure rehospitalization or all-cause mortality among rural patients with heart failure. Copyright © 2015 Elsevier Inc. All rights reserved.

  16. Early warning score independently predicts adverse outcome and mortality in patients with acute pancreatitis.

    PubMed

    Jones, Michael J; Neal, Christopher P; Ngu, Wee Sing; Dennison, Ashley R; Garcea, Giuseppe

    2017-08-01

    The aim of this study was to compare the prognostic value of established scoring systems with early warning scores in a large cohort of patients with acute pancreatitis. In patients presenting with acute pancreatitis, age, sex, American Society of Anaesthesiologists (ASA) grade, Modified Glasgow Score, Ranson criteria, APACHE II scores and early warning score (EWS) were recorded for the first 72 h following admission. These variables were compared between survivors and non-survivors, between patients with mild/moderate and severe pancreatitis (based on the 2012 Atlanta Classification) and between patients with a favourable or adverse outcome. A total of 629 patients were identified. EWS was the best predictor of adverse outcome amongst all of the assessed variables (area under curve (AUC) values 0.81, 0.84 and 0.83 for days 1, 2 and 3, respectively) and was the most accurate predictor of mortality on both days 2 and 3 (AUC values of 0.88 and 0.89, respectively). Multivariable analysis revealed that an EWS ≥2 was independently associated with severity of pancreatitis, adverse outcome and mortality. This study confirms the usefulness of EWS in predicting the outcome of acute pancreatitis. It should become the mainstay of risk stratification in patients with acute pancreatitis.

  17. The effectiveness of BMI, calf circumference and mid-arm circumference in predicting subsequent mortality risk in elderly Taiwanese.

    PubMed

    Tsai, Alan C; Chang, Tsui-Lan

    2011-01-01

    BMI, mid-arm circumference (MAC) and calf circumference (CC) are anthropometric indicators often included in geriatric health measurement scales. However, their relative effectiveness in predicting long-term mortality risk has not been extensively examined. The present study aimed to evaluate the relative effectiveness of these anthropometrics in predicting long-term mortality risk in older adults. The study prospectively analysed the ability of these indicators in predicting 4-year follow-up mortality risk of a population-representative sample of 4191 men and women, 53 years of age or older in the 'Survey of Health and Living Status of the Elderly in Taiwan'. Cox regression analyses were performed to evaluate the association of follow-up mortality risk with low ( < 21 kg/m2) or high ( ≥ 27 kg/m2) BMI, low MAC ( < 23·5/22 cm for men/women) and low CC ( < 30/27 cm) respectively, according to Taiwanese-specific cut-off points. Results showed that low CC and low MAC were more effective than low BMI in predicting follow-up mortality risk in 65-74-year-old elderly. But low CC and low BMI were more effective than low MAC in ≥ 75-year-old elderly, and low BMI was more effective than low MAC or low CC in 53-64-year-old persons. High BMI was not effective in predicting mortality risk in any of these age ranges. These results suggest that in elderly adults, CC is more effective than BMI in predicting long-term mortality risk. Thus, more consideration to CC and MAC in designing geriatric health or nutritional measurement scales is recommended.

  18. A Comparison of Intensive Care Unit Mortality Prediction Models through the Use of Data Mining Techniques

    PubMed Central

    Kim, Woojae; Park, Rae Woong

    2011-01-01

    Objectives The intensive care environment generates a wealth of critical care data suited to developing a well-calibrated prediction tool. This study was done to develop an intensive care unit (ICU) mortality prediction model built on University of Kentucky Hospital (UKH)'s data and to assess whether the performance of various data mining techniques, such as the artificial neural network (ANN), support vector machine (SVM) and decision trees (DT), outperform the conventional logistic regression (LR) statistical model. Methods The models were built on ICU data collected regarding 38,474 admissions to the UKH between January 1998 and September 2007. The first 24 hours of the ICU admission data were used, including patient demographics, admission information, physiology data, chronic health items, and outcome information. Results Only 15 study variables were identified as significant for inclusion in the model development. The DT algorithm slightly outperformed (AUC, 0.892) the other data mining techniques, followed by the ANN (AUC, 0.874), and SVM (AUC, 0.876), compared to that of the APACHE III performance (AUC, 0.871). Conclusions With fewer variables needed, the machine learning algorithms that we developed were proven to be as good as the conventional APACHE III prediction. PMID:22259725

  19. Usefulness of the heart-rate variability complex for predicting cardiac mortality after acute myocardial infarction

    PubMed Central

    2014-01-01

    Background Previous studies indicate that decreased heart-rate variability (HRV) is related to the risk of death in patients after acute myocardial infarction (AMI). However, the conventional indices of HRV have poor predictive value for mortality. Our aim was to develop novel predictive models based on support vector machine (SVM) to study the integrated features of HRV for improving risk stratification after AMI. Methods A series of heart-rate dynamic parameters from 208 patients were analyzed after a mean follow-up time of 28 months. Patient electrocardiographic data were classified as either survivals or cardiac deaths. SVM models were established based on different combinations of heart-rate dynamic variables and compared to left ventricular ejection fraction (LVEF), standard deviation of normal-to-normal intervals (SDNN) and deceleration capacity (DC) of heart rate. We tested the accuracy of predictors by assessing the area under the receiver-operator characteristics curve (AUC). Results We evaluated a SVM algorithm that integrated various electrocardiographic features based on three models: (A) HRV complex; (B) 6 dimension vector; and (C) 8 dimension vector. Mean AUC of HRV complex was 0.8902, 0.8880 for 6 dimension vector and 0.8579 for 8 dimension vector, compared with 0.7424 for LVEF, 0.7932 for SDNN and 0.7399 for DC. Conclusions HRV complex yielded the largest AUC and is the best classifier for predicting cardiac death after AMI. PMID:24886422

  20. Echocardiographic Assessment of Estimated Right Atrial Pressure and Size Predicts Mortality in Pulmonary Arterial Hypertension

    PubMed Central

    Austin, Christopher; Alassas, Khadija; Burger, Charles; Safford, Robert; Pagan, Ricardo; Duello, Katherine; Kumar, Preetham; Zeiger, Tonya

    2015-01-01

    BACKGROUND: Elevated mean right atrial pressure (RAP) measured by cardiac catheterization is an independent risk factor for mortality. Prior studies have demonstrated a modest correlation with invasive and noninvasive echocardiographic RAP, but the prognostic impact of estimated right atrial pressure (eRAP) has not been previously evaluated in patients with pulmonary arterial hypertension (PAH). METHODS: A retrospective analysis of 121 consecutive patients with PAH based on right-sided heart catheterization and echocardiography was performed. The eRAP was calculated by inferior vena cava diameter and collapse using 2005 and 2010 American Society of Echocardiography (ASE) definitions. Accuracy and correlation of eRAP to RAP was assessed. Kaplan-Meier survival analysis by eRAP, right atrial area, and Registry to Evaluate Early and Long-term PAH Disease Management (REVEAL Registry) risk criteria as well as univariate and multivariate analysis of echocardiographic findings was performed. RESULTS: Elevation of eRAP was associated with decreased survival time compared with lower eRAP (P < .001, relative risk = 7.94 for eRAP > 15 mm Hg vs eRAP ≤ 5 mm Hg). Univariate analysis of echocardiographic parameters including eRAP > 15 mm Hg, right atrial area > 18 cm2, presence of pericardial effusion, right ventricular fractional area change < 35%, and at least moderate tricuspid regurgitation was predictive of poor survival. However, multivariate analysis revealed that eRAP > 15 mm Hg was the only echocardiographic risk factor that was predictive of mortality (hazard ratio = 2.28, P = .037). CONCLUSIONS: Elevation of eRAP by echocardiography at baseline assessment was strongly associated with increased risk of death or transplant in patients with PAH. This measurement may represent an important prognostic component in the comprehensive echocardiographic evaluation of PAH. PMID:25211049

  1. Uric acid measurement improves prediction of cardiovascular mortality in later life.

    PubMed

    Dutta, Ambarish; Henley, William; Pilling, Luke C; Wallace, Robert B; Melzer, David

    2013-03-01

    To estimate the association between uric acid and cardiovascular mortality in older adults, independent of traditional risk factors, and to estimate the risk prediction gain by adding uric acid measurements to the Framingham Cardiovascular Risk Score (FCRS). Longitudinal observational study of two population-based cohorts. The Established Populations for Epidemiologic Studies of the Elderly, Iowa (Iowa-EPESE) and the Third National Health and Nutritional Examination Survey (NHANES III). One thousand twenty-eight Iowa-EPESE participants and 1,316 NHANES III participants. Selected participants were aged 70 and older without overt cardiovascular disease, renal dysfunction, or diuretic use who lived for 3 years or longer after baseline. Outcome was age at cardiovascular death during follow-up (12–20 years). Uric acid and cardiovascular risk factors such as smoking, systolic blood pressure, diabetes mellitus, obesity, serum cholesterol, and high-density lipoprotein cholesterol were measured at baseline. High serum uric acid (>7.0 mg/dL) was associated with male sex, obesity, lipid levels, and estimated glomerular filtration rate at baseline. Fully adjusted hazard ratios (HRs) for cardiovascular death with high uric acid versus normal were 1.36 (95% confidence interval (CI) = 1.10–1.69) in Iowa-EPESE and 1.43 (95% CI = 1.04–1.99) in NHANES III; pooled HR was 1.38 (95% CI = 1.16–1.61). The net reclassification improvement achieved by adding uric acid measurement to the FCRS was 9% to 20%. In individuals aged 70 and older without overt CVD, renal dysfunction, or diuretic use, serum uric acid greater than 7.0 mg/dL was associated with greater CVD mortality independent of classic CVD risk factors. Adding uric acid measurement to the FCRS would improve prediction in older adults.

  2. Darcy’s law predicts widespread forest mortality under climate warming

    USGS Publications Warehouse

    McDowell, Nate G.; Allen, Craig D.

    2015-01-01

    Drought and heat-induced tree mortality is accelerating in many forest biomes as a consequence of a warming climate, resulting in a threat to global forests unlike any in recorded history1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12. Forests store the majority of terrestrial carbon, thus their loss may have significant and sustained impacts on the global carbon cycle11,12. We use a hydraulic corollary to Darcy’s law, a core principle of vascular plant physiology13, to predict characteristics of plants that will survive and die during drought under warmer future climates. Plants that are tall with isohydric stomatal regulation, low hydraulic conductance, and high leaf area are most likely to die from future drought stress. Thus, tall trees of old-growth forests are at the greatest risk of loss, which has ominous implications for terrestrial carbon storage. This application of Darcy’s law indicates today’s forests generally should be replaced by shorter and more xeric plants, owing to future warmer droughts and associated wildfires and pest attacks. The Darcy’s corollary also provides a simple, robust framework for informing forest management interventions needed to promote the survival of current forests. Given the robustness of Darcy’s law for predictions of vascular plant function, we conclude with high certainty that today’s forests are going to be subject to continued increases in mortality rates that will result in substantial reorganization of their structure and carbon storage.

  3. Development and Validation of Predictive Models of Cardiac Mortality and Transplantation in Resynchronization Therapy

    PubMed Central

    Rocha, Eduardo Arrais; Pereira, Francisca Tatiana Moreira; Abreu, José Sebastião; Lima, José Wellington O.; Monteiro, Marcelo de Paula Martins; Rocha Neto, Almino Cavalcante; Goés, Camilla Viana Arrais; Farias, Ana Gardênia P.; Rodrigues Sobrinho, Carlos Roberto Martins; Quidute, Ana Rosa Pinto; Scanavacca, Maurício Ibrahim

    2015-01-01

    Background 30-40% of cardiac resynchronization therapy cases do not achieve favorable outcomes. Objective This study aimed to develop predictive models for the combined endpoint of cardiac death and transplantation (Tx) at different stages of cardiac resynchronization therapy (CRT). Methods Prospective observational study of 116 patients aged 64.8 ± 11.1 years, 68.1% of whom had functional class (FC) III and 31.9% had ambulatory class IV. Clinical, electrocardiographic and echocardiographic variables were assessed by using Cox regression and Kaplan-Meier curves. Results The cardiac mortality/Tx rate was 16.3% during the follow-up period of 34.0 ± 17.9 months. Prior to implantation, right ventricular dysfunction (RVD), ejection fraction < 25% and use of high doses of diuretics (HDD) increased the risk of cardiac death and Tx by 3.9-, 4.8-, and 5.9-fold, respectively. In the first year after CRT, RVD, HDD and hospitalization due to congestive heart failure increased the risk of death at hazard ratios of 3.5, 5.3, and 12.5, respectively. In the second year after CRT, RVD and FC III/IV were significant risk factors of mortality in the multivariate Cox model. The accuracy rates of the models were 84.6% at preimplantation, 93% in the first year after CRT, and 90.5% in the second year after CRT. The models were validated by bootstrapping. Conclusion We developed predictive models of cardiac death and Tx at different stages of CRT based on the analysis of simple and easily obtainable clinical and echocardiographic variables. The models showed good accuracy and adjustment, were validated internally, and are useful in the selection, monitoring and counseling of patients indicated for CRT. PMID:26559987

  4. Post-Exercise Heart Rate Recovery Independently Predicts Mortality Risk in Patients with Chronic Heart Failure

    PubMed Central

    Tang, Yi-Da; Dewland, Thomas A.; Wencker, Detlef; Katz, Stuart D.

    2009-01-01

    Background Post-exercise heart rate recovery (HRR) is an index of parasympathetic function associated with clinical outcomes in populations with and without documented coronary heart disease. Decreased parasympathetic activity is thought to be associated with disease progression in chronic heart failure (HF), but an independent association between post-exercise HRR and clinical outcomes among such patients has not been established. Methods and Results We measured HRR (calculated as the difference between heart rate at peak exercise and after 1 minute of recovery) in 202 HF subjects and recorded 17 mortality and 15 urgent transplantation outcome events over 624 days of follow-up. Reduced post-exercise HRR was independently associated with increased event risk after adjusting for other exercise-derived variables (peak oxygen uptake and VE/VCO2 slope), for the Heart Failure Survival Score (adjusted HR 1.09 for one beat/min reduction, 95% CI 1.05-1.13, p<0.0001) and the Seattle Heart Failure Model score (adjusted HR 1.08 for one beat/min reduction, 95% CI 1.05-1.12, p<0.0001). Subjects in the lowest risk tertile based on post-exercise HRR (≥30 beats/min) had low risk of events irrespective of the risk predicted by the survival scores. In a subgroup of 15 subjects, reduced post-exercise HRR was associated with increased serum markers of inflammation (interleukin-6 r=0.58, p=0.024, high sensitivity C-reactive protein r=0.66, p=0.007). Conclusions Post-exercise HRR predicts mortality risk in patients with HF and provides prognostic information independent of previously described survival models. Pathophysiologic links between autonomic function and inflammation may be mediators of this association. PMID:19944361

  5. Post-exercise heart rate recovery independently predicts mortality risk in patients with chronic heart failure.

    PubMed

    Tang, Yi-Da; Dewland, Thomas A; Wencker, Detlef; Katz, Stuart D

    2009-12-01

    Post-exercise heart rate recovery (HRR) is an index of parasympathetic function associated with clinical outcomes in populations with and without documented coronary heart disease. Decreased parasympathetic activity is thought to be associated with disease progression in chronic heart failure (HF), but an independent association between post-exercise HRR and clinical outcomes among such patients has not been established. We measured HRR (calculated as the difference between heart rate at peak exercise and after 1 minute of recovery) in 202 HF subjects and recorded 17 mortality and 15 urgent transplantation outcome events over 624 days of follow-up. Reduced post-exercise HRR was independently associated with increased event risk after adjusting for other exercise-derived variables (peak oxygen uptake and change in minute ventilation per change in carbon dioxide production slope), for the Heart Failure Survival Score (adjusted HR 1.09 for 1 beat/min reduction, 95% CI 1.05-1.13, P < .0001), and the Seattle Heart Failure Model score (adjusted HR 1.08 for one beat/min reduction, 95% CI 1.05-1.12, P < .0001). Subjects in the lowest risk tertile based on post-exercise HRR (>or=30 beats/min) had low risk of events irrespective of the risk predicted by the survival scores. In a subgroup of 15 subjects, reduced post-exercise HRR was associated with increased serum markers of inflammation (interleukin-6, r = 0.58, P = .024; high-sensitivity C-reactive protein, r = 0.66, P = .007). Post-exercise HRR predicts mortality risk in patients with HF and provides prognostic information independent of previously described survival models. Pathophysiologic links between autonomic function and inflammation may be mediators of this association.

  6. Use of the modified frailty index to predict 30-day morbidity and mortality from spine surgery.

    PubMed

    Ali, Rushna; Schwalb, Jason M; Nerenz, David R; Antoine, Heath J; Rubinfeld, Ilan

    2016-10-01

    OBJECTIVE Limited tools exist to stratify perioperative risk in patients undergoing spinal procedures. The modified frailty index (mFI) based on the Canadian Study of Health and Aging Frailty Index (CSHA-FI), constructed from standard demographic variables, has been applied to various other surgical populations for risk stratification. The authors hypothesized that it would be predictive of postoperative morbidity and mortality in patients undergoing spine surgery. METHODS The 2006-2010 National Surgical Quality Improvement Program (NSQIP) data set was accessed for patients undergoing spine surgeries based on Current Procedural Terminology (CPT) codes. Sixteen preoperative clinical NSQIP variables were matched to 11 CSHA-FI variables (changes in daily activities, gastrointestinal problems, respiratory problems, clouding or delirium, hypertension, coronary artery and peripheral vascular disease, congestive heart failure, and so on). The outcomes assessed were 30-day occurrences of adverse events. These were then summarized in groups: any infection, wound-related complication, Clavien IV complications (life-threatening, requiring ICU admission), and mortality. RESULTS A total of 18,294 patients were identified. In 8.1% of patients with an mFI of 0 there was at least one morbid complication, compared with 24.3% of patients with an mFI of ≥ 0.27 (p < 0.001). An mFI of 0 was associated with a mortality rate of 0.1%, compared with 2.3% for an mFI of ≥ 0.27 (p < 0.001). Patients with an mFI of 0 had a 1.7% rate of surgical site infections and a 0.8% rate of Clavien IV complications, whereas patients with an mFI of ≥ 0.27 had rates of 4.1% and 7.1% for surgical site infections and Clavien IV complications, respectively (p < 0.001 for both). Multivariate analysis showed that the preoperative mFI and American Society of Anesthesiologists classification of ≥ III had a significantly increased risk of leading to Clavien IV complications and death. CONCLUSIONS A higher m

  7. Elevated admission international normalized ratio strongly predicts mortality in victims of abusive head trauma.

    PubMed

    Leeper, Christine M; Nasr, Isam; McKenna, Christine; Berger, Rachel P; Gaines, Barbara A

    2016-05-01

    controlling for head AIS score and admission GCS score, the AOR was 5.27 (p = 0.007). Admission INR of 1.3 or greater strongly predicts mortality in abusive head trauma. These patients should be targeted for early aggressive interventions and monitoring with the goal of improving patient outcomes. Further study is warranted to investigate potential therapeutic targets in trauma-induced coagulation dysregulation. Prognostic and epidemiologic study, level III.

  8. Phase angle obtained by bioelectrical impedance analysis independently predicts mortality in patients with cirrhosis

    PubMed Central

    Belarmino, Giliane; Gonzalez, Maria Cristina; Torrinhas, Raquel S; Sala, Priscila; Andraus, Wellington; D’Albuquerque, Luiz Augusto Carneiro; Pereira, Rosa Maria R; Caparbo, Valéria F; Ravacci, Graziela R; Damiani, Lucas; Heymsfield, Steven B; Waitzberg, Dan L

    2017-01-01

    AIM To evaluate the prognostic value of the phase angle (PA) obtained from bioelectrical impedance analysis (BIA) for mortality prediction in patients with cirrhosis. METHODS In total, 134 male cirrhotic patients prospectively completed clinical evaluations and nutritional assessment by BIA to obtain PAs during a 36-mo follow-up period. Mortality risk was analyzed by applying the PA cutoff point recently proposed as a malnutrition marker (PA ≤ 4.9°) in Kaplan-Meier curves and multivariate Cox regression models. RESULTS The patients were divided into two groups according to the PA cutoff value (PA > 4.9°, n = 73; PA ≤ 4.9°, n = 61). Weight, height, and body mass index were similar in both groups, but patients with PAs > 4.9° were younger and had higher mid-arm muscle circumference, albumin, and handgrip-strength values and lower severe ascites and encephalopathy incidences, interleukin (IL)-6/IL-10 ratios and C-reactive protein levels than did patients with PAs ≤ 4.9° (P ≤ 0.05). Forty-eight (35.80%) patients died due to cirrhosis, with a median of 18 mo (interquartile range, 3.3-25.6 mo) follow-up until death. Thirty-one (64.60%) of these patients were from the PA ≤ 4.9° group. PA ≤ 4.9° significantly and independently affected the mortality model adjusted for Model for End-Stage Liver Disease score and age (hazard ratio = 2.05, 95%CI: 1.11-3.77, P = 0.021). In addition, Kaplan-Meier curves showed that patients with PAs ≤ 4.9° were significantly more likely to die. CONCLUSION In male patients with cirrhosis, the PA ≤ 4.9° cutoff was associated independently with mortality and identified patients with worse metabolic, nutritional, and disease progression profiles. The PA may be a useful and reliable bedside tool to evaluate prognosis in cirrhosis. PMID:28321276

  9. Sarcopenia predicts readmission and mortality in elderly patients in acute care wards: a prospective study

    PubMed Central

    Hu, Xiaoyi; Wang, Haozhong; Zhang, Lei; Hao, Qiukui; Dong, Birong

    2016-01-01

    Abstract Background The aim of this study is to assess the prevalence of sarcopenia and investigate the associations between sarcopenia and long‐term mortality and readmission in a population of elderly inpatients in acute care wards. Methods We conducted a prospective observational study in the acute care wards of a teaching hospital in western China. The muscle mass was estimated according to a previously validated anthropometric equation. Handgrip strength was measured with a handheld dynamometer, and physical performance was measured via a 4 m walking test. Sarcopenia was defined according to the recommended diagnostic algorithm of the Asia Working Group for Sarcopenia. The survival status and readmission information were obtained via telephone interviews at 12, 24, and 36 months during the 3 year follow‐up period following the baseline investigation. Results Two hundred and eighty‐eight participants (mean age: 81.1 ± 6.6 years) were included. Forty‐nine participants (17.0%) were identified as having sarcopenia. This condition was similar in men and women (16.9% vs. 17.5%, respectively, P = 0.915). During the 3 year follow‐up period, 49 men (22.7%) and 9 women (16.4%) died (P = 0.307). The mortality of sarcopenic participants was significantly increased compared with non‐sarcopenic participants (40.8% vs. 17.1%, respectively, P < 0.001). After adjusting for age, sex and other confounders, sarcopenia was an independent predictor of 3 year mortality (adjusted hazard ratio: 2.49; 95% confidential interval: 1.25–4.95) and readmission (adjusted hazard ratio: 1.81; 95% confidential interval: 1.17–2.80). Conclusions Sarcopenia, which is evaluated by a combination of anthropometric measures, gait speed, and handgrip strength, is valuable to predict hospital readmission and long‐term mortality in elderly patients in acute care wards. PMID:27896949

  10. Additive value of the CRUSADE score to the GRACE score for mortality risk prediction in patients with acute coronary syndromes.

    PubMed

    Cordero, Alberto; Rodriguez-Manero, Moisés; García-Acuña, Jose M; López-Palop, Ramón; Cid, Belen; Carrillo, Pilar; Agra-Bermejo, Rosa; González-Salvado, Violeta; Iglesias-Alvarez, Diego; Bertomeu-Martínez, Vicente; González-Juanatey, Jose R

    2017-10-15

    Acute coronary syndrome (ACS) treatments increase bleeding complications that also impair prognosis. Bleeding risk scores reclassification of actual mortality risk estimated by the GRACE score might improve overall estimation. Observational and prospective study of all ACS patients admitted in two hospitals. Mortality risk was assessed by the GRACE score and bleeding risk by the CRUSADE score. We analyzed the net reclassification improvement (NRI) of adding the CRUSADE score to the GRACE score. We included 6997 patients, mean age 67.4 (12.9), 38.0% ST-elevation ACS, mean GRACE score 145.2 (39.9). The percentage of patients with CRUSADE score >20 or >50 increased as the GRACE score was higher. Hospital mortality was 5.3% and the addition of the CRUSADE score reclassified a relevant percentage of patients with GRACE score >109; NRI was 3.80% (1.10-6.10). During follow-up, (median 53.0months) mortality rate was 22.6% and patients with CRUSADE score >50 had significantly higher mortality rates in all GRACE score categories; NRI was high (46.6%, 95% CI 41.0-53.1). The multivariate analysis outlined the independent predictive value of CRUSADE score >20 or >50 as well as GRACE scores 109-139 and >140. The addition of the CRUSADE score to the GRACE score improved mortality risk estimation. A CRUSADE score >50 identified patients with higher post-discharge mortality and higher hospital mortality if GRACE score was >109. The CRUSADE score improved hospital and long-term mortality prediction in patients with GRACE score >140. Individual mortality risk estimation should integrate the CRUSADE and GRACE scores. Copyright © 2017 Elsevier B.V. All rights reserved.

  11. Pediatric Cranial Vault Fractures: Analysis of Demographics, Injury Patterns, and Factors Predictive of Mortality.

    PubMed

    Adetayo, Oluwaseun A; Naran, Sanjay; Bonfield, Christopher M; Nguyen, Margaret; Chang, Yue-Fang; Pollack, Ian F; Losee, Joseph E

    2015-09-01

    Pediatric cranial vault fractures are a unique subset of injuries that pose distinct management and treatment challenges. They are anatomically distinct from their adult counterparts with potential implications on the development of the brain and craniofacial skeleton, and require unique considerations for management and treatment outcomes.A detailed analysis of the characteristics and outcomes of pediatric cranial vault fractures remains understudied in this population. Thus, the aim of this study was to characterize the demographics, injury patterns, operative interventions, concomitant injuries, and factors predictive of mortality in pediatric patients sustaining cranial vault fractures. A retrospective review of patients less than 18 years of age presenting to the emergency department of a pediatric level I trauma center between 2000 and 2005 with skull fractures was performed. All patients were included regardless of treating specialty, treatment modality, or inpatient status. Patients were stratified into 3 groups (age < = 5 yrs, 5.1-11 yrs, and >11 yrs). ZIP codes were mapped using ArcGIS 10.2 Software (ESRI Inc, Redlands, CA) with ZIP code shapefiles from ESRI's ArcGIS Online. Socioeconomic and demographic variables at the ZIP code level were linked to each geocoded location using the United States Census Bureau summary files, and spatial clusters of injury were performed using GeoDa to conduct a test of local indicator of spatial autocorrelation. Statistical analysis was performed using the SPSS version 17 (SPSS Inc, Chicago, IL). A total of 923 consecutive patients met the inclusion criteria for the study. Caucasian (P < 0.001) males (P = 0.055) were most likely to sustain cranial vault fractures. The average age at injury was 5.97 years. Falls (53.7%) were the most common cause of injury across all age groups, followed by collisions (20.8%), with falls being more common in the youngest age group (< = 5 yrs), and collisions being more

  12. 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.

  13. Increasing B-type natriuretic peptide levels predict mortality in unselected haemodialysis patients.

    PubMed

    Breidthardt, Tobias; Kalbermatter, Stefan; Socrates, Thenral; Noveanu, Markus; Klima, Theresia; Mebazaa, Alexandre; Mueller, Christian; Kiss, Denes

    2011-08-01

    Cardiac disease is the major cause of death in patients undergoing chronic haemodialysis. Recent studies have found that B-type natriuretic peptide (BNP) levels accurately reflect the cardiovascular burden of dialysis patients. However, the prognostic potential of BNP measurements in dialysis patients remains unknown. The study included 113 chronic dialysis patients who were prospectively followed up. Levels of BNP were measured at baseline and every 6 months thereafter. The potential of baseline BNP and annual BNP changes to predict all-cause and cardiac mortality were assessed as endpoints. Median follow-up was 735 (354-1459) days; 35 (31%) patients died, 17 (15%) of them from cardiac causes. Baseline BNP levels were similar among survivors and non-survivors, and failed to predict all-cause and cardiac death. Cardiac death was preceded by a marked increase in BNP levels. In survivors BNP levels remained stable [median change: +175% (+20-+384%) vs. -14% (-35-+35%) over the 18 months preceding either death or the end of follow-up, P< 0.001]. Hence, annual BNP changes adequately predicted all-cause and cardiac death in the subsequent year {AUC(all-cause) = 0.70 [SD 0.05, 95% CI (0.60-0.81)]; AUC(cardiac) = 0.82 [SD 0.04, 95%CI (0.73-0.90)]}. A BNP increase of 40% provided the best cut-off level. Cox regression analysis confirmed that annual increases over 40% were associated with a seven-fold increased risk for all-cause and cardiac death. Annual BNP increases above 40% predicted all-cause and cardiac death in the subsequent year. Hence, serially measuring BNP levels may present a novel tool for risk stratification and treatment guidance of end-stage renal disease patients on chronic dialysis.

  14. 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.

  15. Factors influencing the predictive power of models for predicting mortality and/or heart failure hospitalization in patients with heart failure.

    PubMed

    Ouwerkerk, Wouter; Voors, Adriaan A; Zwinderman, Aeilko H

    2014-10-01

    The present paper systematically reviews and compares existing prediction models in order to establish the strongest variables, models, and model characteristics in patients with heart failure predicting outcome. To improve decision making accurately predicting mortality and heart-failure hospitalization in patients with heart failure can be important for selecting patients with a poorer prognosis or nonresponders to current therapy, to improve decision making. MEDLINE/PubMed was searched for papers dealing with heart failure prediction models. To identify similar models on the basis of their variables hierarchical cluster analysis was performed. Meta-analysis was used to estimate the mean predictive value of the variables and models; meta-regression was used to find characteristics that explain variation in discriminating values between models. We identified 117 models in 55 papers. These models used 249 different variables. The strongest predictors were blood urea nitrogen and sodium. Four subgroups of models were identified. Mortality was most accurately predicted by prospective registry-type studies using a large number of clinical predictor variables. Mean C-statistic of all models was 0.66 ± 0.0005, with 0.71 ± 0.001, 0.68 ± 0.001 and 0.63 ± 0.001 for models predicting mortality, heart failure hospitalization, or both, respectively. There was no significant difference in discriminating value of models between patients with chronic and acute heart failure. Prediction of mortality and in particular heart failure hospitalization in patients with heart failure remains only moderately successful. The strongest predictors were blood urea nitrogen and sodium. The highest C-statistic values were achieved in a clinical setting, predicting short-term mortality with the use of models derived from prospective cohort/registry studies with a large number of predictor variables.

  16. 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

    2017-06-14

    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.

  17. Multimarker proteomic profiling for the prediction of cardiovascular mortality in patients with chronic heart failure.

    PubMed

    Lemesle, Gilles; Maury, Fleur; Beseme, Olivia; Ovart, Lionel; Amouyel, Philippe; Lamblin, Nicolas; de Groote, Pascal; Bauters, Christophe; Pinet, Florence

    2015-01-01

    Risk stratification of patients with systolic chronic heart failure (HF) is critical to better identify those who may benefit from invasive therapeutic strategies such as cardiac transplantation. Proteomics has been used to provide prognostic information in various diseases. Our aim was to investigate the potential value of plasma proteomic profiling for risk stratification in HF. A proteomic profiling using surface enhanced laser desorption ionization - time of flight - mass spectrometry was performed in a case/control discovery population of 198 patients with systolic HF (left ventricular ejection fraction <45%): 99 patients who died from cardiovascular cause within 3 years and 99 patients alive at 3 years. Proteomic scores predicting cardiovascular death were developed using 3 regression methods: support vector machine, sparse partial least square discriminant analysis, and lasso logistic regression. Forty two ion m/z peaks were differentially intense between cases and controls in the discovery population and were used to develop proteomic scores. In the validation population, score levels were higher in patients who subsequently died within 3 years. Similar areas under the curves (0.66 - 0.68) were observed for the 3 methods. After adjustment on confounders, proteomic scores remained significantly associated with cardiovascular mortality. Use of the proteomic scores allowed a significant improvement in discrimination of HF patients as determined by integrated discrimination improvement and net reclassification improvement indexes. In conclusion, proteomic analysis of plasma proteins may help to improve risk prediction in HF patients.

  18. An Australian risk prediction model for determining early mortality following aortic valve replacement.

    PubMed

    Ariyaratne, Thathya V; Billah, Baki; Yap, Cheng-Hon; Dinh, Diem; Smith, Julian A; Shardey, Gilbert C; Reid, Christopher M

    2011-06-01

    To develop a multivariable logistic risk model for predicting early mortality following aortic valve replacement (AVR) in adults, and to compare its performance against existing AVR-dedicated models. Prospectively collected data from the Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) database project were used. Thirty-five preoperative variables from AVR literature were considered for analysis by chi-square method and multiple logistic regression. Using the bootstrap re-sampling technique for variable selection, five plausible models were identified. Based on models' calibration, discrimination and predictive capacity during n-fold validation, a final model, the AVR-Score, was chosen. An additive score, derived from the final model, was also validated externally in a consecutive cohort. The performance of AVR-dedicated risk models from the North West Quality Improvement Program (NWQIP) and the Northern New England Cardiovascular Study (NNE) groups were also assessed using the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow (H-L) chi-square test. Between July 2001 and June 2008, a total of 3544 AVR procedures were performed. Early mortality was 4.15%. The AVR-Score contained the following predictors: age, New York Heart Association class, left main disease, infective endocarditis, cerebrovascular disease, renal dysfunction, previous cardiac surgery and estimated ejection fraction. Our final model (AVR-Score) obtained an average area under ROC curve of 0.78 (95% confidence interval (CI): 0.76, 0.80) and an H-L p-value of 0.41 (p>0.05) during internal validation, indicating good discrimination and calibration capacity. External validation of the additive score on a consecutive cohort of 1268 procedures produced an ROC of 0.73 (0.62, 0.84) and an H-L p-value of 0.48 (p>0.05). The NWQIP and NNE risk models achieved acceptable discrimination of ROC of 0.77 (0.73, 0.81). However, both models obtained H-L p-values of 0.002 (p<0

  19. Prevalence of multiple organ dysfunction in the pediatric intensive care unit: Pediatric Risk of Mortality III versus Pediatric Logistic Organ Dysfunction scores for mortality prediction

    PubMed Central

    Hamshary, Azza Abd Elkader El; Sherbini, Seham Awad El; Elgebaly, HebatAllah Fadel; Amin, Samah Abdelkrim

    2017-01-01

    Objectives To assess the frequency of primary multiple organ failure and the role of sepsis as a causative agent in critically ill pediatric patients; and calculate and evaluate the accuracy of the Pediatric Risk of Mortality III (PRISM III) and Pediatric Logistic Organ Dysfunction (PELOD) scores to predict the outcomes of critically ill children. Methods Retrospective study, which evaluated data from patients admitted from January to December 2011 in the pediatric intensive care unit of the Children's Hospital of the University of Cairo. Results Out of 237 patients in the study, 72% had multiple organ dysfunctions, and 45% had sepsis with multiple organ dysfunctions. The mortality rate in patients with multiple organ dysfunction was 73%. Independent risk factors for death were mechanical ventilation and neurological failure [OR: 36 and 3.3, respectively]. The PRISM III score was more accurate than the PELOD score in predicting death, with a Hosmer-Lemeshow X2 (Chi-square value) of 7.3 (df = 8, p = 0.5). The area under the curve was 0.723 for PRISM III and 0.78 for PELOD. Conclusion A multiple organ dysfunctions was associated with high mortality. Sepsis was the major cause. Pneumonia, diarrhea and central nervous system infections were the major causes of sepsis. PRISM III had a better calibration than the PELOD for prognosis of the patients, despite the high frequency of the multiple organ dysfunction syndrome.

  20. Early Standard Electroencephalogram Abnormalities Predict Mortality in Septic Intensive Care Unit Patients

    PubMed Central

    Azabou, Eric; Magalhaes, Eric; Braconnier, Antoine; Yahiaoui, Lyria; Moneger, Guy; Heming, Nicholas; Annane, Djillali; Mantz, Jean; Chrétien, Fabrice; Durand, Marie-Christine; Lofaso, Frédéric; Porcher, Raphael; Sharshar, Tarek

    2015-01-01

    Introduction Sepsis is associated with increased mortality, delirium and long-term cognitive impairment in intensive care unit (ICU) patients. Electroencephalogram (EEG) abnormalities occurring at the acute stage of sepsis may correlate with severity of brain dysfunction. Predictive value of early standard EEG abnormalities for mortality in ICU septic patients remains to be assessed. Methods In this prospective, single center, observational study, standard EEG was performed, analyzed and classified according to both Synek and Young EEG scales, in consecutive patients acutely admitted in ICU for sepsis. Delirium, coma and the level of sedation were assessed at the time of EEG recording; and duration of sedation, occurrence of in-ICU delirium or death were assessed during follow-up. Adjusted analyses were carried out using multiple logistic regression. Results One hundred ten patients were included, mean age 63.8 (±18.1) years, median SAPS-II score 38 (29–55). At the time of EEG recording, 46 patients (42%) were sedated and 22 (20%) suffered from delirium. Overall, 54 patients (49%) developed delirium, of which 32 (29%) in the days after EEG recording. 23 (21%) patients died in the ICU. Absence of EEG reactivity was observed in 27 patients (25%), periodic discharges (PDs) in 21 (19%) and electrographic seizures (ESZ) in 17 (15%). ICU mortality was independently associated with a delta-predominant background (OR: 3.36; 95% CI [1.08 to 10.4]), absence of EEG reactivity (OR: 4.44; 95% CI [1.37–14.3], PDs (OR: 3.24; 95% CI [1.03 to 10.2]), Synek grade ≥ 3 (OR: 5.35; 95% CI [1.66–17.2]) and Young grade > 1 (OR: 3.44; 95% CI [1.09–10.8]) after adjustment to Simplified Acute Physiology Score (SAPS-II) at admission and level of sedation. Delirium at the time of EEG was associated with ESZ in non-sedated patients (32% vs 10%, p = 0.037); with Synek grade ≥ 3 (36% vs 7%, p< 0.05) and Young grade > 1 (36% vs 17%, p< 0.001). Occurrence of delirium in the days after

  1. Predicting Tree Mortality From Diameter Growth: A Comparison of Maximum Likelihood and Bayesian Approaches

    Treesearch

    Peter H. Wychoff; James S. Clark

    2000-01-01

    Ecologists and foresters have long noted a link between tree growth rate and mortality, and recent work suggests that i&erspecific differences in low growth tolerauce is a key force shaping forest structure. Little information is available, however, on the growth-mortality relationship for most species. We present three methods for estimating growth-mortality...

  2. 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…

  3. 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…

  4. Nutritional status as marker for disease activity and severity predicting mortality in patients with systemic sclerosis.

    PubMed

    Krause, Lijana; Becker, Mike O; Brueckner, Claudia S; Bellinghausen, Christina-Julia; Becker, Corinna; Schneider, Udo; Haeupl, Thomas; Hanke, Katharina; Hensel-Wiegel, Karin; Ebert, Heidrun; Ziemer, Sabine; Ladner, Ulf-Müller; Pirlich, Matthias; Burmester, Gerd R; Riemekasten, Gabriela

    2010-11-01

    To assess and analyse nutritional status in patients with systemic sclerosis (SSc) and identify possible associations with clinical symptoms and its prognostic value. Body mass index (BMI) and parameters of bioelectrical impedance analysis (BIA) were assessed in 124 patients with SSc and 295 healthy donors and matched for sex, age and BMI for comparisons. In patients with SSc, BMI and BIA values were compared with clinical symptoms in a cross-sectional study. In a prospective open analysis, survival and changes in the nutritional status and energy uptake induced by nutritional treatment were evaluated. Patients with SSc had reduced phase angle (PhA) values, body cell mass (BCM), percentages of cells, increased extracellular mass (ECM) and ECM/BCM values compared with healthy donors. Malnutrition was best reflected by the PhA values. Of the patients with SSc, 69 (55.7%) had malnutrition that was associated with severe disease and activity. As assessed by multivariate analysis, low predicted forced vital capacity and high N-terminal(NT)-proBNP values discriminated best between good and bad nutritional status. Among different clinical parameters, low PhA values were the best predictors for SSc-related mortality. BMI values were not related to disease symptoms or mortality. Fifty per cent of patients with SSc had a lower energy uptake related to their energy requirement, 19.8% related to their basal metabolism. Nutritional treatment improved the patients' nutritional status. In patients with SSc, malnutrition is common and not identified by BMI. BIA parameters reflect disease severity and provide best predictors for patient survival. Therefore, an assessment of nutritional status should be performed in patients with SSc.

  5. 'Malnutrition Universal Screening Tool' predicts mortality and length of hospital stay in acutely ill elderly.

    PubMed

    Stratton, Rebecca J; King, Claire L; Stroud, Mike A; Jackson, Alan A; Elia, Marinos

    2006-02-01

    Malnutrition and its impact on clinical outcome may be underestimated in hospitalised elderly as many screening procedures require measurements of weight and height that cannot often be undertaken in sick elderly patients. The 'Malnutrition Universal Screening Tool' ('MUST') has been developed to screen all adults, even if weight and/or height cannot be measured, enabling more complete information on malnutrition prevalence and its impact on clinical outcome to be obtained. In the present study, 150 consecutively admitted elderly patients (age 85 (sd 5.5) years) were recruited prospectively, screened with 'MUST' and clinical outcome recorded. Although only 56 % of patients could be weighed, all (n 150) could be screened with 'MUST'; 58 % were at malnutrition risk and these individuals had greater mortality (in-hospital and post-discharge, P<0.01) and longer hospital stays (P=0.02) than those at low risk. Both 'MUST' categorisation and component scores (BMI, weight loss, acute disease) were significantly related to mortality (P<0.03). Those patients with no measured or recalled weight ('MUST' subjective criteria used) had a greater risk of malnutrition (P=0.01) and a poorer clinical outcome (P<0.002) than those who could be weighed and, within both groups, clinical outcome was worse in those at risk of malnutrition. The present study suggests that 'MUST' predicts clinical outcome in hospitalised elderly, in whom malnutrition is common (58 %). In those who cannot be weighed, a higher prevalence of malnutrition and associated poorer clinical outcome supports the importance of routine screening with a tool, like 'MUST', that can be used to screen all patients.

  6. Aortic stiffness and plasma brain natriuretic peptide predicts mortality in acute ischemic stroke.

    PubMed

    Biteker, Murat; Özden, Temel; Dayan, Akın; Tekkeşin, Ahmet İlker; Mısırlı, Cemile Handan

    2015-07-01

    The study aimed to evaluate the prognostic role and discriminative power of aortic stiffness and plasma brain natriuretic peptide levels in a cohort of patients hospitalized for acute ischemic stroke. Three hundred and ten consecutive patients aged 50 years and older with a first episode of acute ischemic stroke were prospectively evaluated. All patients were admitted to the hospital within 24 h of the onset of stroke symptoms. The type of acute ischemic stroke was classified according to the Trial of Org 10172 in Acute Stroke Treatment classification. Blood samples were taken for measurement of brain natriuretic peptide levels at admission. Aortic stiffness indices, aortic strain and distensibility, were calculated from the aortic diameters measured by transthoracic echocardiography. The patients were followed for one-year or until death, whichever came first. Death occurred in 51 (16·5%) patients. On multivariate logistic regression analysis, National Institutes of Health Stroke Scale score >13, diabetes, brain natriuretic peptide >235 pg/mL, aortic distensibility, and aortic strain were associated with all-cause mortality. The optimal cutoff level of brain natriuretic peptide to distinguish the deceased group from the survival group was 235 pg/mL (sensitivity 71·0% and specificity 63·0%) and to distinguish cardioembolic stroke from noncardioembolic stroke was 155 pg/mL (sensitivity 81% and specificity 63%). Aortic stiffness and brain natriuretic peptide predict mortality in patients with first-ever acute ischemic stroke. Brain natriuretic peptide also differentiates cardioembolic stroke from noncardioembolic stroke. © 2013 The Authors. International Journal of Stroke © 2013 World Stroke Organization.

  7. Cardiothoracic ratio within the “normal” range independently predicts mortality in patients undergoing coronary angiography

    PubMed Central

    Zaman, M Justin S; Sanders, Julie; Crook, Angela M; Feder, Gene; Shipley, Martin; Timmis, Adam; Hemingway, Harry

    2007-01-01

    Objective To determine whether cardiothoracic ratio (CTR), within the range conventionally considered normal, predicted prognosis in patients undergoing coronary angiography. Design Cohort study with a median of 7‐years follow‐up. Setting Consecutive patients undergoing coronary angiography at Barts and The London National Health Service (NHS) Trust. Subjects 1005 patients with CTRs measured by chest radiography, and who subsequently underwent coronary angiography. Of these patients, 7.3% had a CTR ⩾0.5 and were excluded from the analyses. Outcomes All‐cause mortality and coronary event (non‐fatal myocardial infarction or coronary death). Adjustments were made for age, left ventricular dysfunction, ACE inhibitor treatment, body mass index, number of diseased coronary vessels and past coronary artery bypass graft. Results The risk of death was increased among patients with a CTR in the upper part of the normal range. In total, 94 (18.9%) of those with a CTR below the median of 0.42 died compared with 120 (27.8%) of those with a CTR between 0.42 and 0.49 (log rank test p<0.001). After adjusting for potential confounders, this increased risk remained (adjusted HR 1.45, 95% CI 1.03 to 2.05). CTR, at values below 0.5, was linearly related to the risk of coronary event (test for trend p = 0.024). Conclusion : In patients undergoing coronary angiography, CTR between 0.42 and 0.49 was associated with higher mortality than in patients with smaller hearts. There was evidence of a continuous increase in risk with higher CTR. These findings, along with those in healthy populations, question the conventional textbook cut‐off point of ⩾0.5 being an abnormal CTR. PMID:17164481

  8. Time orientation and executive functions in the prediction of mortality in the elderly: Epidoso study.

    PubMed

    Xavier, André Junqueira; d'Orsi, Eleonora; Sigulem, Daniel; Ramos, Luiz Roberto

    2010-02-01

    To analyze the predictive ability of a functional cognitive index of mortality in the elderly. Cohort study performed with 1,667 elderly individuals aged more than 65 years and living in the city of São Paulo, Southeastern Brazil, between 1991 and 2001. Functional cognitive index was constructed from time orientation and executive functions (going shopping and taking medication), controlled by sociodemographic variables, life habits, morbidity, self-perception of health, hospitalization, edentulism and social support. Deaths occurred during this period were analyzed with family members in home interviews, notary public offices and records from the Fundação Seade (State System of Data Analysis Foundation), until 2003. Crude and adjusted relative risks were calculated with their respective 95% confidence intervals, using bivariate and multiple analysis with Poisson regression and p<0.05. In the final multivariate model, the following independent risk factors were identified by the index: partial loss of time orientation or executive functions (RR=1.37; 95% CI: 1.03;1.83); total loss of orientation and partial loss of functions (RR=1.71; 95% CI: 1.24;2.37); partial loss of orientation and total loss of functions (RR=1.76; 95% CI: 1.35;2.28); and total loss of orientation and functions (RR=1.64; 95% CI: 1.30;2.06). As regards health conditions, the following were observed: hospitalization (RR=1.45; 95% CI: 1.22;1.73); diabetes (RR=1.20; 95% CI: 1.00;1.44); and total edentulism (RR=1.34; 95% CI: 1.09;1.66). Monthly contact with relatives was identified as a protective factor (RR=0.83; 95% CI: 0.69;1.00). The Functional Cognitive Index can help clinicians and health planners to make decisions on strategies for follow-up and prevention of treatable causes of cognitive deficit and functional loss to reduce mortality in the elderly.

  9. PREDICTING FIFTEEN-YEAR CANCER-SPECIFIC MORTALITY BASED ON THE PATHOLOGICAL FEATURES OF PROSTATE CANCER

    PubMed Central

    Eggener, Scott E.; Scardino, Peter T.; Walsh, Patrick C.; Han, Misop; Partin, Alan W.; Trock, Bruce J.; Feng, Zhaoyong; Wood, David P.; Eastham, James A.; Yossepowitch, Ofer; Rabah, Danny M.; Kattan, Michael W.; Yu, Changhong; Klein, Eric A.; Stephenson, Andrew J.

    2014-01-01

    Purpose Long-term prostate cancer-specific mortality (PCSM) after radical prostatectomy is poorly defined in the era of widespread screening. An understanding of the treated natural history of screen-detected cancers and the pathological risk factors for PCSM are needed for treatment decision-making. Methods Using Fine and Gray competing risk regression analysis, the clinical and pathological data and follow-up information of 11,521 patients treated by radical prostatectomy at four academic centers from 1987 to 2005 were modeled to predict PCSM. The model was validated on 12,389 patients treated at a separate institution during the same period. Results The overall 15-year PCSM was 7%. Primary and secondary pathological Gleason grade 4–5 (P < 0.001 for both), seminal vesicle invasion (P < 0.001), and year of surgery (P = 0.002) were significant predictors of PCSM. A nomogram predicting 15-year PCSM based on standard pathological parameters was accurate and discriminating with an externally-validated concordance index of 0.92. Stratified by patient age, 15-year PCSM for Gleason score ≤ 6, 3+4, 4+3, and 8–10 ranged from 0.2–1.2%, 4.2–6.5%, 6.6–11%, and 26–37%, respectively. The 15-year PCSM risks ranged from 0.8–1.5%, 2.9–10%, 15–27%, and 22–30% for organ-confined cancer, extraprostatic extension, seminal vesicle invasion, and lymph node metastasis, respectively. Only 3 of 9557 patients with organ-confined, Gleason score ≤ 6 cancers have died from prostate cancer. Conclusions The presence of poorly differentiated cancer and seminal vesicle invasion are the prime determinants of PCSM after radical prostatectomy. The risk of PCSM can be predicted with unprecedented accuracy once the pathological features of prostate cancer are known. PMID:21239008

  10. Added value of a resting ECG neural network that predicts cardiovascular mortality.

    PubMed

    Perez, Marco V; Dewey, Frederick E; Tan, Swee Y; Myers, Jonathan; Froelicher, Victor F

    2009-01-01

    The resting 12-lead electrocardiogram (ECG) remains the most commonly used test in evaluating patients with suspected cardiovascular disease. Prognostic values of individual findings on the ECG have been reported but may be of limited use. The characteristics of 45,855 ECGs ordered by physician's discretion were first recorded and analyzed using a computerized system. Ninety percent of these ECGs were used to train an artifical neural network (ANN) to predict cardiovascular mortality (CVM) based on 132 ECG and four demographic characteristics. The ANN generated a Resting ECG Neural Network (RENN) score that was then tested in the remaining ECGs. The RENN score was finally assessed in a cohort of 2189 patients who underwent exercise treadmill testing and were followed for CVM. The RENN score was able to better predict CVM compared to individual ECG markers or a traditional Cox regression model in the testing cohort. Over a mean of 8.6 years, there were 156 cardiovascular deaths in the treadmill cohort. Among the patients who were classified as intermediate risk by Duke Treadmill Scoring (DTS), the third tertile of the RENN score demonstrated an adjusted Cox hazard ratio of 5.4 (95% CI 2.0-15.2) compared to the first RENN tertile. The 10-year CVM was 2.8%, 8.6% and 22% in the first, second and third RENN tertiles, respectively. An ANN that uses the resting ECG and demographic variables to predict CVM was created. The RENN score can further risk stratify patients deemed at moderate risk on exercise treadmill testing.

  11. Executive Function [Capacity for Behavioral Self-regulation]and Decline Predicted Mortality in a Longitudinal Study in Southern Colorado

    PubMed Central

    Amirian, E.; Baxter, Judith; Grigsby, Jim; Curran-Everett, Douglas; Hokanson, John E; Bryant, Lucinda L

    2009-01-01

    Objective To assess the relationship between mortality and impairment and decline in a specific executive cognitive function, the capacity for behavioral self-regulation. Study Design & Setting This study examined the association between mortality and baseline and 22-month decline in the capacity for behavioral self-regulation, as measured by the Behavioral Dyscontrol Scale, among 1,293 participants of the San Luis Valley Health and Aging Study (SLVHAS), a population-based longitudinal study. The Behavioral Dyscontrol Scale and a measure of overall mental status, the Mini-Mental State Examination, were administered at baseline and follow-up interviews. Cox regression was used to examine baseline and decline in capacity for behavioral self-regulation as possible predictors of morality. Results Baseline Behavioral Dyscontrol Scale score was predictive of mortality, independent of demographics and comorbidity count (HR=1.07; 95% CI:1.04–1.09). It remained a significant predictor with further adjustment for Mini-Mental State Examination score. Decline in this specific executive cognitive function was associated with mortality after adjustment for covariates and baseline cognitive scores (HR=1.09; 95% CI:1.04–1.13). Conclusion Thus, both baseline capacity for behavioral self-regulation and its decline over time predicted mortality in the SLVHAS cohort. These associations may partly be due to maintaining the ability for self-care. Understanding how specific forms of impairment contribute to mortality may help identify patients who could benefit from early intervention. PMID:19716261

  12. Gender-related risk factors improve mortality predictive ability of VACS Index among HIV-infected women

    PubMed Central

    COHEN, Mardge H; HOTTON, Anna L; HERSHOW, Ronald C; LEVINE, Alexandra; BACCHETTI, Peter; GOLUB, Elizabeth T.; ANASTOS, Kathryn; YOUNG, Mary; GUSTAFSON, Deborah; WEBER, Kathleen M

    2015-01-01

    Background Adding gender-related modifiable characteristics or behaviors to the Veterans Aging Cohort Study (VACS) Index might improve the accuracy of predicting mortality among HIV-infected women on treatment. We evaluated the VACS Index in women with HIV, determined whether additional variables would improve mortality prediction, and quantified the potential for improved survival associated with reduction in these additional risk factors. Methods The VACS Index (based on age, CD4 count, HIV-1 RNA, hemoglobin, AST, ALT, platelets, creatinine and Hepatitis C status) was validated in HIV-infected women in the Women’s Interagency HIV Study (WIHS) who initiated antiretroviral therapy (ART) between January 1996 and December 2007. Models were constructed adding race, depression, abuse, smoking, substance use, transactional sex, and comorbidities to determine whether predictability improved. Population attributable fractions were calculated. Results The VACS Index accurately predicted 5-year mortality in 1057 WIHS women with 1 year on HAART with c-index 0.83 (95% CI 0.79–0.87). In multivariate analysis, the VACS Index score (adjusted hazard ratio [aHR] for 5-point increment 1.30; 95% CI 1.25–1.35), depressive symptoms (aHR 1.73; 95% CI 1.17–2.56) and history of transactional sex (aHR 1.93; 95% CI 1.33–1.82) were independent statistically significant predictors of mortality. Conclusions Including depression and transactional sex significantly improved the performance of the VACS Index in predicting mortality among HIV-infected women. Providing treatment for depression and addressing economic and psychosocial instability in HIV infected women would improve health and perhaps point to a broader public health approach to reducing HIV mortality. PMID:26284531

  13. Charlson comorbidity index derived from chart review or administrative data: agreement and prediction of mortality in intensive care patients.

    PubMed

    Stavem, Knut; Hoel, Henrik; Skjaker, Stein Arve; Haagensen, Rolf

    2017-01-01

    This study compared the Charlson comorbidity index (CCI) information derived from chart review and administrative systems to assess the completeness and agreement between scores, evaluate the capacity to predict 30-day and 1-year mortality in intensive care unit (ICU) patients, and compare the predictive capacity with that of the Simplified Acute Physiology Score (SAPS) II model. Using data from 959 patients admitted to a general ICU in a Norwegian university hospital from 2007 to 2009, we compared the CCI score derived from chart review and administrative systems. Agreement was assessed using % agreement, kappa, and weighted kappa. The capacity to predict 30-day and 1-year mortality was assessed using logistic regression, model discrimination with the c-statistic, and calibration with a goodness-of-fit statistic. The CCI was complete (n=959) when calculated from chart review, but less complete from administrative data (n=839). Agreement was good, with a weighted kappa of 0.667 (95% confidence interval: 0.596-0.714). The c-statistics for categorized CCI scores from charts and administrative data were similar in the model that included age, sex, and type of admission: 0.755 and 0.743 for 30-day mortality, respectively, and 0.783 and 0.775, respectively, for 1-year mortality. Goodness-of-fit statistics supported the model fit. The CCI scores from chart review and administrative data showed good agreement and predicted 30-day and 1-year mortality in ICU patients. CCI combined with age, sex, and type of admission predicted mortality almost as well as the physiology-based SAPS II.

  14. [Value of E-PASS and mE-PASS in predicting morbidity and mortality of gastric cancer surgery].

    PubMed

    Liu, Ningbo; Cui, Jiangong; Zhang, Zengqiang; Zhao, Zhicheng; Li, Weidong; Fu, Weihua

    2015-10-01

    To investigate the clinical value of Physiologic Ability and Surgical Stress (E-PASS) and modified Estimation of Physiologic Ability and Surgical Stress (mE-PASS) scoring systems in predicting the mortality and surgical risk of gastric cancer patients, and to analyze the relationship between the parameters of E-PASS and early postoperative complications. Clinical data of 778 gastric cancer patients who underwent elective surgical resection in Tianjin Medical University General Hospital from Jan. 2010 to Jan. 2014 were analyzed retrospectively. E-PASS and mE-PASS scoring systems were used to predict the mortality of gastric cancer patients, respectively. Univariate and unconditioned logistic regression analyses were performed to assess the relationships between nine parameters of E-PASS system and early postoperative complications. E-PASS and mE-PASS systems were used to predict the mortality in the death group and non-death group. The Z value was -5.067 and -4.492, respectively, showing a significant difference between the two groups (P<0.05). AUCs of mortality predicted by E-PASS and mE-PASS were 0.926 and 0.878 (P>0.05), and the prediction calibration of postoperative mortality showed statistically non-significant difference (P>0.05) between the E-PASS and mE-PASS prediction and actual mortality. Univariate analysis showed that age, operation time, severe heart disease, severe lung disease, diabetes mellitus, physical state index and ASA classification score are related to postoperative complications (P<0.05 for all). Unconditioned logistic regression analysis showed that severe lung disease, diabetes mellitus, ASA classification score and operation time are risk factors for early postoperative complications (P<0.05 for all). Both mE-PASS and E-PASS scoring system have good consistency in the predicting postoperative mortality and actual mortality, and both are suitable for clinical application. Moreover, the mE-PASS scoring system is clinically more simple and

  15. 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.

  16. Sympathetic activity–associated periodic repolarization dynamics predict mortality following myocardial infarction

    PubMed Central

    Rizas, Konstantinos D.; Nieminen, Tuomo; Barthel, Petra; Zürn, Christine S.; Kähönen, Mika; Viik, Jari; Lehtimäki, Terho; Nikus, Kjell; Eick, Christian; Greiner, Tim O.; Wendel, Hans P.; Seizer, Peter; Schreieck, Jürgen; Gawaz, Meinrad; Schmidt, Georg; Bauer, Axel

    2014-01-01

    Background. Enhanced sympathetic activity at the ventricular myocardium can destabilize repolarization, increasing the risk of death. Sympathetic activity is known to cluster in low-frequency bursts; therefore, we hypothesized that sympathetic activity induces periodic low-frequency changes of repolarization. We developed a technique to assess the sympathetic effect on repolarization and identified periodic components in the low-frequency spectral range (≤0.1 Hz), which we termed periodic repolarization dynamics (PRD). Methods. We investigated the physiological properties of PRD in multiple experimental studies, including a swine model of steady-state ventilation (n = 7) and human studies involving fixed atrial pacing (n = 10), passive head-up tilt testing (n = 11), low-intensity exercise testing (n = 11), and beta blockade (n = 10). We tested the prognostic power of PRD in 908 survivors of acute myocardial infarction (MI). Finally, we tested the predictive values of PRD and T-wave alternans (TWA) in 2,965 patients undergoing clinically indicated exercise testing. Results. PRD was not related to underlying respiratory activity (P < 0.001) or heart-rate variability (P = 0.002). Furthermore, PRD was enhanced by activation of the sympathetic nervous system, and pharmacological blockade of sympathetic nervous system activity suppressed PRD (P ≤ 0.005 for both). Increased PRD was the strongest single risk predictor of 5-year total mortality (hazard ratio 4.75, 95% CI 2.94–7.66; P < 0.001) after acute MI. In patients undergoing exercise testing, the predictive value of PRD was strong and complementary to that of TWA. Conclusion. We have described and identified low-frequency rhythmic modulations of repolarization that are associated with sympathetic activity. Increased PRD can be used as a predictor of mortality in survivors of acute MI and patients undergoing exercise testing. Trial registration. ClinicalTrials.gov NCT00196274. Funding. This study was funded by

  17. Variation in the BDNF gene interacts with age to predict mortality in a prospective, longitudinal cohort with severe TBI

    PubMed Central

    Failla, Michelle D.; Kumar, Raj; Peitzman, Andrew; Conley, Yvette P.; Ferrell, Robert E.; Wagner, Amy K.

    2014-01-01

    Background Mortality predictions following traumatic brain injury (TBI) may be improved by including genetic risk in addition to traditional prognostic variables. One promising target is the gene coding for brain-derived neurotrophic factor (BDNF), a ubiquitous neurotrophin important for neuronal survival and neurogenesis. Objective We hypothesized the addition of BDNF genetic variation would improve mortality prediction models and that BDNF Met-carriers (rs6265) and C-carriers (rs7124442) would have the highest mortality rates post-TBI. Methods This study examined BDNF functional single nucleotide polymorphisms (SNPs) rs6265r (val66met) and rs7124442 (T>C) in relation to mortality in a prospective, longitudinal cohort with severe TBI. We examined 315 individuals receiving care for a closed head injury within the University of Pittsburgh Medical Center, aged 16–79. Mortality was examined acutely (0–7 days post-injury) and post-acutely (8–365 days post-injury). A gene risk score (GRS) was developed to examine both BDNF loci. Cox proportional hazards models were used to calculate hazard ratios for survivability post-TBI while controlling for covariates. Results BDNF GRS was significantly associated with acute mortality, regardless of age. Interestingly, subjects in the hypothesized no-risk allele group had the lowest survival probability. Post-acutely, BDNF-GRS interacted with age such that younger participants in the no-risk group had the highest survival probability, while older participants in the hypothesized no-risk group had the lowest probability of survival. Conclusions These data suggest complex relationships between BDNF and TBI mortality that interact with age to influence survival predictions beyond clinical variables alone. Evidence supporting dynamic, temporal balances of pro-survival/pro-apoptotic target receptors may explain injury and age-related gene associations. PMID:25063686

  18. 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.

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

    PubMed Central

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

    2016-01-01

    Background 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. Methods 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. Results 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). Conclusions In patients with coronary heart disease, an increase in leukocyte telomere length over 5 years is associated with decreased mortality. PMID:27783614

  20. External Validation of the Rotterdam Computed Tomography Score in the Prediction of Mortality in Severe Traumatic Brain Injury.

    PubMed

    Charry, Jose D; Falla, Jesus D; Ochoa, Juan D; Pinzón, Miguel A; Tejada, Jorman H; Henriquez, Maria J; Solano, Juan Pablo; Calvache, Camilo

    2017-08-01

    Traumatic brain injury (TBI) is a public health problem. It is a pathology that causes significant mortality and disability in Colombia. Different calculators and prognostic models have been developed to predict the neurological outcomes of these patients. The Rotterdam computed tomography (CT) score was developed for prognostic purposes in TBI. We aimed to examine the accuracy of the prognostic discrimination and prediction of mortality of the Rotterdam CT score in a cohort of trauma patients with severe TBI in a university hospital in Colombia. We analyzed 127 patients with severe TBI treated in a regional trauma center in Colombia over a 2-year period. Bivariate and multivariate analyses were used. The discriminatory power of the score, its accuracy, and precision were assessed by logistic regression and as the area under the receiver operating characteristic curve. Shapiro-Wilk, Chi-square, and Wilcoxon tests were used to compare the real outcomes in the cohort against the predicted outcomes. The median age of the patient cohort was 33 years, and 84.25% were male. The median injury severity score was 25, the median Glasgow Coma Scale motor score was 3, the basal cisterns were closed in 46.46% of the patients, and a midline shift of >5 mm was seen in 50.39%. The 6-month mortality was 29.13%, and the Rotterdam CT score predicted a mortality of 26% (P < 0.0001) (area under the curve: 0.825; 95% confidence interval: 0.745-0.903). The Rotterdam CT score predicted mortality at 6 months in patients with severe head trauma in a university hospital in Colombia. The Rotterdam CT score is useful for predicting early death and the prognosis of patients with TBI.

  1. External Validation of the Rotterdam Computed Tomography Score in the Prediction of Mortality in Severe Traumatic Brain Injury

    PubMed Central

    Charry, Jose D.; Falla, Jesus D.; Ochoa, Juan D.; Pinzón, Miguel A.; Tejada, Jorman H.; Henriquez, Maria J.; Solano, Juan Pablo; Calvache, Camilo

    2017-01-01

    Introduction: Traumatic brain injury (TBI) is a public health problem. It is a pathology that causes significant mortality and disability in Colombia. Different calculators and prognostic models have been developed to predict the neurological outcomes of these patients. The Rotterdam computed tomography (CT) score was developed for prognostic purposes in TBI. We aimed to examine the accuracy of the prognostic discrimination and prediction of mortality of the Rotterdam CT score in a cohort of trauma patients with severe TBI in a university hospital in Colombia. Materials and Methods: We analyzed 127 patients with severe TBI treated in a regional trauma center in Colombia over a 2-year period. Bivariate and multivariate analyses were used. The discriminatory power of the score, its accuracy, and precision were assessed by logistic regression and as the area under the receiver operating characteristic curve. Shapiro–Wilk, Chi-square, and Wilcoxon tests were used to compare the real outcomes in the cohort against the predicted outcomes. Results: The median age of the patient cohort was 33 years, and 84.25% were male. The median injury severity score was 25, the median Glasgow Coma Scale motor score was 3, the basal cisterns were closed in 46.46% of the patients, and a midline shift of >5 mm was seen in 50.39%. The 6-month mortality was 29.13%, and the Rotterdam CT score predicted a mortality of 26% (P < 0.0001) (area under the curve: 0.825; 95% confidence interval: 0.745–0.903). Conclusions: The Rotterdam CT score predicted mortality at 6 months in patients with severe head trauma in a university hospital in Colombia. The Rotterdam CT score is useful for predicting early death and the prognosis of patients with TBI. PMID:28936067

  2. GYM score: 30-day mortality predictive model in elderly patients attended in the emergency department with infection.

    PubMed

    González Del Castillo, Juan; Escobar-Curbelo, Luis; Martínez-Ortíz de Zárate, Mikel; Llopis-Roca, Ferrán; García-Lamberechts, Jorge; Moreno-Cuervo, Álvaro; Fernández, Cristina; Martín-Sánchez, Francisco Javier

    2017-06-01

    To determine the validity of the classic sepsis criteria or systemic inflammatory response syndrome (heart rate, respiratory rate, temperature, and leukocyte count) and the modified sepsis criteria (systemic inflammatory response syndrome criteria plus glycemia and altered mental status), and the validity of each of these variables individually to predict 30-day mortality, as well as develop a predictive model of 30-day mortality in elderly patients attended for infection in emergency departments (ED). A prospective cohort study including patients at least 75 years old attended in three Spanish university ED for infection during 2013 was carried out. Demographic variables and data on comorbidities, functional status, hemodynamic sepsis diagnosis variables, site of infection, and 30-day mortality were collected. A total of 293 patients were finally included, mean age 84.0 (SD 5.5) years, and 158 (53.9%) were men. Overall, 185 patients (64%) fulfilled the classic sepsis criteria and 224 patients (76.5%) fulfilled the modified sepsis criteria. The all-cause 30-day mortality was 13.0%. The area under the curve of the classic sepsis criteria was 0.585 [95% confidence interval (CI) 0.488-0.681; P=0.106], 0.594 for modified sepsis criteria (95% CI: 0.502-0.685; P=0.075), and 0.751 (95% CI: 0.660-0.841; P<0.001) for the GYM score (Glasgow <15; tachYpnea>20 bpm; Morbidity-Charlson index ≥3) to predict 30-day mortality, with statistically significant differences (P=0.004 and P<0.001, respectively). The GYM score showed good calibration after bootstrap correction, with an area under the curve of 0.710 (95% CI: 0.605-0.815). The GYM score showed better capacity than the classic and the modified sepsis criteria to predict 30-day mortality in elderly patients attended for infection in the ED.

  3. The art versus science of predicting prognosis: can a prognostic index predict short-term mortality better than experienced nurses do?

    PubMed

    Casarett, David J; Farrington, Sue; Craig, Teresa; Slattery, Julie; Harrold, Joan; Oldanie, Betty; Roy, Jason; Biehl, Richard; Teno, Joan

    2012-06-01

    To determine whether a prognostic index could predict one-week mortality more accurately than hospice nurses can. An electronic health record-based retrospective cohort study of 21,074 hospice patients was conducted in three hospice programs in the Southeast, Northeast, and Midwest United States. Model development used logistic regression with bootstrapped confidence intervals and multiple imputation to account for missing data. The main outcome measure was mortality within 7 days of hospice enrollment. A total of 21,074 patients were admitted to hospice between October 1, 2008 and May 31, 2011, and 5562 (26.4%) died within 7 days. An optimal predictive model included the Palliative Performance Scale (PPS) score, admission from a hospital, and gender. The model had a c-statistic of 0.86 in the training sample and 0.84 in the validation sample, which was greater than that of nurses' predictions (0.72). The index's performance was best for patients with pulmonary disease (0.89) and worst for patients with cancer and dementia (both 0.80). The index's predictions of mortality rates in each index category were within 5.0% of actual rates, whereas nurses underestimated mortality by up to 18.9%. Using the optimal index threshold (<3), the index's predictions had a better c-statistic (0.78 versus 0.72) and higher sensitivity (74.4% versus 47.8%) than did nurses' predictions but a lower specificity (80.6% versus 95.1%). Although nurses can often identify patients who will die within 7 days, a simple model based on available clinical information offers improved accuracy and could help to identify those patients who are at high risk for short-term mortality.

  4. 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...

  5. Applicability of predictive models of drought-induced tree mortality between the midwest and northeast United States

    Treesearch

    Eric J. Gustafson

    2014-01-01

    Regression models developed in the upper Midwest (United States) to predict drought-induced tree mortality from measures of drought (Palmer Drought Severity Index) were tested in the northeastern United States and found inadequate. The most likely cause of this result is that long drought events were rare in the Northeast during the period when inventory data were...

  6. Can the Surgical Apgar Score predict morbidity and mortality in general orthopaedic surgery?

    PubMed

    Urrutia, Julio; Valdes, Macarena; Zamora, Tomas; Canessa, Valentina; Briceno, Jorge

    2012-12-01

    The Surgical Apgar Score (SAS) is a simple tally based on intra-operative heart rate, blood pressure and blood loss; it predicts 30-day major postoperative complications and mortality in different surgical fields, but no validation has been performed in general orthopaedic surgery. A prospective assessment of the SAS in 723 consecutive patients undergoing major and intermediate orthopaedic procedures was performed in an 18-month period. The SAS was calculated immediately after surgery, and the occurrence of major complications or death was registered within a 30-day follow-up. Thirty-seven patients had ≥1 complication (5.12 %). The complication rate did not augment as the score decreased (SAS 9-10 = 6.56 %; SAS 7-8 = 2.62 %; SAS 5-6 = 7.21 %; SAS ≤4 = 10.2 %), the relative risk did not augment as the score decreased and the likelihood ratio did not increase with decreasing SAS values, except in the subgroup of patients undergoing spine surgery. The C-statistic was 0.59 (95 % confidence interval 0.48-0.69), a weak discriminatory value. Using a threshold of 7 to define high-risk and low-risk patients, the SAS allowed risk stratification only for spine surgery. The SAS does not predict 30-day major complications and death in patients undergoing general orthopaedic surgery, but it is useful in the subgroup of patients undergoing spine surgery.

  7. Citric Acid Cycle Metabolites Predict the Severity of Myocardial Stunning and Mortality in Newborn Pigs.

    PubMed

    Hyldebrandt, Janus Adler; Støttrup, Nicolaj Brejnholt; Frederiksen, Christian Alcaraz; Heiberg, Johan; Dupont Birkler, Rune Isak; Johannsen, Mogens; Schmidt, Michael Rahbek; Ravn, Hanne Berg

    2016-12-01

    Myocardial infarction and chronic heart failure induce specific metabolic changes in the neonatal myocardium that are closely correlated to outcome. The aim of this study was to examine the metabolic responses to noninfarct heart failure and inotropic treatments in the newborn heart, which so far are undetermined. A total of 28 newborn pigs were instrumented with a microdialysis catheter in the right ventricle, and intercellular citric acid cycle intermediates and adenosine metabolite concentrations were determined at 20-minute intervals. Stunning was induced by 10 cycles of 3 minutes of ischemia, which was performed by occluding the right coronary artery, followed by 3 minutes of reperfusion. Animals were randomized for treatment with epinephrine + milrinone, dopamine + milrinone, dobutamine, or saline. University hospital animal laboratory. Ischemia-reperfusion induced right ventricular stunning and increased the concentrations of pyruvate lactate, succinate, malate, hypoxanthine, and xanthine (all, p < 0.01). During inotrope infusion, no differences in metabolite concentrations were detected between the treatment groups. In nonsurviving animals (n = 8), concentrations of succinate (p < 0.0001), malate (p = 0.009), and hypoxanthine (p = 0.04) increased compared with survivors, while contractility was significantly reduced (p = 0.03). Accumulation of citric acid cycle intermediates and adenosine metabolites reflects the presence of myocardial stunning and predicts mortality in acute noninfarct right ventricular heart failure in newborn pigs. This phenomenon occurs independently of the type of inotrope, suggesting that citric acid cycle intermediates represent potential markers of acute noninfarct heart failure.

  8. 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

  9. Abdominal aortic calcification is not superior over other vascular calcification in predicting mortality in hemodialysis patients: a retrospective observational study

    PubMed Central

    2013-01-01

    Background KDIGO (Kidney Disease: Improving Global Outcomes) guidelines recommend that a lateral abdominal radiograph should be performed to assess vascular calcification (VC) in dialysis patients. However, abdominal aortic calcification is a prevalent finding, and it remains unclear whether other anatomical areas of VC can predict mortality more accurately. Methods A total of 217 maintenance hemodialysis patients were enrolled at the Sichuan Provincial People’s Hospital between July 2010 and March 2011. Radiographs of the abdomen, pelvis and hands were evaluated by a radiologist to evaluate the presence of VC. The correlation between different areas of VC and all-cause or cardiovascular mortality was analyzed using univariate and multivariate models. Results The prevalence of VC was 70.0% (152 patients), and most had abdominal aortic calcification (90.1%). During 26 ± 7 months of follow-up, 37 patients died. The VC score was independently associated with patient mortality. VC observed on abdominal radiographs (abdominal aortic calcification) was associated with all-cause mortality in models adjusted for cardiovascular risk factors (HR, 4.69; 95%CI, 1.60-13.69) and dialysis factors (HR, 3.38; 95%CI, 1.18-9.69). VC in the pelvis or hands was associated with all-cause mortality in the model adjusted for dialysis factors. When three combinations of VC in different radiographs were included in models, the presence of abdominal VC was only significantly associated with all-cause mortality in the integrated model. VC in the abdomen and pelvis was associated with all-cause mortality in the model adjusted for cardiovascular factors and the integrated model, but neither was significantly associated with cardiovascular mortality. VC in all radiographs was significantly associated with a more than 6-fold risk of all-cause mortality and a more than 5-fold risk of cardiovascular mortality compared to patients without VC. Conclusions VC in different arteries as shown on

  10. Abdominal aortic calcification is not superior over other vascular calcification in predicting mortality in hemodialysis patients: a retrospective observational study.

    PubMed

    Hong, Daqing; Wu, Shukun; Pu, Lei; Wang, Fang; Wang, Junru; Wang, Zhengtong; Gao, Hui; Zhang, Yue; Deng, Fei; Li, Guisen; He, Qiang; Wang, Li

    2013-06-05

    KDIGO (Kidney Disease: Improving Global Outcomes) guidelines recommend that a lateral abdominal radiograph should be performed to assess vascular calcification (VC) in dialysis patients. However, abdominal aortic calcification is a prevalent finding, and it remains unclear whether other anatomical areas of VC can predict mortality more accurately. A total of 217 maintenance hemodialysis patients were enrolled at the Sichuan Provincial People's Hospital between July 2010 and March 2011. Radiographs of the abdomen, pelvis and hands were evaluated by a radiologist to evaluate the presence of VC. The correlation between different areas of VC and all-cause or cardiovascular mortality was analyzed using univariate and multivariate models. The prevalence of VC was 70.0% (152 patients), and most had abdominal aortic calcification (90.1%). During 26 ± 7 months of follow-up, 37 patients died. The VC score was independently associated with patient mortality. VC observed on abdominal radiographs (abdominal aortic calcification) was associated with all-cause mortality in models adjusted for cardiovascular risk factors (HR, 4.69; 95%CI, 1.60-13.69) and dialysis factors (HR, 3.38; 95%CI, 1.18-9.69). VC in the pelvis or hands was associated with all-cause mortality in the model adjusted for dialysis factors. When three combinations of VC in different radiographs were included in models, the presence of abdominal VC was only significantly associated with all-cause mortality in the integrated model. VC in the abdomen and pelvis was associated with all-cause mortality in the model adjusted for cardiovascular factors and the integrated model, but neither was significantly associated with cardiovascular mortality. VC in all radiographs was significantly associated with a more than 6-fold risk of all-cause mortality and a more than 5-fold risk of cardiovascular mortality compared to patients without VC. VC in different arteries as shown on radiographs is associated with different

  11. Risk prediction for perioperative mortality of endovascular versus open repair of abdominal aortic aneurysms using the Medicare population

    PubMed Central

    Giles, Kristina A.; Schermerhorn, Marc L.; O’Malley, A. James; Cotterill, Philip; Jhaveri, Ami; Pomposelli, Frank; Landon, Bruce E.

    2009-01-01

    INTRODUCTION AND OBJECTIVES The impact of risk factors upon perioperative mortality might differ for patients undergoing open versus endovascular repair (EVAR) of abdominal aortic aneurysms (AAA). In order to investigate this, we developed a differential predictive model of perioperative mortality after AAA repair. METHODS A total of 45,660 propensity score matched Medicare beneficiaries undergoing elective open or endovascular AAA repair from 2001–2004 were studied. Using half the dataset we developed a multiple logistic regression model for a matched cohort of open and EVAR patients and used this to derive an easily evaluable risk prediction score. The remainder of the dataset formed a validation cohort used to confirm results. RESULTS The derivation cohort included 11,415 open and 11,415 endovascular repairs. Perioperative mortality was 5.3% and 1.8% respectively. Independent predictors of mortality (RR, 95% CI) were open repair (3.2, 2.7–3.8), age (71–75 years 1.2, 0.9–1.6; 76–80 years 1.9, 1.4–2.5; >80 years 3.1, 2.4–4.2), female sex (1.5, 1.3–1.8), dialysis (2.6, 1.5–4.6), chronic renal insufficiency (2.0, 1.6–2.6), congestive heart failure (1.7, 1.5–2.1), and vascular disease (1.3, 1.2–1.6). There were no differential predictors of mortality across the two procedures. A simple scoring system was developed from a logistic regression model fit to both endovascular and open patients (area under the ROC curve of 72.6) from which low, medium, and high risk groups were developed. The absolute predicted mortality ranged from 0.7% for an EVAR patient ≤ 70 years of age with no comorbidities to 38% for an open patient > 80 with all the comorbidities considered. Although relative risk was similar among age groups, the absolute difference was greater for older patients (with higher baseline risk). CONCLUSIONS Mortality after AAA repair is predicted by comorbidities, sex, and age and these predictors have similar effects for both methods of AAA

  12. Physical Stress Echocardiography: Prediction of Mortality and Cardiac Events in Patients with Exercise Test showing Ischemia.

    PubMed

    Araujo, Ana Carla Pereira de; Santos, Bruno F de Oliveira; Calasans, Flavia Ricci; Pinto, Ibraim M Francisco; Oliveira, Daniel Pio de; Melo, Luiza Dantas; Andrade, Stephanie Macedo; Tavares, Irlaneide da Silva; Sousa, Antonio Carlos Sobral; Oliveira, Joselina Luzia Menezes

    2014-11-01

    Background: Studies have demonstrated the diagnostic accuracy and prognostic value of physical stress echocardiography in coronary artery disease. However, the prediction of mortality and major cardiac events in patients with exercise test positive for myocardial ischemia is limited. Objective: To evaluate the effectiveness of physical stress echocardiography in the prediction of mortality and major cardiac events in patients with exercise test positive for myocardial ischemia. Methods: This is a retrospective cohort in which 866 consecutive patients with exercise test positive for myocardial ischemia, and who underwent physical stress echocardiography were studied. Patients were divided into two groups: with physical stress echocardiography negative (G1) or positive (G2) for myocardial ischemia. The endpoints analyzed were all-cause mortality and major cardiac events, defined as cardiac death and non-fatal acute myocardial infarction. Results: G2 comprised 205 patients (23.7%). During the mean 85.6 ± 15.0-month follow-up, there were 26 deaths, of which six were cardiac deaths, and 25 non-fatal myocardial infarction cases. The independent predictors of mortality were: age, diabetes mellitus, and positive physical stress echocardiography (hazard ratio: 2.69; 95% confidence interval: 1.20 - 6.01; p = 0.016). The independent predictors of major cardiac events were: age, previous coronary artery disease, positive physical stress echocardiography (hazard ratio: 2.75; 95% confidence interval: 1.15 - 6.53; p = 0.022) and absence of a 10% increase in ejection fraction. All-cause mortality and the incidence of major cardiac events were significantly higher in G2 (p < 0. 001 and p = 0.001, respectively). Conclusion: Physical stress echocardiography provides additional prognostic information in patients with exercise test positive for myocardial ischemia.Fundamento: Estudos têm demonstrado a acurácia diagnóstica e o valor prognóstico da ecocardiografia com estresse f

  13. Missing Value Imputation Improves Mortality Risk Prediction Following Cardiac Surgery: An Investigation of an Australian Patient Cohort.

    PubMed

    Karim, Md Nazmul; Reid, Christopher M; Tran, Lavinia; Cochrane, Andrew; Billah, Baki

    2017-03-01

    The aim of this study was to evaluate the impact of missing values on the prediction performance of the model predicting 30-day mortality following cardiac surgery as an example. Information from 83,309 eligible patients, who underwent cardiac surgery, recorded in the Australia and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) database registry between 2001 and 2014, was used. An existing 30-day mortality risk prediction model developed from ANZSCTS database was re-estimated using the complete cases (CC) analysis and using multiple imputation (MI) analysis. Agreement between the risks generated by the CC and MI analysis approaches was assessed by the Bland-Altman method. Performances of the two models were compared. One or more missing predictor variables were present in 15.8% of the patients in the dataset. The Bland-Altman plot demonstrated significant disagreement between the risk scores (p<0.0001) generated by MI and CC analysis approaches and showed a trend of increasing disagreement for patients with higher risk of mortality. Compared to CC analysis, MI analysis resulted in an average of 8.5% decrease in standard error, a measure of uncertainty. The MI model provided better prediction of mortality risk (observed: 2.69%; MI: 2.63% versus CC: 2.37%, P<0.001). 'Multiple imputation' of missing values improved the 30-day mortality risk prediction following cardiac surgery. Copyright © 2016 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

  14. Careers and mortality in France: evidence on how far occupational mobility predicts differentiated risks.

    PubMed

    Cambois, Emmanuelle

    2004-06-01

    This new study goes beyond the well-established correlation between mortality differentials and occupational status, to focus on the impact of professional careers on mortality risk. It shows heterogeneity in the mortality risks within occupational classes, strongly related to the type of occupational moves experienced. The occupational data are taken from the French longitudinal census sample-using 1968 and 1975 census records-and mortality risks are estimated over the 1975-1980 period, for both occupational classes and pathways between classes. Results show a close relationship between occupational mobility and mortality. For men, favorable occupational moves-e.g. from clerks to upper class-put them less at risk of mortality than their counterparts who remained in their class. An inverse relationship is found for unfavorable moves. In most cases, the mortality risks of the movers are in between the risks in the class left and in the class joined. Similar patterns apply to specific groups of women only (upper classes, manual workers, clerks) for which occupational moves are probably driven, as for most men, by mortality related determinants (level of education, qualifications, health, etc.). The findings strongly support the use of a dynamic approach, based on individuals' experiences, to improve our understanding of mortality differentials.

  15. External validation of a biomarker and clinical prediction model for hospital mortality in acute respiratory distress syndrome.

    PubMed

    Zhao, Zhiguo; Wickersham, Nancy; Kangelaris, Kirsten N; May, Addison K; Bernard, Gordon R; Matthay, Michael A; Calfee, Carolyn S; Koyama, Tatsuki; Ware, Lorraine B

    2017-08-01

    Mortality prediction in ARDS is important for prognostication and risk stratification. However, no prediction models have been independently validated. A combination of two biomarkers with age and APACHE III was superior in predicting mortality in the NHLBI ARDSNet ALVEOLI trial. We validated this prediction tool in two clinical trials and an observational cohort. The validation cohorts included 849 patients from the NHLBI ARDSNet Fluid and Catheter Treatment Trial (FACTT), 144 patients from a clinical trial of sivelestat for ARDS (STRIVE), and 545 ARDS patients from the VALID observational cohort study. To evaluate the performance of the prediction model, the area under the receiver operating characteristic curve (AUC), model discrimination, and calibration were assessed, and recalibration methods were applied. The biomarker/clinical prediction model performed well in all cohorts. Performance was better in the clinical trials with an AUC of 0.74 (95% CI 0.70-0.79) in FACTT, compared to 0.72 (95% CI 0.67-0.77) in VALID, a more heterogeneous observational cohort. The AUC was 0.73 (95% CI 0.70-0.76) when FACTT and VALID were combined. We validated a mortality prediction model for ARDS that includes age, APACHE III, surfactant protein D, and interleukin-8 in a variety of clinical settings. Although the model performance as measured by AUC was lower than in the original model derivation cohort, the biomarker/clinical model still performed well and may be useful for risk assessment for clinical trial enrollment, an issue of increasing importance as ARDS mortality declines, and better methods are needed for selection of the most severely ill patients for inclusion.

  16. Predicting Mortality and Independence at Discharge in the Aging Traumatic Brain Injury Population Using Data Available at Admission.

    PubMed

    Miller, Preston R; Chang, Michael C; Hoth, J Jason; Hildreth, Amy N; Wolfe, Stacey Q; Gross, Jessica L; Martin, R Shayn; Carter, Jeffrey E; Meredith, J Wayne; D'Agostino, Ralph

    2017-04-01

    Aging worsens outcome in traumatic brain injury (TBI), but available studies may not provide accurate outcomes predictions due to confounding associated injuries. Our goal was to develop a predictive tool using variables available at admission to predict outcomes related to severity of brain injury in aging patients. Characteristics and outcomes of blunt trauma patients, aged 50 or older, with isolated TBI, in the National Trauma Data Bank (NTDB), were evaluated. Equations predicting survival and independence at discharge (IDC) were developed and validated using patients from our trauma registry, comparing predicted with actual outcomes. Logistic regression for survival and IDC was performed in 57,588 patients using age, sex, Glasgow Coma Scale score (GCS), and Revised Trauma Score (RTS). All variables were independent predictors of outcome. Two models were developed using these data. The first included age, sex, and GCS. The second substituted RTS for GCS. C statistics from the models for survival and IDC were 0.90 and 0.82 in the GCS model. In the RTS model, C statistics were 0.80 and 0.67. The use of GCS provided better discrimination and was chosen for further examination. Using a predictive equation derived from the logistic regression model, outcome probabilities were calculated for 894 similar patients from our trauma registry (January 2012 to March 2016). The survival and IDC models both showed excellent discrimination (p < 0.0001). Survival and IDC generally decreased by decade: age 50 to 59 (80% IDC, 6.5% mortality), 60 to 69 (82% IDC, 7.0% mortality), 70 to 79 (76% IDC, 8.9% mortality), and 80 to 89 (67% IDC, 13.4% mortality). These models can assist in predicting the probability of survival and IDC for aging patients with TBI. This provides important data for loved ones of these patients when addressing goals of care. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

  17. Contemporary Mortality Risk Prediction for Percutaneous Coronary Intervention: Results from 588,398 Procedures in the National Cardiovascular Data Registry

    PubMed Central

    Peterson, Eric D.; Dai, David; DeLong, Elizabeth R.; Brennan, J. Matthew; Singh, Mandeep; Rao, Sunil V.; Shaw, Richard E; Roe, Matthew T.; Ho, Kalon K. L.; Klein, Lloyd W.; Krone, Ronald J.; Weintraub, William S.; Brindis, Ralph G.; Rumsfeld, John S.; Spertus, John A.

    2014-01-01

    Objective We sought to create contemporary models for predicting mortality risk following percutaneous coronary intervention (PCI). Background There is a need to identify PCI risk factors and accurately quantify procedural risks to facilitate comparative effectiveness research, provider comparisons, and informed patient decision making. Methods Data from 181,775 procedures performed from January 2004 to March 2006 were used to develop risk models based on pre-procedural and/or angiographic factors using logistic regression. These models were independently evaluated in two validation cohorts: contemporary (n=121,183, January 2004 to March 2006) and prospective (n=285,440, March 2006 to March 2007). Results Overall, PCI in-hospital mortality was 1.27%, ranging from 0.65% in elective PCI to 4.81% in STEMI patients. Multiple pre-procedural clinical factors were significantly associated with in-hospital mortality. Angiographic variables provided only modest incremental information to pre-procedural risk assessments. The overall NCDR model, as well as a simplified NCDR risk score (based on 8 key pre-procedure factors), had excellent discrimination (c-index 0.93 and 0.91, respectively). Discrimination and calibration of both risk tools were retained among specific patient subgroups, in the validation samples, and when used to estimate 30-day mortality rates among Medicare patients. Conclusions Risks for early mortality following PCI can be accurately predicted in contemporary practice. Incorporation of such risk tools should facilitate research, clinical, and policy applications. PMID:20430263

  18. Predictive score for mortality in patients with COPD exacerbations attending hospital emergency departments

    PubMed Central

    2014-01-01

    Background Limited information is available about predictors of short-term outcomes in patients with exacerbation of chronic obstructive pulmonary disease (eCOPD) attending an emergency department (ED). Such information could help stratify these patients and guide medical decision-making. The aim of this study was to develop a clinical prediction rule for short-term mortality during hospital admission or within a week after the index ED visit. Methods This was a prospective cohort study of patients with eCOPD attending the EDs of 16 participating hospitals. Recruitment started in June 2008 and ended in September 2010. Information on possible predictor variables was recorded during the time the patient was evaluated in the ED, at the time a decision was made to admit the patient to the hospital or discharge home, and during follow-up. Main short-term outcomes were death during hospital admission or within 1 week of discharge to home from the ED, as well as at death within 1 month of the index ED visit. Multivariate logistic regression models were developed in a derivation sample and validated in a validation sample. The score was compared with other published prediction rules for patients with stable COPD. Results In total, 2,487 patients were included in the study. Predictors of death during hospital admission, or within 1 week of discharge to home from the ED were patient age, baseline dyspnea, previous need for long-term home oxygen therapy or non-invasive mechanical ventilation, altered mental status, and use of inspiratory accessory muscles or paradoxical breathing upon ED arrival (area under the curve (AUC) = 0.85). Addition of arterial blood gas parameters (oxygen and carbon dioxide partial pressures (PO2 and PCO2)) and pH) did not improve the model. The same variables were predictors of death at 1 month (AUC = 0.85). Compared with other commonly used tools for predicting the severity of COPD in stable patients, our rule was significantly better

  19. Prediction of Mortality and Postoperative Complications using the Hip-Multidimensional Frailty Score in Elderly Patients with Hip Fracture

    PubMed Central

    Choi, Jung-Yeon; Cho, Kwan-Jae; Kim, Sun-wook; Yoon, Sol-Ji; Kang, Min-gu; Kim, Kwang-il; Lee, Young-Kyun; Koo, Kyung-Hoi; Kim, Cheol-Ho

    2017-01-01

    High mortality and dependent living after hip fracture pose a significant public health concern. Retrospective study was conducted with 481 hip fracture patients (≥65 years of age) undergoing surgery from March 2009 to May 2014. The Hip-MFS was calculated by Comprehensive Geriatric Assessment (CGA). The primary outcome was the 6-month all-cause mortality rate. The secondary outcomes were 1-year all-cause mortality, postoperative complications and prolonged hospital stay, and institutionalization. Thirty-five patients (7.3%) died within 6 months after surgery (median [interquartile range], 2.9 [1.4–3.9] months). The fully adjusted hazard ratio per 1 point increase in Hip-MFS was 1.458 (95% confidence interval [CI]: 1.210–1.758) for 6-months mortality and odds ratio were 1.239 (95% CI: 1.115–1.377), 1.156 (95% CI: 1.031–1.296) for postoperative complications and prolonged total hospital stay, respectively. High-risk patients (Hip-MFS > 8) showed higher risk of 6-month mortality (hazard ratio: 3.545, 95% CI: 1.466–8.572) than low-risk patients after adjustment. Hip-MFS successfully predict 6-month mortality, postoperative complications and prolonged hospital stay in elderly hip fracture patients after surgery. Hip-MFS more precisely predict 6-month mortality than age or existing tools (P values of comparison of ROC curve: 0.002, 0.004, and 0.044 for the ASA classification, age and NHFS, respectively). PMID:28233870

  20. Usefulness of the Delta Neutrophil Index to Predict 30-Day Mortality in Patients with Upper Gastrointestinal Bleeding.

    PubMed

    Kong, Taeyoung; In, Sangkook; Park, Yoo Seok; Lee, Hye Sun; Lee, Jong Wook; You, Je Sung; Chung, Hyun Soo; Park, Incheol; Chung, Sung Phil

    2017-10-01

    The delta neutrophil index (DNI), reflecting the fraction of circulating immature granulocytes, is associated with increased mortality in patients with systemic inflammation. It is rapidly and easily measured while performing a complete blood count. This study aimed to determine whether the DNI can predict short-term mortality in patients presenting to the emergency department (ED) with upper gastrointestinal hemorrhage (UGIH). We retrospectively identified consecutive patients (>18 years old) with UGIH admitted to the ED from January 1, 2015 to February 28, 2016. The diagnosis of UGIH was confirmed using clinical, laboratory, and endoscopic findings. The DNI was determined on each day of hospitalization. The outcome of interest was 30-day mortality. Overall, 432 patients with UGIH met our inclusion criteria. The multivariate Cox regression model demonstrated that higher DNI values on days 0 (hazard ratio [HR], 1.09; 95% confidence interval [CI], 1.02-1.17; P = 0.012) and 1 (HR, 1.15; 95% CI, 1.06-1.24; P = 0.001) were strong independent predictors of short-term mortality. Further, a DNI >1% at ED admission was associated with an increased risk (HR, 40.9; 95% CI, 20.8-80.5; P < 0.001) of 30-day mortality. The optimal cut-off value for DNI on day 1 was 2.6%; this was associated with an increased hazard of 30-day mortality following UGIH (HR, 7.85; 95% CI, 3.59-17.15; P < 0.001). The DNI can be measured rapidly and simply at ED admission without additional cost or time burden. Increased DNI values independently predict 30-day mortality in patients with UGIH.

  1. A predictive model for early mortality after surgical treatment of heart valve or prosthesis infective endocarditis. The EndoSCORE.

    PubMed

    Di Mauro, Michele; Dato, Guglielmo Mario Actis; Barili, Fabio; Gelsomino, Sandro; Santè, Pasquale; Corte, Alessandro Della; Carrozza, Antonio; Ratta, Ester Della; Cugola, Diego; Galletti, Lorenzo; Devotini, Roger; Casabona, Riccardo; Santini, Francesco; Salsano, Antonio; Scrofani, Roberto; Antona, Carlo; Botta, Luca; Russo, Claudio; Mancuso, Samuel; Rinaldi, Mauro; De Vincentiis, Carlo; Biondi, Andrea; Beghi, Cesare; Cappabianca, Giangiuseppe; Tarzia, Vincenzo; Gerosa, Gino; De Bonis, Michele; Pozzoli, Alberto; Nicolini, Francesco; Benassi, Filippo; Rosato, Francesco; Grasso, Elena; Livi, Ugolino; Sandro, Sponga; Pacini, Davide; Di Bartolomeo, Roberto; De Martino, Andrea; Bortolotti, Uberto; Onorati, Francesco; Faggian, Giuseppe; Lorusso, Roberto; Vizzardi, Enrico; Di Giammarco, Gabriele; Marinelli, Daniele; Villa, Emmanuel; Troise, Giovanni; Picichè, Marco; Musumeci, Francesco; Paparella, Domenico; Margari, Vito; Tritto, Francesco; Damiani, Girolamo; Scrascia, Giuseppe; Zaccaria, Salvatore; Renzulli, Attilio; Serraino, Giuseppe; Mariscalco, Giovanni; Maselli, Daniele; Foschi, Massimiliano; Parolari, Alessandro; Nappi, Giannantonio

    2017-08-15

    The aim of this large retrospective study was to provide a logistic risk model along an additive score to predict early mortality after surgical treatment of patients with heart valve or prosthesis infective endocarditis (IE). From 2000 to 2015, 2715 patients with native valve endocarditis (NVE) or prosthesis valve endocarditis (PVE) were operated on in 26 Italian Cardiac Surgery Centers. The relationship between early mortality and covariates was evaluated with logistic mixed effect models. Fixed effects are parameters associated with the entire population or with certain repeatable levels of experimental factors, while random effects are associated with individual experimental units (centers). Early mortality was 11.0% (298/2715); At mixed effect logistic regression the following variables were found associated with early mortality: age class, female gender, LVEF, preoperative shock, COPD, creatinine value above 2mg/dl, presence of abscess, number of treated valve/prosthesis (with respect to one treated valve/prosthesis) and the isolation of Staphylococcus aureus, Fungus spp., Pseudomonas Aeruginosa and other micro-organisms, while Streptococcus spp., Enterococcus spp. and other Staphylococci did not affect early mortality, as well as no micro-organisms isolation. LVEF was found linearly associated with outcomes while non-linear association between mortality and age was tested and the best model was found with a categorization into four classes (AUC=0.851). The following study provides a logistic risk model to predict early mortality in patients with heart valve or prosthesis infective endocarditis undergoing surgical treatment, called "The EndoSCORE". Copyright © 2017. Published by Elsevier B.V.

  2. The Romhilt-Estes left ventricular hypertrophy score and its components predict all-cause mortality in the general population.

    PubMed

    Estes, E Harvey; Zhang, Zhu-Ming; Li, Yabing; Tereschenko, Larisa G; Soliman, Elsayed Z

    2015-07-01

    The same electrocardiographic (ECG) criteria that have been used for detection of left ventricular hypertrophy (LVH) have recently been recognized as predictors of adverse clinical outcomes, but this predictive ability is inadequately explored and understood. A total of 14,984 participants from the ARIC study were included in this analysis. Romhilt-Estes (R-E) LVH score was measured from the automatically processed baseline (1987-1989) ECG data. All-cause mortality was ascertained up to December 2010. Cox proportional hazard models were used to examine the association between baseline R-E score, overall and each of its 6 individual components separately, with all-cause mortality. The associations between change in R-E score between baseline and first follow-up visit with mortality were also examined. During a median follow-up of 21.7 years, 4,549 all-cause mortality events occurred during follow-up. In multivariable-adjusted models, increasing levels of the R-E score was associated with increasing risk of mortality both as a baseline finding and as a change between the baseline and the first follow-up visit. Of the 6 ECG components of the score, 4 were predictive of all-cause mortality (P-terminal force, QRS amplitude, LV strain, and intrinsicoid deflection), whereas 2 of the components were not (left axis deviation and prolonged QRS duration). Differences in the strengths of the associations between the individual components of the score and mortality were observed. The R-E score, traditionally used for detection of LVH, could be used as a useful tool for predication of adverse outcomes. Copyright © 2015. Published by Elsevier Inc.

  3. Systemic inflammatory response syndrome criteria and the prediction of hospital mortality in critically ill patients: a retrospective cohort study.

    PubMed

    Taniguchi, Leandro Utino; Pires, Ellen Maria Campos; Vieira, José Mauro; Azevedo, Luciano Cesar Pontes de

    2017-09-28

    This study intended to determine whether the systemic inflammatory response syndrome criteria can predict hospital mortality in a Brazilian cohort of critically ill patients. We performed a retrospective cohort study at a private tertiary hospital in São Paulo (SP), Brazil. We extracted information from the adult intensive care unit database (Sistema EpimedTM). We compared the SAPS 3 and the systemic inflammatory response syndrome model as dichotomous (≥ 2 criteria: systemic inflammatory response syndrome -positive versus 0 - 1 criterion: systemic inflammatory response syndrome -negative) and ordinal variables from 0 to 4 (according to the number of systemic inflammatory response syndrome criteria met) in the prediction of hospital mortality at intensive care unit admission. Model discrimination was compared using the area under the receiver operating characteristics (AUROC) curve. From January to December 2012, we studied 932 patients (60.4% were systemic inflammatory response syndrome -positive). systemic inflammatory response syndrome -positive patients were more critically ill than systemic inflammatory response syndrome -negative patients and had higher hospital mortality (16.9% versus 8.1%, p < 0.001). In the adjusted analysis, being systemic inflammatory response syndrome -positive independently increased the risk of death by 82% (odds ratio 1.82; 95% confidence interval [CI] 1.12 - 2.96, p = 0.016). However, the AUROC curve for the SAPS 3 model was higher (0.81, 95%CI 0.78 - 0.85) compared to the systemic inflammatory response syndrome model with the systemic inflammatory response syndrome criteria as a dichotomous variable (0.60, 95%CI 0.55 - 0.65) and as an ordinal variable (0.62, 95%CI 0.57 - 0.68; p < 0.001) for hospital mortality. Although systemic inflammatory response syndrome is associated with hospital mortality, the systemic inflammatory response syndrome criteria show low accuracy in the prediction of mortality compared with the SAPS 3.

  4. AusSCORE II in predicting 30-day mortality after isolated coronary artery bypass grafting in Australia and New Zealand.

    PubMed

    Billah, Baki; Huq, Molla M; Smith, Julian A; Sufi, Fahim; Tran, Lavinia; Shardey, Gilbert C; Reid, Christopher M

    2014-11-01

    To update the Australian System for Cardiac Operative Risk Evaluation (AusSCORE) model for operative estimation of 30-day mortality risk after isolated coronary artery bypass grafting in the Australian population. Data were collected by the Australian and New Zealand Society of Cardiac and Thoracic Surgeons registry from 2001 to 2011 in 25 hospitals. A total of 31,250 patients underwent isolated coronary artery bypass grafting and the outcome was 30-day mortality. A total of 2154 (6.9%) patients had 1 or multiple missing values. Missing values were estimated assuming missing completely at random and logistic regression with a generalized estimating equation was used to address within-hospital variance. Bootstrapping methods were used to construct and validate the updated model (AusSCORE II). Also the model was validated on an out-of-creation sample of 4700 patients who underwent bypass surgery in 2012. The average age of the patients was 65.6±12.9 years and 78.6% were male. Thirteen variables were selected in the updated model. The bootstrap discrimination and calibration of the AusSCORE II was very good (receiver operating characteristics [ROC], 82.0%; slope calibration, 0.987). The overall observed/AusSCORE II predicted mortality was 1.63% compared with the original AusSCORE predicted mortality of 1.01%. The validation of the AusSCORE II on the out-of-sample data also showed a high performance of the model (ROC, 84.5%; Hosmer-Lemoshow P value, .7654). The AusSCORE II model provides improved prediction of 30-day mortality and successfully stratifies patient risk. The model will be useful to improve the preoperative consultation regarding risk stratification in terms of 30-day mortality. Copyright © 2014 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

  5. Lifetime cumulative risk factors predict cardiovascular disease mortality in a 50-year follow-up study in Finland.

    PubMed

    Reinikainen, Jaakko; Laatikainen, Tiina; Karvanen, Juha; Tolonen, Hanna

    2015-02-01

    Systolic blood pressure, total cholesterol and smoking are known predictors of cardiovascular disease (CVD) mortality. Less is known about the effect of lifetime accumulation and changes of risk factors over time as predictors of CVD mortality, especially in very long follow-up studies. Data from the Finnish cohorts of the Seven Countries Study were used. The baseline examination was in 1959 and seven re-examinations were carried out at approximately 5-year intervals. Cohorts were followed up for mortality until the end of 2011. Time-dependent Cox models with regular time-updated risk factors, time-dependent averages of risk factors and latest changes in risk factors, using smoothing splines to discover nonlinear effects, were used to analyse the predictive effect of risk factors for CVD mortality. A model using cumulative risk factors, modelled as the individual-level averages of several risk factor measurements over time, predicted CVD mortality better than a model using the most recent measurement information. This difference seemed to be most prominent for systolic blood pressure. U-shaped effects of the original predictors can be explained by partitioning a risk factor effect between the recent level and the change trajectory. The change in body mass index predicted the risk although body mass index itself did not. The lifetime accumulation of risk factors and the observed changes in risk factor levels over time are strong predictors of CVD mortality. It is important to investigate different ways of using the longitudinal risk factor measurements to take full advantage of them. © The Author 2014; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

  6. Evaluation of diagnostic relevance of mRNA levels in peripheral blood: predictive value for mortality in hemodialysis patients.

    PubMed

    Füth, Reiner; Herder, Christian; Förster, Stefan; Müller-Scholze, Sylvia; Kruse, Niels; Rieckmann, Peter; Heinig, Antonia; Koenig, Wolfgang; Scherbaum, Werner A; Kolb, Hubert; Martin, Stephan

    2004-09-21

    In clinical practice, diagnosis and risk prediction are usually based on the analysis of serum or plasma proteins whereas gene expression analysis is not used on a routine basis. In order to compare the diagnostic and predictive relevance of serum protein and peripheral blood mRNA levels, we determined cytokine levels of end-stage renal failure patients undergoing hemodialysis. These patients face a high mortality mainly due to acceleration of atherosclerosis and subsequent severe vascular events. mRNA expression of the pro-inflammatory cytokine TNF alpha was significantly elevated in hemodialysis patients and further increased after 2 h of dialysis treatment. In contrast, gene expression of the anti-inflammatory cytokine TGF beta was significantly decreased. Patients who died during the observation period of 36 months had significantly increased mRNA levels of TNF alpha and decreased TGF beta mRNA expression at baseline. Survival analysis indicated that increased TNF alpha mRNA levels (P < 0.02) and TNF alpha/TGF beta mRNA ratios (P < 0.001) predict mortality. The corresponding cytokines in serum showed some association with disease, but serum concentrations neither changed during hemodialysis nor predicted mortality. This study shows that gene expression patterns of circulating leukocytes may present an important new diagnostic tool to predict clinical outcome in patients with inflammatory vascular diseases.

  7. A systematic review on the rotational thrombelastometry (ROTEM®) values for the diagnosis of coagulopathy, prediction and guidance of blood transfusion and prediction of mortality in trauma patients.

    PubMed

    Veigas, Precilla V; Callum, Jeannie; Rizoli, Sandro; Nascimento, Bartolomeu; da Luz, Luis Teodoro

    2016-10-03

    Viscoelastic assays have been promoted as an improvement over traditional coagulation tests in the management of trauma patients. Rotational thromboelastometry (ROTEM®) has been used to diagnose coagulopathy and guide hemostatic therapy in trauma. This systematic review of clinical studies in trauma investigates the ROTEM® parameters thresholds used for the diagnosing coagulopathy, predicting and guiding transfusion and predicting mortality. Systematic literature search was performed using MEDLINE, EMBASE and Cochrane databases. We included studies without restricting year of publication, language or geographic location. Original studies reporting the thresholds of ROTEM® parameters in the diagnosis or management of coagulopathy in trauma patients were included. Data on patient demographics, measures of coagulopathy, transfusion and mortality were extracted. We reported our findings according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. Quality assessment and risk of bias were performed using Newcastle Ottawa Scale (NOS) and the quality assessment of diagnostic accuracy studies (QUADAS-2) tools, respectively. A total of 13 observational studies involving 2835 adult trauma patients met the inclusion criteria. Nine studies were prospective and four were retrospective. There were no randomized controlled trials. The quality of the included studies was moderate (mean NOS 5.92, standard deviation 0.26). Using QUADAS-2, only 1 study (7.6 %) had low risk of bias in all domains, and 9 studies (69.2 %) had low risk of applicability concerns. Outcomes from 13 studies were grouped into three categories: diagnosis of coagulopathy (n = 10), prediction of massive transfusion or transfusion guidance (n = 6) and prediction of mortality (n = 6). Overall, specific ROTEM® parameters measured (clot amplitude and lysis) in the extrinsically activated test (EXTEM) and the fibrin-based extrinsically activated test

  8. 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.

  9. Important factors in predicting mortality outcome from stroke: findings from the Anglia Stroke Clinical Network Evaluation Study

    PubMed Central

    O. Bachmann, Max; Loke, Yoon Kong; D. Musgrave, Stanley; Price, Gill M.; Hale, Rachel; Metcalf, Anthony Kneale; Turner, David A.; Day, Diana J.; A. Warburton, Elizabeth; Potter, John F.

    2017-01-01

    Abstract Background although variation in stroke service provision and outcomes have been previously investigated, it is less well known what service characteristics are associated with reduced short- and medium-term mortality. Methods data from a prospective multicentre study (2009–12) in eight acute regional NHS trusts with a catchment population of about 2.6 million were used to examine the prognostic value of patient-related factors and service characteristics on stroke mortality outcome at 7, 30 and 365 days post stroke, and time to death within 1 year. Results a total of 2,388 acute stroke patients (mean (standard deviation) 76.9 (12.7) years; 47.3% men, 87% ischaemic stroke) were included in the study. Among patients characteristics examined increasing age, haemorrhagic stroke, total anterior circulation stroke type, higher prestroke frailty, history of hypertension and ischaemic heart disease and admission hyperglycaemia predicted 1-year mortality. Additional inclusion of stroke service characteristics controlling for patient and service level characteristics showed varying prognostic impact of service characteristics on stroke mortality over the disease course during first year after stroke at different time points. The most consistent finding was the benefit of higher nursing levels; an increase in one trained nurses per 10 beds was associated with reductions in 30-day mortality of 11–28% (P < 0.0001) and in 1-year mortality of 8–12% (P < 0.001). Conclusions there appears to be consistent and robust evidence of direct clinical benefit on mortality up to 1 year after acute stroke of higher numbers of trained nursing staff over and above that of other recognised mortality risk factors. PMID:28181626

  10. High blood glucose independent of pre-existing diabetic status predicts mortality in patients initiating peritoneal dialysis therapy.

    PubMed

    Chung, Sung Hee; Han, Dong Cheol; Noh, Hyunjin; Jeon, Jin Seok; Kwon, Soon Hyo; Lindholm, Bengt; Lee, Hi Bahl

    2015-06-01

    Poor glycemic control associates with increased mortality in diabetic (DM) dialysis patients, but it is less well established whether high blood glucose (BG) independent of pre-existing diabetic status associates with mortality in dialysis patients. We assessed factors affecting BG at the start of peritoneal dialysis (PD) and its mortality-predictive impact in Korean PD patients. In 174 PD patients (55 % males, 56 % DM), BG, nutritional status, comorbidity (CMD), and residual renal function (RRF) were assessed in conjunction with dialysis initiation. Determinants of BG and its association with mortality after a mean follow-up period of 30 ± 24 months were analyzed. On Cox proportional hazards analysis comprising all patients, old age, high CMD score, presence of protein energy wasting, and low serum albumin (Salb) concentration were independent predictors of mortality but not a high-BG level, while in patients without pre-existing diabetic status, high BG, together with old age and high CMD score, was an independent predictor of mortality. After adjustment for age, CMD score, and Salb, the risk ratio for mortality increased by 12 % per 1 mg/dL increase in BG in the non-DM patients. Patient survival in patients without pre-existing diabetic status with high BG did not differ from DM patients, but the survival of patients with high BG was significantly lower than in patients with low BG. In patients without pre-existing diabetic status, in multiple regression analysis, high BG at initiation of PD associated with high age, high body mass index, and low RRF. High blood glucose at initiation of PD associated with an increased mortality risk in PD patients without pre-existing diabetic status suggesting that blood glucose monitoring and surveillance of factors contributing to poor glycemic control are warranted in patients initiating PD therapy.

  11. Multivariate prediction of total and cardiovascular mortality in an obese Polynesian population.

    PubMed

    Crews, D E

    1989-08-01

    The effects of body weight and blood pressure on the risk of total mortality and mortality from cardiovascular diseases (CVD) were examined in a prospective sample of 5,866 adult residents of American Samoa, a Polynesian population noted for exhibiting high levels of obesity. Data collected during 1975-76 were linked to mortality records from 1976 through 1981. In logistic regression models which did not include blood pressure, percent of desirable weight was an important risk factor for mortality from CVD, but it was not an important risk factor when diastolic blood pressure was included in the model. Percent of desirable weight was not related to mortality from all causes combined in either Samoan men or women. Age and diastolic blood pressure were predictors of total and CVD mortality in men and women. These results, in an obese population, suggest that body weight and obesity are not independently related to excess mortality in the very obese, although they may associate with high blood pressure. These results also suggest that relations between physiological characteristics and mortality may vary with cultural, genetic, or other factors not examined in this study.

  12. Serum globulin predicts all-cause mortality for life insurance applicants.

    PubMed

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

    2014-01-01

    Determine the relative mortality in apparently healthy adults with various levels of serum globulin. By use of the Social Security Death Master File, mortality in 2010 was determined for 7.7 million life insurance applicants age 20 to 89 providing blood samples with valid globulin results between 1992 and 2006. Relative mortality by Cox regression for bands of globulin values was determined by age-sex group, with age split into 20 to 59 and 60 to 89, with each grouping also including age as a covariate. Further analysis was conducted by excluding applicants with elevations of other test values associated with increased globulin levels and mortality risk. After accounting for the mortality impact of frequently associated laboratory test abnormalities including BMI, alkaline phosphatase and albumin, relative mortality was found to increase gradually for globulin values > 3.2 g/dL. Values > 4.0 were associated with a mortality risk that was approximately doubled. There is also a small increased risk for globulin values < 1.9 g/dL. The highest 20% of globulin levels were associated with steadily increasing mortality in life insurance applicants. In many cases, other laboratory findings were not informative of the risk.

  13. Factors Predicting Mortality in Midlife Adults with and without Down Syndrome Living with Family

    ERIC Educational Resources Information Center

    Esbensen, A. J.; Seltzer, M. M.; Greenberg, J. S.

    2007-01-01

    Background: Little is known about the mortality of individuals with Down syndrome who have lived at home with their families throughout their lives. The current study evaluates the predictors, causes and patterns of mortality among co-residing individuals in midlife with Down syndrome as compared with co-residing individuals with ID owing to other…

  14. Mastication and prescribed fire influences on tree mortality and predicted fire behavior in ponderosa pine

    Treesearch

    Alicia L. Reiner; Nicole M. Vaillant; Scott N. Dailey

    2012-01-01

    The purpose of this study was to provide land managers with information on potential wildfire behavior and tree mortality associated with mastication and masticated/fire treatments in a plantation. Additionally, the effect of pulling fuels away from tree boles before applying fire treatment was studied in relation to tree mortality. Fuel characteristics and tree...

  15. Factors Predicting Mortality in Midlife Adults with and without Down Syndrome Living with Family

    ERIC Educational Resources Information Center

    Esbensen, A. J.; Seltzer, M. M.; Greenberg, J. S.

    2007-01-01

    Background: Little is known about the mortality of individuals with Down syndrome who have lived at home with their families throughout their lives. The current study evaluates the predictors, causes and patterns of mortality among co-residing individuals in midlife with Down syndrome as compared with co-residing individuals with ID owing to other…

  16. Renal insufficiency predicts mortality in geriatric patients undergoing emergent general surgery.

    PubMed

    Yaghoubian, Arezou; Ge, Phillip; Tolan, Amy; Saltmarsh, Guy; Kaji, Amy H; Neville, Angela L; Bricker, Scott; De Virgilio, Christian

    2011-10-01

    Clinical predictors of perioperative mortality in geriatric patients undergoing emergent general surgery have not been well described. The purpose of this study was to determine the incidence of postoperative morbidity and mortality in geriatric patients and factors associated with mortality. A retrospective review of patients 65 years of age or older undergoing emergent general surgery at a public teaching hospital was performed over a 7-year period. Data collected included demographics, comorbidities, laboratory studies, perioperative morbidities, and mortality. Descriptive statistics and predictors of morbidity and mortality are described. The mean age was 74 years. Indications for surgery included small bowel obstruction (24%), diverticulitis (20%), perforated viscous (16%), and large bowel obstruction (9%). The overall complication rate was 41 per cent with six cardiac complications (14%) and seven perioperative (16%) deaths. Mean admission serum creatinine was significantly higher in patients who died (3.6 vs 1.5 mg/dL, P = 0.004). Mortality for patients with an admission serum creatinine greater than 2.0 mg/dL was 42 per cent (5 of 12) compared with 3 per cent (2 of 32) for those 2.0 mg/dL or less (OR, 10.7; CI, 1.7 to 67; P = 0.01). Morbidity and mortality in geriatric patients undergoing emergency surgery remains high with the most significant predictor of mortality being the presence of renal insufficiency on admission.

  17. Predicting the onset and severity of coral bleaching and mortality using satellite-observed light and temperature

    NASA Astrophysics Data System (ADS)

    Eakin, C. M.; Skirving, W. J.; Iglesias-Prieto, R.; Dove, S.; Hedley, J.; Hoegh-Guldberg, O.; Enriquez, S. D.; Christensen, T. R.; Heron, S. F.; Mumby, P. J.; Strong, A. E.; Gledhill, D. K.; Liu, G.; Morgan, J. A.; Parker, B. A.

    2009-05-01

    The NOAA Coral Reef Watch (CRW) suite of satellite products is designed to help coral reef managers monitor thermal stress to better understand and predict mass coral bleaching. The current products are based purely on ocean temperature, and yet both temperature and light contribute to mass coral bleaching. A new satellite- derived solar radiation product has been developed and, when combined with the thermal stress indices, is expected to improve predictions of the severity of mass coral bleaching events and resultant mortality. Here, we describe the development of a new coral physiology-based method to predict coral bleaching based on the total Light Stress Damage experienced by the coral holobiont.

  18. Poor performance of the modified early warning score for predicting mortality in critically ill patients presenting to an emergency department

    PubMed Central

    Ho, Le Onn; Li, Huihua; Shahidah, Nur; Koh, Zhi Xiong; Sultana, Papia; Hock Ong, Marcus Eng

    2013-01-01

    BACKGROUND: This study was undertaken to validate the use of the modified early warning score (MEWS) as a predictor of patient mortality and intensive care unit (ICU)/ high dependency (HD) admission in an Asian population. METHODS: The MEWS was applied to a retrospective cohort of 1 024 critically ill patients presenting to a large Asian tertiary emergency department (ED) between November 2006 and December 2007. Individual MEWS was calculated based on vital signs parameters on arrival at ED. Outcomes of mortality and ICU/HD admission were obtained from hospital records. The ability of the composite MEWS and its individual components to predict mortality within 30 days from ED visit was assessed. Sensitivity, specificity, positive and negative predictive values were derived and compared with values from other cohorts. A MEWS of !4 was chosen as the cut-off value for poor prognosis based on previous studies. RESULTS: A total of 311 (30.4%) critically ill patients were presented with a MEWS !4. Their mean age was 61.4 years (SD 18.1) with a male to female ratio of 1.10. Of the 311 patients, 53 (17%) died within 30 days, 64 (20.6%) were admitted to ICU and 86 (27.7%) were admitted to HD. The area under the receiver operating characteristic curve was 0.71 with a sensitivity of 53.0% and a specificity of 72.1% in addition to a positive predictive value (PPV) of 17.0% and a negative predictive value (NPV) of 93.4% (MEWS cut-off of !4) for predicting mortality. CONCLUSION: The composite MEWS did not perform well in predicting poor patient outcomes for critically ill patients presenting to an ED. PMID:25215131

  19. The AFC Score: Validation of a 4-Item Predicting Score of Postoperative Mortality After Colorectal Resection for Cancer or Diverticulitis

    PubMed Central

    Alves, Arnaud; Panis, Yves; Mantion, Georges; Slim, Karem; Kwiatkowski, Fabrice; Vicaut, Eric

    2007-01-01

    Objective: The aim of the present prospective study was to validate externally a 4-item predictive score of mortality after colorectal surgery (the AFC score) by testing its generalizability on a new population. Summary Background Data: We have recently reported, in a French prospective multicenter study, that age older than 70 years, neurologic comorbidity, underweight (body weight loss >10% in <6 months), and emergency surgery significantly increased postoperative mortality after resection for cancer or diverticulitis. Patients and Methods: From June to September 2004, 1049 consecutive patients (548 men and 499 women) with a mean age of 67 ± 14 years, undergoing open or laparoscopic colorectal resection, were prospectively included. The AFC score was validated in this population. We assessed also the predictive value of other scores, such as the “Glasgow” score and the ASA score. To express and compare the predictive value of the different scores, a receiver operating characteristic curve was calculated. Results: Postoperative mortality rate was 4.6%. Variables already identified as predictors of mortality and used in the AFC score were also found to be associated with a high odds ratio in this study: emergency surgery, body weight loss >10%, neurologic comorbidity, and age older than 70 years in a multivariate logistic model. The validity of the AFC score in this population was found very high based both on the Hosmer-Lemeshow goodness of fit test (P = 0.37) and on the area under the ROC curve (0.89). We also found that discriminatory capacity was higher than other currently used risk scoring systems such as the Glasgow or ASA score. Conclusion: The present prospective study validated the AFC score as a pertinent predictive score of postoperative mortality after colorectal surgery. Because it is based on only 4 risk factors, the AFC score can be used in daily practice. PMID:17592296

  20. Do pre-hospital anaesthesiologists reliably predict mortality using the NACA severity score? A retrospective cohort study.

    PubMed

    Raatiniemi, L; Mikkelsen, K; Fredriksen, K; Wisborg, T

    2013-11-01

    The National Advisory Committee on Aeronautics' (NACA) severity score is widely used in pre-hospital emergency medicine to grade the severity of illness or trauma in patient groups but is scarcely validated. The aim of this study was to assess the score's ability to predict mortality and need for advanced in-hospital interventions in a cohort from one anaesthesiologist-manned helicopter service in Northern Norway. All missions completed by one helicopter service during January 1999 to December 2009 were reviewed. One thousand eight hundred forty-one patients were assessed by the NACA score. Pre-hospital and in-hospital interventions were collected from patient records. The relationship between NACA score and the outcome measures was assessed using receiver operating characteristic (ROC) curves. A total of 1533 patients were included in the analysis; uninjured and dead victims were excluded per protocol. Overall mortality rate of the patients with NACA score 1-6 was 5.2%. Trauma patients with NACA score 1-6 had overall mortality rate of 1.9% (12/625) and non-trauma patients 7.4% (67/908). The NACA score's ability to predict mortality was assessed by using ROC area under curve (AUC) and was 0.86 for all, 0.82 for non-trauma and 0.98 for trauma patients. The NACA score's ability to predict a need for respiratory therapy within 24 h revealed an AUC of 0.90 for all patients combined. The NACA score had good discrimination for predicting mortality and need for respiratory therapy. It is thus useful as a tool to measure overall severity of the patient population in this kind of emergency medicine system. © 2013 The Acta Anaesthesiologica Scandinavica Foundation. Published by John Wiley & Sons Ltd.

  1. Do pre-hospital anaesthesiologists reliably predict mortality using the NACA severity score? A retrospective cohort study

    PubMed Central

    RAATINIEMI, L; MIKKELSEN, K; FREDRIKSEN, K; WISBORG, T

    2013-01-01

    Introduction The National Advisory Committee on Aeronautics' (NACA) severity score is widely used in pre-hospital emergency medicine to grade the severity of illness or trauma in patient groups but is scarcely validated. The aim of this study was to assess the score's ability to predict mortality and need for advanced in-hospital interventions in a cohort from one anaesthesiologist-manned helicopter service in Northern Norway. Methods All missions completed by one helicopter service during January 1999 to December 2009 were reviewed. One thousand eight hundred forty-one patients were assessed by the NACA score. Pre-hospital and in-hospital interventions were collected from patient records. The relationship between NACA score and the outcome measures was assessed using receiver operating characteristic (ROC) curves. Results A total of 1533 patients were included in the analysis; uninjured and dead victims were excluded per protocol. Overall mortality rate of the patients with NACA score 1–6 was 5.2%. Trauma patients with NACA score 1–6 had overall mortality rate of 1.9% (12/625) and non-trauma patients 7.4% (67/908). The NACA score's ability to predict mortality was assessed by using ROC area under curve (AUC) and was 0.86 for all, 0.82 for non-trauma and 0.98 for trauma patients. The NACA score's ability to predict a need for respiratory therapy within 24 h revealed an AUC of 0.90 for all patients combined. Conclusion The NACA score had good discrimination for predicting mortality and need for respiratory therapy. It is thus useful as a tool to measure overall severity of the patient population in this kind of emergency medicine system. PMID:24134443

  2. Development and validation of a prognostic score to predict mortality in patients with acute-on-chronic liver failure.

    PubMed

    Jalan, Rajiv; Saliba, Faouzi; Pavesi, Marco; Amoros, Alex; Moreau, Richard; Ginès, Pere; Levesque, Eric; Durand, Francois; Angeli, Paolo; Caraceni, Paolo; Hopf, Corinna; Alessandria, Carlo; Rodriguez, Ezequiel; Solis-Muñoz, Pablo; Laleman, Wim; Trebicka, Jonel; Zeuzem, Stefan; Gustot, Thierry; Mookerjee, Rajeshwar; Elkrief, Laure; Soriano, German; Cordoba, Joan; Morando, Filippo; Gerbes, Alexander; Agarwal, Banwari; Samuel, Didier; Bernardi, Mauro; Arroyo, Vicente

    2014-11-01

    Acute-on-chronic liver failure (ACLF) is a frequent syndrome (30% prevalence), characterized by acute decompensation of cirrhosis, organ failure(s) and high short-term mortality. This study develops and validates a specific prognostic score for ACLF patients. Data from 1349 patients included in the CANONIC study were used. First, a simplified organ function scoring system (CLIF Consortium Organ Failure score, CLIF-C OFs) was developed to diagnose ACLF using data from all patients. Subsequently, in 275 patients with ACLF, CLIF-C OFs and two other independent predictors of mortality (age and white blood cell count) were combined to develop a specific prognostic score for ACLF (CLIF Consortium ACLF score [CLIF-C ACLFs]). A concordance index (C-index) was used to compare the discrimination abilities of CLIF-C ACLF, MELD, MELD-sodium (MELD-Na), and Child-Pugh (CPs) scores. The CLIF-C ACLFs was validated in an external cohort and assessed for sequential use. The CLIF-C ACLFs showed a significantly higher predictive accuracy than MELDs, MELD-Nas, and CPs, reducing (19-28%) the corresponding prediction error rates at all main time points after ACLF diagnosis (28, 90, 180, and 365 days) in both the CANONIC and the external validation cohort. CLIF-C ACLFs computed at 48 h, 3-7 days, and 8-15 days after ACLF diagnosis predicted the 28-day mortality significantly better than at diagnosis. The CLIF-C ACLFs at ACLF diagnosis is superior to the MELDs and MELD-Nas in predicting mortality. The CLIF-C ACLFs is a clinically relevant, validated scoring system that can be used sequentially to stratify the risk of mortality in ACLF patients. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  3. Atypical symptom cluster predicts a higher mortality in patients with first-time acute myocardial infarction.

    PubMed

    Hwang, Seon Young; Ahn, Young Geun; Jeong, Myung Ho

    2012-01-01

    Identifying symptom clusters of acute myocardial infarction (AMI) and their clinical significance may be useful in guiding treatment seeking behaviors and in planning treatment strategy. The aim of this study was to identify clusters of acute symptoms and their associated factors that manifested in patients with first-time AMI, and to compare clinical outcomes among cluster groups within 1-year of follow-up. A total of 391 AMI patients were interviewed individually using a structured questionnaire for acute and associated symptoms between March 2008 and June 2009 in Korea. Among 14 acute symptoms, three distinct clusters were identified by Latent Class Cluster Analysis: typical chest symptom (57.0%), multiple symptom (27.9%), and atypical symptom (15.1%) clusters. The cluster with atypical symptoms was characterized by the least chest pain (3.4%) and moderate frequencies (31-61%) of gastrointestinal symptoms, weakness or fatigue, and shortness of breath; they were more likely to be older, diabetic and to have worse clinical markers at hospital presentation compared with those with other clusters. Cox proportional hazards regression analysis showed that, when age and gender were adjusted for, the atypical symptom cluster significantly predicted a higher risk of 1-year mortality compared to the typical chest pain cluster (hazard ratio 3.288, 95% confidence interval 1.087-9.943, p=0.035). Clusters of symptoms can be utilized in guiding a rapid identification of symptom patterns and in detecting higher risk patients. Intensive treatment should be considered for older and diabetic patients with atypical presentation.

  4. Prediction Models and Their External Validation Studies for Mortality of Patients with Acute Kidney Injury: A Systematic Review

    PubMed Central

    Ohnuma, Tetsu; Uchino, Shigehiko

    2017-01-01

    Objectives To systematically review AKI outcome prediction models and their external validation studies, to describe the discrepancy of reported accuracy between the results of internal and external validations, and to identify variables frequently included in the prediction models. Methods We searched the MEDLINE and Web of Science electronic databases (until January 2016). Studies were eligible if they derived a model to predict mortality of AKI patients or externally validated at least one of the prediction models, and presented area under the receiver-operator characteristic curves (AUROC) to assess model discrimination. Studies were excluded if they described only results of logistic regression without reporting a scoring system, or if a prediction model was generated from a specific cohort. Results A total of 2204 potentially relevant articles were found and screened, of which 12 articles reporting original prediction models for hospital mortality in AKI patients and nine articles assessing external validation were selected. Among the 21 studies for AKI prediction models and their external validation, 12 were single-center (57%), and only three included more than 1,000 patients (14%). The definition of AKI was not uniform and none used recently published consensus criteria for AKI. Although good performance was reported in their internal validation, most of the prediction models had poor discrimination with an AUROC below 0.7 in the external validation studies. There were 10 common non-renal variables that were reported in more than three prediction models: mechanical ventilation, age, gender, hypotension, liver failure, oliguria, sepsis/septic shock, low albumin, consciousness and low platelet count. Conclusions Information in this systematic review should be useful for future prediction model derivation by providing potential candidate predictors, and for future external validation by listing up the published prediction models. PMID:28056039

  5. Predictive Factors of Hospital Mortality Due to Myocardial Infarction: A Multilevel Analysis of Iran's National Data

    PubMed Central

    Ahmadi, Ali; Soori, Hamid; Mehrabi, Yadollah; Etemad, Koorosh; Sajjadi, Homeira; Sadeghi, Mehraban

    2015-01-01

    Background: Regarding failure to establish the statistical presuppositions for analysis of the data by conventional approaches, hierarchical structure of the data as well as the effect of higher-level variables, this study was conducted to determine the factors independently associated with hospital mortality due to myocardial infarction (MI) in Iran using a multilevel analysis. Methods: This study was a national, hospital-based, and cross-sectional study. In this study, the data of 20750 new MI patients between April, 2012 and March, 2013 in Iran were used. The hospital mortality due to MI was considered as the dependent variable. The demographic data, clinical and behavioral risk factors at the individual level and environmental data were gathered. Multilevel logistic regression models with Stata software were used to analyze the data. Results: Within 1-year of study, the frequency (%) of hospital mortality within 30 days of admission was derived 2511 (12.1%) patients. The adjusted odds ratio (OR) of mortality with (95% confidence interval [CI]) was derived 2.07 (95% CI: 1.5–2.8) for right bundle branch block, 1.5 (95% CI: 1.3–1.7) for ST-segment elevation MI, 1.3 (95% CI: 1.1–1.4) for female gender, and 1.2 (95% CI: 1.1–1.3) for humidity, all of which were considered as risk factors of mortality. But, OR of mortality was 0.7 for precipitation (95% CI: 0.7–0.8) and 0.5 for angioplasty (95% CI: 0.4–0.6) were considered as protective factors of mortality. Conclusions: Individual risk factors had independent effects on the hospital mortality due to MI. Variables in the province level had no significant effect on the outcome of MI. Increasing access and quality to treatment could reduce the mortality due to MI. PMID:26730342

  6. The "Surprise Question" Asked of Emergency Physicians May Predict 12-Month Mortality among Older Emergency Department Patients.

    PubMed

    Ouchi, Kei; Jambaulikar, Guru; George, Naomi R; Xu, Wanlu; Obermeyer, Ziad; Aaronson, Emily L; Schuur, Jeremiah D; Schonberg, Mara A; Tulsky, James A; Block, Susan D

    2017-08-28

    Identification of older adults with serious illness (life expectancy less than one year) who may benefit from serious illness conversations or other palliative care interventions in the emergency department (ED) is difficult. To assess the performance of the "surprise question (SQ)" asked of emergency physicians to predict 12-month mortality. We asked attending emergency physician "Would you be surprised whether this patient died in the next 12 months?" regarding patients ≥65 years old that they had cared for that shift. We prospectively obtained death records from Massachusetts Department of Health Vital Records. An urban, university-affiliated ED. Twelve-month mortality. We approached 38 physicians to answer the SQ, and 86% participated. The mean age of our cohort was 76 years, 51% were male, and 45% had at least one serious illness. Out of 207 patients, the physicians stated that they "would not be surprised" if the patient died in the next 12 months for 102 of the patients (49%); 44 of the 207 patients (21%) died within 12 months. The SQ demonstrated sensitivity of 77%, specificity of 56%, positive predictive value of 32%, and negative predictive value of 90%. When combined with other predictors, the model sorted the patient who lived from the patient who died correctly 72% of the time (c-statistic = 0.72). Use of the SQ by emergency physicians may predict 12-month mortality in older ED patients and may help emergency physicians identify older adults in need of palliative care interventions.

  7. Blood Lactate Levels Cutoff and Mortality Prediction in Sepsis—Time for a Reappraisal? a Retrospective Cohort Study

    PubMed Central

    Filho, Roberto Rabello; Rocha, Leonardo Lima; Corrêa, Thiago Domingos; Pessoa, Camila Menezes Souza; Colombo, Giancarlo; Assuncao, Murillo Santucci Cesar

    2016-01-01

    Abstract The objective of this study was to identify the initial value of blood lactate that best correlates with 28-day mortality in resuscitated septic shock patients. This was a retrospective cohort study including 443 patients admitted to an intensive care unit (ICU) with severe sepsis or septic shock from the emergency department. A receiver-operating characteristic (ROC) curve was drawn to obtain the best cutoff value for initial blood lactate associated with 28-day mortality. Patients were then dichotomized according to the chosen lactate cutoff, and sensitivity, specificity, and positive and negative predictive values were calculated. Baseline blood lactate level more than 2.5 mmol/L showed the largest area under the ROC curve to predict 28-day mortality (ROC area, 0.70; 95% confidence interval [CI], 0.62–0.79), with sensitivity, specificity, and negative predictive value of 67.4%, 61.7%, and 94.2%, respectively. Mortality at 28 days was 16.9% (31/183) in patients with initial lactate more than 2.5 mmol/L and 5.8% (15/260) in patients with initial lactate at most 2.5 mmol/L (relative risk, 2.93; 95% CI, 1.63–5.28; P < 0.001). Initial blood lactate levels more than 2.5 mmol/L (hazard ratio [HR], 2.86; 95% CI, 1.53–5.33; P = 0.001) and Sepsis-related Organ Failure Assessment score at ICU admission (HR, 1.18; 95% CI, 1.09–1.27; P < 0.001) were associated with increased 28-day mortality in the adjusted Cox regression. In this retrospective cohort study, a lactate level more than 2.5 mmol/L was the best threshold to predict 28-day mortality among severe sepsis and septic shock patients. Further prospective studies should address the impact on morbidity and mortality of this threshold as a trigger to resuscitation in this population of critically ill patients. PMID:27380535

  8. Prediction of all-cause mortality with copeptin in cardio-cerebrovascular patients: A meta-analysis of prospective studies.

    PubMed

    Sun, Hao; Sun, Ting; Ma, Bing; Yang, Bo-wen; Zhang, Yao; Huang, Dong-hui; Shi, Jing-pu

    2015-07-01

    Measurement of the biomarker copeptin may help identify disease severity and risk of mortality for a various diseases. This study sought to determine the relationship between copeptin and all-cause mortality of patients with cardio-cerebrovascular disease. Database of Medline and Web of Science were searched for studies with data involving the baseline copeptin levels and subsequent all-cause mortality outcomes. The pooled HRs of all-cause mortality were calculated and presented with 95%CIs. Subgroup analysis and sensitivity analysis were conducted to explore the possible sources of heterogeneity. Data from 14,395 participants were derived from 28 prospective studies. Higher copeptin significantly increased the risk of all-cause mortality (per unit copeptin: HR=1.020, 95%CI=1.004-1.036; log unit copeptin: HR=2.884, 95%CI=1.844-4.512; categorical copeptin: HR=3.371, 95%CI=2.077-5.472). Subgroup analysis indicated that the risk of all-cause death was higher in cerebrovascular patients (per unit copeptin: HR=2.537, 95%CI=0.956-6.731; log unit copeptin: HR=3.419, 95%CI=2.391-4.888) than cardiovascular patients (per unit copeptin: HR=1.011, 95%CI=1.002-1.020; log unit copeptin: HR=2.009, 95%CI=1.119-3.608). Copeptin is associated with all-cause mortality of patients with cardiovascular and cerebrovascular disease. Our study suggests that copeptin seems to be a promising novel biomarker for prediction of mortality in cardio-cerebrovascular patients, especially for cerebrovascular patients. Copyright © 2015 Elsevier Inc. All rights reserved.

  9. Usefulness of a single-item measure of depression to predict mortality: the GAZEL prospective cohort study

    PubMed Central

    Lefèvre, Thomas; Singh-Manoux, Archana; Stringhini, Silvia; Dugravot, Aline; Lemogne, Cédric; Consoli, Silla M.; Goldberg, Marcel; Zins, Marie

    2012-01-01

    Background: It remains unknown whether short measures of depression perform as well as long measures in predicting adverse outcomes such as mortality. The present study aims to examine the predictive value of a single-item measure of depression for mortality. Methods: A total of 14 185 participants of the GAZEL cohort completed the 20-item Center-for-Epidemiologic-Studies-Depression (CES-D) scale in 1996. One of these items (I felt depressed) was used as a single-item measure of depression. All-cause mortality data were available until 30 September 2009, a mean follow-up period of 12.7 years with a total of 650 deaths. Results: In Cox regression model adjusted for baseline socio-demographic characteristics, a one-unit increase in the single-item score (range 0–3) was associated with a 25% higher risk of all-cause mortality (95% CI: 13–37%, P < 0.001). Further adjustment for health-related behaviours and physical chronic diseases reduced this risk by 36% and 8%, respectively. After adjustment for all these variables, every one-unit increase in the single-item score predicted a 15% increased risk of death (95% CI: 5–27%, P < 0.01). There is also an evidence of a dose–reponse relationship between reponse scores on the single-item measure of depression and mortality. Conclusion: This study shows that a single-item measure of depression is associated with an increased risk of death. Given its simplicity and ease of administration, a very simple single-item measure of depression might be useful for identifying middle-aged adults at risk for elevated depressive symptoms in large epidemiological studies and clinical settings. PMID:21840893

  10. Principal component analysis of the T wave and prediction of cardiovascular mortality in American Indians: the Strong Heart Study.

    PubMed

    Okin, Peter M; Devereux, Richard B; Fabsitz, Richard R; Lee, Elisa T; Galloway, James M; Howard, Barbara V

    2002-02-12

    Increased QT interval dispersion (QTd) is a proposed ECG marker of vulnerability to ventricular arrhythmias and of cardiovascular (CV) mortality. However, principal component analysis (PCA) of the T-wave vector loop may more accurately represent repolarization abnormalities than QTd. Predictive values of QTd and PCA were assessed in 1839 American Indian participants in the first Strong Heart Study examination. T-wave loop morphology was quantified by the ratio of the second to first eigenvalues of the T-wave vector by PCA (PCA ratio); QTd was quantified as the difference between maximum and minimum QT intervals. After 3.7+/-0.9 years mean follow-up, there were 55 CV deaths. In univariate analyses, an increased PCA ratio predicted CV mortality in women (chi2=7.8, P=0.0053) and men (chi2=9.5, P=0.0021). In contrast, increased QTd was a significant predictor of CV mortality in women (chi2=30.6, P<0.0001) but not in men (chi2=2.0, P=NS). In multivariate Cox analyses controlling for risk factors and rate-corrected QT interval, the PCA ratio remained a significant predictor of CV mortality in women (chi2=4.0 P=0.043) and men (chi2=6.4, P=0.011); QTd was a significant predictor in women only (chi2=11.0, P=0.0009). PCA ratios >90th percentile (32% in women and 24.6% in men) identified women with a 3.68-fold increased risk of CV mortality (95% CI, 1.54 to 8.83) and men with a 2.77-fold increased risk (95% CI, 1.18 to 6.49). Abnormalities of repolarization measured by PCA of the T-wave loop predict CV death in men and women, supporting use of PCA for quantifying repolarization abnormalities.

  11. Predicting 30-day mortality after hip fracture surgery: Evaluation of the National Hip Fracture Database case-mix adjustment model.

    PubMed

    Tsang, C; Boulton, C; Burgon, V; Johansen, A; Wakeman, R; Cromwell, D A

    2017-09-01

    The National Hip Fracture Database (NHFD) publishes hospital-level risk-adjusted mortality rates following hip fracture surgery in England, Wales and Northern Ireland. The performance of the risk model used by the NHFD was compared with the widely-used Nottingham Hip Fracture Score. Data from 94 hospitals on patients aged 60 to 110 who had hip fracture surgery between May 2013 and July 2013 were analysed. Data were linked to the Office for National Statistics (ONS) death register to calculate the 30-day mortality rate. Risk of death was predicted for each patient using the NHFD and Nottingham models in a development dataset using logistic regression to define the models' coefficients. This was followed by testing the performance of these refined models in a second validation dataset. The 30-day mortality rate was 5.36% in the validation dataset (n = 3861), slightly lower than the 6.40% in the development dataset (n = 4044). The NHFD and Nottingham models showed a slightly lower discrimination in the validation dataset compared with the development dataset, but both still displayed moderate discriminative power (c-statistic for NHFD = 0.71, 95% confidence interval (CI) 0.67 to 0.74; Nottingham model = 0.70, 95% CI 0.68 to 0.75). Both models defined similar ranges of predicted mortality risk (1% to 18%) in assessment of calibration. Both models have limitations in predicting mortality for individual patients after hip fracture surgery, but the NHFD risk adjustment model performed as well as the widely-used Nottingham prognostic tool and is therefore a reasonable alternative for risk adjustment in the United Kingdom hip fracture population.Cite this article: Bone Joint Res 2017;6:550-556. © 2017 Tsang et al.

  12. Uric acid predicts mortality and ischaemic stroke in subjects with diastolic dysfunction: the Tromsø Study 1994-2013.

    PubMed

    Norvik, Jon V; Schirmer, Henrik; Ytrehus, Kirsti; Storhaug, Hilde M; Jenssen, Trond G; Eriksen, Bjørn O; Mathiesen, Ellisiv B; Løchen, Maja-Lisa; Wilsgaard, Tom; Solbu, Marit D

    2017-05-01

    To investigate whether serum uric acid predicts adverse outcomes in persons with indices of diastolic dysfunction in a general population. We performed a prospective cohort study among 1460 women and 1480 men from 1994 to 2013. Endpoints were all-cause mortality, incident myocardial infarction, and incident ischaemic stroke. We stratified the analyses by echocardiographic markers of diastolic dysfunction, and uric acid was the independent variable of interest. Hazard ratios (HR) were estimated per 59 μmol/L increase in baseline uric acid. Multivariable adjusted Cox proportional hazards models showed that uric acid predicted all-cause mortality in subjects with E/A ratio <0.75 (HR 1.12, 95% confidence interval [CI] 1.00-1.25) or E/A ratio >1.5 (HR 1.51, 95% CI 1.09-2.09, P for interaction between E/A ratio category and uric acid = 0.02). Elevated uric acid increased mortality risk in persons with E-wave deceleration time <140 ms or >220 ms (HR 1.46, 95% CI 1.01-2.12 and HR 1.13, 95% CI 1.02-1.26, respectively; P for interaction = 0.04). Furthermore, in participants with isovolumetric relaxation time ≤60 ms, mortality risk was higher with increasing uric acid (HR 4.98, 95% CI 2.02-12.26, P for interaction = 0.004). Finally, elevated uric acid predicted ischaemic stroke in subjects with severely enlarged left atria (HR 1.62, 95% CI 1.03-2.53, P for interaction = 0.047). Increased uric acid was associated with higher all-cause mortality risk in subjects with echocardiographic indices of diastolic dysfunction, and with higher ischaemic stroke risk in persons with severely enlarged left atria.

  13. Upper gastrointestinal haemorrhage: predictive factors of in-hospital mortality in patients treated in the medical intensive care unit.

    PubMed

    Skok, P; Sinkovič, A

    2011-01-01

    This prospective, cohort study assessed the independent predictors of in-hospital mortality in patients with acute upper gastrointestinal haemorrhage admitted to the medical intensive care unit (MICU) at the University Clinical Centre Maribor, Slovenia. Using univariate, multivariate and logistic regression methods the predictors of mortality in 54 upper gastrointestinal haemorrhage patients (47 men, mean ± SD age 61.6 ± 14.2 years) were investigated. The mean ± SD duration of treatment in the MICU was 2.8 ± 2.9 days and the mortality rate was 31.5%. Significant differences between nonsurvivors and survivors were observed in haemorrhagic shock, heart failure, infection, diastolic blood pressure at admission, haemoglobin and red blood cell count at admission, and lowest haemoglobin and red blood cell count during treatment. Heart failure (odds ratio 59.13) was the most significant independent predictor of in-hospital mortality. Haemorrhagic shock and the lowest red blood cell count during treatment were also important independent predictive factors of in-hospital mortality.

  14. Prediction of mortality in type 2 diabetes from health-related quality of life (ZODIAC-4).

    PubMed

    Kleefstra, Nanne; Landman, Gijs W D; Houweling, Sebastiaan T; Ubink-Veltmaat, Lielith J; Logtenberg, Susan J J; Meyboom-de Jong, Betty; Coyne, James C; Groenier, Klaas H; Bilo, Henk J G

    2008-05-01

    To investigate the relationship between health-related quality of life (HRQOL) and mortality in type 2 diabetes. In 1998, 1,143 primary care patients with type 2 diabetes participated in the Zwolle Outpatient Diabetes project Integrating Available Care (ZODIAC) study. At baseline, HRQOL was assessed with the RAND-36 and, after almost 6 years, life status was retrieved. Cox proportional hazards modeling was used to investigate the association between HRQOL (continuous data) and mortality with adjustment for selected confounders (smoking, age, sex, diabetes duration, A1C, renal function, BMI, blood pressure, HDL cholesterol, and macrovascular complications). The Physical Component Summary of the RAND-36 was inversely associated with mortality (hazard ratio [HR] 0.979 [95% CI 0.966-0.992]), as were two separate RAND-36 dimensions. This study found that HRQOL is an independent marker of mortality and emphasizes the importance of looking beyond clinical parameters in patients with type 2 diabetes.

  15. Case fatality proportions and predictive factors for mortality among children hospitalized with severe pneumonia in a rural developing country setting.

    PubMed

    Djelantik, I G G; Gessner, Bradford D; Sutanto, Augustinus; Steinhoff, Mark; Linehan, Mary; Moulton, Lawrence H; Arjoso, Soemarjati

    2003-12-01

    Few large studies have evaluated risk factors for mortality among children hospitalized for pneumonia and this may contribute to suboptimal case management efficiency. To identify useful screening criteria for mortality among children hospitalized for pneumonia in a developing country setting, we conducted a population-based hospital cohort study among children less than 2 years of age admitted for pneumonia during 1999-2001 at one of three major hospitals on Lombok Island, Indonesia. Of 4351 children admitted for pneumonia, 12 per cent died before discharge. Case fatality proportions were seasonal, with peaks occurring immediately after peaks in the proportion of cases positive for respiratory syncytial virus. Children with an oxygen saturation < or = 85 per cent or age younger than 4 months were 5.6 times more likely to die than children with none of these predictive factors (95 per cent CI, 4.5-7.1); 83 per cent of children who died had one of these two risk factors. For children < 4 months old, mortality increased at an oxygen saturation < 88 per cent compared with < 80 per cent for older children. Laboratory, physical examination, and radiological findings were not associated with or did not contribute substantially to mortality prediction. Among children hospitalized for pneumonia, age less than 4 months and hypoxia were identified with those at high risk of death. Age influences cut-off levels for hypoxia.

  16. Height loss starting in middle age predicts increased mortality in the elderly.

    PubMed

    Masunari, Naomi; Fujiwara, Saeko; Kasagi, Fumiyoshi; Takahashi, Ikuno; Yamada, Michiko; Nakamura, Toshitaka

    2012-01-01

    The purpose of this study was to determine the mortality risk among Japanese men and women with height loss starting in middle age, taking into account lifestyle and physical factors. A total of 2498 subjects (755 men and 1743 women) aged 47 to 91 years old underwent physical examinations during the period 1994 to 1995. Those individuals were followed for mortality status through 2003. Mortality risk was estimated using an age-stratified Cox proportional hazards model. In addition to sex, adjustment factors such as radiation dose, lifestyle, and physical factors measured at the baseline--including smoking status, alcohol intake, total cholesterol, blood pressure, and diagnosed diseases--were used for analysis of total mortality and mortality from each cause of death. There were a total of 302 all-cause deaths, 46 coronary heart disease and stroke deaths, 58 respiratory deaths including 45 pneumonia deaths, and 132 cancer deaths during the follow-up period. Participants were followed for 20,787 person-years after baseline. Prior history of vertebral deformity and hip fracture were not associated with mortality risk. However, more than 2 cm of height loss starting in middle age showed a significant association with all-cause mortality among the study participants (HR = 1.76, 95% CI 1.31 to 2.38, p = 0.0002), after adjustment was made for sex, attained age, atomic-bomb radiation exposure, and lifestyle and physical factors. Such height loss also was significantly associated with death due to coronary heart disease or stroke (HR = 3.35, 95% CI 1.63 to 6.86, p = 0.0010), as well as respiratory-disease death (HR = 2.52, 95% CI 1.25 to 5.22, p = 0.0130), but not cancer death. Continuous HL also was associated with all-cause mortality and CHD- or stroke-caused mortality. Association between height loss and mortality was still significant, even after excluding persons with vertebral deformity. Height loss of more than 2 cm starting in middle age

  17. An Australian risk prediction model for 30-day mortality after isolated coronary artery bypass: the AusSCORE.

    PubMed

    Reid, Christopher; Billah, Baki; Dinh, Diem; Smith, Julian; Skillington, Peter; Yii, Michael; Seevanayagam, Seven; Mohajeri, Morteza; Shardey, Gil

    2009-10-01

    Our objective was to identify risk factors associated with 30-day mortality after isolated coronary artery bypass grafting in the Australian context and to develop a preoperative model for 30-day mortality risk prediction. Preoperative risk associated with cardiac surgery can be ascertained through a variety of risk prediction models, none of which is specific to the Australian population. Recently, it was shown that the widely used EuroSCORE model validated poorly for an Australian cohort. Hence, a valid model is required to appropriately guide surgeons and patients in assessing preoperative risk. Data from the Australasian Society of Cardiac and Thoracic Surgeons database project was used. All patients undergoing isolated coronary artery bypass grafting between July 2001 and June 2005 were included for analysis. The data were divided into creation and validation sets. The data in the creation set was used to develop the model and then the model was validated in the validation set. Preoperative variables with a P value of less than .25 in chi(2) analysis were entered into multiple logistic regression analysis to develop a preoperative predictive model. Bootstrap and backward elimination methods were used to identify variables that are truly independent predictors of mortality, and 6 candidate models were identified. The Akaike Information Criteria (AIC) and prediction mean square error were used to select the final model (AusSCORE) from this group of candidate models. The AusSCORE model was then validated by average receiver operating characteristic, the P value for the Hosmer-Lemeshow goodness-of-fit test, and prediction mean square error obtained from n-fold validation. Over the 4-year period, 11,823 patients underwent cardiac surgery, of whom 65.9% (7709) had isolated coronary bypass procedures. The 30-day mortality rate for this group was 1.74% (134/7709). Factors selected as independent predictors in the preoperative isolated coronary bypass AusSCORE model

  18. Childhood-Onset Disease Predicts Mortality in an Adult Cohort of Patients with Systemic Lupus Erythematosus

    PubMed Central

    Hersh, Aimee O.; Trupin, Laura; Yazdany, Jinoos; Panopalis, Peter; Julian, Laura; Katz, Patricia; Criswell, Lindsey A.; Yelin, Edward

    2013-01-01

    Objective To examine childhood-onset disease as a predictor of mortality in a cohort of adult patients with systemic lupus erythematosus (SLE). Methods Data were derived from the University of California Lupus Outcomes Study, a longitudinal cohort of 957 adult subjects with SLE that includes 98 subjects with childhood-onset SLE. Baseline and follow-up data were obtained via telephone interviews conducted between 2002-2007. The number of deaths during 5 years of follow-up was determined and standardized mortality ratios (SMRs) for the cohort, and across age groups, were calculated. Kaplan-Meier life table analysis was used to compare mortality rates between childhood (defined as SLE diagnosis <18 years) and adult-onset SLE. Multivariate Cox proportional hazard models were used to determine predictors of mortality. Results During the median follow-up period of 48 months, 72 deaths (7.5% of subjects) occurred, including 9 (12.5%) among those with childhood-onset SLE. The overall SMR was 2.5 (CI 2.0-3.2). In Kaplan-Meier survival analysis, after adjusting for age, childhood-onset subjects were at increased risk for mortality throughout the follow-up period (p<0.0001). In a multivariate model adjusting for age, disease duration and other covariates, childhood-onset SLE was independently associated with an increased mortality risk (hazard ratio [HR]: 3.1; 95% confidence interval [CI]: 1.3-7.3), as was low socioeconomic status measured by education (HR: 1.9; 95% CI 1.1-3.2) and end stage renal disease (HR: 2.1; 95% CI 1.1-4.0). Conclusion Childhood-onset SLE was a strong predictor of mortality in this cohort. Interventions are needed to prevent early mortality in this population. PMID:20235215

  19. Season of death and birth predict patterns of mortality in Burkina Faso.

    PubMed

    Kynast-Wolf, Gisela; Hammer, Gaël P; Müller, Olaf; Kouyaté, Bocar; Becher, Heiko

    2006-04-01

    Mortality in developing countries has multiple causes. Some of these causes are linked to climatic conditions that differ over the year. Data on season-specific mortality are sparse. We analysed longitudinal data from a population of approximately 35,000 individuals in Burkina Faso. During the observation period 1993-2001, a total number of 4,098 deaths were recorded. The effect of season on mortality was investigated separately by age group as (i) date of death and (ii) date of birth. For (i), age-specific death rates by month of death were calculated. The relative effect of each month was assessed using the floating relative risk method and modelled continuously. For (ii), age-specific death rates by month of birth were calculated and the mean date of birth among deat