Defining the Scope of Prognosis: Primary Care Clinicians' Perspectives on Predicting the Future Health of Older Adults.

PubMed

Thomas, John M; Fried, Terri R

2018-05-01

Studies examining the attitudes of clinicians toward prognostication for older adults have focused on life expectancy prediction. Little is known about whether clinicians approach prognostication in other ways. To describe how clinicians approach prognostication for older adults, defined broadly as making projections about patients' future health. In five focus groups, 30 primary care clinicians from community-based, academic-affiliated, and Veterans Affairs primary care practices were given open-ended questions about how they make projections about their patients' future health and how this informs the approach to care. Content analysis was used to organize responses into themes. Clinicians spoke about future health in terms of a variety of health outcomes in addition to life expectancy, including independence in activities and decision making, quality of life, avoiding hospitalization, and symptom burden. They described approaches in predicting these health outcomes, including making observations about the overall trajectory of patients to predict health outcomes and recognizing increased risk for adverse health outcomes. Clinicians expressed reservations about using estimates of mortality risk and life expectancy to think about and communicate patients' future health. They discussed ways in which future research might help them in thinking about and discussing patients' future health to guide care decisions, including identifying when and whether interventions might impact future health. The perspectives of primary care clinicians in this study confirm that prognostic considerations can go beyond precise estimates of mortality risk and life expectancy to include a number of outcomes and approaches to predicting those outcomes. Published by Elsevier Inc.

Risk and the physics of clinical prediction.

PubMed

McEvoy, John W; Diamond, George A; Detrano, Robert C; Kaul, Sanjay; Blaha, Michael J; Blumenthal, Roger S; Jones, Steven R

2014-04-15

The current paradigm of primary prevention in cardiology uses traditional risk factors to estimate future cardiovascular risk. These risk estimates are based on prediction models derived from prospective cohort studies and are incorporated into guideline-based initiation algorithms for commonly used preventive pharmacologic treatments, such as aspirin and statins. However, risk estimates are more accurate for populations of similar patients than they are for any individual patient. It may be hazardous to presume that the point estimate of risk derived from a population model represents the most accurate estimate for a given patient. In this review, we exploit principles derived from physics as a metaphor for the distinction between predictions regarding populations versus patients. We identify the following: (1) predictions of risk are accurate at the level of populations but do not translate directly to patients, (2) perfect accuracy of individual risk estimation is unobtainable even with the addition of multiple novel risk factors, and (3) direct measurement of subclinical disease (screening) affords far greater certainty regarding the personalized treatment of patients, whereas risk estimates often remain uncertain for patients. In conclusion, shifting our focus from prediction of events to detection of disease could improve personalized decision-making and outcomes. We also discuss innovative future strategies for risk estimation and treatment allocation in preventive cardiology. Copyright © 2014 Elsevier Inc. All rights reserved.

Youth Offender Care Needs Assessment Tool (YO-CNAT): an actuarial risk assessment tool for predicting problematic child-rearing situations in juvenile offenders on the basis of police records.

PubMed

van der Put, Claudia E; Stams, Geert Jan J M

2013-12-01

In the juvenile justice system, much attention is paid to estimating the risk for recidivism among juvenile offenders. However, it is also important to estimate the risk for problematic child-rearing situations (care needs) in juvenile offenders, because these problems are not always related to recidivism. In the present study, an actuarial care needs assessment tool for juvenile offenders, the Youth Offender Care Needs Assessment Tool (YO-CNAT), was developed to predict the probability of (a) a future supervision order imposed by the child welfare agency, (b) a future entitlement to care indicated by the youth care agency, and (c) future incidents involving child abuse, domestic violence, and/or sexual norm trespassing behavior at the juvenile's address. The YO-CNAT has been developed for use by the police and is based solely on information available in police registration systems. It is designed to assist a police officer without clinical expertise in making a quick assessment of the risk for problematic child-rearing situations. The YO-CNAT was developed on a sample of 1,955 juvenile offenders and was validated on another sample of 2,045 juvenile offenders. The predictive validity (area under the receiver-operating-characteristic curve) scores ranged between .70 (for predicting future entitlement to care) and .75 (for predicting future worrisome incidents at the juvenile's address); therefore, the predictive accuracy of the test scores of the YO-CNAT was sufficient to justify its use as a screening instrument for the police in deciding to refer a juvenile offender to the youth care agency for further assessment into care needs.

Applying Risk Prediction Models to Optimize Lung Cancer Screening: Current Knowledge, Challenges, and Future Directions.

PubMed

Sakoda, Lori C; Henderson, Louise M; Caverly, Tanner J; Wernli, Karen J; Katki, Hormuzd A

2017-12-01

Risk prediction models may be useful for facilitating effective and high-quality decision-making at critical steps in the lung cancer screening process. This review provides a current overview of published lung cancer risk prediction models and their applications to lung cancer screening and highlights both challenges and strategies for improving their predictive performance and use in clinical practice. Since the 2011 publication of the National Lung Screening Trial results, numerous prediction models have been proposed to estimate the probability of developing or dying from lung cancer or the probability that a pulmonary nodule is malignant. Respective models appear to exhibit high discriminatory accuracy in identifying individuals at highest risk of lung cancer or differentiating malignant from benign pulmonary nodules. However, validation and critical comparison of the performance of these models in independent populations are limited. Little is also known about the extent to which risk prediction models are being applied in clinical practice and influencing decision-making processes and outcomes related to lung cancer screening. Current evidence is insufficient to determine which lung cancer risk prediction models are most clinically useful and how to best implement their use to optimize screening effectiveness and quality. To address these knowledge gaps, future research should be directed toward validating and enhancing existing risk prediction models for lung cancer and evaluating the application of model-based risk calculators and its corresponding impact on screening processes and outcomes.

Frailty Versus Stopping Elderly Accidents, Deaths and Injuries Initiative Fall Risk Score: Ability to Predict Future Falls.

PubMed

Crow, Rebecca S; Lohman, Matthew C; Pidgeon, Dawna; Bruce, Martha L; Bartels, Stephen J; Batsis, John A

2018-03-01

To compare the ability of frailty status to predict fall risk with that of community fall risk screening tools. Analysis of cross-sectional and longitudinal data from NHATS. National Health and Aging Trend Study (NHATS) 2011-2015. Individuals aged 65 and older (N = 7,392). Fall risk was defined according to the Stopping Elderly Accidents, Deaths and Injuries (STEADI) initiative. Frailty was defined as exhaustion, weight loss, low activity, slow gait speed, and weak grip strength. Robust was defined as meeting 0 criteria, prefrailty as 1 or 2 criteria, and frailty as 3 or more criteria. Falls were self-reported and ascertained using NHATS subsequent rounds (2012-2015). We compared the ability of frailty to predict future falls with that of STEADI score, adjusting for age, race, sex, education, comorbidities, hearing and vision impairment, and disability. Of the 7,392 participants (58.5% female), there 3,545 (48.0%) were classified as being at low risk of falling, 2,966 (40.1%) as being at moderate risk, and 881 (11.9%) as being at high risk. The adjusted risk of falling over the 4 subsequent years was 2.5 times as great for the moderate-risk group (hazard ratio (HR) = 2.50, 95% confidence interval (CI) = 2.16-2.89) and almost 4 times as great (HR = 3.79, 95% CI = 2.76-5.21) for the high-risk group as for the low-risk group. Risk of falling was greater for those who were prefrail (HR = 1.34, 95% CI 1.16-1.55) and frail (HR = 1.20, 95% CI = 0.94-1.54) than for those who were robust. STEADI score is a strong predictor of future falls. Addition of frailty status does not improve the ability of the STEADI measure to predict future falls. © 2018, Copyright the Authors Journal compilation © 2018, The American Geriatrics Society.

Self-Esteem and Future Orientation Predict Adolescents' Risk Engagement

ERIC Educational Resources Information Center

Jackman, Danielle M.; MacPhee, David

2017-01-01

This study's purpose was to examine the relations among future orientation, self-esteem, and later adolescent risk behaviors, and to compare two mediational models involving self-esteem versus future orientation as mediators. An ethnically diverse sample of 12- to 14-year-olds (N = 862, 54% female, 53% ethnic minority) was assessed longitudinally.…

Pattern recognition and functional neuroimaging help to discriminate healthy adolescents at risk for mood disorders from low risk adolescents.

PubMed

Mourão-Miranda, Janaina; Oliveira, Leticia; Ladouceur, Cecile D; Marquand, Andre; Brammer, Michael; Birmaher, Boris; Axelson, David; Phillips, Mary L

2012-01-01

There are no known biological measures that accurately predict future development of psychiatric disorders in individual at-risk adolescents. We investigated whether machine learning and fMRI could help to: 1. differentiate healthy adolescents genetically at-risk for bipolar disorder and other Axis I psychiatric disorders from healthy adolescents at low risk of developing these disorders; 2. identify those healthy genetically at-risk adolescents who were most likely to develop future Axis I disorders. 16 healthy offspring genetically at risk for bipolar disorder and other Axis I disorders by virtue of having a parent with bipolar disorder and 16 healthy, age- and gender-matched low-risk offspring of healthy parents with no history of psychiatric disorders (12-17 year-olds) performed two emotional face gender-labeling tasks (happy/neutral; fearful/neutral) during fMRI. We used Gaussian Process Classifiers (GPC), a machine learning approach that assigns a predictive probability of group membership to an individual person, to differentiate groups and to identify those at-risk adolescents most likely to develop future Axis I disorders. Using GPC, activity to neutral faces presented during the happy experiment accurately and significantly differentiated groups, achieving 75% accuracy (sensitivity = 75%, specificity = 75%). Furthermore, predictive probabilities were significantly higher for those at-risk adolescents who subsequently developed an Axis I disorder than for those at-risk adolescents remaining healthy at follow-up. We show that a combination of two promising techniques, machine learning and neuroimaging, not only discriminates healthy low-risk from healthy adolescents genetically at-risk for Axis I disorders, but may ultimately help to predict which at-risk adolescents subsequently develop these disorders.

Predicting Future Reconviction in Offenders with Intellectual Disabilities: The Predictive Efficacy of VRAG, PCL-SV, and the HCR-20

ERIC Educational Resources Information Center

Gray, Nicola S.; Fitzgerald, Suzanne; Taylor, John; MacCulloch, Malcolm J.; Snowden, Robert J.

2007-01-01

Accurate predictions of future reconviction, including those for violent crimes, have been shown to be greatly aided by the use of formal risk assessment instruments. However, it is unclear as to whether these instruments would also be predictive in a sample of offenders with intellectual disabilities. In this study, the authors have shown that…

Validation of a multifactorial risk factor model used for predicting future caries risk with Nevada adolescents.

PubMed

Ditmyer, Marcia M; Dounis, Georgia; Howard, Katherine M; Mobley, Connie; Cappelli, David

2011-05-20

The objective of this study was to measure the validity and reliability of a multifactorial Risk Factor Model developed for use in predicting future caries risk in Nevada adolescents in a public health setting. This study examined retrospective data from an oral health surveillance initiative that screened over 51,000 students 13-18 years of age, attending public/private schools in Nevada across six academic years (2002/2003-2007/2008). The Risk Factor Model included ten demographic variables: exposure to fluoridation in the municipal water supply, environmental smoke exposure, race, age, locale (metropolitan vs. rural), tobacco use, Body Mass Index, insurance status, sex, and sealant application. Multiple regression was used in a previous study to establish which significantly contributed to caries risk. Follow-up logistic regression ascertained the weight of contribution and odds ratios of the ten variables. Researchers in this study computed sensitivity, specificity, positive predictive value (PVP), negative predictive value (PVN), and prevalence across all six years of screening to assess the validity of the Risk Factor Model. Subjects' overall mean caries prevalence across all six years was 66%. Average sensitivity across all six years was 79%; average specificity was 81%; average PVP was 89% and average PVN was 67%. Overall, the Risk Factor Model provided a relatively constant, valid measure of caries that could be used in conjunction with a comprehensive risk assessment in population-based screenings by school nurses/nurse practitioners, health educators, and physicians to guide them in assessing potential future caries risk for use in prevention and referral practices.

Presence of High-Risk HPV mRNA in Relation to Future High-Grade Lesions among High-Risk HPV DNA Positive Women with Minor Cytological Abnormalities

PubMed Central

Johansson, Hanna; Bjelkenkrantz, Kaj; Darlin, Lotten; Dilllner, Joakim; Forslund, Ola

2015-01-01

Objective Continuous expression of E6- and E7-oncogenes of high-risk human papillomavirus (HPV) types is necessary for the development and maintenance of the dysplastic phenotype. The aim of the study was to determine the sensitivity and specificity of the APTIMA HPV mRNA assay (Hologic) in predicting future development of high-grade cervical intraepithelial neoplasia (CIN) among high-risk HPV-DNA-positive women with atypical squamous cells of undetermined significance (ASCUS) or low-grade squamous epithelial lesion (LSIL) cytology. Methods Archived SurePath cervical samples of women ≥ 35 years of age with high-risk HPV DNA-positive ASCUS (n = 211) or LSIL, (n = 131) were tested for the presence of high-risk HPV E6/E7 mRNA using the APTIMA HPV assay, and the women were monitored for development of histopathologically verified CIN2+. Results Twenty-nine percent (61/211) of the women in the ASCUS group, and 34.3% (45/131) in the LSIL group developed CIN2+ within 4.5 years of follow-up. The prevalence of HPV mRNA was 90.0% (95% CI 85.9-94.0) among women with ASCUS and 95.4% (95% CI 91.8-99.0) among women with LSIL. The presence of HPV E6/E7 mRNA was associated with future development of CIN2+ among women with ASCUS and LSIL (p=0.02). The mRNA assay demonstrated high sensitivity in predicting future CIN2+ and CIN3 for index ASCUS (96.7%; 95% CI 87.6-99.4 and 100%; 95% CI 82.2-100, respectively) and LSIL (97.8%, 95% CI 86.8-99.9 and 100%, 95% CI 79.9-100, respectively). The corresponding specificity was low, 12.7% (95% CI 7.9-19.3) and 5.8% (95% CI 2.2-13.6), for future CIN2+, respectively. The negative predictive value of the HPV mRNA assay for detecting future CIN3 was 100%, since no mRNA-negative woman developed CIN3 (0/27) as compared to 13.6% (43/315) of the mRNA-positive women (p = 0.03). Conclusion The APTIMA mRNA assay demonstrated high sensitivity but low specificity in predicting future CIN2+ among women with minor cytological abnormalities. The assay had high negative predictive value for future CIN3, indicating that HPV-mRNA-negative women are at low risk of progression to high grade CIN. PMID:25893988

Are predictors of future suicide attempts and the transition from suicidal ideation to suicide attempts shared or distinct: a 12-month prospective study among patients with depressive disorders.

PubMed

Chan, Lai Fong; Shamsul, Azhar Shah; Maniam, Thambu

2014-12-30

Our study aimed to examine the interplay between clinical and social predictors of future suicide attempt and the transition from suicidal ideation to suicide attempt in depressive disorders. Sixty-six Malaysian inpatients with a depressive disorder were assessed at index admission and within 1 year for suicide attempt, suicidal ideation, depression severity, life event changes, treatment history and relevant clinical and socio-demographic factors. One-fifth of suicidal ideators transitioned to a future suicide attempt. All future attempters (12/66) had prior ideation and 83% of attempters had a prior attempt. The highest risk for transitioning from ideation to attempt was 5 months post-discharge. Single predictor models showed that previous psychiatric hospitalization and ideation severity were shared predictors of future attempt and ideation to attempt transition. Substance use disorders (especially alcohol) predicted future attempt and approached significance for the transition process. Low socio-economic status predicted the transition process while major personal injury/illness predicted future suicide attempt. Past suicide attempt, subjective depression severity and medication compliance predicted only future suicide attempt. The absence of prior suicide attempt did not eliminate the risk of future attempt. Given the limited sample, future larger studies on mechanisms underlying the interactions of such predictors are needed. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

VTE Risk assessment - a prognostic Model: BATER Cohort Study of young women.

PubMed

Heinemann, Lothar Aj; Dominh, Thai; Assmann, Anita; Schramm, Wolfgang; Schürmann, Rolf; Hilpert, Jan; Spannagl, Michael

2005-04-18

BACKGROUND: Community-based cohort studies are not available that evaluated the predictive power of both clinical and genetic risk factors for venous thromboembolism (VTE). There is, however, clinical need to forecast the likelihood of future occurrence of VTE, at least qualitatively, to support decisions about intensity of diagnostic or preventive measures. MATERIALS AND METHODS: A 10-year observation period of the Bavarian Thromboembolic Risk (BATER) study, a cohort study of 4337 women (18-55 years), was used to develop a predictive model of VTE based on clinical and genetic variables at baseline (1993). The objective was to prepare a probabilistic scheme that discriminates women with virtually no VTE risk from those at higher levels of absolute VTE risk in the foreseeable future. A multivariate analysis determined which variables at baseline were the best predictors of a future VTE event, provided a ranking according to the predictive power, and permitted to design a simple graphic scheme to assess the individual VTE risk using five predictor variables. RESULTS: Thirty-four new confirmed VTEs occurred during the observation period of over 32,000 women-years (WYs). A model was developed mainly based on clinical information (personal history of previous VTE and family history of VTE, age, BMI) and one composite genetic risk markers (combining Factor V Leiden and Prothrombin G20210A Mutation). Four levels of increasing VTE risk were arbitrarily defined to map the prevalence in the study population: No/low risk of VTE (61.3%), moderate risk (21.1%), high risk (6.0%), very high risk of future VTE (0.9%). In 10.6% of the population the risk assessment was not possible due to lacking VTE cases. The average incidence rates for VTE in these four levels were: 4.1, 12.3, 47.2, and 170.5 per 104 WYs for no, moderate, high, and very high risk, respectively. CONCLUSION: Our prognostic tool - containing clinical information (and if available also genetic data) - seems to be worthwhile testing in medical practice in order to confirm or refute the positive findings of this study. Our cohort study will be continued to include more VTE cases and to increase predictive value of the model.

A 6-year longitudinal study of predictors for suicide attempts in major depressive disorder.

PubMed

Eikelenboom, Merijn; Beekman, Aartjan T F; Penninx, Brenda W J H; Smit, Johannes H

2018-06-13

Major depressive disorder (MDD), represent a major source of risk for suicidality. However, knowledge about risk factors for future suicide attempts (SAs) within MDD is limited. The present longitudinal study examined a wide range of putative non-clinical risk factors (demographic, social, lifestyle, personality) and clinical risk factors (depressive and suicidal indicators) for future SAs among persons with MDD. Furthermore, we examined the relationship between a number of significant predictors and the incidence of a future SA. Data are from 1713 persons (18-65 years) with a lifetime MDD at the baseline measurement of the Netherlands Study of Depression and Anxiety who were subsequently followed up 2, 4 and 6 years. SAs were assessed in the face-to-face measurements. Cox proportional hazard regression analyses were used to examine a wide range of possible non-clinical and clinical predictors for subsequent SAs during 6-year follow-up. Over a period of 6 years, 3.4% of the respondents attempted suicide. Younger age, lower education, unemployment, insomnia, antidepressant use, a previous SA and current suicidal thoughts independently predicted a future SA. The number of significant risk factors (ranging from 0 to 7) linearly predicted the incidence of future SAs: in those with 0 predictors the SA incidence was 0%, which increased to 32% incidence in those with 6+ predictors. Of the non-clinical factors, particularly socio-economic factors predicted a SA independently. Furthermore, preexisting suicidal ideation and insomnia appear to be important clinical risk factors for subsequent SA that are open to preventative intervention.

Use of prescription drugs and future delinquency among adolescent offenders.

PubMed

Drazdowski, Tess K; Jäggi, Lena; Borre, Alicia; Kliewer, Wendy L

2015-01-01

Non-medical use of prescription drugs (NMUPD) by adolescents is a significant public health concern. The present study investigated the profile of NMUPD in 1349 adolescent offenders from the Pathways to Desistance project, and whether NMUPD predicted future delinquency using longitudinal data. Results indicated that increased frequency and recency of NMUPD in adolescent offenders are related to some demographic factors, as well as increased risk for violence exposure, mental health diagnoses, other drug use, and previous delinquency, suggesting that severity of NMUPD is important to consider. However, ANCOVA analyses found that NMUPD was not a significant predictor of drug-related, non-aggressive, or aggressive delinquency 12 months later beyond other known correlates of delinquency. Age, sex, exposure to violence, lower socioeconomic status, more alcohol use, and having delinquency histories were more important than NMUPD in predicting future delinquency. These findings suggest that although NMUPD is an important risk factor relating to many correlates of delinquency, it does not predict future delinquency beyond other known risk factors. Copyright © 2014 Elsevier Inc. All rights reserved.

Benign Breast Disease: Toward Molecular Prediction of Breast Cancer Risk

DTIC Science & Technology

2008-06-01

of benign histology in predicting risk of future breast cancer, examining in detail the role of proliferative disease, atypia , papillomas, radial...who had proliferative disease with atypia , especially those of younger age. • We identified a marked increased risk of breast cancer in women with...imparts an increased risk of developing a subsequent carcinoma similar to other forms of proliferative breast disease without atypia . Atypical

Limitations in predicting the space radiation health risk for exploration astronauts.

PubMed

Chancellor, Jeffery C; Blue, Rebecca S; Cengel, Keith A; Auñón-Chancellor, Serena M; Rubins, Kathleen H; Katzgraber, Helmut G; Kennedy, Ann R

2018-01-01

Despite years of research, understanding of the space radiation environment and the risk it poses to long-duration astronauts remains limited. There is a disparity between research results and observed empirical effects seen in human astronaut crews, likely due to the numerous factors that limit terrestrial simulation of the complex space environment and extrapolation of human clinical consequences from varied animal models. Given the intended future of human spaceflight, with efforts now to rapidly expand capabilities for human missions to the moon and Mars, there is a pressing need to improve upon the understanding of the space radiation risk, predict likely clinical outcomes of interplanetary radiation exposure, and develop appropriate and effective mitigation strategies for future missions. To achieve this goal, the space radiation and aerospace community must recognize the historical limitations of radiation research and how such limitations could be addressed in future research endeavors. We have sought to highlight the numerous factors that limit understanding of the risk of space radiation for human crews and to identify ways in which these limitations could be addressed for improved understanding and appropriate risk posture regarding future human spaceflight.

Forgiveness and Consideration of Future Consequences in Aggressive Driving

PubMed Central

Moore, Michael; Dahlen, Eric R.

2008-01-01

Most research on aggressive driving has focused on identifying aspects of driver personality which will exacerbate it (e.g., sensation seeking, impulsiveness, driving anger, etc.). The present study was designed to examine two theoretically relevant but previously unexplored personality factors predicted to reduce the risk of aggressive driving: trait forgiveness and consideration of future consequences. The utility of these variables in predicting aggressive driving and driving anger expression was evaluated among 316 college student volunteers. Hierarchical multiple regressions permitted an analysis of the incremental validity of these constructs beyond respondent gender, age, miles driven per week, and driving anger. Both forgiveness and consideration of future consequences contributed to the prediction of aggressive driving and driving anger expression, independent of driving anger. Research on aggressive driving may be enhanced by greater attention to adaptive, potentially risk-reducing traits. Moreover, forgiveness and consideration of future consequences may have implications for accident prevention. PMID:18760093

No Worries about the Future: Young Adults' Perceptions of Risk and Opportunity while Attending Technical College

ERIC Educational Resources Information Center

Barabasch, Antje

2006-01-01

In this ever-changing economy, young adults must remain flexible and adaptable as they transition from school to work and plan their future life courses. It is difficult for today's youth to choose training programs which will guarantee them secure, long-term employment. As the future grows less predictable, greater uncertainty and risk are…

Recent ecological responses to climate change support predictions of high extinction risk

PubMed Central

Maclean, Ilya M. D.; Wilson, Robert J.

2011-01-01

Predicted effects of climate change include high extinction risk for many species, but confidence in these predictions is undermined by a perceived lack of empirical support. Many studies have now documented ecological responses to recent climate change, providing the opportunity to test whether the magnitude and nature of recent responses match predictions. Here, we perform a global and multitaxon metaanalysis to show that empirical evidence for the realized effects of climate change supports predictions of future extinction risk. We use International Union for Conservation of Nature (IUCN) Red List criteria as a common scale to estimate extinction risks from a wide range of climate impacts, ecological responses, and methods of analysis, and we compare predictions with observations. Mean extinction probability across studies making predictions of the future effects of climate change was 7% by 2100 compared with 15% based on observed responses. After taking account of possible bias in the type of climate change impact analyzed and the parts of the world and taxa studied, there was less discrepancy between the two approaches: predictions suggested a mean extinction probability of 10% across taxa and regions, whereas empirical evidence gave a mean probability of 14%. As well as mean overall extinction probability, observations also supported predictions in terms of variability in extinction risk and the relative risk associated with broad taxonomic groups and geographic regions. These results suggest that predictions are robust to methodological assumptions and provide strong empirical support for the assertion that anthropogenic climate change is now a major threat to global biodiversity. PMID:21746924

Recent ecological responses to climate change support predictions of high extinction risk.

PubMed

Maclean, Ilya M D; Wilson, Robert J

2011-07-26

Predicted effects of climate change include high extinction risk for many species, but confidence in these predictions is undermined by a perceived lack of empirical support. Many studies have now documented ecological responses to recent climate change, providing the opportunity to test whether the magnitude and nature of recent responses match predictions. Here, we perform a global and multitaxon metaanalysis to show that empirical evidence for the realized effects of climate change supports predictions of future extinction risk. We use International Union for Conservation of Nature (IUCN) Red List criteria as a common scale to estimate extinction risks from a wide range of climate impacts, ecological responses, and methods of analysis, and we compare predictions with observations. Mean extinction probability across studies making predictions of the future effects of climate change was 7% by 2100 compared with 15% based on observed responses. After taking account of possible bias in the type of climate change impact analyzed and the parts of the world and taxa studied, there was less discrepancy between the two approaches: predictions suggested a mean extinction probability of 10% across taxa and regions, whereas empirical evidence gave a mean probability of 14%. As well as mean overall extinction probability, observations also supported predictions in terms of variability in extinction risk and the relative risk associated with broad taxonomic groups and geographic regions. These results suggest that predictions are robust to methodological assumptions and provide strong empirical support for the assertion that anthropogenic climate change is now a major threat to global biodiversity.

Predicting Future Suicide Attempts among Depressed Suicide Ideators: A 10-year Longitudinal Study

PubMed Central

May, Alexis M.; Klonsky, E. David; Klein, Daniel N.

2012-01-01

Suicidal ideation and attempts are a major public health problem. Research has identified many risk factors for suicidality; however, most fail to identify which suicide ideators are at greatest risk of progressing to a suicide attempt. Thus, the present study identified predictors of future suicide attempts in a sample of psychiatric patients reporting suicidal ideation. The sample comprised 49 individuals who met full DSM-IV criteria for major depressive disorder and/or dysthymic disorder and reported suicidal ideation at baseline. Participants were followed for 10 years. Demographic, psychological, personality, and psychosocial risk factors were assessed using validated questionnaires and structured interviews. Phi coefficients and point-biserial correlations were used to identify prospective predictors of attempts, and logistic regressions were used to identify which variables predicted future attempts over and above past suicide attempts. Six significant predictors of future suicide attempts were identified – cluster A personality disorder, cluster B personality disorder, lifetime substance abuse, baseline anxiety disorder, poor maternal relationship, and poor social adjustment. Finally, exploratory logistic regressions were used to examine the unique contribution of each significant predictor controlling for the others. Co-morbid cluster B personality disorder emerged as the only robust, unique predictor of future suicide attempts among depressed suicide ideators. Future research should continue to identify variables that predict transition from suicidal thoughts to suicide attempts, as such work will enhance clinical assessment of suicide risk as well as theoretical models of suicide. PMID:22575331

Relationships Between Future Orientation, Impulsive Sensation Seeking, and Risk Behavior Among Adjudicated Adolescents

PubMed Central

Robbins, Reuben N.; Bryan, Angela

2005-01-01

Because of high levels of risk behavior, adjudicated adolescents are at high risk for negative health outcomes such as nicotine and drug addiction and sexually transmitted diseases. The goal of this article is to examine relationships between future orientation and impulsive-sensation-seeking personality constructs to risk behaviors among 300 adjudicated adolescents. Significant relationships between impulsive sensation seeking and future orientation were found for several risk behaviors. Individuals with more positive future orientation were less likely to use marijuana, hard drugs, alcohol during sex, had fewer alcohol problems, had lower levels of alcohol frequency and quantity of use, and perceived greater risks associated with such behaviors. Higher impulsivity reliably predicted alcohol problems, alcohol use, condom use, and cigarette smoking. PMID:16429605

Fall risk: the clinical relevance of falls and how to integrate fall risk with fracture risk.

PubMed

Peeters, G; van Schoor, Natasja M; Lips, Paul

2009-12-01

In old age, 5-10% percent of all falls result in a fracture, and up to 90% of all fractures result from a fall. This article describes the link between fall risk and fracture risk in community-dwelling older persons. Which factors attribute to both the fall risk and the fracture risk? Which falls result in a fracture? Which tools are available to predict falls and fractures? Directions for the use of prediction tools in clinical practice are given. Challenges for future research include further validation of existing prediction tools and evaluation of the cost-effectiveness of treatment after screening.

Experimental evidence for adaptive personalities in a wild passerine bird

PubMed Central

Nicolaus, Marion; Tinbergen, Joost M.; Bouwman, Karen M.; Michler, Stephanie P. M.; Ubels, Richard; Both, Christiaan; Kempenaers, Bart; Dingemanse, Niels J.

2012-01-01

Individuals of the same species differ consistently in risky actions. Such ‘animal personality’ variation is intriguing because behavioural flexibility is often assumed to be the norm. Recent theory predicts that between-individual differences in propensity to take risks should evolve if individuals differ in future fitness expectations: individuals with high long-term fitness expectations (i.e. that have much to lose) should behave consistently more cautious than individuals with lower expectations. Consequently, any manipulation of future fitness expectations should result in within-individual changes in risky behaviour in the direction predicted by this adaptive theory. We tested this prediction and confirmed experimentally that individuals indeed adjust their ‘exploration behaviour’, a proxy for risk-taking behaviour, to their future fitness expectations. We show for wild great tits (Parus major) that individuals with experimentally decreased survival probability become faster explorers (i.e. increase risk-taking behaviour) compared to individuals with increased survival probability. We also show, using quantitative genetics approaches, that non-genetic effects (i.e. permanent environment effects) underpin adaptive personality variation in this species. This study thereby confirms a key prediction of adaptive personality theory based on life-history trade-offs, and implies that selection may indeed favour the evolution of personalities in situations where individuals differ in future fitness expectations. PMID:23097506

Predictive Validity of the HKT-R Risk Assessment Tool: Two and 5-Year Violent Recidivism in a Nationwide Sample of Dutch Forensic Psychiatric Patients.

PubMed

Bogaerts, Stefan; Spreen, Marinus; Ter Horst, Paul; Gerlsma, Coby

2018-06-01

This study has examined the predictive validity of the Historical Clinical Future [ Historisch Klinisch Toekomst] Revised risk assessment scheme in a cohort of 347 forensic psychiatric patients, which were discharged between 2004 and 2008 from any of 12 highly secure forensic centers in the Netherlands. Predictive validity was measured 2 and 5 years after release. Official reconviction data obtained from the Dutch Ministry of Security and Justice were used as outcome measures. Violent reoffending within 2 and 5 years after discharge was assessed. With regard to violent reoffending, results indicated that the predictive validity of the Historical domain was modest for 2 (area under the curve [AUC] = .75) and 5 (AUC = .74) years. The predictive validity of the Clinical domain was marginal for 2 (admission: AUC = .62; discharge: AUC = .63) and 5 (admission: AUC = .69; discharge: AUC = .62) years after release. The predictive validity of the Future domain was modest (AUC = .71) for 2 years and low for 5 (AUC = .58) years. The total score of the instrument was modest for 2 years (AUC = .78) and marginal for 5 (AUC = .68) years. Finally, the Final Risk Judgment was modest for 2 years (AUC = .78) and marginal for 5 (AUC = .63) years time at risk. It is concluded that this risk assessment instrument appears to be a satisfactory instrument for risk assessment.

Early warning model based on correlated networks in global crude oil markets

NASA Astrophysics Data System (ADS)

Yu, Jia-Wei; Xie, Wen-Jie; Jiang, Zhi-Qiang

2018-01-01

Applying network tools on predicting and warning the systemic risks provides a novel avenue to manage risks in financial markets. Here, we construct a series of global crude oil correlated networks based on the historical 57 oil prices covering a period from 1993 to 2012. Two systemic risk indicators are constructed based on the density and modularity of correlated networks. The local maximums of the risk indicators are found to have the ability to predict the trends of oil prices. In our sample periods, the indicator based on the network density sends five signals and the indicator based on the modularity index sends four signals. The four signals sent by both indicators are able to warn the drop of future oil prices and the signal only sent by the network density is followed by a huge rise of oil prices. Our results deepen the application of network measures on building early warning models of systemic risks and can be applied to predict the trends of future prices in financial markets.

Evaluation of Non-Laboratory and Laboratory Prediction Models for Current and Future Diabetes Mellitus: A Cross-Sectional and Retrospective Cohort Study

PubMed Central

Hahn, Seokyung; Moon, Min Kyong; Park, Kyong Soo; Cho, Young Min

2016-01-01

Background Various diabetes risk scores composed of non-laboratory parameters have been developed, but only a few studies performed cross-validation of these scores and a comparison with laboratory parameters. We evaluated the performance of diabetes risk scores composed of non-laboratory parameters, including a recently published Korean risk score (KRS), and compared them with laboratory parameters. Methods The data of 26,675 individuals who visited the Seoul National University Hospital Healthcare System Gangnam Center for a health screening program were reviewed for cross-sectional validation. The data of 3,029 individuals with a mean of 6.2 years of follow-up were reviewed for longitudinal validation. The KRS and 16 other risk scores were evaluated and compared with a laboratory prediction model developed by logistic regression analysis. Results For the screening of undiagnosed diabetes, the KRS exhibited a sensitivity of 81%, a specificity of 58%, and an area under the receiver operating characteristic curve (AROC) of 0.754. Other scores showed AROCs that ranged from 0.697 to 0.782. For the prediction of future diabetes, the KRS exhibited a sensitivity of 74%, a specificity of 54%, and an AROC of 0.696. Other scores had AROCs ranging from 0.630 to 0.721. The laboratory prediction model composed of fasting plasma glucose and hemoglobin A1c levels showed a significantly higher AROC (0.838, P < 0.001) than the KRS. The addition of the KRS to the laboratory prediction model increased the AROC (0.849, P = 0.016) without a significant improvement in the risk classification (net reclassification index: 4.6%, P = 0.264). Conclusions The non-laboratory risk scores, including KRS, are useful to estimate the risk of undiagnosed diabetes but are inferior to the laboratory parameters for predicting future diabetes. PMID:27214034

Predicting healthcare trajectories from medical records: A deep learning approach.

PubMed

Pham, Trang; Tran, Truyen; Phung, Dinh; Venkatesh, Svetha

2017-05-01

Personalized predictive medicine necessitates the modeling of patient illness and care processes, which inherently have long-term temporal dependencies. Healthcare observations, stored in electronic medical records are episodic and irregular in time. We introduce DeepCare, an end-to-end deep dynamic neural network that reads medical records, stores previous illness history, infers current illness states and predicts future medical outcomes. At the data level, DeepCare represents care episodes as vectors and models patient health state trajectories by the memory of historical records. Built on Long Short-Term Memory (LSTM), DeepCare introduces methods to handle irregularly timed events by moderating the forgetting and consolidation of memory. DeepCare also explicitly models medical interventions that change the course of illness and shape future medical risk. Moving up to the health state level, historical and present health states are then aggregated through multiscale temporal pooling, before passing through a neural network that estimates future outcomes. We demonstrate the efficacy of DeepCare for disease progression modeling, intervention recommendation, and future risk prediction. On two important cohorts with heavy social and economic burden - diabetes and mental health - the results show improved prediction accuracy. Copyright © 2017 Elsevier Inc. All rights reserved.

The development and validation of the Youth Actuarial Care Needs Assessment Tool for Non-Offenders (Y-ACNAT-NO).

PubMed

Assink, Mark; van der Put, Claudia E; Oort, Frans J; Stams, Geert Jan J M

2015-03-04

In The Netherlands, police officers not only come into contact with juvenile offenders, but also with a large number of juveniles who were involved in a criminal offense, but not in the role of a suspect (i.e., juvenile non-offenders). Until now, no valid and reliable instrument was available that can be used by Dutch police officers for estimating the risk for future care needs of juvenile non-offenders. In the present study, the Youth Actuarial Care Needs Assessment Tool for Non-Offenders (Y-ACNAT-NO) was developed for predicting the risk for future care needs that consisted of (1) a future supervision order as imposed by a juvenile court judge and (2) future worrisome incidents involving child abuse, domestic violence/strife, and/or sexual offensive behavior at the juvenile's living address (i.e., problems in the child-rearing environment). Police records of 3,200 juveniles were retrieved from the Dutch police registration system after which the sample was randomly split in a construction (n = 1,549) and validation sample (n = 1,651). The Y-ACNAT-NO was developed by performing an Exhaustive CHAID analysis using the construction sample. The predictive validity of the instrument was examined in the validation sample by calculating several performance indicators that assess discrimination and calibration. The CHAID output yielded an instrument that consisted of six variables and eleven different risk groups. The risk for future care needs ranged from 0.06 in the lowest risk group to 0.83 in the highest risk group. The AUC value in the validation sample was .764 (95% CI [.743, .784]) and Sander's calibration score indicated an average assessment error of 3.74% in risk estimates per risk category. The Y-ACNAT-NO is the first instrument that can be used by Dutch police officers for estimating the risk for future care needs of juvenile non-offenders. The predictive validity of the Y-ACNAT-NO in terms of discrimination and calibration was sufficient to justify its use as an initial screening instrument when a decision is needed about referring a juvenile for further assessment of care needs.

FutureTox II: In vitro Data and In Silico Models for Predictive Toxicology

PubMed Central

Knudsen, Thomas B.; Keller, Douglas A.; Sander, Miriam; Carney, Edward W.; Doerrer, Nancy G.; Eaton, David L.; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L.; Mendrick, Donna L.; Tice, Raymond R.; Watkins, Paul B.; Whelan, Maurice

2015-01-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. PMID:25628403

Mammographic density, breast cancer risk and risk prediction

PubMed Central

Vachon, Celine M; van Gils, Carla H; Sellers, Thomas A; Ghosh, Karthik; Pruthi, Sandhya; Brandt, Kathleen R; Pankratz, V Shane

2007-01-01

In this review, we examine the evidence for mammographic density as an independent risk factor for breast cancer, describe the risk prediction models that have incorporated density, and discuss the current and future implications of using mammographic density in clinical practice. Mammographic density is a consistent and strong risk factor for breast cancer in several populations and across age at mammogram. Recently, this risk factor has been added to existing breast cancer risk prediction models, increasing the discriminatory accuracy with its inclusion, albeit slightly. With validation, these models may replace the existing Gail model for clinical risk assessment. However, absolute risk estimates resulting from these improved models are still limited in their ability to characterize an individual's probability of developing cancer. Promising new measures of mammographic density, including volumetric density, which can be standardized using full-field digital mammography, will likely result in a stronger risk factor and improve accuracy of risk prediction models. PMID:18190724

Future-oriented emotions in the prediction of binge-drinking intention and expectation: the role of anticipated and anticipatory emotions.

PubMed

Carrera, Pilar; Caballero, Amparo; Muñoz, Dolores

2012-06-01

The Theory of Planned Behavior (TPB) offers a parsimonious explanation of purposive behavior, but in the study of healthy and risk behaviors its sufficiency may be questioned. Working with binge-drinking, a very common risk behavior in Spanish undergraduate students, we used two strategies for improving predictions from TPB: using behavioral intention (BI) and behavioral expectation (BE) as proximal antecedents of behaviors and adding as new predictors two future-oriented emotions (anticipated and anticipatory). Hierarchical regression analyses show that while anticipated emotions improved TPB explanations of BI, anticipatory emotions improved the explanations of BE. The present results show the influence of future emotions in the prediction of behavioral intention and behavioral expectation. © 2012 The Authors. Scandinavian Journal of Psychology © 2012 The Scandinavian Psychological Associations.

Climate change risk to forests in China associated with warming.

PubMed

Yin, Yunhe; Ma, Danyang; Wu, Shaohong

2018-01-11

Variations in forest net primary productivity (NPP) reflects the combined effects of key climate variables on ecosystem structure and function, especially on the carbon cycle. We performed risk analysis indicated by the magnitude of future negative anomalies in NPP in comparison with the natural interannual variability to investigate the impact of future climatic projections on forests in China. Results from the multi-model ensemble showed that climate change risk of decreases in forest NPP would be more significant in higher emission scenario in China. Under relatively low emission scenarios, the total area of risk was predicted to decline, while for RCP8.5, it was predicted to first decrease and then increase after the middle of 21st century. The rapid temperature increases predicted under the RCP8.5 scenario would be probably unfavorable for forest vegetation growth in the long term. High-level risk area was likely to increase except RCP2.6. The percentage area at high risk was predicted to increase from 5.39% (2021-2050) to 27.62% (2071-2099) under RCP8.5. Climate change risk to forests was mostly concentrated in southern subtropical and tropical regions, generally significant under high emission scenario of RCP8.5, which was mainly attributed to the intensified dryness in south China.

Enduring Risk? Old Criminal Records and Predictions of Future Criminal Involvement

ERIC Educational Resources Information Center

Kurlychek, Megan C.; Brame, Robert; Bushway, Shawn D.

2007-01-01

It is well accepted that criminal records impose collateral consequences on offenders. Such records affect access to public housing, student financial aid, welfare benefits, and voting rights. An axiom of these policies is that individuals with criminal records--even old criminal records--exhibit significantly higher risk of future criminal…

Intrapersonal positive future thinking predicts repeat suicide attempts in hospital-treated suicide attempters.

PubMed

O'Connor, Rory C; Smyth, Roger; Williams, J Mark G

2015-02-01

Although there is clear evidence that low levels of positive future thinking (anticipation of positive experiences in the future) and hopelessness are associated with suicide risk, the relationship between the content of positive future thinking and suicidal behavior has yet to be investigated. This is the first study to determine whether the positive future thinking-suicide attempt relationship varies as a function of the content of the thoughts and whether positive future thinking predicts suicide attempts over time. A total of 388 patients hospitalized following a suicide attempt completed a range of clinical and psychological measures (depression, hopelessness, suicidal ideation, suicidal intent and positive future thinking). Fifteen months later, a nationally linked database was used to determine who had been hospitalized again after a suicide attempt. During follow-up, 25.6% of linked participants were readmitted to hospital following a suicide attempt. In univariate logistic regression analyses, previous suicide attempts, suicidal ideation, hopelessness, and depression-as well as low levels of achievement, low levels of financial positive future thoughts, and high levels of intrapersonal (thoughts about the individual and no one else) positive future thoughts predicted repeat suicide attempts. However, only previous suicide attempts, suicidal ideation, and high levels of intrapersonal positive future thinking were significant predictors in multivariate analyses. Positive future thinking has predictive utility over time; however, the content of the thinking affects the direction and strength of the positive future thinking-suicidal behavior relationship. Future research is required to understand the mechanisms that link high levels of intrapersonal positive future thinking to suicide risk and how intrapersonal thinking should be targeted in treatment interventions. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Intrapersonal Positive Future Thinking Predicts Repeat Suicide Attempts in Hospital-Treated Suicide Attempters

PubMed Central

2014-01-01

Objective: Although there is clear evidence that low levels of positive future thinking (anticipation of positive experiences in the future) and hopelessness are associated with suicide risk, the relationship between the content of positive future thinking and suicidal behavior has yet to be investigated. This is the first study to determine whether the positive future thinking–suicide attempt relationship varies as a function of the content of the thoughts and whether positive future thinking predicts suicide attempts over time. Method: A total of 388 patients hospitalized following a suicide attempt completed a range of clinical and psychological measures (depression, hopelessness, suicidal ideation, suicidal intent and positive future thinking). Fifteen months later, a nationally linked database was used to determine who had been hospitalized again after a suicide attempt. Results: During follow-up, 25.6% of linked participants were readmitted to hospital following a suicide attempt. In univariate logistic regression analyses, previous suicide attempts, suicidal ideation, hopelessness, and depression—as well as low levels of achievement, low levels of financial positive future thoughts, and high levels of intrapersonal (thoughts about the individual and no one else) positive future thoughts predicted repeat suicide attempts. However, only previous suicide attempts, suicidal ideation, and high levels of intrapersonal positive future thinking were significant predictors in multivariate analyses. Discussion: Positive future thinking has predictive utility over time; however, the content of the thinking affects the direction and strength of the positive future thinking–suicidal behavior relationship. Future research is required to understand the mechanisms that link high levels of intrapersonal positive future thinking to suicide risk and how intrapersonal thinking should be targeted in treatment interventions. PMID:25181026

Predicting relapse risk in childhood acute lymphoblastic leukaemia.

PubMed

Teachey, David T; Hunger, Stephen P

2013-09-01

Intensive multi-agent chemotherapy regimens and the introduction of risk-stratified therapy have substantially improved cure rates for children with acute lymphoblastic leukaemia (ALL). Current risk allocation schemas are imperfect, as some children are classified as lower-risk and treated with less intensive therapy relapse, while others deemed higher-risk are probably over-treated. Most cooperative groups previously used morphological clearance of blasts in blood and marrow during the initial phases of chemotherapy as a primary factor for risk group allocation; however, this has largely been replaced by the detection of minimal residual disease (MRD). Other than age and white blood cell count (WBC) at presentation, many clinical variables previously used for risk group allocation are no longer prognostic, as MRD and the presence of sentinel genetic lesions are more reliable at predicting outcome. Currently, a number of sentinel genetic lesions are used by most cooperative groups for risk stratification; however, in the near future patients will probably be risk-stratified using genomic signatures and clustering algorithms, rather than individual genetic alterations. This review will describe the clinical, biological, and response-based features known to predict relapse risk in childhood ALL, including those currently used and those likely to be used in the near future to risk-stratify therapy. © 2013 John Wiley & Sons Ltd.

A test of the vulnerability model: temperament and temperament change as predictors of future mental disorders - the TRAILS study.

PubMed

Laceulle, Odilia M; Ormel, Johan; Vollebergh, Wilma A M; van Aken, Marcel A G; Nederhof, Esther

2014-03-01

This study aimed to test the vulnerability model of the relationship between temperament and mental disorders using a large sample of adolescents from the TRacking Adolescents Individual Lives' Survey (TRAILS). The vulnerability model argues that particular temperaments can place individuals at risk for the development of mental health problems. Importantly, the model may imply that not only baseline temperament predicts mental health problems prospectively, but additionally, that changes in temperament predict corresponding changes in risk for mental health problems. Data were used from 1195 TRAILS participants. Adolescent temperament was assessed both at age 11 and at age 16. Onset of mental disorders between age 16 and 19 was assessed at age 19, by means of the World Health Organization Composite International Diagnostic Interview (WHO CIDI). Results showed that temperament at age 11 predicted future mental disorders, thereby providing support for the vulnerability model. Moreover, temperament change predicted future mental disorders above and beyond the effect of basal temperament. For example, an increase in frustration increased the risk of mental disorders proportionally. This study confirms, and extends, the vulnerability model. Consequences of both temperament and temperament change were general (e.g., changes in frustration predicted both internalizing and externalizing disorders) as well as dimension specific (e.g., changes in fear predicted internalizing but not externalizing disorders). These findings confirm previous studies, which showed that mental disorders have both unique and shared underlying temperamental risk factors. © 2013 The Authors. Journal of Child Psychology and Psychiatry © 2013 Association for Child and Adolescent Mental Health.

Recent victimization increases risk for violence in justice-involved persons with mental illness.

PubMed

Sadeh, Naomi; Binder, Renée L; McNiel, Dale E

2014-04-01

A large body of research has examined relationships between distal experiences of victimization and the likelihood of engaging in violence later in life. Less is known about the influence of recent violent victimization on risk for violence perpetration. To our knowledge, this is the first study to examine prospectively whether recent victimization in adulthood increases the risk of future violence. Specifically, the present study assessed the incremental validity of recent violent victimization in the prediction of future violence in a sample of justice-involved adults with serious mental illness. The study examined (a) whether recent experiences of violent victimization (i.e., within 6 months of the baseline assessment) predicted a greater likelihood of perpetrating violence in the next year, and (b) whether inclusion of recent victimization enhanced the predictive validity of a model of violence risk in a sample of justice-involved adults with severe mental illness (N = 167). Hierarchical logistic regression analyses indicated that exposure to recent violent victimization at the baseline assessment predicted a greater likelihood of engaging in violent behavior during the year follow-up period. Additionally, recent exposure to violence at the baseline assessment continued to explain a significant amount of variance in a model of future violence perpetration above the variance accounted for by well-established violence risk factors. Taken together, the findings suggest that recent victimization is important to consider in understanding and evaluating risk of violence by persons with mental disorders who are involved in the criminal justice system. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Enteric disease episodes and the risk of acquiring a future sexually transmitted infection: a prediction model in Montreal residents.

PubMed

Caron, Melissa; Allard, Robert; Bédard, Lucie; Latreille, Jérôme; Buckeridge, David L

2016-11-01

The sexual transmission of enteric diseases poses an important public health challenge. We aimed to build a prediction model capable of identifying individuals with a reported enteric disease who could be at risk of acquiring future sexually transmitted infections (STIs). Passive surveillance data on Montreal residents with at least 1 enteric disease report was used to construct the prediction model. Cases were defined as all subjects with at least 1 STI report following their initial enteric disease episode. A final logistic regression prediction model was chosen using forward stepwise selection. The prediction model with the greatest validity included age, sex, residential location, number of STI episodes experienced prior to the first enteric disease episode, type of enteric disease acquired, and an interaction term between age and male sex. This model had an area under the curve of 0.77 and had acceptable calibration. A coordinated public health response to the sexual transmission of enteric diseases requires that a distinction be made between cases of enteric diseases transmitted through sexual activity from those transmitted through contaminated food or water. A prediction model can aid public health officials in identifying individuals who may have a higher risk of sexually acquiring a reportable disease. Once identified, these individuals could receive specialized intervention to prevent future infection. The information produced from a prediction model capable of identifying higher risk individuals can be used to guide efforts in investigating and controlling reported cases of enteric diseases and STIs. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Land use planning and wildfire: development policies influence future probability of housing loss

USGS Publications Warehouse

Syphard, Alexandra D.; Massada, Avi Bar; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

The role of lymphadenectomy in endometrial cancer: was the ASTEC trial doomed by design and are we destined to repeat that mistake?

PubMed

Naumann, R Wendel

2012-07-01

This study examines the design of previous and future trials of lymph node dissection in endometrial cancer. Data from previous trials were used to construct a decision analysis modeling the risk of lymphatic spread and the effects of treatment on patients with endometrial cancer. This model was then applied to previous trials as well as other future trial designs that might be used to address this subject. Comparing the predicted and actual results in the ASTEC trial, the model closely mimics the survival results with and without lymph node dissection for the low and high risk groups. The model suggests a survival difference of less than 2% between the experimental and control arms of the ASTEC trial under all circumstances. Sensitivity analyses reveal that these conclusions are robust. Future trial designs were also modeled with hysterectomy only, hysterectomy with radiation in intermediate risk patients, and staging with radiation only with node positive patients. Predicted outcomes for these approaches yield survival rates of 88%, 90%, and 93% in clinical stage I patients who have a risk of pelvic node involvement of approximately 7%. These estimates were 78%, 82%, and 89% in intermediate risk patients who have a risk of nodal spread of approximately 15%. This model accurately predicts the outcome of previous trials and demonstrates that even if lymph node dissection was therapeutic, these trials would have been negative due to study design. Furthermore, future trial designs that are being considered would need to be conducted in high-intermediate risk patients to detect any difference. Copyright © 2012 Elsevier Inc. All rights reserved.

Plant distributions in the southwestern United States; a scenario assessment of the modern-day and future distribution ranges of 166 Species

USGS Publications Warehouse

Thomas, Kathryn A.; Guertin, Patricia P.; Gass, Leila

2012-01-01

The authors developed spatial models of the predicted modern-day suitable habitat (SH) of 166 dominant and indicator plant species of the southwestern United States (herein referred to as the Southwest) and then conducted a coarse assessment of potential future changes in the distribution of their suitable habitat under three climate-change scenarios for two time periods. We used Maxent-based spatial modeling to predict the modern-day and future scenarios of SH for each species in an over 342-million-acre area encompassing all or parts of six states in the Southwest--Arizona, California, Colorado, Nevada, New Mexico, and Utah. Modern-day SH models were predicted by our using 26 annual and monthly average temperature and precipitation variables, averaged for the years 1971-2000. Future SH models were predicted for each species by our using six climate models based on application of the average of 16 General Circulation Models to Intergovernmental Panel on Climate Change emission scenarios B1, A1B, and A2 for two time periods, 2040 to 2069 and 2070 and 2100, referred to respectively as the 2050 and 2100 time periods. The assessment examined each species' vulnerability to loss of modern-day SH under future climate scenarios, potential to gain SH under future climate scenarios, and each species' estimated risk as a function of both vulnerability and potential gains. All 166 species were predicted to lose modern-day SH in the future climate change scenarios. In the 2050 time period, nearly 30 percent of the species lost 75 percent or more of their modern-day suitable habitat, 21 species gained more new SH than their modern-day SH, and 30 species gained less new SH than 25 percent of their modern-day SH. In the 2100 time period, nearly half of the species lost 75 percent or more of their modern-day SH, 28 species gained more new SH than their modern-day SH, and 34 gained less new SH than 25 percent of their modern-day SH. Using nine risk categories we found only two species were in the least risk category, while 20 species were in the highest risk category. The assessment showed that species respond independently to predicted climate change, suggesting that current plant assemblages may disassemble under predicted climate change scenarios. This report presents the results for each species in tables (Appendix A) and maps (14 for each species) in Appendix B.

Risk terrain modeling predicts child maltreatment.

PubMed

Daley, Dyann; Bachmann, Michael; Bachmann, Brittany A; Pedigo, Christian; Bui, Minh-Thuy; Coffman, Jamye

2016-12-01

As indicated by research on the long-term effects of adverse childhood experiences (ACEs), maltreatment has far-reaching consequences for affected children. Effective prevention measures have been elusive, partly due to difficulty in identifying vulnerable children before they are harmed. This study employs Risk Terrain Modeling (RTM), an analysis of the cumulative effect of environmental factors thought to be conducive for child maltreatment, to create a highly accurate prediction model for future substantiated child maltreatment cases in the City of Fort Worth, Texas. The model is superior to commonly used hotspot predictions and more beneficial in aiding prevention efforts in a number of ways: 1) it identifies the highest risk areas for future instances of child maltreatment with improved precision and accuracy; 2) it aids the prioritization of risk-mitigating efforts by informing about the relative importance of the most significant contributing risk factors; 3) since predictions are modeled as a function of easily obtainable data, practitioners do not have to undergo the difficult process of obtaining official child maltreatment data to apply it; 4) the inclusion of a multitude of environmental risk factors creates a more robust model with higher predictive validity; and, 5) the model does not rely on a retrospective examination of past instances of child maltreatment, but adapts predictions to changing environmental conditions. The present study introduces and examines the predictive power of this new tool to aid prevention efforts seeking to improve the safety, health, and wellbeing of vulnerable children. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Predicting running away in girls who are victims of commercial sexual exploitation.

PubMed

Hershberger, Alexandra R; Sanders, Jasmyn; Chick, Crisanna; Jessup, Megan; Hanlin, Hugh; Cyders, Melissa A

2018-05-01

Youth that are victims of commercial sexual exploitation of children (CSEC) have a host of clinical problems and often run away from home, residential care, and treatment, which complicates and limits treatment effectiveness. No research to date has attempted to predict running away in CSEC victims. The present study aimed to 1) characterize a clinically referred sample of girls who were victims of CSEC and compare them to other high-risk girls (i.e., girls who also have a history of trauma and running away, but deny CSEC); and 2) examine the utility of using the Youth Level of Service/Case Management Inventory (YLS/CMI) to predict future running away. Data were collected from de-identified charts of 80 girls (mean age = 15.38, SD = 1.3, 37.9% White, 52.5% CSEC victims) who were referred for psychological assessment by the Department of Child Services. Girls in the CSEC group were more likely to have experienced sexual abuse (χ 2  = 6.85, p = .009), an STI (χ 2  = 6.45, p = .01), a post-traumatic stress disorder diagnosis (χ 2  = 11.84, p = .001), and a substance use disorder diagnosis (χ 2  = 11.32, p = .001) than high-risk girls. Moderated regression results indicated that YLS/CMI scores significantly predicted future running away among the CSEC group (β = 0.23, SE = .06, p = .02), but not the high-risk group (β = -.008, SE = .11, p =.90). The YLS/CMI shows initial promise for predicting future running away in girls who are CSEC victims. Predicting running away can help identify those at risk for and prevent running away and improve treatment outcomes. We hope current findings stimulate future work in this area. Copyright © 2018 Elsevier Ltd. All rights reserved.

[From "deadly quartet" to "metabolic syndrome". An analysis of its clinical relevance].

PubMed

Vancheri, Federico; Burgio, Antonio; Dovico, Rossana

2007-03-01

The metabolic syndrome denotes a clustering of specific risk factors for both cardiovascular disease and type 2 diabetes, whose underlying pathophysiology is believed to include insulin resistance. It has been widely reported that the syndrome is a simple clinical tool to identify people at high long term risk of cardiovascular disease and diabetes. However, its clinical importance is under debate. There are substantial uncertainties about the clinical definition of the syndrome, as to whether the risk factors clustering indicates a single unifying disorder, whether the risk conferred by the condition as a whole is higher risk than its individual components, and whether its predictive value of future cardiovascular events or diabetes is greater than established predicting models such as the Framingham Risk Score and the Diabetes Risk Score. We undertook an extensive review of the literature. Our analysis indicates that current definitions of the syndrome are incomplete or ambiguous, more than one pathophysiological process underlies the syndrome, although the combination of insulin resistance and hyperinsulinemia are related to most cases; the risk associated with the syndrome is no greater than that explained by the presence of its components, and the syndrome is less effective in predicting the future development of cardiovascular events and diabetes than established predicting models. Although the syndrome has some importance in understanding the pathophysiology of cardiovascular and diabetes risk factors clustering, its use as a clinical syndrome is not justified by current data.

HSV-2 serology can be predictive of HIV epidemic potential and hidden sexual-risk behavior in the Middle East and North Africa

PubMed Central

Abu-Raddad, Laith J.; Schiffer, Joshua T.; Ashley, Rhoda; Mumtaz, Ghina; Alsallaq, Ramzi A.; Akala, Francisca Ayodeji; Semini, Iris; Riedner, Gabriele; Wilson, David

2013-01-01

Background HIV prevalence is low in the Middle East and North Africa (MENA) region, though the risk or potential for further spread in the future is not well understood. Behavioral surveys are limited in this region and when available have serious limitations in assessing the risk of HIV acquisition. We demonstrate the potential use of herpes simplex virus-2 (HSV-2) seroprevalence as a marker for HIV risk within MENA. Methods We designed a mathematical model to assess whether HSV-2 prevalence can be predictive of future HIV spread. We also conducted a systematic literature review of HSV-2 seroprevalence studies within MENA. Results We found that HSV-2 prevalence data are rather limited in this region. Prevalence is typically low among the general population but high in established core groups prone to sexually transmitted infections such as men who have sex with men and female sex workers. Our model predicts that if HSV-2 prevalence is low and stable, then the risk of future HIV epidemics is low. However, expanding or high HSV-2 prevalence (greater than about 20%), implies a risk for a considerable HIV epidemic. Based on available HSV-2 prevalence data, it is not likely that the general population in MENA is experiencing or will experience such a considerable HIV epidemic. Nevertheless, the risk for concentrated HIV epidemics among several high-risk core groups is high. Conclusions HSV-2 prevalence surveys provide a useful mechanism for identifying and corroborating populations at risk for HIV within MENA. HSV-2 serology offers an effective tool for probing hidden risk behaviors in a region where quality behavioral data are limited. PMID:21352788

The Shape of Ecosystem Management to Come: Anticipating Risks and Fostering Resilience

PubMed Central

Seidl, Rupert

2014-01-01

Global change is increasingly challenging the sustainable provisioning of ecosystem services to society. Addressing future uncertainty and risk has therefore become a central problem of ecosystem management. With risk management and resilience-based stewardship, two contrasting approaches have been proposed to address this issue. Whereas one is concentrated on anticipating and mitigating risks, the other is focused on fostering the ability to absorb perturbations and maintain desired properties. While they have hitherto been discussed largely separately in the literature, I here propose a unifying framework of anticipating risks and fostering resilience in ecosystem management. Anticipatory action is advocated when the predictability of risk is high and sufficient knowledge to address it is available. Conversely, in situations in which predictability and knowledge are limited, resilience-based measures are paramount. I conclude that, by adopting a purposeful combination of insights from risk and resilience research, we can make ecosystem services provisioning more robust to future uncertainty and change. PMID:25729079

Fire risk in San Diego County, California: A weighted Bayesian model approach

USGS Publications Warehouse

Kolden, Crystal A.; Weigel, Timothy J.

2007-01-01

Fire risk models are widely utilized to mitigate wildfire hazards, but models are often based on expert opinions of less understood fire-ignition and spread processes. In this study, we used an empirically derived weights-of-evidence model to assess what factors produce fire ignitions east of San Diego, California. We created and validated a dynamic model of fire-ignition risk based on land characteristics and existing fire-ignition history data, and predicted ignition risk for a future urbanization scenario. We then combined our empirical ignition-risk model with a fuzzy fire behavior-risk model developed by wildfire experts to create a hybrid model of overall fire risk. We found that roads influence fire ignitions and that future growth will increase risk in new rural development areas. We conclude that empirically derived risk models and hybrid models offer an alternative method to assess current and future fire risk based on management actions.

A prospective study of mandibular trabecular bone to predict fracture incidence in women: a low-cost screening tool in the dental clinic.

PubMed

Jonasson, Grethe; Sundh, Valter; Ahlqwist, Margareta; Hakeberg, Magnus; Björkelund, Cecilia; Lissner, Lauren

2011-10-01

Bone structure is the key to the understanding of fracture risk. The hypothesis tested in this prospective study is that dense mandibular trabeculation predicts low fracture risk, whereas sparse trabeculation is predictive of high fracture risk. Out of 731 women from the Prospective Population Study of Women in Gothenburg with dental examinations at baseline 1968, 222 had their first fracture in the follow-up period until 2006. Mandibular trabeculation was defined as dense, mixed dense plus sparse, and sparse based on panoramic radiographs from 1968 and/or 1980. Time to fracture was ascertained and used as the dependent variable in three Cox proportional hazards regression analyses. The first analysis covered 12 years of follow-up with self-reported endpoints; the second covered 26 years of follow-up with hospital verified endpoints; and the third combined the two follow-up periods, totaling 38 years. Mandibular trabeculation was the main independent variable predicting incident fractures, with age, physical activity, alcohol consumption and body mass index as covariates. The Kaplan-Meier curve indicated a graded association between trabecular density and fracture risk. During the whole period covered, the hazard ratio of future fracture for sparse trabeculation compared to mixed trabeculation was 2.9 (95% CI: 2.2-3.8, p<0.0001), and for dense versus mixed trabeculation was 0.21 (95% CI: 0.1-0.4, p<0.0001). The trabecular pattern was a highly significant predictor of future fracture risk. Our findings imply that dentists, using ordinary dental radiographs, can identify women at high risk for future fractures at 38-54 years of age, often long before the first fracture occurs. Copyright © 2011 Elsevier Inc. All rights reserved.

Biological risk factors for suicidal behaviors: a meta-analysis

PubMed Central

Chang, B P; Franklin, J C; Ribeiro, J D; Fox, K R; Bentley, K H; Kleiman, E M; Nock, M K

2016-01-01

Prior studies have proposed a wide range of potential biological risk factors for future suicidal behaviors. Although strong evidence exists for biological correlates of suicidal behaviors, it remains unclear if these correlates are also risk factors for suicidal behaviors. We performed a meta-analysis to integrate the existing literature on biological risk factors for suicidal behaviors and to determine their statistical significance. We conducted a systematic search of PubMed, PsycInfo and Google Scholar for studies that used a biological factor to predict either suicide attempt or death by suicide. Inclusion criteria included studies with at least one longitudinal analysis using a biological factor to predict either of these outcomes in any population through 2015. From an initial screen of 2541 studies we identified 94 cases. Random effects models were used for both meta-analyses and meta-regression. The combined effect of biological factors produced statistically significant but relatively weak prediction of suicide attempts (weighted mean odds ratio (wOR)=1.41; CI: 1.09–1.81) and suicide death (wOR=1.28; CI: 1.13–1.45). After accounting for publication bias, prediction was nonsignificant for both suicide attempts and suicide death. Only two factors remained significant after accounting for publication bias—cytokines (wOR=2.87; CI: 1.40–5.93) and low levels of fish oil nutrients (wOR=1.09; CI: 1.01–1.19). Our meta-analysis revealed that currently known biological factors are weak predictors of future suicidal behaviors. This conclusion should be interpreted within the context of the limitations of the existing literature, including long follow-up intervals and a lack of tests of interactions with other risk factors. Future studies addressing these limitations may more effectively test for potential biological risk factors. PMID:27622931

A threshold-free summary index of prediction accuracy for censored time to event data.

PubMed

Yuan, Yan; Zhou, Qian M; Li, Bingying; Cai, Hengrui; Chow, Eric J; Armstrong, Gregory T

2018-05-10

Prediction performance of a risk scoring system needs to be carefully assessed before its adoption in clinical practice. Clinical preventive care often uses risk scores to screen asymptomatic population. The primary clinical interest is to predict the risk of having an event by a prespecified future time t 0 . Accuracy measures such as positive predictive values have been recommended for evaluating the predictive performance. However, for commonly used continuous or ordinal risk score systems, these measures require a subjective cutoff threshold value that dichotomizes the risk scores. The need for a cutoff value created barriers for practitioners and researchers. In this paper, we propose a threshold-free summary index of positive predictive values that accommodates time-dependent event status and competing risks. We develop a nonparametric estimator and provide an inference procedure for comparing this summary measure between 2 risk scores for censored time to event data. We conduct a simulation study to examine the finite-sample performance of the proposed estimation and inference procedures. Lastly, we illustrate the use of this measure on a real data example, comparing 2 risk score systems for predicting heart failure in childhood cancer survivors. Copyright © 2018 John Wiley & Sons, Ltd.

Predicting stroke through genetic risk functions: the CHARGE Risk Score Project.

PubMed

Ibrahim-Verbaas, Carla A; Fornage, Myriam; Bis, Joshua C; Choi, Seung Hoan; Psaty, Bruce M; Meigs, James B; Rao, Madhu; Nalls, Mike; Fontes, Joao D; O'Donnell, Christopher J; Kathiresan, Sekar; Ehret, Georg B; Fox, Caroline S; Malik, Rainer; Dichgans, Martin; Schmidt, Helena; Lahti, Jari; Heckbert, Susan R; Lumley, Thomas; Rice, Kenneth; Rotter, Jerome I; Taylor, Kent D; Folsom, Aaron R; Boerwinkle, Eric; Rosamond, Wayne D; Shahar, Eyal; Gottesman, Rebecca F; Koudstaal, Peter J; Amin, Najaf; Wieberdink, Renske G; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G; Destefano, Anita L; Debette, Stephanie; Xue, Luting; Beiser, Alexa; Wolf, Philip A; Decarli, Charles; Ikram, M Arfan; Seshadri, Sudha; Mosley, Thomas H; Longstreth, W T; van Duijn, Cornelia M; Launer, Lenore J

2014-02-01

Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors. The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke. In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)). The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.

Two-Step Approach for the Prediction of Future Type 2 Diabetes Risk

PubMed Central

Abdul-Ghani, Muhammad A.; Abdul-Ghani, Tamam; Stern, Michael P.; Karavic, Jasmina; Tuomi, Tiinamaija; Bo, Insoma; DeFronzo, Ralph A.; Groop, Leif

2011-01-01

OBJECTIVE To develop a model for the prediction of type 2 diabetes mellitus (T2DM) risk on the basis of a multivariate logistic model and 1-h plasma glucose concentration (1-h PG). RESEARCH DESIGN AND METHODS The model was developed in a cohort of 1,562 nondiabetic subjects from the San Antonio Heart Study (SAHS) and validated in 2,395 nondiabetic subjects in the Botnia Study. A risk score on the basis of anthropometric parameters, plasma glucose and lipid profile, and blood pressure was computed for each subject. Subjects with a risk score above a certain cut point were considered to represent high-risk individuals, and their 1-h PG concentration during the oral glucose tolerance test was used to further refine their future T2DM risk. RESULTS We used the San Antonio Diabetes Prediction Model (SADPM) to generate the initial risk score. A risk-score value of 0.065 was found to be an optimal cut point for initial screening and selection of high-risk individuals. A 1-h PG concentration >140 mg/dL in high-risk individuals (whose risk score was >0.065) was the optimal cut point for identification of subjects at increased risk. The two cut points had 77.8, 77.4, and 44.8% (for the SAHS) and 75.8, 71.6, and 11.9% (for the Botnia Study) sensitivity, specificity, and positive predictive value, respectively, in the SAHS and Botnia Study. CONCLUSIONS A two-step model, based on the combination of the SADPM and 1-h PG, is a useful tool for the identification of high-risk Mexican-American and Caucasian individuals. PMID:21788628

Recent and projected future climatic suitability of North America for the Asian tiger mosquito Aedes albopictus.

PubMed

Ogden, Nicholas H; Milka, Radojević; Caminade, Cyril; Gachon, Philippe

2014-12-02

Since the 1980s, populations of the Asian tiger mosquito Aedes albopictus have become established in south-eastern, eastern and central United States, extending to approximately 40°N. Ae. albopictus is a vector of a wide range of human pathogens including dengue and chikungunya viruses, which are currently emerging in the Caribbean and Central America and posing a threat to North America. The risk of Ae. albopictus expanding its geographic range in North America under current and future climate was assessed using three climatic indicators of Ae. albopictus survival: overwintering conditions (OW), OW combined with annual air temperature (OWAT), and a linear index of precipitation and air temperature suitability expressed through a sigmoidal function (SIG). The capacity of these indicators to predict Ae. albopictus occurrence was evaluated using surveillance data from the United States. Projected future climatic suitability for Ae. albopictus was obtained using output of nine Regional Climate Model experiments (RCMs). OW and OWAT showed >90% specificity and sensitivity in predicting observed Ae. albopictus occurrence and also predicted moderate to high risk of Ae. albopictus invasion in Pacific coastal areas of the Unites States and Canada under current climate. SIG also well predicted observed Ae. albopictus occurrence (ROC area under the curve was 0.92) but predicted wider current climatic suitability in the north-central and north-eastern United States and south-eastern Canada. RCM output projected modest (circa 500 km) future northward range expansion of Ae. albopictus by the 2050s when using OW and OWAT indicators, but greater (600-1000 km) range expansion, particularly in eastern and central Canada, when using the SIG indicator. Variation in future possible distributions of Ae. albopictus was greater amongst the climatic indicators used than amongst the RCM experiments. Current Ae. albopictus distributions were well predicted by simple climatic indicators and northward range expansion was predicted for the future with climate change. However, current and future predicted geographic distributions of Ae. albopictus varied amongst the climatic indicators used. Further field studies are needed to assess which climatic indicator is the most accurate in predicting regions suitable for Ae. albopictus survival in North America.

New methods in hydrologic modeling and decision support for culvert flood risk under climate change

NASA Astrophysics Data System (ADS)

Rosner, A.; Letcher, B. H.; Vogel, R. M.; Rees, P. S.

2015-12-01

Assessing culvert flood vulnerability under climate change poses an unusual combination of challenges. We seek a robust method of planning for an uncertain future, and therefore must consider a wide range of plausible future conditions. Culverts in our case study area, northwestern Massachusetts, USA, are predominantly found in small, ungaged basins. The need to predict flows both at numerous sites and under numerous plausible climate conditions requires a statistical model with low data and computational requirements. We present a statistical streamflow model that is driven by precipitation and temperature, allowing us to predict flows without reliance on reference gages of observed flows. The hydrological analysis is used to determine each culvert's risk of failure under current conditions. We also explore the hydrological response to a range of plausible future climate conditions. These results are used to determine the tolerance of each culvert to future increases in precipitation. In a decision support context, current flood risk as well as tolerance to potential climate changes are used to provide a robust assessment and prioritization for culvert replacements.

Health-based risk adjustment: is inpatient and outpatient diagnostic information sufficient?

PubMed

Lamers, L M

Adequate risk adjustment is critical to the success of market-oriented health care reforms in many countries. Currently used risk adjusters based on demographic and diagnostic cost groups (DCGs) do not reflect expected costs accurately. This study examines the simultaneous predictive accuracy of inpatient and outpatient morbidity measures and prior costs. DCGs, pharmacy cost groups (PCGs), and prior year's costs improve the predictive accuracy of the demographic model substantially. DCGs and PCGs seem complementary in their ability to predict future costs. However, this study shows that the combination of DCGs and PCGs still leaves room for cream skimming.

Multi-component assessment of chronic obstructive pulmonary disease: an evaluation of the ADO and DOSE indices and the global obstructive lung disease categories in international primary care data sets

PubMed Central

Jones, Rupert C; Price, David; Chavannes, Niels H; Lee, Amanda J; Hyland, Michael E; Ställberg, Björn; Lisspers, Karin; Sundh, Josefin; van der Molen, Thys; Tsiligianni, Ioanna

2016-01-01

Suitable tools for assessing the severity of chronic obstructive pulmonary disease (COPD) include multi-component indices and the global initiative for chronic obstructive lung disease (GOLD) categories. The aim of this study was to evaluate the dyspnoea, obstruction, smoking, exacerbation (DOSE) and the age, dyspnoea, obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients. This was an observational cohort study comprising 5,114 primary care COPD patients across three databases from UK, Sweden and Holland. The associations of DOSE and ADO indices with (i) health status using the Clinical COPD Questionnaire (CCQ) and St George’s Respiratory Questionnaire (SGRQ) and COPD Assessment test (CAT) and with (ii) current and future exacerbations, admissions and mortality were assessed in GOLD categories and DOSE and ADO indices. DOSE and ADO indices were significant predictors of future exacerbations: incident rate ratio was 1.52 (95% confidence intervals 1.46–1.57) for DOSE, 1.16 (1.12–1.20) for ADO index and 1.50 (1.33–1.68) and 1.23 (1.10–1.39), respectively, for hospitalisations. Negative binomial regression showed that the DOSE index was a better predictor of future admissions than were its component items. The hazard ratios for mortality were generally higher for ADO index groups than for DOSE index groups. The GOLD categories produced widely differing assessments for future exacerbation risk or for hospitalisation depending on the methods used to calculate them. None of the assessment systems were excellent at predicting future risk in COPD; the DOSE index appears better than the ADO index for predicting many outcomes, but not mortality. The GOLD categories predict future risk inconsistently. The DOSE index and the GOLD categories using exacerbation frequency may be used to identify those at high risk for exacerbations and admissions. PMID:27053297

Multi-component assessment of chronic obstructive pulmonary disease: an evaluation of the ADO and DOSE indices and the global obstructive lung disease categories in international primary care data sets.

PubMed

Jones, Rupert C; Price, David; Chavannes, Niels H; Lee, Amanda J; Hyland, Michael E; Ställberg, Björn; Lisspers, Karin; Sundh, Josefin; van der Molen, Thys; Tsiligianni, Ioanna

2016-04-07

Suitable tools for assessing the severity of chronic obstructive pulmonary disease (COPD) include multi-component indices and the global initiative for chronic obstructive lung disease (GOLD) categories. The aim of this study was to evaluate the dyspnoea, obstruction, smoking, exacerbation (DOSE) and the age, dyspnoea, obstruction (ADO) indices and GOLD categories as measures of current health status and future outcomes in COPD patients. This was an observational cohort study comprising 5,114 primary care COPD patients across three databases from UK, Sweden and Holland. The associations of DOSE and ADO indices with (i) health status using the Clinical COPD Questionnaire (CCQ) and St George's Respiratory Questionnaire (SGRQ) and COPD Assessment test (CAT) and with (ii) current and future exacerbations, admissions and mortality were assessed in GOLD categories and DOSE and ADO indices. DOSE and ADO indices were significant predictors of future exacerbations: incident rate ratio was 1.52 (95% confidence intervals 1.46-1.57) for DOSE, 1.16 (1.12-1.20) for ADO index and 1.50 (1.33-1.68) and 1.23 (1.10-1.39), respectively, for hospitalisations. Negative binomial regression showed that the DOSE index was a better predictor of future admissions than were its component items. The hazard ratios for mortality were generally higher for ADO index groups than for DOSE index groups. The GOLD categories produced widely differing assessments for future exacerbation risk or for hospitalisation depending on the methods used to calculate them. None of the assessment systems were excellent at predicting future risk in COPD; the DOSE index appears better than the ADO index for predicting many outcomes, but not mortality. The GOLD categories predict future risk inconsistently. The DOSE index and the GOLD categories using exacerbation frequency may be used to identify those at high risk for exacerbations and admissions.

Caries Risk Assessment Item Importance

PubMed Central

Chaffee, B.W.; Featherstone, J.D.B.; Gansky, S.A.; Cheng, J.; Zhan, L.

2016-01-01

Caries risk assessment (CRA) is widely recommended for dental caries management. Little is known regarding how practitioners use individual CRA items to determine risk and which individual items independently predict clinical outcomes in children younger than 6 y. The objective of this study was to assess the relative importance of pediatric CRA items in dental providers’ decision making regarding patient risk and in association with clinically evident caries, cross-sectionally and longitudinally. CRA information was abstracted retrospectively from electronic patient records of children initially aged 6 to 72 mo at a university pediatric dentistry clinic (n = 3,810 baseline; n = 1,315 with follow-up). The 17-item CRA form included caries risk indicators, caries protective items, and clinical indicators. Conditional random forests classification trees were implemented to identify and assign variable importance to CRA items independently associated with baseline high-risk designation, baseline evident tooth decay, and follow-up evident decay. Thirteen individual CRA items, including all clinical indicators and all but 1 risk indicator, were independently and statistically significantly associated with student/resident providers’ caries risk designation. Provider-assigned baseline risk category was strongly associated with follow-up decay, which increased from low (20.4%) to moderate (30.6%) to high/extreme risk patients (68.7%). Of baseline CRA items, before adjustment, 12 were associated with baseline decay and 7 with decay at follow-up; however, in the conditional random forests models, only the clinical indicators (evident decay, dental plaque, and recent restoration placement) and 1 risk indicator (frequent snacking) were independently and statistically significantly associated with future disease, for which baseline evident decay was the strongest predictor. In this predominantly high-risk population under caries-preventive care, more individual CRA items were independently associated with providers’ risk determination than with future caries status. These university dental providers considered many items in decision making regarding patient risk, suggesting that, in turn, these comprehensive CRA forms could also aid individualized care, linking risk assessment to disease management. Knowledge Transfer Statement: Caries risk assessment (CRA) is widely recommended for patient-tailored, prevention-focused caries management. Studies show mixed predictive performance of pediatric CRA instruments, but little is known regarding how information captured in CRA forms guides clinical decision making. This study, in high-caries prevalence 6- to 72-mo-olds, demonstrates the following: 1) most items in a CRA instrument were independently associated with practitioners’ risk designations, 2) practitioners’ risk designations were significantly associated with future disease, and 3) of baseline measures associated with future caries, evident decay was the strongest independent indicator of future caries status. Although current disease (resulting from existing pathological and protective factor imbalance) may sufficiently predict future caries status in populations, other CRA items incorporated during risk categorization could aid practitioners to develop individualized intervention strategies against identified risk factors. PMID:27403458

Predictors of smoking lapse in a human laboratory paradigm.

PubMed

Roche, Daniel J O; Bujarski, Spencer; Moallem, Nathasha R; Guzman, Iris; Shapiro, Jenessa R; Ray, Lara A

2014-07-01

During a smoking quit attempt, a single smoking lapse is highly predictive of future relapse. While several risk factors for a smoking lapse have been identified during clinical trials, a laboratory model of lapse was until recently unavailable and, therefore, it is unclear whether these characteristics also convey risk for lapse in a laboratory environment. The primary study goal was to examine whether real-world risk factors of lapse are also predictive of smoking behavior in a laboratory model of smoking lapse. After overnight abstinence, 77 smokers completed the McKee smoking lapse task, in which they were presented with the choice of smoking or delaying in exchange for monetary reinforcement. Primary outcome measures were the latency to initiate smoking behavior and the number of cigarettes smoked during the lapse. Several baseline measures of smoking behavior, mood, and individual traits were examined as predictive factors. Craving to relieve the discomfort of withdrawal, withdrawal severity, and tension level were negatively predictive of latency to smoke. In contrast, average number of cigarettes smoked per day, withdrawal severity, level of nicotine dependence, craving for the positive effects of smoking, and craving to relieve the discomfort of withdrawal were positively predictive of number of cigarettes smoked. The results suggest that real-world risk factors for smoking lapse are also predictive of smoking behavior in a laboratory model of lapse. Future studies using the McKee lapse task should account for between subject differences in the unique factors that independently predict each outcome measure.

Comparison of the Fullerton Advanced Balance Scale, Mini-BESTest, and Berg Balance Scale to Predict Falls in Parkinson Disease.

PubMed

Schlenstedt, Christian; Brombacher, Stephanie; Hartwigsen, Gesa; Weisser, Burkhard; Möller, Bettina; Deuschl, Günther

2016-04-01

The correct identification of patients with Parkinson disease (PD) at risk for falling is important to initiate appropriate treatment early. This study compared the Fullerton Advanced Balance (FAB) scale with the Mini-Balance Evaluation Systems Test (Mini-BESTest) and Berg Balance Scale (BBS) to identify individuals with PD at risk for falls and to analyze which of the items of the scales best predict future falls. This was a prospective study to assess predictive criterion-related validity. The study was conducted at a university hospital in an urban community. Eighty-five patients with idiopathic PD (Hoehn and Yahr stages: 1-4) participated in the study. Measures were number of falls (assessed prospectively over 6 months), FAB scale, Mini-BESTest, BBS, and Unified Parkinson's Disease Rating Scale. The FAB scale, Mini-BESTest, and BBS showed similar accuracy to predict future falls, with values for area under the curve (AUC) of the receiver operating characteristic (ROC) curve of 0.68, 0.65, and 0.69, respectively. A model combining the items "tandem stance," "rise to toes," "one-leg stance," "compensatory stepping backward," "turning," and "placing alternate foot on stool" had an AUC of 0.84 of the ROC curve. There was a dropout rate of 19/85 participants. The FAB scale, Mini-BESTest, and BBS provide moderate capacity to predict "fallers" (people with one or more falls) from "nonfallers." Only some items of the 3 scales contribute to the detection of future falls. Clinicians should particularly focus on the item "tandem stance" along with the items "one-leg stance," "rise to toes," "compensatory stepping backward," "turning 360°," and "placing foot on stool" when analyzing postural control deficits related to fall risk. Future research should analyze whether balance training including the aforementioned items is effective in reducing fall risk. © 2016 American Physical Therapy Association.

Stress and anger as contextual factors and preexisting cognitive schemas: predicting parental child maltreatment risk.

PubMed

Rodriguez, Christina M; Richardson, Michael J

2007-11-01

Progress in the child maltreatment field depends on refinements in leading models. This study examines aspects of social information processing theory (Milner, 2000) in predicting physical maltreatment risk in a community sample. Consistent with this theory, selected preexisting schema (external locus-of-control orientation, inappropriate developmental expectations, low empathic perspective-taking ability, and low perceived attachment relationship to child) were expected to predict child abuse risk beyond contextual factors (parenting stress and anger expression). Based on 115 parents' self-report, results from this study support cognitive factors that predict abuse risk (with locus of control, perceived attachment, or empathy predicting different abuse risk measures, but not developmental expectations), although the broad contextual factors involving negative affectivity and stress were consistent predictors across abuse risk markers. Findings are discussed with regard to implications for future model evaluations, with indications the model may apply to other forms of maltreatment, such as psychological maltreatment or neglect.

The Relationship of Baseline Prostate Specific Antigen and Risk of Future Prostate Cancer and Its Variance by Race.

PubMed

Verges, Daniel P; Dani, Hasan; Sterling, William A; Weedon, Jeremy; Atallah, William; Mehta, Komal; Schreiber, David; Weiss, Jeffrey P; Karanikolas, Nicholas T

2017-01-01

Several studies suggest that a baseline prostate specific antigen (PSA) measured in young men predicts future risk of prostate cancer. Considering recent recommendations against PSA screening, high-risk populations (e.g. black men, men with a high baseline PSA) may be particularly vulnerable in the coming years. Thus, we investigated the relationship between baseline PSA and future prostate cancer in a black majority-minority urban population. A retrospective analysis was performed of the prostate biopsy database (n = 994) at the Brooklyn Veterans Affairs Hospital. These men were referred to urology clinic for elevated PSA and biopsied between 2007 and 2014. Multivariate logistic regression was used to predict positive prostate biopsy from log-transformed baseline PSA, race (black, white, or other), and several other variables. The majority of men identified as black (50.2%). Median age at time of baseline PSA and biopsy was 58.6 and 64.8, respectively. Median baseline PSA was similar among black men and white men (2.70 vs 2.91 for black men vs white men, p = 0.232). Even so, black men were more likely than white men to be diagnosed with prostate cancer (OR 1.62, p < 0.0001). Black men less than age 70 were at particularly greater risk than their white counterparts. Baseline PSA was not a statistically significant predictor of future prostate cancer (p = 0.101). Black men were more likely to be diagnosed with prostate cancer than were white men, despite comparable baseline PSA. In our pre-screened population at the urology clinic, a retrospective examination of baseline PSA did not predict future prostate cancer. Copyright © 2016 National Medical Association. Published by Elsevier Inc. All rights reserved.

Early Identification of Children at Risk for Academic Difficulties Using Standardized Assessment: Stability and Predictive Validity of Preschool Math and Language Scores

ERIC Educational Resources Information Center

Frans, Niek; Post, Wendy J.; Huisman, Mark; Oenema-Mostert, Ineke C. E.; Keegstra, Anne L.; Minnaert, Alexander E. M. G.

2017-01-01

Despite the claim by several researchers that variability in performance may complicate the identification of "at-risk" children, variability in the academic performance of young children remains an undervalued area of research. The goal of this study is to examine the predictive validity for future scores and the score stability of two…

Forecasting the future risk of Barmah Forest virus disease under climate change scenarios in Queensland, Australia.

PubMed

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

2013-01-01

Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000-2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland.

Predicting the Future Impact of Droughts on Ungulate Populations in Arid and Semi-Arid Environments

PubMed Central

Duncan, Clare; Chauvenet, Aliénor L. M.; McRae, Louise M.; Pettorelli, Nathalie

2012-01-01

Droughts can have a severe impact on the dynamics of animal populations, particularly in semi-arid and arid environments where herbivore populations are strongly limited by resource availability. Increased drought intensity under projected climate change scenarios can be expected to reduce the viability of such populations, yet this impact has seldom been quantified. In this study, we aim to fill this gap and assess how the predicted worsening of droughts over the 21st century is likely to impact the population dynamics of twelve ungulate species occurring in arid and semi-arid habitats. Our results provide support to the hypotheses that more sedentary, grazing and mixed feeding species will be put at high risk from future increases in drought intensity, suggesting that management intervention under these conditions should be targeted towards species possessing these traits. Predictive population models for all sedentary, grazing or mixed feeding species in our study show that their probability of extinction dramatically increases under future emissions scenarios, and that this extinction risk is greater for smaller populations than larger ones. Our study highlights the importance of quantifying the current and future impacts of increasing extreme natural events on populations and species in order to improve our ability to mitigate predicted biodiversity loss under climate change. PMID:23284700

FutureTox II: in vitro data and in silico models for predictive toxicology.

PubMed

Knudsen, Thomas B; Keller, Douglas A; Sander, Miriam; Carney, Edward W; Doerrer, Nancy G; Eaton, David L; Fitzpatrick, Suzanne Compton; Hastings, Kenneth L; Mendrick, Donna L; Tice, Raymond R; Watkins, Paul B; Whelan, Maurice

2015-02-01

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Land Use Planning and Wildfire: Development Policies Influence Future Probability of Housing Loss

PubMed Central

Syphard, Alexandra D.; Bar Massada, Avi; Butsic, Van; Keeley, Jon E.

2013-01-01

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction. PMID:23977120

Mammographic density and breast cancer risk: current understanding and future prospects

PubMed Central

2011-01-01

Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making. PMID:22114898

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions.

PubMed

Mosedale, Jonathan R; Wilson, Robert J; Maclean, Ilya M D

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions.

Climate Change and Crop Exposure to Adverse Weather: Changes to Frost Risk and Grapevine Flowering Conditions

PubMed Central

Mosedale, Jonathan R.; Wilson, Robert J.; Maclean, Ilya M. D.

2015-01-01

The cultivation of grapevines in the UK and many other cool climate regions is expected to benefit from the higher growing season temperatures predicted under future climate scenarios. Yet the effects of climate change on the risk of adverse weather conditions or events at key stages of crop development are not always captured by aggregated measures of seasonal or yearly climates, or by downscaling techniques that assume climate variability will remain unchanged under future scenarios. Using fine resolution projections of future climate scenarios for south-west England and grapevine phenology models we explore how risks to cool-climate vineyard harvests vary under future climate conditions. Results indicate that the risk of adverse conditions during flowering declines under all future climate scenarios. In contrast, the risk of late spring frosts increases under many future climate projections due to advancement in the timing of budbreak. Estimates of frost risk, however, were highly sensitive to the choice of phenology model, and future frost exposure declined when budbreak was calculated using models that included a winter chill requirement for dormancy break. The lack of robust phenological models is a major source of uncertainty concerning the impacts of future climate change on the development of cool-climate viticulture in historically marginal climatic regions. PMID:26496127

Risk-Based Questionnaires Fail to Detect Adolescent Iron Deficiency and Anemia.

PubMed

Sekhar, Deepa L; Murray-Kolb, Laura E; Schaefer, Eric W; Paul, Ian M

2017-08-01

To evaluate the predictive ability of screening questionnaires to identify adolescent women at high-risk for iron deficiency or iron deficiency anemia who warrant objective laboratory testing. Cross-sectional study of 96 female individuals 12-21 years old seen at an academic medical center. Participants completed an iron deficiency risk assessment questionnaire including the 4 Bright Futures Adolescent Previsit Questionnaire anemia questions, along with depression, attention, food insecurity, and daytime sleepiness screens. Multiple linear regression controlling for age, race, and hormonal contraception use compared the predictive ability of 2 models for adolescent iron deficiency (defined as ferritin <12 mcg/L) and anemia (hemoglobin <12 g/dL). Model 1, the Bright Futures questions, was compared with model 2, which included the 4 aforementioned screens and body mass index percentile. Among participants, 18% (17/96) had iron deficiency and 5% (5/96) had iron deficiency anemia. Model 1 (Bright Futures) poorly predicted ferritin and hemoglobin values (R 2  = 0.03 and 0.08, respectively). Model 2 demonstrated similarly poor predictive ability (R 2  = 0.05 and 0.06, respectively). Mean differences for depressive symptoms (0.3, 95% CI -0.2, 0.8), attention difficulty (-0.1, 95% CI -0.5, 0.4), food insecurity (0.04, 95% CI -0.5, 0.6), daytime sleepiness (0.1, 95% CI -0.1, 0.3), and body mass index percentile (-0.04, 95% CI -0.3, 0.2) were not significantly associated with ferritin in model 2. Mean differences for hemoglobin were also nonsignificant. Risk-based surveys poorly predict objective measures of iron status using ferritin and hemoglobin. Next steps are to establish the optimal timing for objective assessment of adolescent iron deficiency and anemia. Copyright © 2017 Elsevier Inc. All rights reserved.

Temperament and Parenting during the First Year of Life Predict Future Child Conduct Problems

PubMed Central

Lahey, Benjamin B.; Van Hulle, Carol A.; Keenan, Kate; Rathouz, Paul J.; D’Onofrio, Brian M.; Rodgers, Joseph Lee; Waldman, Irwin D.

2010-01-01

Predictive associations between parenting and temperament during the first year of life and child conduct problems were assessed longitudinally in 1,863 offspring of a representative sample of women. Maternal ratings of infant fussiness, activity level, predictability, and positive affect each independently predicted maternal ratings of conduct problems during ages 4–13 years. Furthermore, a significant interaction indicated that infants who were both low in fussiness and high in predictability were at very low risk for future conduct problems. Fussiness was a stronger predictor of conduct problems in boys whereas fearfulness was a stronger predictor in girls. Conduct problems also were robustly predicted by low levels of early mother-report cognitive stimulation. Interviewer-rated maternal responsiveness was a robust predictor of conduct problems, but only among infants low in fearfulness. Spanking during infancy predicted slightly more severe conduct problems, but the prediction was moderated by infant fussiness and positive affect. Thus, individual differences in risk for mother-rated conduct problems across childhood are already partly evident in maternal ratings of temperament during the first year of life and are predicted by early parenting and parenting-by-temperament interactions. PMID:18568397

Sensitivity and specificity of a brief personality screening instrument in predicting future substance use, emotional, and behavioral problems: 18-month predictive validity of the Substance Use Risk Profile Scale.

PubMed

Castellanos-Ryan, Natalie; O'Leary-Barrett, Maeve; Sully, Laura; Conrod, Patricia

2013-01-01

This study assessed the validity, sensitivity, and specificity of the Substance Use Risk Profile Scale (SURPS), a measure of personality risk factors for substance use and other behavioral problems in adolescence. The concurrent and predictive validity of the SURPS was tested in a sample of 1,162 adolescents (mean age: 13.7 years) using linear and logistic regressions, while its sensitivity and specificity were examined using the receiver operating characteristics curve analyses. Concurrent and predictive validity tests showed that all 4 brief scales-hopelessness (H), anxiety sensitivity (AS), impulsivity (IMP), and sensation seeking (SS)-were related, in theoretically expected ways, to measures of substance use and other behavioral and emotional problems. Results also showed that when using the 4 SURPS subscales to identify adolescents "at risk," one can identify a high number of those who developed problems (high sensitivity scores ranging from 72 to 91%). And, as predicted, because each scale is related to specific substance and mental health problems, good specificity was obtained when using the individual personality subscales (e.g., most adolescents identified at high risk by the IMP scale developed conduct or drug use problems within the next 18 months [a high specificity score of 70 to 80%]). The SURPS is a valuable tool for identifying adolescents at high risk for substance misuse and other emotional and behavioral problems. Implications of findings for the use of this measure in future research and prevention interventions are discussed. Copyright © 2012 by the Research Society on Alcoholism.

Examining Overgeneral Autobiographical Memory as a Risk Factor for Adolescent Depression

ERIC Educational Resources Information Center

Rawal, Adhip; Rice, Frances

2012-01-01

Objective: Identifying risk factors for adolescent depression is an important research aim. Overgeneral autobiographical memory (OGM) is a feature of adolescent depression and a candidate cognitive risk factor for future depression. However, no study has ascertained whether OGM predicts the onset of adolescent depressive disorder. OGM was…

Scientific reporting is suboptimal for aspects that characterize genetic risk prediction studies: a review of published articles based on the Genetic RIsk Prediction Studies statement.

PubMed

Iglesias, Adriana I; Mihaescu, Raluca; Ioannidis, John P A; Khoury, Muin J; Little, Julian; van Duijn, Cornelia M; Janssens, A Cecile J W

2014-05-01

Our main objective was to raise awareness of the areas that need improvements in the reporting of genetic risk prediction articles for future publications, based on the Genetic RIsk Prediction Studies (GRIPS) statement. We evaluated studies that developed or validated a prediction model based on multiple DNA variants, using empirical data, and were published in 2010. A data extraction form based on the 25 items of the GRIPS statement was created and piloted. Forty-two studies met our inclusion criteria. Overall, more than half of the evaluated items (34 of 62) were reported in at least 85% of included articles. Seventy-seven percentage of the articles were identified as genetic risk prediction studies through title assessment, but only 31% used the keywords recommended by GRIPS in the title or abstract. Seventy-four percentage mentioned which allele was the risk variant. Overall, only 10% of the articles reported all essential items needed to perform external validation of the risk model. Completeness of reporting in genetic risk prediction studies is adequate for general elements of study design but is suboptimal for several aspects that characterize genetic risk prediction studies such as description of the model construction. Improvements in the transparency of reporting of these aspects would facilitate the identification, replication, and application of genetic risk prediction models. Copyright © 2014 Elsevier Inc. All rights reserved.

Probability of criminal acts of violence: a test of jury predictive accuracy.

PubMed

Reidy, Thomas J; Sorensen, Jon R; Cunningham, Mark D

2013-01-01

The ability of capital juries to accurately predict future prison violence at the sentencing phase of aggravated murder trials was examined through retrospective review of the disciplinary records of 115 male inmates sentenced to either life (n = 65) or death (n = 50) in Oregon from 1985 through 2008, with a mean post-conviction time at risk of 15.3 years. Violent prison behavior was completely unrelated to predictions made by capital jurors, with bidirectional accuracy simply reflecting the base rate of assaultive misconduct in the group. Rejection of the special issue predicting future violence enjoyed 90% accuracy. Conversely, predictions that future violence was probable had 90% error rates. More than 90% of the assaultive rule violations committed by these offenders resulted in no harm or only minor injuries. Copyright © 2013 John Wiley & Sons, Ltd.

Predicting stroke through genetic risk functions: The CHARGE risk score project

PubMed Central

Ibrahim-Verbaas, Carla A; Fornage, Myriam; Bis, Joshua C; Choi, Seung Hoan; Psaty, Bruce M; Meigs, James B; Rao, Madhu; Nalls, Mike; Fontes, Joao D; O’Donnell, Christopher J.; Kathiresan, Sekar; Ehret, Georg B.; Fox, Caroline S; Malik, Rainer; Dichgans, Martin; Schmidt, Helena; Lahti, Jari; Heckbert, Susan R; Lumley, Thomas; Rice, Kenneth; Rotter, Jerome I; Taylor, Kent D; Folsom, Aaron R; Boerwinkle, Eric; Rosamond, Wayne D; Shahar, Eyal; Gottesman, Rebecca F.; Koudstaal, Peter J; Amin, Najaf; Wieberdink, Renske G.; Dehghan, Abbas; Hofman, Albert; Uitterlinden, André G; DeStefano, Anita L.; Debette, Stephanie; Xue, Luting; Beiser, Alexa; Wolf, Philip A.; DeCarli, Charles; Ikram, M. Arfan; Seshadri, Sudha; Mosley, Thomas H; Longstreth, WT; van Duijn, Cornelia M; Launer, Lenore J

2014-01-01

Background and Purpose Beyond the Framingham Stroke Risk Score (FSRS), prediction of future stroke may improve with a genetic risk score (GRS) based on Single nucleotide polymorphisms (SNPs) associated with stroke and its risk factors. Methods The study includes four population-based cohorts with 2,047 first incident strokes from 22,720 initially stroke-free European origin participants aged 55 years and older, who were followed for up to 20 years. GRS were constructed with 324 SNPs implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with Area under the curve (AUC) statistics comparing the GRS to age sex, and FSRS models, and with reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke (IS). Results In the meta-analysis, adding the GRS to the FSRS, age and sex model resulted in a significant improvement in discrimination (All stroke: Δjoint AUC =0.016, p-value=2.3*10-6; IS: Δ joint AUC =0.021, p-value=3.7*10−7), although the overall AUC remained low. In all studies there was a highly significantly improved net reclassification index (p-values <10−4). Conclusions The SNPs associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared to the classical epidemiological risk factors for stroke. PMID:24436238

Oil prices and long-run risk

NASA Astrophysics Data System (ADS)

Ready, Robert Clayton

I show that relative levels of aggregate consumption and personal oil consumption provide an excellent proxy for oil prices, and that high oil prices predict low future aggregate consumption growth. Motivated by these facts, I add an oil consumption good to the long-run risk model of Bansal and Yaron [2004] to study the asset pricing implications of observed changes in the dynamic interaction of consumption and oil prices. Empirically I observe that, compared to the first half of my 1987--2010 sample, oil consumption growth in the last 10 years is unresponsive to levels of oil prices, creating an decrease in the mean-reversion of oil prices, and an increase in the persistence of oil price shocks. The model implies that the change in the dynamics of oil consumption generates increased systematic risk from oil price shocks due to their increased persistence. However, persistent oil prices also act as a counterweight for shocks to expected consumption growth, with high expected growth creating high expectations of future oil prices which in turn slow down growth. The combined effect is to reduce overall consumption risk and lower the equity premium. The model also predicts that these changes affect the riskiness of of oil futures contracts, and combine to create a hump shaped term structure of oil futures, consistent with recent data.

Comparison between Frailty Index of Deficit Accumulation and Phenotypic Model to Predict Risk of Falls: Data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) Hamilton Cohort

PubMed Central

Thabane, Lehana; Ioannidis, George; Kennedy, Courtney; Papaioannou, Alexandra

2015-01-01

Objectives To compare the predictive accuracy of the frailty index (FI) of deficit accumulation and the phenotypic frailty (PF) model in predicting risks of future falls, fractures and death in women aged ≥55 years. Methods Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort (n = 3,985), we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1) investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20%) of the FI and PF; (2) trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail) which were defined by the PF; (3) categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures. Results The FI and PF agreed with each other at a good level of consensus (correlation coefficients ≥ 0.56) in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs) for falls (AUCs ≥ 0.68) and death (AUCs ≥ 0.79), and c-indices for fractures (c-indices ≥ 0.69) respectively. Conclusions The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings. PMID:25764521

Comparison between frailty index of deficit accumulation and phenotypic model to predict risk of falls: data from the global longitudinal study of osteoporosis in women (GLOW) Hamilton cohort.

PubMed

Li, Guowei; Thabane, Lehana; Ioannidis, George; Kennedy, Courtney; Papaioannou, Alexandra; Adachi, Jonathan D

2015-01-01

To compare the predictive accuracy of the frailty index (FI) of deficit accumulation and the phenotypic frailty (PF) model in predicting risks of future falls, fractures and death in women aged ≥55 years. Based on the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort (n = 3,985), we compared the predictive accuracy of the FI and PF in risks of falls, fractures and death using three strategies: (1) investigated the relationship with adverse health outcomes by increasing per one-fifth (i.e., 20%) of the FI and PF; (2) trichotomized the FI based on the overlap in the density distribution of the FI by the three groups (robust, pre-frail and frail) which were defined by the PF; (3) categorized the women according to a predicted probability function of falls during the third year of follow-up predicted by the FI. Logistic regression models were used for falls and death, while survival analyses were conducted for fractures. The FI and PF agreed with each other at a good level of consensus (correlation coefficients ≥ 0.56) in all the three strategies. Both the FI and PF approaches predicted adverse health outcomes significantly. The FI quantified the risks of future falls, fractures and death more precisely than the PF. Both the FI and PF discriminated risks of adverse outcomes in multivariable models with acceptable and comparable area under the curve (AUCs) for falls (AUCs ≥ 0.68) and death (AUCs ≥ 0.79), and c-indices for fractures (c-indices ≥ 0.69) respectively. The FI is comparable with the PF in predicting risks of adverse health outcomes. These findings may indicate the flexibility in the choice of frailty model for the elderly in the population-based settings.

The predictive validity of the HERO Scorecard in determining future health care cost and risk trends.

PubMed

Goetzel, Ron Z; Henke, Rachel Mosher; Benevent, Richele; Tabrizi, Maryam J; Kent, Karen B; Smith, Kristyn J; Roemer, Enid Chung; Grossmeier, Jessica; Mason, Shawn T; Gold, Daniel B; Noeldner, Steven P; Anderson, David R

2014-02-01

To determine the ability of the Health Enhancement Research Organization (HERO) Scorecard to predict changes in health care expenditures. Individual employee health care insurance claims data for 33 organizations completing the HERO Scorecard from 2009 to 2011 were linked to employer responses to the Scorecard. Organizations were dichotomized into "high" versus "low" scoring groups and health care cost trends were compared. A secondary analysis examined the tool's ability to predict health risk trends. "High" scorers experienced significant reductions in inflation-adjusted health care costs (averaging an annual trend of -1.6% over 3 years) compared with "low" scorers whose cost trend remained stable. The risk analysis was inconclusive because of the small number of employers scoring "low." The HERO Scorecard predicts health care cost trends among employers. More research is needed to determine how well it predicts health risk trends for employees.

Predicting Coronary Artery Aneurysms in Kawasaki Disease at a North American Center: An Assessment of Baseline z Scores.

PubMed

Son, Mary Beth F; Gauvreau, Kimberlee; Kim, Susan; Tang, Alexander; Dedeoglu, Fatma; Fulton, David R; Lo, Mindy S; Baker, Annette L; Sundel, Robert P; Newburger, Jane W

2017-05-31

Accurate risk prediction of coronary artery aneurysms (CAAs) in North American children with Kawasaki disease remains a clinical challenge. We sought to determine the predictive utility of baseline coronary dimensions adjusted for body surface area ( z scores) for future CAAs in Kawasaki disease and explored the extent to which addition of established Japanese risk scores to baseline coronary artery z scores improved discrimination for CAA development. We explored the relationships of CAA with baseline z scores; with Kobayashi, Sano, Egami, and Harada risk scores; and with the combination of baseline z scores and risk scores. We defined CAA as a maximum z score (zMax) ≥2.5 of the left anterior descending or right coronary artery at 4 to 8 weeks of illness. Of 261 patients, 77 patients (29%) had a baseline zMax ≥2.0. CAAs occurred in 15 patients (6%). CAAs were strongly associated with baseline zMax ≥2.0 versus <2.0 (12 [16%] versus 3 [2%], respectively, P <0.001). Baseline zMax ≥2.0 had a C statistic of 0.77, good sensitivity (80%), and excellent negative predictive value (98%). None of the risk scores alone had adequate discrimination. When high-risk status per the Japanese risk scores was added to models containing baseline zMax ≥2.0, none were significantly better than baseline zMax ≥2.0 alone. In a North American center, baseline zMax ≥2.0 in children with Kawasaki disease demonstrated high predictive utility for later development of CAA. Future studies should validate the utility of our findings. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.

Neuroprediction, Violence, and the Law: Setting the Stage.

PubMed

Nadelhoffer, Thomas; Bibas, Stephanos; Grafton, Scott; Kiehl, Kent A; Mansfield, Andrew; Sinnott-Armstrong, Walter; Gazzaniga, Michael

2012-04-01

In this paper, our goal is to (a) survey some of the legal contexts within which violence risk assessment already plays a prominent role, (b) explore whether developments in neuroscience could potentially be used to improve our ability to predict violence, and (c) discuss whether neuropredictive models of violence create any unique legal or moral problems above and beyond the well worn problems already associated with prediction more generally. In "Violence Risk Assessment and the Law", we briefly examine the role currently played by predictions of violence in three high stakes legal contexts: capital sentencing ("Violence Risk Assessment and Capital Sentencing"), civil commitment hearings ("Violence Risk Assessment and Civil Commitment"), and "sexual predator" statutes ("Violence Risk Assessment and Sexual Predator Statutes"). In "Clinical vs. Actuarial Violence Risk Assessment", we briefly examine the distinction between traditional clinical methods of predicting violence and more recently developed actuarial methods, exemplified by the Classification of Violence Risk (COVR) software created by John Monahan and colleagues as part of the MacArthur Study of Mental Disorder and Violence [1]. In "The Neural Correlates of Psychopathy", we explore what neuroscience currently tells us about the neural correlates of violence, using the recent neuroscientific research on psychopathy as our focus. We also discuss some recent advances in both data collection ("Cutting-Edge Data Collection: Genetically Informed Neuroimaging") and data analysis ("Cutting-Edge Data Analysis: Pattern Classification") that we believe will play an important role when it comes to future neuroscientific research on violence. In "The Potential Promise of Neuroprediction", we discuss whether neuroscience could potentially be used to improve our ability to predict future violence. Finally, in "The Potential Perils of Neuroprediction", we explore some potential evidentiary ("Evidentiary Issues"), constitutional ("Constitutional Issues"), and moral ("Moral Issues") issues that may arise in the context of the neuroprediction of violence.

Spread of the Tiger: Global Risk of Invasion by the Mosquito Aedes albopictus

PubMed Central

BENEDICT, MARK Q.; LEVINE, REBECCA S.; HAWLEY, WILLIAM A.; LOUNIBOS, L. PHILIP

2008-01-01

Aedes albopictus, commonly known as the Asian tiger mosquito, is currently the most invasive mosquito in the world. It is of medical importance due to its aggressive daytime human-biting behavior and ability to vector many viruses, including dengue, LaCrosse, and West Nile. Invasions into new areas of its potential range are often initiated through the transportation of eggs via the international trade in used tires. We use a genetic algorithm, Genetic Algorithm for Rule Set Production (GARP), to determine the ecological niche of Ae. albopictus and predict a global ecological risk map for the continued spread of the species. We combine this analysis with risk due to importation of tires from infested countries and their proximity to countries that have already been invaded to develop a list of countries most at risk for future introductions and establishments. Methods used here have potential for predicting risks of future invasions of vectors or pathogens. PMID:17417960

The Predictive Value of Indocyanine Green Clearance in Future Liver Remnant for Posthepatectomy Liver Failure Following Hepatectomy with Extrahepatic Bile Duct Resection.

PubMed

Yokoyama, Yukihiro; Ebata, Tomoki; Igami, Tsuyoshi; Sugawara, Gen; Mizuno, Takashi; Yamaguchi, Junpei; Nagino, Masato

2016-06-01

Postoperative liver failure (PHLF) is one of the most common complications following major hepatectomy. The preoperative assessment of future liver remnant (FLR) function is critical to predict the incidence of PHLF. To determine the efficacy of the plasma clearance rate of indocyanine green clearance of FLR (ICGK-F) in predicting PHLF in cases of highly invasive hepatectomy with extrahepatic bile duct resection. Five hundred and eighty-five patients who underwent major hepatectomy with extrahepatic bile duct resection, from 2002 to 2014 in a single institution, were evaluated. Among them, 192 patients (33 %) had PHLF. The predictive value of ICGK-F for PHLF was determined and compared with other risk factors for PHLF. The incidence of PHLF was inversely proportional to the level of ICGK-F. With multivariate logistic regression analysis, ICGK-F, combined pancreatoduodenectomy, the operation time, and blood loss were identified as independent risk factors of PHLF. The risk of PHLF increased according to the decrement of ICGK-F (the odds ratio of ICGK-F for each decrement of 0.01 was 1.22; 95 % confidence interval 1.12-1.33; P < 0.001). Low ICGK-F was also identified as an independent risk factor predicting the postoperative mortality. ICGK-F is useful in predicting the PHLF and mortality in patients undergoing major hepatectomy with extrahepatic bile duct resection. This criterion may be useful for highly invasive hepatectomy, such as that with extrahepatic bile duct resection.

Effective Mitigation and Adaptation Strategies for Public Health Impacts of Heatwaves for Brookline, MA

NASA Astrophysics Data System (ADS)

Jalalzadeh Fard, B.; Hassanzadeh, H.; Bhatia, U.; Ganguly, A. R.

2016-12-01

Studies on urban areas show a significant increase in frequency and intensity of heatwaves over the past decades, and predict the same trend for future. Since heatwaves have been responsible for a large number of life losses, urgent adaptation and mitigation strategies are required in the policy and decision making level for a sustainable urban planning. The Sustainability and Data Sciences Laboratory at Northeastern University, under the aegis of Thriving Earth Exchange of AGU, is working with the town of Brookline to understand the potential public health impacts of anticipated heatwaves. We consider the most important social and physical factors to obtain vulnerability and exposure parameters for each census block group of the town. Utilizing remote sensing data, we locate Urban Heat Islands (UHIs) during a recent heatwave event, as the hazard parameter. We then create priority risk map using the risk framework. Our analyses show spatial correlations between the UHIs and social factors such as poverty, and physical factors such as land cover variations. Furthermore, we investigate the future heatwave frequency and intensity increases by analyzing the climate models predictions. For future changes of UHIs, land cover changes are investigated using available predictive data. Also, socioeconomic predictions are carried out to complete the futuristic models of heatwave risks. Considering plausible scenarios for Brookline, we develop different risk maps based on the vulnerability, exposure and hazard parameters. Eventually, we suggest guidelines for Heatwave Action Plans for prioritizing effective mitigation and adaptation strategies in urban planning for the town of Brookline.

Predictors of future anabolic androgenic steroid use.

PubMed

Wichstrøm, Lars

2006-09-01

To prospectively study the stability of anabolic androgenic steroid (AAS) use and predictors of AAS use, and to investigate whether AAS use alters the risk of later emotional and behavioral problems. Survey of a national sample of Norwegian high school students (age 15-19) in 1994 followed up in 1999 (N = 2924). Measures of frequent alcohol intoxication (50+ times per 12 months), cannabis use (12 months), hard drug use (12 months), being offered cannabis, eating problems, conduct problems, sexual debut before age 15, BMI, involvement in power sports, perceived physical appearance, and satisfaction with body parts were obtained. Life-time prevalence of AAS use were 1.9 and 0.8% in the follow-up period. Multivariate logistic regression revealed that future AAS use was predicted by young age, male gender, previous AAS use, involvement in power sports, and frequent alcohol intoxication. AAS use did not predict future emotional or behavioral problems other than reducing the risk of future frequent alcohol intoxication. Frequent alcohol intoxication and involvement in power sports appear to predict future AAS use. At the population level there was little stability in individual AAS use from adolescence to early adulthood. No detrimental effects of AAS use could be detected in this study, but low statistical power limits this conclusion.

Predicting future major depression and persistent depressive symptoms: Development of a prognostic screener and PHQ-4 cutoffs in breast cancer patients.

PubMed

Weihs, Karen L; Wiley, Joshua F; Crespi, Catherine M; Krull, Jennifer L; Stanton, Annette L

2018-02-01

Create a brief, self-report screener for recently diagnosed breast cancer patients to identify patients at risk of future depression. Breast cancer patients (N = 410) within 2 ± 1 months after diagnosis provided data on depression vulnerability. Depression outcomes were defined as a high depressive symptom trajectory or a major depressive episode during 16 months after diagnosis. Stochastic gradient boosting of regression trees identified 7 items highly predictive for the depression outcomes from a pool of 219 candidate depression vulnerability items. Three of the 7 items were from the Patient Health Questionnaire 4 (PHQ-4), a validated screener for current anxiety/depressive disorder that has not been tested to identify risk for future depression. Thresholds classifying patients as high or low risk on the new Depression Risk Questionnaire 7 (DRQ-7) and the PHQ-4 were obtained. Predictive performance of the DRQ-7 and PHQ-4 was assessed on a holdout validation subsample. DRQ-7 items assess loneliness, irritability, persistent sadness, and low acceptance of emotion as well as 3 items from the PHQ-4 (anhedonia, depressed mood, and worry). A DRQ-7 score of ≥6/23 identified depression outcomes with 0.73 specificity, 0.83 sensitivity, 0.68 positive predictive value, and 0.86 negative predictive value. A PHQ-4 score of ≥3/12 performed moderately well but less accurately than the DRQ-7 (net reclassification improvement = 10%; 95% CI [0.5-16]). The DRQ-7 and the PHQ-4 with a new cutoff score are clinically accessible screeners for risk of depression in newly diagnosed breast cancer patients. Use of the screener to select patients for preventive interventions awaits validation of the screener in other samples. Copyright © 2017 John Wiley & Sons, Ltd.

Prognostic implications of serial risk score assessments in patients with pulmonary arterial hypertension: a Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL) analysis.

PubMed

Benza, Raymond L; Miller, Dave P; Foreman, Aimee J; Frost, Adaani E; Badesch, David B; Benton, Wade W; McGoon, Michael D

2015-03-01

Data from the Registry to Evaluate Early and Long-Term Pulmonary Arterial Hypertension Disease Management (REVEAL) were used previously to develop a risk score calculator to predict 1-year survival. We evaluated prognostic implications of changes in the risk score and individual risk-score parameters over 12 months. Patients were grouped by decreased, unchanged, or increased risk score from enrollment to 12 months. Kaplan-Meier estimates of subsequent 1-year survival were made based on change in the risk score during the initial 12 months of follow-up. Cox regression was used for multivariable analysis. Of 2,529 patients in the analysis cohort, the risk score was decreased in 800, unchanged in 959, and increased in 770 at 12 months post-enrollment. Six parameters (functional class, systolic blood pressure, heart rate, 6-minute walk distance, brain natriuretic peptide levels, and pericardial effusion) each changed sufficiently over time to improve or worsen risk scores in ≥5% of patients. One-year survival estimates in the subsequent year were 93.7%, 90.3%, and 84.6% in patients with a decreased, unchanged, and increased risk score at 12 months, respectively. Change in risk score significantly predicted future survival, adjusting for risk at enrollment. Considering follow-up risk concurrently with risk at enrollment, follow-up risk was a much stronger predictor, although risk at enrollment maintained a significant effect on future survival. Changes in REVEAL risk scores occur in most patients with pulmonary arterial hypertension over a 12-month period and are predictive of survival. Thus, serial risk score assessments can identify changes in disease trajectory that may warrant treatment modifications. Copyright © 2015 International Society for Heart and Lung Transplantation. All rights reserved.

Improvement of cardiovascular risk prediction: time to review current knowledge, debates, and fundamentals on how to assess test characteristics.

PubMed

Romanens, Michel; Ackermann, Franz; Spence, John David; Darioli, Roger; Rodondi, Nicolas; Corti, Roberto; Noll, Georg; Schwenkglenks, Matthias; Pencina, Michael

2010-02-01

Cardiovascular risk assessment might be improved with the addition of emerging, new tests derived from atherosclerosis imaging, laboratory tests or functional tests. This article reviews relative risk, odds ratios, receiver-operating curves, posttest risk calculations based on likelihood ratios, the net reclassification improvement and integrated discrimination. This serves to determine whether a new test has an added clinical value on top of conventional risk testing and how this can be verified statistically. Two clinically meaningful examples serve to illustrate novel approaches. This work serves as a review and basic work for the development of new guidelines on cardiovascular risk prediction, taking into account emerging tests, to be proposed by members of the 'Taskforce on Vascular Risk Prediction' under the auspices of the Working Group 'Swiss Atherosclerosis' of the Swiss Society of Cardiology in the future.

22 Years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium.

PubMed

Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W

2016-10-01

Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10(-5), the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9-18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value.

Prediction of future risk of insulin resistance and metabolic syndrome based on Korean boy's metabolite profiling.

PubMed

Lee, AeJin; Jang, Han Byul; Ra, Moonjin; Choi, Youngshim; Lee, Hye-Ja; Park, Ju Yeon; Kang, Jae Heon; Park, Kyung-Hee; Park, Sang Ick; Song, Jihyun

2015-01-01

Childhood obesity is strongly related to future insulin resistance and metabolic syndrome. Thus, identifying early biomarkers of obesity-related diseases based on metabolic profiling is useful to control future metabolic disorders. We compared metabolic profiles between obese and normal-weight children and investigated specific biomarkers of future insulin resistance and metabolic syndrome. In all, 186 plasma metabolites were analysed at baseline and after 2 years in 109 Korean boys (age 10.5±0.4 years) from the Korean Child Obesity Cohort Study using the AbsoluteIDQ™ p180 Kit. We observed that levels of 41 metabolites at baseline and 40 metabolites at follow-up were significantly altered in obese children (p<0.05). Obese children showed significantly higher levels of branched-chain amino acids (BCAAs) and several acylcarnitines and lower levels of acyl-alkyl phosphatidylcholines. Also, baseline BCAAs were significantly positively correlated with both homeostasis model assessment for insulin resistance (HOMA-IR) and continuous metabolic risk score at the 2-year follow-up. In logistic regression analyses with adjustments for degree of obesity at baseline, baseline BCAA concentration, greater than the median value, was identified as a predictor of future risk of insulin resistance and metabolic syndrome. High BCAA concentration could be "early" biomarkers for predicting future metabolic diseases. Copyright © 2014 Asian Oceanian Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Father Involvement and Young, Rural African American Men's Engagement in Substance Misuse and Multiple Sexual Partnerships.

PubMed

Barton, Allen W; Kogan, Steven M; Cho, Junhan; Brown, Geoffrey L

2015-12-01

This study was designed to examine the associations of biological father and social father involvement during childhood with African American young men's development and engagement in risk behaviors. With a sample of 505 young men living in the rural South of the United States, a dual mediation model was tested in which retrospective reports of involvement from biological fathers and social fathers were linked to young men's substance misuse and multiple sexual partnerships through men's relational schemas and future expectations. Results from structural equation modeling indicated that levels of involvement from biological fathers and social fathers predicted young men's relational schemas; only biological fathers' involvement predicted future expectations. In turn, future expectations predicted levels of substance misuse, and negative relational schemas predicted multiple sexual partnerships. Biological fathers' involvement evinced significant indirect associations with young men's substance misuse and multiple sexual partnerships through both schemas and expectations; social fathers' involvement exhibited an indirect association with multiple sexual partnerships through relational schemas. Findings highlight the unique influences of biological fathers and social fathers on multiple domains of African American young men's psychosocial development that subsequently render young men more or less likely to engage in risk behaviors.

Predicting Health Resilience in Pediatric Type 1 Diabetes: A Test of the Resilience Model Framework

PubMed Central

Huang, Bin; Pendley, Jennifer Shroff; Delamater, Alan; Dolan, Lawrence; Reeves, Grafton; Drotar, Dennis

2015-01-01

Objectives This research examined whether individual and family-level factors during the transition from late childhood to early adolescence protected individuals from an increased risk of poor glycemic control across time, which is a predictor of future diabetes-related complications (i.e., health resilience). Methods This longitudinal, multisite study included 239 patients with type 1 diabetes and their caregivers. Glycemic control was based on hemoglobin A1c. Individual and family-level factors included: demographic variables, youth behavioral regulation, adherence (frequency of blood glucose monitoring), diabetes self-management, level of parental support for diabetes autonomy, level of youth mastery and responsibility for diabetes management, and diabetes-related family conflict. Results Longitudinal mixed-effects logistic regression indicated that testing blood glucose more frequently, better self-management, and less diabetes-related family conflict were indicators of health resilience. Conclusions Multiple individual and family-level factors predicted risk for future health complications. Future research should develop interventions targeting specific individual and family-level factors to sustain glycemic control within recommended targets, which reduces the risk of developing future health complications during the transition to adolescence and adulthood. PMID:26152400

SELF-RATED EXPECTATIONS OF SUICIDAL BEHAVIOR PREDICT FUTURE SUICIDE ATTEMPTS AMONG ADOLESCENT AND YOUNG ADULT PSYCHIATRIC EMERGENCY PATIENTS.

PubMed

Czyz, Ewa K; Horwitz, Adam G; King, Cheryl A

2016-06-01

This study's purpose was to examine the predictive validity and clinical utility of a brief measure assessing youths' own expectations of their future risk of suicidal behavior, administered in a psychiatric emergency (PE) department; and determine if youths' ratings improve upon a clinician-administered assessment of suicidal ideation severity. The outcome was suicide attempts up to 18 months later. In this medical record review study, 340 consecutively presenting youths (ages 13-24) seeking PE services over a 7-month period were included. Subsequent PE visits and suicide attempts were retrospectively tracked for up to 18 months. The 3-item scale assessing patients' perception of their own suicidal behavior risk and the clinician-administered ideation severity scale were used routinely at the study site. Cox regression results showed that youths' expectations of suicidal behavior were independently associated with increased risk of suicide attempts, even after adjusting for key covariates. Results were not moderated by sex, suicide attempt history, or age. Receiver-operating characteristic (ROC) analyses indicated that self-assessed expectations of risk improved the predictive accuracy of the clinician-administered suicidal ideation measure. Youths' ratings indicative of lower confidence in maintaining safety uniquely predicted follow-up attempts and provided incremental validity over and above the clinician-administered assessment and improved its accuracy, suggesting their potential for augmenting suicide risk formulation. Assessing youths' own perceptions of suicide risk appears to be clinically useful, feasible to implement in PE settings, and, if replicated, promising for improving identification of youth at risk for suicidal behavior. © 2016 Wiley Periodicals, Inc.

Forecasting the Future Risk of Barmah Forest Virus Disease under Climate Change Scenarios in Queensland, Australia

PubMed Central

Naish, Suchithra; Mengersen, Kerrie; Hu, Wenbiao; Tong, Shilu

2013-01-01

Background Mosquito-borne diseases are climate sensitive and there has been increasing concern over the impact of climate change on future disease risk. This paper projected the potential future risk of Barmah Forest virus (BFV) disease under climate change scenarios in Queensland, Australia. Methods/Principal Findings We obtained data on notified BFV cases, climate (maximum and minimum temperature and rainfall), socio-economic and tidal conditions for current period 2000–2008 for coastal regions in Queensland. Grid-data on future climate projections for 2025, 2050 and 2100 were also obtained. Logistic regression models were built to forecast the otential risk of BFV disease distribution under existing climatic, socio-economic and tidal conditions. The model was applied to estimate the potential geographic distribution of BFV outbreaks under climate change scenarios. The predictive model had good model accuracy, sensitivity and specificity. Maps on potential risk of future BFV disease indicated that disease would vary significantly across coastal regions in Queensland by 2100 due to marked differences in future rainfall and temperature projections. Conclusions/Significance We conclude that the results of this study demonstrate that the future risk of BFV disease would vary across coastal regions in Queensland. These results may be helpful for public health decision making towards developing effective risk management strategies for BFV disease control and prevention programs in Queensland. PMID:23690959

A Systematic Review of Biomarkers and Risk of Incident Type 2 Diabetes: An Overview of Epidemiological, Prediction and Aetiological Research Literature

PubMed Central

Sahlqvist, Anna-Stina; Lotta, Luca; Brosnan, Julia M.; Vollenweider, Peter; Giabbanelli, Philippe; Nunez, Derek J.; Waterworth, Dawn; Scott, Robert A.; Langenberg, Claudia; Wareham, Nicholas J.

2016-01-01

Background Blood-based or urinary biomarkers may play a role in quantifying the future risk of type 2 diabetes (T2D) and in understanding possible aetiological pathways to disease. However, no systematic review has been conducted that has identified and provided an overview of available biomarkers for incident T2D. We aimed to systematically review the associations of biomarkers with risk of developing T2D and to highlight evidence gaps in the existing literature regarding the predictive and aetiological value of these biomarkers and to direct future research in this field. Methods and Findings We systematically searched PubMed MEDLINE (January 2000 until March 2015) and Embase (until January 2016) databases for observational studies of biomarkers and incident T2D according to the 2009 PRISMA guidelines. We also searched availability of meta-analyses, Mendelian randomisation and prediction research for the identified biomarkers. We reviewed 3910 titles (705 abstracts) and 164 full papers and included 139 papers from 69 cohort studies that described the prospective relationships between 167 blood-based or urinary biomarkers and incident T2D. Only 35 biomarkers were reported in large scale studies with more than 1000 T2D cases, and thus the evidence for association was inconclusive for the majority of biomarkers. Fourteen biomarkers have been investigated using Mendelian randomisation approaches. Only for one biomarker was there strong observational evidence of association and evidence from genetic association studies that was compatible with an underlying causal association. In additional search for T2D prediction, we found only half of biomarkers were examined with formal evidence of predictive value for a minority of these biomarkers. Most biomarkers did not enhance the strength of prediction, but the strongest evidence for prediction was for biomarkers that quantify measures of glycaemia. Conclusions This study presents an extensive review of the current state of the literature to inform the strategy for future interrogation of existing and newly described biomarkers for T2D. Many biomarkers have been reported to be associated with the risk of developing T2D. The evidence of their value in adding to understanding of causal pathways to disease is very limited so far. The utility of most biomarkers remains largely unknown in clinical prediction. Future research should focus on providing good genetic instruments across consortia for possible biomarkers in Mendelian randomisation, prioritising biomarkers for measurement in large-scale cohort studies and examining predictive utility of biomarkers for a given context. PMID:27788146

Development and validation of a risk assessment tool for gastric cancer in a general Japanese population.

PubMed

Iida, Masahiro; Ikeda, Fumie; Hata, Jun; Hirakawa, Yoichiro; Ohara, Tomoyuki; Mukai, Naoko; Yoshida, Daigo; Yonemoto, Koji; Esaki, Motohiro; Kitazono, Takanari; Kiyohara, Yutaka; Ninomiya, Toshiharu

2018-05-01

There have been very few reports of risk score models for the development of gastric cancer. The aim of this study was to develop and validate a risk assessment tool for discerning future gastric cancer risk in Japanese. A total of 2444 subjects aged 40 years or over were followed up for 14 years from 1988 (derivation cohort), and 3204 subjects of the same age group were followed up for 5 years from 2002 (validation cohort). The weighting (risk score) of each risk factor for predicting future gastric cancer in the risk assessment tool was determined based on the coefficients of a Cox proportional hazards model in the derivation cohort. The goodness of fit of the established risk assessment tool was assessed using the c-statistic and the Hosmer-Lemeshow test in the validation cohort. During the follow-up, gastric cancer developed in 90 subjects in the derivation cohort and 35 subjects in the validation cohort. In the derivation cohort, the risk prediction model for gastric cancer was established using significant risk factors: age, sex, the combination of Helicobacter pylori antibody and pepsinogen status, hemoglobin A1c level, and smoking status. The incidence of gastric cancer increased significantly as the sum of risk scores increased (P trend < 0.001). The risk assessment tool was validated internally and showed good discrimination (c-statistic = 0.76) and calibration (Hosmer-Lemeshow test P = 0.43) in the validation cohort. We developed a risk assessment tool for gastric cancer that provides a useful guide for stratifying an individual's risk of future gastric cancer.

Clinical application of the Melbourne risk prediction tool in a high-risk upper abdominal surgical population: an observational cohort study.

PubMed

Parry, S; Denehy, L; Berney, S; Browning, L

2014-03-01

(1) To determine the ability of the Melbourne risk prediction tool to predict a pulmonary complication as defined by the Melbourne Group Scale in a medically defined high-risk upper abdominal surgery population during the postoperative period; (2) to identify the incidence of postoperative pulmonary complications; and (3) to examine the risk factors for postoperative pulmonary complications in this high-risk population. Observational cohort study. Tertiary Australian referral centre. 50 individuals who underwent medically defined high-risk upper abdominal surgery. Presence of postoperative pulmonary complications was screened daily for seven days using the Melbourne Group Scale (Version 2). Postoperative pulmonary risk prediction was calculated according to the Melbourne risk prediction tool. (1) Melbourne risk prediction tool; and (2) the incidence of postoperative pulmonary complications. Sixty-six percent (33/50) underwent hepatobiliary or upper gastrointestinal surgery. Mean (SD) anaesthetic duration was 377.8 (165.5) minutes. The risk prediction tool classified 84% (42/50) as high risk. Overall postoperative pulmonary complication incidence was 42% (21/50). The tool was 91% sensitive and 21% specific with a 50% chance of correct classification. This is the first study to externally validate the Melbourne risk prediction tool in an independent medically defined high-risk population. There was a higher incidence of pulmonary complications postoperatively observed compared to that previously reported. Results demonstrated poor validity of the tool in a population already defined medically as high risk and when applied postoperatively. This observational study has identified several important points to consider in future trials. Copyright © 2013 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

Incorporating population viability models into species status assessment and listing decisions under the U.S. Endangered Species Act

USGS Publications Warehouse

McGowan, Conor P.; Allan, Nathan; Servoss, Jeff; Hedwall, Shaula J.; Wooldridge, Brian

2017-01-01

Assessment of a species' status is a key part of management decision making for endangered and threatened species under the U.S. Endangered Species Act. Predicting the future state of the species is an essential part of species status assessment, and projection models can play an important role in developing predictions. We built a stochastic simulation model that incorporated parametric and environmental uncertainty to predict the probable future status of the Sonoran desert tortoise in the southwestern United States and North Central Mexico. Sonoran desert tortoise was a Candidate species for listing under the Endangered Species Act, and decision makers wanted to use model predictions in their decision making process. The model accounted for future habitat loss and possible effects of climate change induced droughts to predict future population growth rates, abundances, and quasi-extinction probabilities. Our model predicts that the population will likely decline over the next few decades, but there is very low probability of quasi-extinction less than 75 years into the future. Increases in drought frequency and intensity may increase extinction risk for the species. Our model helped decision makers predict and characterize uncertainty about the future status of the species in their listing decision. We incorporated complex ecological processes (e.g., climate change effects on tortoises) in transparent and explicit ways tailored to support decision making processes related to endangered species.

Tryptophan Predicts the Risk for Future Type 2 Diabetes

PubMed Central

Chen, Tianlu; Zheng, Xiaojiao; Ma, Xiaojing; Bao, Yuqian; Ni, Yan; Hu, Cheng; Rajani, Cynthia; Huang, Fengjie; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recently, 5 amino acids were identified and verified as important metabolites highly associated with type 2 diabetes (T2D) development. This report aims to assess the association of tryptophan with the development of T2D and to evaluate its performance with existing amino acid markers. A total of 213 participants selected from a ten-year longitudinal Shanghai Diabetes Study (SHDS) were examined in two ways: 1) 51 subjects who developed diabetes and 162 individuals who remained metabolically healthy in 10 years; 2) the same 51 future diabetes and 23 strictly matched ones selected from the 162 healthy individuals. Baseline fasting serum tryptophan concentrations were quantitatively measured using ultra-performance liquid chromatography triple quadruple mass spectrometry. First, serum tryptophan level was found significantly higher in future T2D and was positively and independently associated with diabetes onset risk. Patients with higher tryptophan level tended to present higher degree of insulin resistance and secretion, triglyceride and blood pressure. Second, the prediction potential of tryptophan is non-inferior to the 5 existing amino acids. The predictive performance of the combined score improved after taking tryptophan into account. Our findings unveiled the potential of tryptophan as a new marker associated with diabetes risk in Chinese populations. The addition of tryptophan provided complementary value to the existing amino acid predictors. PMID:27598004

Exercise blood pressure and the risk of future hypertension.

PubMed

Holmqvist, L; Mortensen, L; Kanckos, C; Ljungman, C; Mehlig, K; Manhem, K

2012-12-01

The aim of this prospective cohort study was to identify which blood pressure measurement during exercise is the best predictor of future hypertension. Further we aimed to create a risk chart to facilitate the evaluation of blood pressure reaction during exercise testing. A number (n=1047) of exercise tests by bicycle ergometry, performed in 1996 and 1997 were analysed. In 2007-2008, 606 patients without hypertension at the time of the exercise test were sent a questionnaire aimed to identify current hypertension. The response rate was 58% (n=352). During the 10-12 years between exercise test and questionnaire, 23% developed hypertension. The strongest predictors of future hypertension were systolic blood pressure (SBP) before exercise (odds ratios (OR) 1.63 (1.31-2.01) for 10 mm Hg difference) in combination with the increase of SBP over time during exercise testing (OR 1.12 (1.01-1.24) steeper increase for every 1 mm Hg min(-1)). A high SBP before exercise and a steep rise in SBP over time represented a higher risk of developing hypertension. A risk chart based on SBP before exercise, increase of SBP over time and body mass index was created. SBP before exercise, maximal SBP during exercise and SBP at 100 W were significant single predictors of future hypertension and the prediction by maximal SBP was improved by adjusting for time/power at which SBP max was reached during exercise testing. Recovery ratio (maximal SBP/SBP 4 min after exercise) was not predictive of future hypertension.

Is low cognitive functioning a predictor or consequence of major depressive disorder? A test in two longitudinal birth cohorts.

PubMed

Schaefer, Jonathan D; Scult, Matthew A; Caspi, Avshalom; Arseneault, Louise; Belsky, Daniel W; Hariri, Ahmad R; Harrington, Honalee; Houts, Renate; Ramrakha, Sandhya; Poulton, Richie; Moffitt, Terrie E

2017-11-16

Cognitive impairment has been identified as an important aspect of major depressive disorder (MDD). We tested two theories regarding the association between MDD and cognitive functioning using data from longitudinal cohort studies. One theory, the cognitive reserve hypothesis, suggests that higher cognitive ability in childhood decreases risk of later MDD. The second, the scarring hypothesis, instead suggests that MDD leads to persistent cognitive deficits following disorder onset. We tested both theories in the Dunedin Study, a population-representative cohort followed from birth to midlife and assessed repeatedly for both cognitive functioning and psychopathology. We also used data from the Environmental Risk Longitudinal Twin Study to test whether childhood cognitive functioning predicts future MDD risk independent of family-wide and genetic risk using a discordant twin design. Contrary to both hypotheses, we found that childhood cognitive functioning did not predict future risk of MDD, nor did study members with a past history of MDD show evidence of greater cognitive decline unless MDD was accompanied by other comorbid psychiatric conditions. Our results thus suggest that low cognitive functioning is related to comorbidity, but is neither an antecedent nor an enduring consequence of MDD. Future research may benefit from considering cognitive deficits that occur during depressive episodes from a transdiagnostic perspective.

Increased wind risk from sting-jet windstorms with climate change

NASA Astrophysics Data System (ADS)

Martínez-Alvarado, Oscar; Gray, Suzanne L.; Hart, Neil C. G.; Clark, Peter A.; Hodges, Kevin; Roberts, Malcolm J.

2018-04-01

Extra-tropical cyclones dominate autumn and winter weather over western Europe. The strongest cyclones, often termed windstorms, have a large socio-economic impact on landfall due to strong surface winds and coastal storm surges. Climate model integrations have predicted a future increase in the frequency of, and potential damage from, European windstorms and yet these integrations cannot properly represent localised jets, such as sting jets, that may significantly enhance damage. Here we present the first prediction of how the climatology of sting-jet-containing cyclones will change in a future warmer climate, considering the North Atlantic and Europe. A proven sting-jet precursor diagnostic is applied to 13 year present-day and future (~2100) climate integrations from the Met Office Unified Model in its Global Atmosphere 3.0 configuration. The present-day climate results are consistent with previously-published results from a reanalysis dataset (with around 32% of cyclones exhibiting the sing-jet precursor), lending credibility to the analysis of the future-climate integration. The proportion of cyclones exhibiting the sting-jet precursor in the future-climate integration increases to 45%. Furthermore, while the proportion of explosively-deepening storms increases only slightly in the future climate, the proportion of those storms with the sting-jet precursor increases by 60%. The European resolved-wind risk associated with explosively-deepening storms containing a sting-jet precursor increases substantially in the future climate; in reality this wind risk is likely to be further enhanced by the release of localised moist instability, unresolved by typical climate models.

Can We Use Neurocognition to Predict Repetition of Self-Harm, and Why Might This Be Clinically Useful? A Perspective

PubMed Central

de Cates, Angharad N.; Broome, Matthew R.

2016-01-01

Over 800,000 people die by suicide each year globally, with non-fatal self-harm 20 times more common. With each episode of self-harm, the risks of future self-harm and suicide increase, as well as personal and healthcare costs. Therefore, early delineation of those at high risk of future self-harm is important. Historically, research has focused on clinical and demographic factors, but risk assessments based on these have low sensitivity to predict repetition. Various neurocognitive factors have been associated with self-harming behavior, but it is less certain if we can use these factors clinically (i) as risk markers to predict future self-harm and (ii) to become therapeutic targets for interventions. Recent systematic reviews and meta-analyses of behavioral tasks and fMRI studies point to an emerging hypothesis for neurocognition in self-harm: an underactive pre-frontal cortex is unable to respond appropriately to non-emotional stimuli, or inhibit a hyperactive emotionally-/threat-driven limbic system. However, there is almost no imaging data examining repetition of self-harm. Extrapolating from the non-repetition data, there may be several potential neurocognitive targets for interventions to prevent repeat self-harm: cognitive training; pharmacological regimes to promote non-emotional neurocognition; or other techniques, such as repetitive transcranial magnetic stimulation. Hence, there is an urgent need for imaging studies examining repetition and to test specific hypotheses. Until we investigate the functional neurocognitive basis underlying repetition of self-harm in a systematic manner using second-generational imaging techniques, we will be unable to inform third-generational imaging and potential future clinical applications. PMID:26858659

HEALTH AND ECOLOGICAL IMPACTS OF HARMFUL ALGAL BLOOMS: RISK ASSESSMENT NEEDS

EPA Science Inventory

The symposium session, Indicators for Effects and Predictions of Harmful Algal Blooms, explored the current state of indicators used to assess the human health and ecological risks caused by harmful algal blooms, and highlighted future needs and impediments that must be overcome...

Assessing Risk for Future Firearms Violence in Young People Who Present to ED.

PubMed

2017-06-01

A new clinical index tool designed specifically for the emergency environment predicts the risk for future firearms violence in young people 14-24 years of age. The approach employs a brief, 10-point instrument that can be administered in one to two minutes, according to investigators. They also note that while the tool is based on data from a single ED in Flint, Ml, the tool should be applicable to urban EDs in regions that have similar characteristics. To create the tool, investigators used data from the Flint Youth Injury Study, an investigation of a group of patients 14-24 years of age who reported using drugs in the previous six months and accessed care at a Level I trauma center. Using a machine learning classification approach, investigators combed through the data, finding that the most predictive factors for firearm violence could be categorized into four domains: peer and partner violence victimization, community violence exposure, peer/family influences, and fighting. Ideally, investigators note the tool will be employed along with interventions targeted toward patients at high risk for future firearms violence.

Risk levels of invasive Fusarium oxysporum f. sp. in areas suitable for date palm (Phoenix dactylifera) cultivation under various climate change projections.

PubMed

Shabani, Farzin; Kumar, Lalit

2013-01-01

Global climate model outputs involve uncertainties in prediction, which could be reduced by identifying agreements between the output results of different models, covering all assumptions included in each. Fusarium oxysporum f.sp. is an invasive pathogen that poses risk to date palm cultivation, among other crops. Therefore, in this study, the future distribution of invasive Fusarium oxysporum f.sp., confirmed by CSIRO-Mk3.0 (CS) and MIROC-H (MR) GCMs, was modeled and combined with the future distribution of date palm predicted by the same GCMs, to identify areas suitable for date palm cultivation with different risk levels of invasive Fusarium oxysporum f.sp., for 2030, 2050, 2070 and 2100. Results showed that 40%, 37%, 33% and 28% areas projected to become highly conducive to date palm are under high risk of its lethal fungus, compared with 37%, 39%, 43% and 42% under low risk, for the chosen years respectively. Our study also indicates that areas with marginal risk will be limited to 231, 212, 186 and 172 million hectares by 2030, 2050, 2070 and 2100. The study further demonstrates that CLIMEX outputs refined by a combination of different GCMs results of different species that have symbiosis or parasite relationship, ensure that the predictions become robust, rather than producing hypothetical findings, limited purely to publication.

Risk Levels of Invasive Fusarium oxysporum f. sp. in Areas Suitable for Date Palm (Phoenix dactylifera) Cultivation under Various Climate Change Projections

PubMed Central

Shabani, Farzin; Kumar, Lalit

2013-01-01

Global climate model outputs involve uncertainties in prediction, which could be reduced by identifying agreements between the output results of different models, covering all assumptions included in each. Fusarium oxysporum f.sp. is an invasive pathogen that poses risk to date palm cultivation, among other crops. Therefore, in this study, the future distribution of invasive Fusarium oxysporum f.sp., confirmed by CSIRO-Mk3.0 (CS) and MIROC-H (MR) GCMs, was modeled and combined with the future distribution of date palm predicted by the same GCMs, to identify areas suitable for date palm cultivation with different risk levels of invasive Fusarium oxysporum f.sp., for 2030, 2050, 2070 and 2100. Results showed that 40%, 37%, 33% and 28% areas projected to become highly conducive to date palm are under high risk of its lethal fungus, compared with 37%, 39%, 43% and 42% under low risk, for the chosen years respectively. Our study also indicates that areas with marginal risk will be limited to 231, 212, 186 and 172 million hectares by 2030, 2050, 2070 and 2100. The study further demonstrates that CLIMEX outputs refined by a combination of different GCMs results of different species that have symbiosis or parasite relationship, ensure that the predictions become robust, rather than producing hypothetical findings, limited purely to publication. PMID:24340100

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

PubMed

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

2011-02-01

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

Serum creatinine role in predicting outcome after cardiac surgery beyond acute kidney injury

PubMed Central

Najafi, Mahdi

2014-01-01

Serum creatinine is still the most important determinant in the assessment of perioperative renal function and in the prediction of adverse outcome in cardiac surgery. Many biomarkers have been studied to date; still, there is no surrogate for serum creatinine measurement in clinical practice because it is feasible and inexpensive. High levels of serum creatinine and its equivalents have been the most important preoperative risk factor for postoperative renal injury. Moreover, creatinine is the mainstay in predicting risk models and risk factor reduction has enhanced its importance in outcome prediction. The future perspective is the development of new definitions and novel tools for the early diagnosis of acute kidney injury largely based on serum creatinine and a panel of novel biomarkers. PMID:25276301

Characteristics of construction firms at risk for future workers' compensation claims using administrative data systems, Washington State.

PubMed

Marcum, Jennifer L; Foley, Michael; Adams, Darrin; Bonauto, Dave

2018-06-01

Construction is high-hazard industry, and continually ranks among those with the highest workers' compensation (WC) claim rates in Washington State (WA). However, not all construction firms are at equal risk. We tested the ability to identify those construction firms most at risk for future claims using only administrative WC and unemployment insurance data. We collected information on construction firms with 10-50 average full time equivalent (FTE) employees from the WA unemployment insurance and WC data systems (n=1228). Negative binomial regression was used to test the ability of firm characteristics measured during 2011-2013 to predict time-loss claim rates in the following year, 2014. Claim rates in 2014 varied by construction industry groups, ranging from 0.7 (Land Subdivision) to 4.6 (Foundation, Structure, and Building Construction) claims per 100 FTE. Construction firms with higher average WC premium rates, a history of WC claims, increasing number of quarterly FTE, and lower average wage rates during 2011-2013 were predicted to have higher WC claim rates in 2014. We demonstrate the ability to leverage administrative data to identify construction firms predicted to have future WC claims. This study should be repeated to determine if these results are applicable to other high-hazard industries. Practical Applications: This study identified characteristics that may be used to further refine targeted outreach and prevention to construction firms at risk. Published by Elsevier Ltd.

Predictors associated with MRI surveillance screening in women with a personal history of unilateral breast cancer but without a genetic predisposition for future contralateral breast cancer.

PubMed

Hegde, John V; Wang, Xiaoyan; Attai, Deanna J; DiNome, Maggie L; Kusske, Amy; Hoyt, Anne C; Hurvitz, Sara A; Weidhaas, Joanne B; Steinberg, Michael L; McCloskey, Susan A

2017-11-01

For women with a personal history of breast cancer (PHBC), no validated mechanisms exist to calculate future contralateral breast cancer (CBC) risk. The Manchester risk stratification guidelines were developed to evaluate CBC risk in women with a PHBC, primarily for surgical decision making. This tool may be informative for the use of MRI screening, as CBC risk is an assumed consideration for high-risk surveillance. Three hundred twenty-two women with a PHBC were treated with unilateral surgery within our multidisciplinary breast clinic. We calculated lifetime CBC risk using the Manchester tool, which incorporates age at diagnosis, family history, genetic mutation status, estrogen receptor positivity, and endocrine therapy use. Univariate and multivariate logistic regression analyses (UVA/MVA) were performed, evaluating whether CBC risk predicted MRI surveillance. For women with invasive disease undergoing MRI surveillance, 66% had low, 23% above-average, and 11% moderate/high risk for CBC. On MVA, previous mammography-occult breast cancer [odds ratio (OR) 18.95, p < 0.0001], endocrine therapy use (OR 3.89, p = 0.009), dense breast tissue (OR 3.69, p = 0.0007), mastectomy versus lumpectomy (OR 3.12, p = 0.0041), and CBC risk (OR 3.17 for every 10% increase, p = 0.0002) were associated with MRI surveillance. No pathologic factors increasing ipsilateral breast cancer recurrence were significant on MVA. Although CBC risk predicted MRI surveillance, 89% with invasive disease undergoing MRI had <20% calculated CBC risk. Concerns related to future breast cancer detectability (dense breasts and/or previous mammography-occult disease) predominate decision making. Pathologic factors important for determining ipsilateral recurrence risk, aside from age, were not associated with MRI surveillance.

Assessing the impact of climate change on vector-borne viruses in the EU through the elicitation of expert opinion.

PubMed

Gale, P; Brouwer, A; Ramnial, V; Kelly, L; Kosmider, R; Fooks, A R; Snary, E L

2010-02-01

Expert opinion was elicited to undertake a qualitative risk assessment to estimate the current and future risks to the European Union (EU) from five vector-borne viruses listed by the World Organization for Animal Health. It was predicted that climate change will increase the risk of incursions of African horse sickness virus (AHSV), Crimean-Congo haemorrhagic fever virus (CCHFV) and Rift Valley fever virus (RVFV) into the EU from other parts of the world, with African swine fever virus (ASFV) and West Nile virus (WNV) being less affected. Currently the predicted risks of incursion were lowest for RVFV and highest for ASFV. Risks of incursion were considered for six routes of entry (namely vectors, livestock, meat products, wildlife, pets and people). Climate change was predicted to increase the risk of incursion from entry of vectors for all five viruses to some degree, the strongest effects being predicted for AHSV, CCHFV and WNV. This work will facilitate identification of appropriate risk management options in relation to adaptations to climate change.

Metabolite Profiles and the Risk of Developing Diabetes

PubMed Central

Wang, Thomas J.; Larson, Martin G.; Vasan, Ramachandran S.; Cheng, Susan; Rhee, Eugene P.; McCabe, Elizabeth; Lewis, Gregory D.; Fox, Caroline S.; Jacques, Paul F.; Fernandez, Céline; O’Donnell, Christopher J.; Carr, Stephen A.; Mootha, Vamsi K.; Florez, Jose C.; Souza, Amanda; Melander, Olle; Clish, Clary B.; Gerszten, Robert E.

2011-01-01

Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines, and other polar metabolites were profiled in baseline specimens using liquid chromatography-tandem mass spectrometry. Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly-significant associations with future diabetes: isoleucine, leucine, valine, tyrosine, and phenylalanine. A combination of three amino acids predicted future diabetes (>5-fold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential importance of amino acid metabolism early in the pathogenesis of diabetes, and suggest that amino acid profiles could aid in diabetes risk assessment. PMID:21423183

Metabolite profiles and the risk of developing diabetes.

PubMed

Wang, Thomas J; Larson, Martin G; Vasan, Ramachandran S; Cheng, Susan; Rhee, Eugene P; McCabe, Elizabeth; Lewis, Gregory D; Fox, Caroline S; Jacques, Paul F; Fernandez, Céline; O'Donnell, Christopher J; Carr, Stephen A; Mootha, Vamsi K; Florez, Jose C; Souza, Amanda; Melander, Olle; Clish, Clary B; Gerszten, Robert E

2011-04-01

Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography-tandem mass spectrometry (LC-MS). Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly significant associations with future diabetes: isoleucine, leucine, valine, tyrosine and phenylalanine. A combination of three amino acids predicted future diabetes (with a more than fivefold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment.

Decision support systems and methods for complex networks

DOEpatents

Huang, Zhenyu [Richland, WA; Wong, Pak Chung [Richland, WA; Ma, Jian [Richland, WA; Mackey, Patrick S [Richland, WA; Chen, Yousu [Richland, WA; Schneider, Kevin P [Seattle, WA

2012-02-28

Methods and systems for automated decision support in analyzing operation data from a complex network. Embodiments of the present invention utilize these algorithms and techniques not only to characterize the past and present condition of a complex network, but also to predict future conditions to help operators anticipate deteriorating and/or problem situations. In particular, embodiments of the present invention characterize network conditions from operation data using a state estimator. Contingency scenarios can then be generated based on those network conditions. For at least a portion of all of the contingency scenarios, risk indices are determined that describe the potential impact of each of those scenarios. Contingency scenarios with risk indices are presented visually as graphical representations in the context of a visual representation of the complex network. Analysis of the historical risk indices based on the graphical representations can then provide trends that allow for prediction of future network conditions.

The role of objective personality inventories in suicide risk assessment: an evaluation and proposal.

PubMed

Johnson, W B; Lall, R; Bongar, B; Nordlund, M D

1999-01-01

Objective personality assessment instruments offer a comparatively underutilized source of clinical data in attempts to evaluate and predict risk for suicide. In contrast to focal suicide risk measures, global personality inventories may be useful in identification of long-standing styles that predispose persons to eventual suicidal behavior. This article reviews the empirical literature regarding the efficacy of established personality inventories in predicting suicidality. The authors offer several recommendations for future research with these measures and conclude that such objective personality instruments offer only marginal utility as sources of clinical information in comprehensive suicide risk evaluations. Personality inventories may offer greatest utility in long-term assessment of suicide risk.

Family cumulative risk and at-risk kindergarteners' social competence: the mediating role of parent representations of the attachment relationship.

PubMed

Sparks, Lauren A; Trentacosta, Christopher J; Owusu, Erika; McLear, Caitlin; Smith-Darden, Joanne

2018-08-01

Secure attachment relationships have been linked to social competence in at-risk children. In the current study, we examined the role of parent secure base scripts in predicting at-risk kindergarteners' social competence. Parent representations of secure attachment were hypothesized to mediate the relationship between lower family cumulative risk and children's social competence. Participants included 106 kindergarteners and their primary caregivers recruited from three urban charter schools serving low-income families as a part of a longitudinal study. Lower levels of cumulative risk predicted greater secure attachment representations in parents, and scores on the secure base script assessment predicted children's social competence. An indirect relationship between lower cumulative risk and kindergarteners' social competence via parent secure base script scores was also supported. Parent script-based representations of the attachment relationship appear to be an important link between lower levels of cumulative risk and low-income kindergarteners' social competence. Implications of these findings for future interventions are discussed.

PREDICTING REGIONAL ALLERGY HOTSPOTS IN FUTURE CLIMATE SCENARIOS – PUTTING THE WHERE & WHEN ON WHEEZING

EPA Science Inventory

This research addresses both the effects and mechanisms by which current and future climate conditions affect the risk factors related to allergic airway disease in humans. Our intensive sampling of pollen production, output, and potency in ecologically distinct ragweed popul...

22 Years of predictive testing for Huntington's disease: the experience of the UK Huntington's Prediction Consortium

PubMed Central

Baig, Sheharyar S; Strong, Mark; Rosser, Elisabeth; Taverner, Nicola V; Glew, Ruth; Miedzybrodzka, Zosia; Clarke, Angus; Craufurd, David; Quarrell, Oliver W

2016-01-01

Huntington's disease (HD) is a progressive neurodegenerative condition. At-risk individuals have accessed predictive testing via direct mutation testing since 1993. The UK Huntington's Prediction Consortium has collected anonymised data on UK predictive tests, annually, from 1993 to 2014: 9407 predictive tests were performed across 23 UK centres. Where gender was recorded, 4077 participants were male (44.3%) and 5122 were female (55.7%). The median age of participants was 37 years. The most common reason for predictive testing was to reduce uncertainty (70.5%). Of the 8441 predictive tests on individuals at 50% prior risk, 4629 (54.8%) were reported as mutation negative and 3790 (44.9%) were mutation positive, with 22 (0.3%) in the database being uninterpretable. Using a prevalence figure of 12.3 × 10−5, the cumulative uptake of predictive testing in the 50% at-risk UK population from 1994 to 2014 was estimated at 17.4% (95% CI: 16.9–18.0%). We present the largest study conducted on predictive testing in HD. Our findings indicate that the vast majority of individuals at risk of HD (>80%) have not undergone predictive testing. Future therapies in HD will likely target presymptomatic individuals; therefore, identifying the at-risk population whose gene status is unknown is of significant public health value. PMID:27165004

FORUM - FutureTox II: In vitro Data and In Silico Models for ...

EPA Pesticide Factsheets

FutureTox II, a Society of Toxicology Contemporary Concepts in Toxicology workshop, was held in January, 2014. The meeting goals were to review and discuss the state of the science in toxicology in the context of implementing the NRC 21st century vision of predicting in vivo responses from in vitro and in silico data, and to define the goals for the future. Presentations and discussions were held on priority concerns such as predicting and modeling of metabolism, cell growth and differentiation, effects on sensitive subpopulations, and integrating data into risk assessment. Emerging trends in technologies such as stem cell-derived human cells, 3D organotypic culture models, mathematical modeling of cellular processes and morphogenesis, adverse outcome pathway development, and high-content imaging of in vivo systems were discussed. Although advances in moving towards an in vitro/in silico based risk assessment paradigm were apparent, knowledge gaps in these areas and limitations of technologies were identified. Specific recommendations were made for future directions and research needs in the areas of hepatotoxicity, cancer prediction, developmental toxicity, and regulatory toxicology. This article reports on the outcome of FutureTox II1,2, the second in a series of Society of Toxicology (SOT) Contemporary Concepts in Toxicology (CCT) Workshops, which was attended by invitees and participants from governmental and regulatory agencies, research institutes, academ

A Naive Bayes machine learning approach to risk prediction using censored, time-to-event data.

PubMed

Wolfson, Julian; Bandyopadhyay, Sunayan; Elidrisi, Mohamed; Vazquez-Benitez, Gabriela; Vock, David M; Musgrove, Donald; Adomavicius, Gediminas; Johnson, Paul E; O'Connor, Patrick J

2015-09-20

Predicting an individual's risk of experiencing a future clinical outcome is a statistical task with important consequences for both practicing clinicians and public health experts. Modern observational databases such as electronic health records provide an alternative to the longitudinal cohort studies traditionally used to construct risk models, bringing with them both opportunities and challenges. Large sample sizes and detailed covariate histories enable the use of sophisticated machine learning techniques to uncover complex associations and interactions, but observational databases are often 'messy', with high levels of missing data and incomplete patient follow-up. In this paper, we propose an adaptation of the well-known Naive Bayes machine learning approach to time-to-event outcomes subject to censoring. We compare the predictive performance of our method with the Cox proportional hazards model which is commonly used for risk prediction in healthcare populations, and illustrate its application to prediction of cardiovascular risk using an electronic health record dataset from a large Midwest integrated healthcare system. Copyright © 2015 John Wiley & Sons, Ltd.

Negative HPV screening test predicts low cervical cancer risk better than negative Pap test

Cancer.gov

Based on a study that included more than 1 million women, investigators at NCI have determined that a negative test for HPV infection compared to a negative Pap test provides greater safety, or assurance, against future risk of cervical cancer.

Climate change, agricultural insecticide exposure, and risk for freshwater communities.

PubMed

Kattwinkel, Mira; Kühne, Jan-Valentin; Foit, Kaarina; Liess, Matthias

2011-09-01

Climate change exerts direct effects on ecosystems but has additional indirect effects due to changes in agricultural practice. These include the increased use of pesticides, changes in the areas that are cultivated, and changes in the crops cultivated. It is well known that pesticides, and in particular insecticides, affect aquatic ecosystems adversely. To implement effective mitigation measures it is necessary to identify areas that are affected currently and those that will be affected in the future. As a consequence, we predicted potential exposure to insecticide (insecticide runoff potential, RP) under current conditions (1990) and under a model scenario of future climate and land use (2090) using a spatially explicit model on a continental scale, with a focus on Europe. Space-for-time substitution was used to predict future levels of insecticide application, intensity of agricultural land use, and cultivated crops. To assess the indirect effects of climate change, evaluation of the risk of insecticide exposure was based on a trait-based, climate-insensitive indicator system (SPEAR, SPEcies At Risk). To this end, RP and landscape characteristics that are relevant for the recovery of affected populations were combined to estimate the ecological risk (ER) of insecticides for freshwater communities. We predicted a strong increase in the application of, and aquatic exposure to, insecticides under the future scenario, especially in central and northern Europe. This, in turn, will result in a severe increase in ER in these regions. Hence, the proportion of stream sites adjacent to arable land that do not meet the requirements for good ecological status as defined by the EU Water Framework Directive will increase (from 33% to 39% for the EU-25 countries), in particular in the Scandinavian and Baltic countries (from 6% to 19%). Such spatially explicit mapping of risk enables the planning of adaptation and mitigation strategies including vegetated buffer strips and nonagricultural recolonization zones along streams.

Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

PubMed Central

Holt, Ashley C; Salkeld, Daniel J; Fritz, Curtis L; Tucker, James R; Gong, Peng

2009-01-01

Background Plague, caused by the bacterium Yersinia pestis, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (Spermophilus beecheyi) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (Canis latrans) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance. Results Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras. Conclusion Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions. PMID:19558717

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance.

PubMed

Meads, Catherine; Ahmed, Ikhlaaq; Riley, Richard D

2012-04-01

A risk prediction model is a statistical tool for estimating the probability that a currently healthy individual with specific risk factors will develop a condition in the future such as breast cancer. Reliably accurate prediction models can inform future disease burdens, health policies and individual decisions. Breast cancer prediction models containing modifiable risk factors, such as alcohol consumption, BMI or weight, condom use, exogenous hormone use and physical activity, are of particular interest to women who might be considering how to reduce their risk of breast cancer and clinicians developing health policies to reduce population incidence rates. We performed a systematic review to identify and evaluate the performance of prediction models for breast cancer that contain modifiable factors. A protocol was developed and a sensitive search in databases including MEDLINE and EMBASE was conducted in June 2010. Extensive use was made of reference lists. Included were any articles proposing or validating a breast cancer prediction model in a general female population, with no language restrictions. Duplicate data extraction and quality assessment were conducted. Results were summarised qualitatively, and where possible meta-analysis of model performance statistics was undertaken. The systematic review found 17 breast cancer models, each containing a different but often overlapping set of modifiable and other risk factors, combined with an estimated baseline risk that was also often different. Quality of reporting was generally poor, with characteristics of included participants and fitted model results often missing. Only four models received independent validation in external data, most notably the 'Gail 2' model with 12 validations. None of the models demonstrated consistently outstanding ability to accurately discriminate between those who did and those who did not develop breast cancer. For example, random-effects meta-analyses of the performance of the 'Gail 2' model showed the average C statistic was 0.63 (95% CI 0.59-0.67), and the expected/observed ratio of events varied considerably across studies (95% prediction interval for E/O ratio when the model was applied in practice was 0.75-1.19). There is a need for models with better predictive performance but, given the large amount of work already conducted, further improvement of existing models based on conventional risk factors is perhaps unlikely. Research to identify new risk factors with large additionally predictive ability is therefore needed, alongside clearer reporting and continual validation of new models as they develop.

Prediction of lung function response for populations exposed to a wide range of ozone conditions

EPA Science Inventory

Abstract Context: A human exposure-response (E-R) model that has previously been demonstrated to accurately predict population mean FEV1 response to ozone exposure has been proposed as the foundation for future risk assessments for ambient ozone. Objective: Fit the origi...

Future methods in pharmacy practice research.

PubMed

Almarsdottir, A B; Babar, Z U D

2016-06-01

This article describes the current and future practice of pharmacy scenario underpinning and guiding this research and then suggests future directions and strategies for such research. First, it sets the scene by discussing the key drivers which could influence the change in pharmacy practice research. These are demographics, technology and professional standards. Second, deriving from this, it seeks to predict and forecast the future shifts in use of methodologies. Third, new research areas and availability of data impacting on future methods are discussed. These include the impact of aging information technology users on healthcare, understanding and responding to cultural and social disparities, implementing multidisciplinary initiatives to improve health care, medicines optimization and predictive risk analysis, and pharmacy as business and health care institution. Finally, implications of the trends for pharmacy practice research methods are discussed.

Developing predictive models for return to work using the Military Power, Performance and Prevention (MP3) musculoskeletal injury risk algorithm: a study protocol for an injury risk assessment programme.

PubMed

Rhon, Daniel I; Teyhen, Deydre S; Shaffer, Scott W; Goffar, Stephen L; Kiesel, Kyle; Plisky, Phil P

2018-02-01

Musculoskeletal injuries are a primary source of disability in the US Military, and low back pain and lower extremity injuries account for over 44% of limited work days annually. History of prior musculoskeletal injury increases the risk for future injury. This study aims to determine the risk of injury after returning to work from a previous injury. The objective is to identify criteria that can help predict likelihood for future injury or re-injury. There will be 480 active duty soldiers recruited from across four medical centres. These will be patients who have sustained a musculoskeletal injury in the lower extremity or lumbar/thoracic spine, and have now been cleared to return back to work without any limitations. Subjects will undergo a battery of physical performance tests and fill out sociodemographic surveys. They will be followed for a year to identify any musculoskeletal injuries that occur. Prediction algorithms will be derived using regression analysis from performance and sociodemographic variables found to be significantly different between injured and non-injured subjects. Due to the high rates of injuries, injury prevention and prediction initiatives are growing. This is the first study looking at predicting re-injury rates after an initial musculoskeletal injury. In addition, multivariate prediction models appear to have move value than models based on only one variable. This approach aims to validate a multivariate model used in healthy non-injured individuals to help improve variables that best predict the ability to return to work with lower risk of injury, after a recent musculoskeletal injury. NCT02776930. 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/.

Isokinetic strength assessment offers limited predictive validity for detecting risk of future hamstring strain in sport: a systematic review and meta-analysis.

PubMed

Green, Brady; Bourne, Matthew N; Pizzari, Tania

2018-03-01

To examine the value of isokinetic strength assessment for predicting risk of hamstring strain injury, and to direct future research into hamstring strain injuries. Systematic review. Database searches for Medline, CINAHL, Embase, AMED, AUSPORT, SPORTDiscus, PEDro and Cochrane Library from inception to April 2017. Manual reference checks, ahead-of-press and citation tracking. Prospective studies evaluating isokinetic hamstrings, quadriceps and hip extensor strength testing as a risk factor for occurrence of hamstring muscle strain. Independent search result screening. Risk of bias assessment by independent reviewers using Quality in Prognosis Studies tool. Best evidence synthesis and meta-analyses of standardised mean difference (SMD). Twelve studies were included, capturing 508 hamstring strain injuries in 2912 athletes. Isokinetic knee flexor, knee extensor and hip extensor outputs were examined at angular velocities ranging 30-300°/s, concentric or eccentric, and relative (Nm/kg) or absolute (Nm) measures. Strength ratios ranged between 30°/s and 300°/s. Meta-analyses revealed a small, significant predictive effect for absolute (SMD=-0.16, P=0.04, 95% CI -0.31 to -0.01) and relative (SMD=-0.17, P=0.03, 95% CI -0.33 to -0.014) eccentric knee flexor strength (60°/s). No other testing speed or strength ratio showed statistical association. Best evidence synthesis found over half of all variables had moderate or strong evidence for no association with future hamstring injury. Despite an isolated finding for eccentric knee flexor strength at slow speeds, the role and application of isokinetic assessment for predicting hamstring strain risk should be reconsidered, particularly given costs and specialised training required. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Plaque Structural Stress Estimations Improve Prediction of Future Major Adverse Cardiovascular Events After Intracoronary Imaging.

PubMed

Brown, Adam J; Teng, Zhongzhao; Calvert, Patrick A; Rajani, Nikil K; Hennessy, Orla; Nerlekar, Nitesh; Obaid, Daniel R; Costopoulos, Charis; Huang, Yuan; Hoole, Stephen P; Goddard, Martin; West, Nick E J; Gillard, Jonathan H; Bennett, Martin R

2016-06-01

Although plaque rupture is responsible for most myocardial infarctions, few high-risk plaques identified by intracoronary imaging actually result in future major adverse cardiovascular events (MACE). Nonimaging markers of individual plaque behavior are therefore required. Rupture occurs when plaque structural stress (PSS) exceeds material strength. We therefore assessed whether PSS could predict future MACE in high-risk nonculprit lesions identified on virtual-histology intravascular ultrasound. Baseline nonculprit lesion features associated with MACE during long-term follow-up (median: 1115 days) were determined in 170 patients undergoing 3-vessel virtual-histology intravascular ultrasound. MACE was associated with plaque burden ≥70% (hazard ratio: 8.6; 95% confidence interval, 2.5-30.6; P<0.001) and minimal luminal area ≤4 mm(2) (hazard ratio: 6.6; 95% confidence interval, 2.1-20.1; P=0.036), although absolute event rates for high-risk lesions remained <10%. PSS derived from virtual-histology intravascular ultrasound was subsequently estimated in nonculprit lesions responsible for MACE (n=22) versus matched control lesions (n=22). PSS showed marked heterogeneity across and between similar lesions but was significantly increased in MACE lesions at high-risk regions, including plaque burden ≥70% (13.9±11.5 versus 10.2±4.7; P<0.001) and thin-cap fibroatheroma (14.0±8.9 versus 11.6±4.5; P=0.02). Furthermore, PSS improved the ability of virtual-histology intravascular ultrasound to predict MACE in plaques with plaque burden ≥70% (adjusted log-rank, P=0.003) and minimal luminal area ≤4 mm(2) (P=0.002). Plaques responsible for MACE had larger superficial calcium inclusions, which acted to increase PSS (P<0.05). Baseline PSS is increased in plaques responsible for MACE and improves the ability of intracoronary imaging to predict events. Biomechanical modeling may complement plaque imaging for risk stratification of coronary nonculprit lesions. © 2016 American Heart Association, Inc.

The Theory of Planned Behavior as a Predictor of HIV Testing Intention.

PubMed

Ayodele, Olabode

2017-03-01

This investigation tests the theory of planned behavior (TPB) as a predictor of HIV testing intention among Nigerian university undergraduate students. A cross-sectional study of 392 students was conducted using a self-administered structured questionnaire that measured socio-demographics, perceived risk of human immunodeficiency virus (HIV) infection, and TPB constructs. Analysis was based on 273 students who had never been tested for HIV. Hierarchical multiple regression analysis assessed the applicability of the TPB in predicting HIV testing intention and additional predictive value of perceived risk of HIV infection. The prediction model containing TPB constructs explained 35% of the variance in HIV testing intention, with attitude and perceived behavioral control making significant and unique contributions to intention. Perceived risk of HIV infection contributed marginally (2%) but significantly to the final prediction model. Findings supported the TPB in predicting HIV testing intention. Although future studies must determine the generalizability of these results, the findings highlight the importance of perceived behavioral control, attitude, and perceived risk of HIV infection in the prediction of HIV testing intention among students who have not previously tested for HIV.

Predicting Health Resilience in Pediatric Type 1 Diabetes: A Test of the Resilience Model Framework.

PubMed

Rohan, Jennifer M; Huang, Bin; Pendley, Jennifer Shroff; Delamater, Alan; Dolan, Lawrence; Reeves, Grafton; Drotar, Dennis

2015-10-01

This research examined whether individual and family-level factors during the transition from late childhood to early adolescence protected individuals from an increased risk of poor glycemic control across time, which is a predictor of future diabetes-related complications (i.e., health resilience). This longitudinal, multisite study included 239 patients with type 1 diabetes and their caregivers. Glycemic control was based on hemoglobin A1c. Individual and family-level factors included: demographic variables, youth behavioral regulation, adherence (frequency of blood glucose monitoring), diabetes self-management, level of parental support for diabetes autonomy, level of youth mastery and responsibility for diabetes management, and diabetes-related family conflict. Longitudinal mixed-effects logistic regression indicated that testing blood glucose more frequently, better self-management, and less diabetes-related family conflict were indicators of health resilience. Multiple individual and family-level factors predicted risk for future health complications. Future research should develop interventions targeting specific individual and family-level factors to sustain glycemic control within recommended targets, which reduces the risk of developing future health complications during the transition to adolescence and adulthood. © The Author 2015. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Peer Deviance, Parental Divorce, and Genetic Risk in the Prediction of Drug Abuse in a Nationwide Swedish Sample

PubMed Central

Kendler, Kenneth S.; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan

2014-01-01

IMPORTANCE Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA). OBJECTIVES To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels. DESIGN, SETTING, AND PARTICIPANTS Studies of future DA registration in 1 401 698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA. MAIN OUTCOMES AND MEASURES Drug abuse recorded in medical, legal, or pharmacy registry records. RESULTS Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure. CONCLUSIONS AND RELEVANCE With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors. PMID:24576925

Peer deviance, parental divorce, and genetic risk in the prediction of drug abuse in a nationwide Swedish sample: evidence of environment-environment and gene-environment interaction.

PubMed

Kendler, Kenneth S; Ohlsson, Henrik; Sundquist, Kristina; Sundquist, Jan

2014-04-01

Peer deviance (PD) strongly predicts externalizing psychopathologic conditions but has not been previously assessable in population cohorts. We sought to develop such an index of PD and to clarify its effects on risk of drug abuse (DA). To examine how strongly PD increases the risk of DA and whether this community-level liability indicator interacts with key DA risk factors at the individual and family levels. Studies of future DA registration in 1,401,698 Swedish probands born from January 1, 1970, through December 31, 1985, and their adolescent peers in approximately 9200 small community areas. Peer deviance was defined as the proportion of individuals born within 5 years of the proband living in the same small community when the proband was 15 years old who eventually were registered for DA. Drug abuse recorded in medical, legal, or pharmacy registry records. Peer deviance was associated with future DA in the proband, with rates of DA in older and male peers more strongly predictive than in younger or female peers. The predictive power of PD was only slightly attenuated by adding measures of community deprivation, collective efficacy, or family socioeconomic status. Probands whose parents were divorced were more sensitive to the pathogenic effects of high PD environments. A robust positive interaction was also seen between genetic risk of DA (indexed by rates of DA in first-, second-, and third-degree relatives) and PD exposure. With sufficient data, PD can be measured in populations and strongly predicts DA. In a nationwide sample, risk factors at the level of the individual (genetic vulnerability), family (parental loss), and community (PD) contribute substantially to risk of DA. Individuals at elevated DA risk because of parental divorce or high genetic liability are more sensitive to the pathogenic effects of PD. Although the effect of our PD measure on DA liability cannot be explained by standard measures of community or family risk, we cannot, with available data, discriminate definitively between the effect of true peer effects and other unmeasured risk factors.

Neuroprediction, Violence, and the Law: Setting the Stage

PubMed Central

Bibas, Stephanos; Grafton, Scott; Kiehl, Kent A.; Mansfield, Andrew; Sinnott-Armstrong, Walter; Gazzaniga, Michael

2014-01-01

In this paper, our goal is to (a) survey some of the legal contexts within which violence risk assessment already plays a prominent role, (b) explore whether developments in neuroscience could potentially be used to improve our ability to predict violence, and (c) discuss whether neuropredictive models of violence create any unique legal or moral problems above and beyond the well worn problems already associated with prediction more generally. In “Violence Risk Assessment and the Law”, we briefly examine the role currently played by predictions of violence in three high stakes legal contexts: capital sentencing (“Violence Risk Assessment and Capital Sentencing”), civil commitment hearings (“Violence Risk Assessment and Civil Commitment”), and “sexual predator” statutes (“Violence Risk Assessment and Sexual Predator Statutes”). In “Clinical vs. Actuarial Violence Risk Assessment”, we briefly examine the distinction between traditional clinical methods of predicting violence and more recently developed actuarial methods, exemplified by the Classification of Violence Risk (COVR) software created by John Monahan and colleagues as part of the MacArthur Study of Mental Disorder and Violence [1]. In “The Neural Correlates of Psychopathy”, we explore what neuroscience currently tells us about the neural correlates of violence, using the recent neuroscientific research on psychopathy as our focus. We also discuss some recent advances in both data collection (“Cutting-Edge Data Collection: Genetically Informed Neuroimaging”) and data analysis (“Cutting-Edge Data Analysis: Pattern Classification”) that we believe will play an important role when it comes to future neuroscientific research on violence. In “The Potential Promise of Neuroprediction”, we discuss whether neuroscience could potentially be used to improve our ability to predict future violence. Finally, in “The Potential Perils of Neuroprediction”, we explore some potential evidentiary (“Evidentiary Issues”), constitutional (“Constitutional Issues”), and moral (“Moral Issues”) issues that may arise in the context of the neuroprediction of violence. PMID:25083168

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.

Accurately Predicting Future Reading Difficulty for Bilingual Latino Children at Risk for Language Impairment

ERIC Educational Resources Information Center

Petersen, Douglas B.; Gillam, Ronald B.

2013-01-01

Sixty-three bilingual Latino children who were at risk for language impairment were administered reading-related measures in English and Spanish (letter identification, phonological awareness, rapid automatized naming, and sentence repetition) and descriptive measures including English language proficiency (ELP), language ability (LA),…

The 12-lead electrocardiogram and risk of sudden death: current utility and future prospects.

PubMed

Narayanan, Kumar; Chugh, Sumeet S

2015-10-01

More than 100 years after it was first invented, the 12-lead electrocardiogram (ECG) continues to occupy an important place in the diagnostic armamentarium of the practicing clinician. With the recognition of relatively rare but important clinical entities such as Wolff-Parkinson-White and the long QT syndrome, this clinical tool was firmly established as a test for assessing risk of sudden cardiac death (SCD). However, over the past two decades the role of the ECG in risk prediction for common forms of SCD, for example in patients with coronary artery disease, has been the focus of considerable investigation. Especially in light of the limitations of current risk stratification approaches, there is a renewed focus on this broadly available and relatively inexpensive test. Various abnormalities of depolarization and repolarization on the ECG have been linked to SCD risk; however, more focused work is needed before they can be deployed in the clinical arena. The present review summarizes the current knowledge on various ECG risk markers for prediction of SCD and discusses some future directions in this field. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2015. For permissions please email: journals.permissions@oup.com.

A new perspective on optimal care for patients with COPD.

PubMed

Postma, Dirkje; Anzueto, Antonio; Calverley, Peter; Jenkins, Christine; Make, Barry J; Sciurba, Frank C; Similowski, Thomas; van der Molen, Thys; Eriksson, Göran

2011-06-01

Worldwide, clinicians face the task of providing millions of patients with the best possible treatment and management of COPD. Currently, management primarily involves short-term 'here-and-now' goals, targeting immediate patient benefit. However, although there is considerable knowledge available to assist clinicians in minimising the current impact of COPD on patients, relatively little is known about which dominant factors predict future risks. These predictors may vary for different outcomes, such as exacerbations, mortality, co-morbidities, and the long-term consequences of COPD. We propose a new paradigm to achieve 'optimal COPD care' based on the concept that here-and-now goals should be integrated with goals to improve long-term outcomes and reduce future risks. Whilst knowledge on risk factors for poorer outcomes in COPD is growing and some data exist on positive effects of pharmacological interventions, information on defining the benefits of all commonly used interventions for reducing the risk of various future disease outcomes is still scarce. Greater insight is needed into the relationships between the two pillars of optimal COPD care: 'best current control' and 'future risk reduction'. This broader approach to disease management should result in improved care for every COPD patient now and into the future.

An integrated approach to evaluating alternative risk prediction strategies: a case study comparing alternative approaches for preventing invasive fungal disease.

PubMed

Sadique, Z; Grieve, R; Harrison, D A; Jit, M; Allen, E; Rowan, K M

2013-12-01

This article proposes an integrated approach to the development, validation, and evaluation of new risk prediction models illustrated with the Fungal Infection Risk Evaluation study, which developed risk models to identify non-neutropenic, critically ill adult patients at high risk of invasive fungal disease (IFD). Our decision-analytical model compared alternative strategies for preventing IFD at up to three clinical decision time points (critical care admission, after 24 hours, and end of day 3), followed with antifungal prophylaxis for those judged "high" risk versus "no formal risk assessment." We developed prognostic models to predict the risk of IFD before critical care unit discharge, with data from 35,455 admissions to 70 UK adult, critical care units, and validated the models externally. The decision model was populated with positive predictive values and negative predictive values from the best-fitting risk models. We projected lifetime cost-effectiveness and expected value of partial perfect information for groups of parameters. The risk prediction models performed well in internal and external validation. Risk assessment and prophylaxis at the end of day 3 was the most cost-effective strategy at the 2% and 1% risk threshold. Risk assessment at each time point was the most cost-effective strategy at a 0.5% risk threshold. Expected values of partial perfect information were high for positive predictive values or negative predictive values (£11 million-£13 million) and quality-adjusted life-years (£11 million). It is cost-effective to formally assess the risk of IFD for non-neutropenic, critically ill adult patients. This integrated approach to developing and evaluating risk models is useful for informing clinical practice and future research investment. © 2013 International Society for Pharmacoeconomics and Outcomes Research (ISPOR) Published by International Society for Pharmacoeconomics and Outcomes Research (ISPOR) All rights reserved.

Do We Need Better Climate Predictions to Adapt to a Changing Climate? (Invited)

NASA Astrophysics Data System (ADS)

Dessai, S.; Hulme, M.; Lempert, R.; Pielke, R., Jr.

2009-12-01

Based on a series of international scientific assessments, climate change has been presented to society as a major problem that needs urgently to be tackled. The science that underpins these assessments has been pre-dominantly from the realm of the natural sciences and central to this framing have been ‘projections’ of future climate change (and its impacts on environment and society) under various greenhouse gas emissions scenarios and using a variety of climate model predictions with embedded assumptions. Central to much of the discussion surrounding adaptation to climate change is the claim - explicit or implicit - that decision makers need accurate and increasingly precise assessments of future impacts of climate change in order to adapt successfully. If true, this claim places a high premium on accurate and precise climate predictions at a range of geographical and temporal scales; such predictions therefore become indispensable, and indeed a prerequisite for, effective adaptation decision-making. But is effective adaptation tied to the ability of the scientific enterprise to predict future climate with accuracy and precision? If so, this may impose a serious and intractable limit on adaptation. This paper proceeds in three sections. It first gathers evidence of claims that climate prediction is necessary for adaptation decision-making. This evidence is drawn from peer-reviewed literature and from published science funding strategies and government policy in a number of different countries. The second part discusses the challenges of climate prediction and why science will consistently be unable to provide accurate and precise predictions of future climate relevant for adaptation (usually at the local/regional level). Section three discusses whether these limits to future foresight represent a limit to adaptation, arguing that effective adaptation need not be limited by a general inability to predict future climate. Given the deep uncertainties involved in climate prediction (and even more so in the prediction of climate impacts) and given that climate is usually only one factor in decisions aimed at climate adaptation, we conclude that the ‘predict and provide’ approach to science in support of climate change adaptation is largely flawed. We consider other important areas of public policy fraught with uncertainty - e.g. earthquake risk, national security, public health - where such a ‘predict and provide’ approach is not attempted. Instead of relying on an approach which has climate prediction (and consequent risk assessment) at its heart - which because of the associated epistemological limits to prediction will consequently act as an apparent limit to adaptation - we need to view adaptation differently, in a manner that opens up options for decision making under uncertainty. We suggest an approach which examines the robustness of adaptation strategies/policies/activities to the myriad of uncertainties that face us in the future, only one of which is the state of climate.

Regional analysis of drought and heat impacts on forests: current and future science directions.

PubMed

Law, Beverly E

2014-12-01

Accurate assessments of forest response to current and future climate and human actions are needed at regional scales. Predicting future impacts on forests will require improved analysis of species-level adaptation, resilience, and vulnerability to mortality. Land system models can be enhanced by creating trait-based groupings of species that better represent climate sensitivity, such as risk of hydraulic failure from drought. This emphasizes the need for more coordinated in situ and remote sensing observations to track changes in ecosystem function, and to improve model inputs, spatio-temporal diagnosis, and predictions of future conditions, including implications of actions to mitigate climate change. © 2014 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Risk adjustment model of credit life insurance using a genetic algorithm

NASA Astrophysics Data System (ADS)

Saputra, A.; Sukono; Rusyaman, E.

2018-03-01

In managing the risk of credit life insurance, insurance company should acknowledge the character of the risks to predict future losses. Risk characteristics can be learned in a claim distribution model. There are two standard approaches in designing the distribution model of claims over the insurance period i.e, collective risk model and individual risk model. In the collective risk model, the claim arises when risk occurs is called individual claim, accumulation of individual claim during a period of insurance is called an aggregate claim. The aggregate claim model may be formed by large model and a number of individual claims. How the measurement of insurance risk with the premium model approach and whether this approach is appropriate for estimating the potential losses occur in the future. In order to solve the problem Genetic Algorithm with Roulette Wheel Selection is used.

Predicting asthma exacerbations in children.

PubMed

Forno, Erick; Celedón, Juan C

2012-01-01

This review critically assesses recently published literature on predicting asthma exacerbations in children, while also providing general recommendations for future research in this field. Current evidence suggests that every effort should be made to provide optimal treatment to achieve adequate asthma control, as this will significantly reduce the risk of severe disease exacerbations. Children who have had at least one asthma exacerbation in the previous year are at highest risk for subsequent exacerbations, regardless of disease severity and/or control. Although several tools and biomarkers to predict asthma exacerbations have been recently developed, these approaches need further validation and/or have only had partial success in identifying children at risk. Although considerable progress has been made, much remains to be done. Future studies should clearly differentiate severe asthma exacerbations due to inadequate asthma control from those occurring in children whose asthma is well controlled, utilize standardized definitions of asthma exacerbations, and use a systematic approach to identify the best predictors after accounting for the multiple dimensions of the problem. Our ability to correctly predict the development of severe asthma exacerbations in an individual child should improve in parallel with increased knowledge and/or understanding of the complex interactions among genetic, environmental (e.g. viral infections) and lifestyle (e.g. adherence to treatment) factors underlying these events.

Predicting risky choices from brain activity patterns

PubMed Central

Helfinstein, Sarah M.; Schonberg, Tom; Congdon, Eliza; Karlsgodt, Katherine H.; Mumford, Jeanette A.; Sabb, Fred W.; Cannon, Tyrone D.; London, Edythe D.; Bilder, Robert M.; Poldrack, Russell A.

2014-01-01

Previous research has implicated a large network of brain regions in the processing of risk during decision making. However, it has not yet been determined if activity in these regions is predictive of choices on future risky decisions. Here, we examined functional MRI data from a large sample of healthy subjects performing a naturalistic risk-taking task and used a classification analysis approach to predict whether individuals would choose risky or safe options on upcoming trials. We were able to predict choice category successfully in 71.8% of cases. Searchlight analysis revealed a network of brain regions where activity patterns were reliably predictive of subsequent risk-taking behavior, including a number of regions known to play a role in control processes. Searchlights with significant predictive accuracy were primarily located in regions more active when preparing to avoid a risk than when preparing to engage in one, suggesting that risk taking may be due, in part, to a failure of the control systems necessary to initiate a safe choice. Additional analyses revealed that subject choice can be successfully predicted with minimal decrements in accuracy using highly condensed data, suggesting that information relevant for risky choice behavior is encoded in coarse global patterns of activation as well as within highly local activation within searchlights. PMID:24550270

Extinctions in ancient and modern seas.

PubMed

Harnik, Paul G; Lotze, Heike K; Anderson, Sean C; Finkel, Zoe V; Finnegan, Seth; Lindberg, David R; Liow, Lee Hsiang; Lockwood, Rowan; McClain, Craig R; McGuire, Jenny L; O'Dea, Aaron; Pandolfi, John M; Simpson, Carl; Tittensor, Derek P

2012-11-01

In the coming century, life in the ocean will be confronted with a suite of environmental conditions that have no analog in human history. Thus, there is an urgent need to determine which marine species will adapt and which will go extinct. Here, we review the growing literature on marine extinctions and extinction risk in the fossil, historical, and modern records to compare the patterns, drivers, and biological correlates of marine extinctions at different times in the past. Characterized by markedly different environmental states, some past periods share common features with predicted future scenarios. We highlight how the different records can be integrated to better understand and predict the impact of current and projected future environmental changes on extinction risk in the ocean. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multimethod prediction of child abuse risk in an at-risk sample of male intimate partner violence offenders.

PubMed

Rodriguez, Christina M; Gracia, Enrique; Lila, Marisol

2016-10-01

The vast majority of research on child abuse potential has concentrated on women demonstrating varying levels of risk of perpetrating physical child abuse. In contrast, the current study considered factors predictive of physical child abuse potential in a group of 70 male intimate partner violence offenders, a group that would represent a likely high risk group. Elements of Social Information Processing theory were evaluated, including pre-existing schemas of empathy, anger, and attitudes approving of parent-child aggression considered as potential moderators of negative attributions of child behavior. To lend methodological rigor, the study also utilized multiple measures and multiple methods, including analog tasks, to predict child abuse risk. Contrary to expectations, findings did not support the role of anger independently predicting child abuse risk in this sample of men. However, preexisting beliefs approving of parent-child aggression, lower empathy, and more negative child behavior attributions independently predicted abuse potential; in addition, greater anger, poorer empathy, and more favorable attitudes toward parent-child aggression also exacerbated men's negative child attributions to further elevate their child abuse risk. Future work is encouraged to consider how factors commonly considered in women parallel or diverge from those observed to elevate child abuse risk in men of varying levels of risk. Copyright © 2016 Elsevier Ltd. All rights reserved.

External validation of the Probability of repeated admission (Pra) risk prediction tool in older community-dwelling people attending general practice: a prospective cohort study.

PubMed

Wallace, Emma; McDowell, Ronald; Bennett, Kathleen; Fahey, Tom; Smith, Susan M

2016-11-14

Emergency admission is associated with the potential for adverse events in older people and risk prediction models are available to identify those at highest risk of admission. The aim of this study was to externally validate and compare the performance of the Probability of repeated admission (Pra) risk model and a modified version (incorporating a multimorbidity measure) in predicting emergency admission in older community-dwelling people. 15 general practices (GPs) in the Republic of Ireland. n=862, ≥70 years, community-dwelling people prospectively followed up for 2 years (2010-2012). Pra risk model (original and modified) calculated for baseline year where ≥0.5 denoted high risk (patient questionnaire, GP medical record review) of future emergency admission. Emergency admission over 1 year (GP medical record review). descriptive statistics, model discrimination (c-statistic) and calibration (Hosmer-Lemeshow statistic). Of 862 patients, a total of 154 (18%) had ≥1 emergency admission(s) in the follow-up year. 63 patients (7%) were classified as high risk by the original Pra and of these 26 (41%) were admitted. The modified Pra classified 391 (45%) patients as high risk and 103 (26%) were subsequently admitted. Both models demonstrated only poor discrimination (original Pra: c-statistic 0.65 (95% CI 0.61 to 0.70); modified Pra: c-statistic 0.67 (95% CI 0.62 to 0.72)). When categorised according to risk-category model, specificity was highest for the original Pra at cut-point of ≥0.5 denoting high risk (95%), and for the modified Pra at cut-point of ≥0.7 (95%). Both models overestimated the number of admissions across all risk strata. While the original Pra model demonstrated poor discrimination, model specificity was high and a small number of patients identified as high risk. Future validation studies should examine higher cut-points denoting high risk for the modified Pra, which has practical advantages in terms of application in GP. The original Pra tool may have a role in identifying higher-risk community-dwelling older people for inclusion in future trials aiming to reduce emergency admissions. 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/.

Serum TSH within the reference range as a predictor of future hypothyroidism and hyperthyroidism: 11-year follow-up of the HUNT Study in Norway.

PubMed

Åsvold, Bjørn O; Vatten, Lars J; Midthjell, Kristian; Bjøro, Trine

2012-01-01

Serum TSH in the upper part of the reference range may sometimes be a response to autoimmune thyroiditis in early stage and may therefore predict future hypothyroidism. Conversely, relatively low serum TSH could predict future hyperthyroidism. The objective of the study was to assess TSH within the reference range and subsequent risk of hypothyroidism and hyperthyroidism. This was a prospective population-based study with linkage to the Norwegian Prescription Database. A total of 10,083 women and 5,023 men without previous thyroid disease who had a baseline TSH of 0.20-4.5 mU/liter and who participated at a follow-up examination 11 yr later. Predicted probabilities of developing hypothyroidism or hyperthyroidism during follow-up, by categories of baseline TSH, were estimated. During 11 yr of follow-up, 3.5% of women and 1.3% of men developed hypothyroidism, and 1.1% of women and 0.6% of men developed hyperthyroidism. In both sexes, the baseline TSH was positively associated with the risk of subsequent hypothyroidism. The risk increased gradually from TSH of 0.50-1.4 mU/liter [women, 1.1%, 95% confidence interval (CI) 0.8-1.4; men, 0.3%, 95% CI 0.1-0.6] to a TSH of 4.0-4.5 mU/liter (women, 31.5%, 95% CI 24.6-39.3; men, 14.7%, 95% CI 7.7-26.2). The risk of hyperthyroidism was higher in women with a baseline TSH of 0.20-0.49 mU/liter (3.9%, 95% CI 1.8-8.4) than in women with a TSH of 0.50-0.99 mU/liter (1.4%, 95% CI 0.9-2.1) or higher (∼1.0%). TSH within the reference range is positively and strongly associated with the risk of future hypothyroidism. TSH at the lower limit of the reference range may be associated with an increased risk of hyperthyroidism.

The use of machine learning for the identification of peripheral artery disease and future mortality risk.

PubMed

Ross, Elsie Gyang; Shah, Nigam H; Dalman, Ronald L; Nead, Kevin T; Cooke, John P; Leeper, Nicholas J

2016-11-01

A key aspect of the precision medicine effort is the development of informatics tools that can analyze and interpret "big data" sets in an automated and adaptive fashion while providing accurate and actionable clinical information. The aims of this study were to develop machine learning algorithms for the identification of disease and the prognostication of mortality risk and to determine whether such models perform better than classical statistical analyses. Focusing on peripheral artery disease (PAD), patient data were derived from a prospective, observational study of 1755 patients who presented for elective coronary angiography. We employed multiple supervised machine learning algorithms and used diverse clinical, demographic, imaging, and genomic information in a hypothesis-free manner to build models that could identify patients with PAD and predict future mortality. Comparison was made to standard stepwise linear regression models. Our machine-learned models outperformed stepwise logistic regression models both for the identification of patients with PAD (area under the curve, 0.87 vs 0.76, respectively; P = .03) and for the prediction of future mortality (area under the curve, 0.76 vs 0.65, respectively; P = .10). Both machine-learned models were markedly better calibrated than the stepwise logistic regression models, thus providing more accurate disease and mortality risk estimates. Machine learning approaches can produce more accurate disease classification and prediction models. These tools may prove clinically useful for the automated identification of patients with highly morbid diseases for which aggressive risk factor management can improve outcomes. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

A Novel Risk Stratification to Predict Local-Regional Failures in Urothelial Carcinoma of the Bladder After Radical Cystectomy

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

Baumann, Brian C.; Guzzo, Thomas J.; He Jiwei

2013-01-01

Purpose: Local-regional failures (LF) following radical cystectomy (RC) plus pelvic lymph node dissection (PLND) with or without chemotherapy for invasive urothelial bladder carcinoma are more common than previously reported. Adjuvant radiation therapy (RT) could reduce LF but currently has no defined role because of previously reported morbidity. Modern techniques with improved normal tissue sparing have rekindled interest in RT. We assessed the risk of LF and determined those factors that predict recurrence to facilitate patient selection for future adjuvant RT trials. Methods and Materials: From 1990-2008, 442 patients with urothelial bladder carcinoma at University of Pennsylvania were prospectively followed aftermore » RC plus PLND with or without chemotherapy with routine pelvic computed tomography (CT) or magnetic resonance imaging (MRI). One hundred thirty (29%) patients received chemotherapy. LF was any pelvic failure detected before or within 3 months of distant failure. Competing risk analyses identified factors predicting increased LF risk. Results: On univariate analysis, pathologic stage {>=}pT3, <10 nodes removed, positive margins, positive nodes, hydronephrosis, lymphovascular invasion, and mixed histology significantly predicted LF; node density was marginally predictive, but use of chemotherapy, number of positive nodes, type of surgical diversion, age, gender, race, smoking history, and body mass index were not. On multivariate analysis, only stage {>=}pT3 and <10 nodes removed were significant independent LF predictors with hazard ratios of 3.17 and 2.37, respectively (P<.01). Analysis identified 3 patient subgroups with significantly different LF risks: low-risk ({<=}pT2), intermediate-risk ({>=}pT3 and {>=}10 nodes removed), and high-risk ({>=}pT3 and <10 nodes) with 5-year LF rates of 8%, 23%, and 42%, respectively (P<.01). Conclusions: This series using routine CT and MRI surveillance to detect LF confirms that such failures are relatively common in cases of locally advanced disease and provides a rubric based on pathological stage and number of nodes removed that stratifies patients into 3 groups with significantly different LF risks to simplify patient selection for future adjuvant radiation therapy trials.« less

White Matter Integrity, Substance Use, and Risk Taking in Adolescence

PubMed Central

Jacobus, Joanna; Thayer, Rachel E.; Trim, Ryan S.; Bava, Sunita; Frank, Lawrence R.; Tapert, Susan F.

2012-01-01

White matter development is important for efficient communication between brain regions, higher order cognitive functioning, and complex behaviors. Adolescents have a higher propensity for engaging in risky behaviors, yet few studies have explored associations between white matter integrity and risk taking directly. Altered white matter integrity in mid-adolescence was hypothesized to predict subsequent risk taking behaviors 1.5 years later. Adolescent substance users (predominantly alcohol and marijuana, n=47) and demographically similar non-users (n=49) received diffusion tensor imaging at baseline (ages 16–19), and risk taking measures at both baseline and an 18-month follow-up (i.e., at ages 17–20). Brain regions of interest were: fornix, superior corona radiata, superior longitudinal fasciculus, and superior fronto-occipital fasciculus. In substance using youth (n=47), lower white matter integrity at baseline in the fornix and superior corona radiata predicted follow-up substance use (ΔR2 =10–12%, ps < .01), and baseline fornix integrity predicted follow-up delinquent behaviors (ΔR2 = 10%, p < .01) 1.5 years later. Poorer fronto-limbic white matter integrity was linked to a greater propensity for future risk taking behaviors among youth who initiated heavy substance use by mid-adolescence. Most notable were relationships between projection and limbic system fibers and future substance use frequency. Subcortical white matter coherence along with an imbalance between the maturation levels in cognitive control and reward systems may disadvantage the resistance to engage in risk taking behaviors during adolescence. PMID:22564204

White matter integrity, substance use, and risk taking in adolescence.

PubMed

Jacobus, Joanna; Thayer, Rachel E; Trim, Ryan S; Bava, Sunita; Frank, Lawrence R; Tapert, Susan F

2013-06-01

White matter development is important for efficient communication between brain regions, higher order cognitive functioning, and complex behaviors. Adolescents have a higher propensity for engaging in risky behaviors, yet few studies have explored associations between white matter integrity and risk taking directly. Altered white matter integrity in mid-adolescence was hypothesized to predict subsequent risk taking behaviors 1.5 years later. Adolescent substance users (predominantly alcohol and marijuana, n = 47) and demographically similar nonusers (n = 49) received diffusion tensor imaging at baseline (ages 16-19), and risk taking measures at both baseline and an 18-month follow-up (i.e., at ages 17-20). Brain regions of interest were the fornix, superior corona radiata, superior longitudinal fasciculus, and superior fronto-occipital fasciculus. In substance-using youth (n = 47), lower white matter integrity at baseline in the fornix and superior corona radiata predicted follow-up substance use (ΔR2 = 10-12%, ps < .01), and baseline fornix integrity predicted follow-up delinquent behaviors (ΔR2 = 10%, p < .01) 1.5 years later. Poorer fronto-limbic white matter integrity was linked to a greater propensity for future risk taking behaviors among youth who initiated heavy substance use by mid-adolescence. Most notable were relationships between projection and limbic-system fibers and future substance-use frequency. Subcortical white matter coherence, along with an imbalance between the maturation levels in cognitive control and reward systems, may disadvantage the resistance to engage in risk taking behaviors during adolescence. 2013 APA, all rights reserved

Combining the ASA Physical Classification System and Continuous Intraoperative Surgical Apgar Score Measurement in Predicting Postoperative Risk.

PubMed

Jering, Monika Zdenka; Marolen, Khensani N; Shotwell, Matthew S; Denton, Jason N; Sandberg, Warren S; Ehrenfeld, Jesse Menachem

2015-11-01

The surgical Apgar score predicts major 30-day postoperative complications using data assessed at the end of surgery. We hypothesized that evaluating the surgical Apgar score continuously during surgery may identify patients at high risk for postoperative complications. We retrospectively identified general, vascular, and general oncology patients at Vanderbilt University Medical Center. Logistic regression methods were used to construct a series of predictive models in order to continuously estimate the risk of major postoperative complications, and to alert care providers during surgery should the risk exceed a given threshold. Area under the receiver operating characteristic curve (AUROC) was used to evaluate the discriminative ability of a model utilizing a continuously measured surgical Apgar score relative to models that use only preoperative clinical factors or continuously monitored individual constituents of the surgical Apgar score (i.e. heart rate, blood pressure, and blood loss). AUROC estimates were validated internally using a bootstrap method. 4,728 patients were included. Combining the ASA PS classification with continuously measured surgical Apgar score demonstrated improved discriminative ability (AUROC 0.80) in the pooled cohort compared to ASA (0.73) and the surgical Apgar score alone (0.74). To optimize the tradeoff between inadequate and excessive alerting with future real-time notifications, we recommend a threshold probability of 0.24. Continuous assessment of the surgical Apgar score is predictive for major postoperative complications. In the future, real-time notifications might allow for detection and mitigation of changes in a patient's accumulating risk of complications during a surgical procedure.

Comparison of risk assessment based on clinical judgement and Cariogram in addition to patient perceived treatment need.

PubMed

Hänsel Petersson, Gunnel; Åkerman, Sigvard; Isberg, Per-Erik; Ericson, Dan

2016-07-07

Predicting future risk for oral diseases, treatment need and prognosis are tasks performed daily in clinical practice. A large variety of methods have been reported, ranging from clinical judgement or "gut feeling" or even patient interviewing, to complex assessments of combinations of known risk factors. In clinical practice, there is an ongoing continuous search for less complicated and more valid tools for risk assessment. There is also a lack of knowledge how different common methods relates to one another. The aim of this study was to investigate if caries risk assessment (CRA) based on clinical judgement and the Cariogram model give similar results. In addition, to assess which factors from clinical status and history agree best with the CRA based on clinical judgement and how the patient's own perception of future oral treatment need correspond with the sum of examiners risk score. Clinical examinations were performed on randomly selected individuals 20-89 years old living in Skåne, Sweden. In total, 451 individuals were examined, 51 % women. The clinical examination included caries detection, saliva samples and radiographic examination together with history and a questionnaire. The examiners made a risk classification and the authors made a second risk calculation according to the Cariogram. For those assessed as low risk using the Cariogram 69 % also were assessed as low risk based on clinical judgement. For the other risk groups the agreement was lower. Clinical variables that significantly related to CRA based on clinical judgement were DS (decayed surfaces) and combining DS and incipient lesions, DMFT (decayed, missed, filled teeth), plaque amount, history and soft drink intake. Patients' perception of future oral treatment need correlated to some extent with the sum of examiners risk score. The main finding was that CRA based on clinical judgement and the Cariogram model gave similar results for the groups that were predicted at low level of future disease, but not so well for the other groups. CRA based on clinical judgement agreed best with the number of DS plus incipient lesions.

Building and validating a prediction model for paediatric type 1 diabetes risk using next generation targeted sequencing of class II HLA genes.

PubMed

Zhao, Lue Ping; Carlsson, Annelie; Larsson, Helena Elding; Forsander, Gun; Ivarsson, Sten A; Kockum, Ingrid; Ludvigsson, Johnny; Marcus, Claude; Persson, Martina; Samuelsson, Ulf; Örtqvist, Eva; Pyo, Chul-Woo; Bolouri, Hamid; Zhao, Michael; Nelson, Wyatt C; Geraghty, Daniel E; Lernmark, Åke

2017-11-01

It is of interest to predict possible lifetime risk of type 1 diabetes (T1D) in young children for recruiting high-risk subjects into longitudinal studies of effective prevention strategies. Utilizing a case-control study in Sweden, we applied a recently developed next generation targeted sequencing technology to genotype class II genes and applied an object-oriented regression to build and validate a prediction model for T1D. In the training set, estimated risk scores were significantly different between patients and controls (P = 8.12 × 10 -92 ), and the area under the curve (AUC) from the receiver operating characteristic (ROC) analysis was 0.917. Using the validation data set, we validated the result with AUC of 0.886. Combining both training and validation data resulted in a predictive model with AUC of 0.903. Further, we performed a "biological validation" by correlating risk scores with 6 islet autoantibodies, and found that the risk score was significantly correlated with IA-2A (Z-score = 3.628, P < 0.001). When applying this prediction model to the Swedish population, where the lifetime T1D risk ranges from 0.5% to 2%, we anticipate identifying approximately 20 000 high-risk subjects after testing all newborns, and this calculation would identify approximately 80% of all patients expected to develop T1D in their lifetime. Through both empirical and biological validation, we have established a prediction model for estimating lifetime T1D risk, using class II HLA. This prediction model should prove useful for future investigations to identify high-risk subjects for prevention research in high-risk populations. Copyright © 2017 John Wiley & Sons, Ltd.

Predicting hypothetical willingness to participate (WTP) in a future phase III HIV vaccine trial among high-risk adolescents.

PubMed

Giocos, Georgina; Kagee, Ashraf; Swartz, Leslie

2008-11-01

The present study sought to determine whether the Theory of Planned Behaviour predicted stated hypothetical willingness to participate (WTP) in future Phase III HIV vaccine trials among South African adolescents. Hierarchical logistic regression analyses showed that The Theory of Planned Behaviour (TPB) significantly predicted WTP. Of all the predictors, Subjective norms significantly predicted WTP (OR = 1.19, 95% C.I. = 1.06-1.34). A stepwise logistic regression analysis revealed that Subjective Norms (OR = 1.19, 95% C.I. = 1.07-1.34) and Attitude towards participation in an HIV vaccine trial (OR = 1.32, 95% C.I. = 1.00-1.74) were significant predictors of WTP. The addition of Knowledge of HIV vaccines and HIV vaccine trials, Perceived self-risk of HIV infection, Health-promoting behaviours and Attitudes towards HIV/AIDS yielded non-significant results. These findings provide support for the Theory of Reasoned Action (TRA) and suggest that psychosocial factors may play an important role in WTP in Phase III HIV vaccine trials among adolescents.

Predictability of the future development of aggressive behavior of cranial dural arteriovenous fistulas based on decision tree analysis.

PubMed

Satomi, Junichiro; Ghaibeh, A Ammar; Moriguchi, Hiroki; Nagahiro, Shinji

2015-07-01

The severity of clinical signs and symptoms of cranial dural arteriovenous fistulas (DAVFs) are well correlated with their pattern of venous drainage. Although the presence of cortical venous drainage can be considered a potential predictor of aggressive DAVF behaviors, such as intracranial hemorrhage or progressive neurological deficits due to venous congestion, accurate statistical analyses are currently not available. Using a decision tree data mining method, the authors aimed at clarifying the predictability of the future development of aggressive behaviors of DAVF and at identifying the main causative factors. Of 266 DAVF patients, 89 were eligible for analysis. Under observational management, 51 patients presented with intracranial hemorrhage/infarction during the follow-up period. The authors created a decision tree able to assess the risk for the development of aggressive DAVF behavior. Evaluated by 10-fold cross-validation, the decision tree's accuracy, sensitivity, and specificity were 85.28%, 88.33%, and 80.83%, respectively. The tree shows that the main factor in symptomatic patients was the presence of cortical venous drainage. In its absence, the lesion location determined the risk of a DAVF developing aggressive behavior. Decision tree analysis accurately predicts the future development of aggressive DAVF behavior.

Asthma pharmacogenetics and the development of genetic profiles for personalized medicine

PubMed Central

Ortega, Victor E; Meyers, Deborah A; Bleecker, Eugene R

2015-01-01

Human genetics research will be critical to the development of genetic profiles for personalized or precision medicine in asthma. Genetic profiles will consist of gene variants that predict individual disease susceptibility and risk for progression, predict which pharmacologic therapies will result in a maximal therapeutic benefit, and predict whether a therapy will result in an adverse response and should be avoided in a given individual. Pharmacogenetic studies of the glucocorticoid, leukotriene, and β2-adrenergic receptor pathways have focused on candidate genes within these pathways and, in addition to a small number of genome-wide association studies, have identified genetic loci associated with therapeutic responsiveness. This review summarizes these pharmacogenetic discoveries and the future of genetic profiles for personalized medicine in asthma. The benefit of a personalized, tailored approach to health care delivery is needed in the development of expensive biologic drugs directed at a specific biologic pathway. Prior pharmacogenetic discoveries, in combination with additional variants identified in future studies, will form the basis for future genetic profiles for personalized tailored approaches to maximize therapeutic benefit for an individual asthmatic while minimizing the risk for adverse events. PMID:25691813

Clinical history and biologic age predicted falls better than objective functional tests.

PubMed

Gerdhem, Paul; Ringsberg, Karin A M; Akesson, Kristina; Obrant, Karl J

2005-03-01

Fall risk assessment is important because the consequences, such as a fracture, may be devastating. The objective of this study was to find the test or tests that best predicted falls in a population-based sample of elderly women. The fall-predictive ability of a questionnaire, a subjective estimate of biologic age and objective functional tests (gait, balance [Romberg and sway test], thigh muscle strength, and visual acuity) were compared in 984 randomly selected women, all 75 years of age. A recalled fall was the most important predictor for future falls. Only recalled falls and intake of psycho-active drugs independently predicted future falls. Women with at least five of the most important fall predictors (previous falls, conditions affecting the balance, tendency to fall, intake of psychoactive medication, inability to stand on one leg, high biologic age) had an odds ratio of 11.27 (95% confidence interval 4.61-27.60) for a fall (sensitivity 70%, specificity 79%). The more time-consuming objective functional tests were of limited importance for fall prediction. A simple clinical history, the inability to stand on one leg, and a subjective estimate of biologic age were more important as part of the fall risk assessment.

The Joint Effects of Risk Status, Gender, Early Literacy and Cognitive Skills on the Presence of Dyslexia among a Group of High-Risk Chinese Children

ERIC Educational Resources Information Center

Wong, Simpson W. L.; McBride-Chang, Catherine; Lam, Catherine; Chan, Becky; Lam, Fanny W. F.; Doo, Sylvia

2012-01-01

This study sought to examine factors that are predictive of future developmental dyslexia among a group of 5-year-old Chinese children at risk for dyslexia, including 62 children with a sibling who had been previously diagnosed with dyslexia and 52 children who manifested clinical at-risk factors in aspects of language according to testing by…

Can demographic, clinical and treatment-related factors available at hormonal therapy initiation predict non-persistence in women with stage I-III breast cancer?

PubMed

Cahir, Caitriona; Barron, Thomas I; Sharp, Linda; Bennett, Kathleen

2017-03-01

To investigate whether demographic, clinical and treatment-related risk factors known at treatment initiation can be used to reliably predict future hormonal therapy non-persistence in women with breast cancer, and to inform intervention development. Women with stage I-III breast cancer diagnosed 2000-2012 and prescribed hormonal therapy were identified from the National Cancer Registry Ireland (NCRI) and linked to pharmacy claims data from Ireland's Primary Care Reimbursement Services (PCRS). Non-persistence was defined as a treatment gap of ≥180 days within 5 years of initiation. Seventeen demographic, clinical and treatment-related risk factors, identified from a systematic review, were abstracted from the NCRI-PCRS dataset. Multivariate binomial models were used to estimate relative risks (RR) and risk differences (RD) for associations between risk factors and non-persistence. Calibration and discriminative performance of the models were assessed. The analysis was repeated for early non-persistence (<1 year of initiation). Within 5 years of treatment initiation 680 women (19.9%) were non-persistent. Women aged <50 years (adjusted RR 1.41, 95% CI 1.16-1.70) and those prescribed antidepressants (RR 1.22, 95% CI 1.04-1.45) had increased risk of non-persistence. Married women (RR 0.82 95% CI 0.71-0.94) and those with prior medication use (RR 0.62 95% CI 0.51-0.75) had reduced risk of non-persistence. The area under the receiver-operating characteristic (ROC) curve for non-persistence was 0.61. Findings were similar for early non-persistence. The risk prediction model did not discriminate well between women at higher and lower risk of non-persistence at treatment initiation. Future studies should consider other factors, such as psychological characteristics and experience of side-effects.

Market Efficiency and the Risks and Returns of Dynamic Trading Strategies with Commodity Futures

NASA Astrophysics Data System (ADS)

Switzer, Lorne N.; Jiang, Hui

This paper investigates relationships between profits from dynamic trading strategies, risk premium, convenience yields, and net hedging pressures for commodity futures. As a market efficiency study, it crosses a number of disciplines, including traditional finance, behavioral finance, and behavioral psychology. The term structure of oil, gold, copper and soybeans futures markets contains predictive power for the corresponding term premium. However, only oil futures and soybean futures lead their spot premium. Significant momentum profits are identified in both outright futures and spread trading strategies when the spot premium and the term premium are used to form winner and loser portfolios. Profits from active strategies based on winner and loser portfolios are conditioned on market structure and net hedging pressure effects. Dynamic trading strategies based on contracts with extreme backwardation, extreme contango, and extreme hedging pressures are also tested. On average, spread trading outperforms outright futures trading in capturing the term structure risk and hedging pressure risk. For such strategies, long-short the long-term spread offers the greatest and most significant return and it offers the only exploitable trading profits built on the past hedging pressure. The existence of profits from active trading strategies based on winners is consistent with behavioral finance and behavioral psychology models in which market participants irrationally overreact to information and trends.

Body composition indices and predicted cardiovascular disease risk profile among urban dwellers in Malaysia.

PubMed

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

2015-01-01

This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions.

Body Composition Indices and Predicted Cardiovascular Disease Risk Profile among Urban Dwellers in Malaysia

PubMed Central

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Dahlui, Maznah; Majid, Hazreen Abdul

2015-01-01

Objectives. This study aims to compare various body composition indices and their association with a predicted cardiovascular disease (CVD) risk profile in an urban population in Kuala Lumpur, Malaysia. Methods. A cross-sectional survey was conducted in metropolitan Kuala Lumpur, Malaysia, in 2012. Households were selected using a simple random-sampling method, and adult members were invited for medical screening. The Framingham Risk Scoring algorithm was used to predict CVD risk, which was then analyzed in association with body composition measurements, including waist circumference, waist-hip ratio, waist-height ratio, body fat percentage, and body mass index. Results. Altogether, 882 individuals were included in our analyses. Indices that included waist-related measurements had the strongest association with CVD risk in both genders. After adjusting for demographic and socioeconomic variables, waist-related measurements retained the strongest correlations with predicted CVD risk in males. However, body mass index, waist-height ratio, and waist circumference had the strongest correlation with CVD risk in females. Conclusions. The waist-related indicators of abdominal obesity are important components of CVD risk profiles. As waist-related parameters can quickly and easily be measured, they should be routinely obtained in primary care settings and population health screens in order to assess future CVD risk profiles and design appropriate interventions. PMID:25710002

Psychosis prediction and clinical utility in familial high-risk studies: Selective review, synthesis, and implications for early detection and intervention

PubMed Central

Shah, Jai L.; Tandon, Neeraj; Keshavan, Matcheri S.

2016-01-01

Aim Accurate prediction of which individuals will go on to develop psychosis would assist early intervention and prevention paradigms. We sought to review investigations of prospective psychosis prediction based on markers and variables examined in longitudinal familial high-risk (FHR) studies. Methods We performed literature searches in MedLine, PubMed and PsycINFO for articles assessing performance characteristics of predictive clinical tests in FHR studies of psychosis. Studies were included if they reported one or more predictive variables in subjects at FHR for psychosis. We complemented this search strategy with references drawn from articles, reviews, book chapters and monographs. Results Across generations of familial high-risk projects, predictive studies have investigated behavioral, cognitive, psychometric, clinical, neuroimaging, and other markers. Recent analyses have incorporated multivariate and multi-domain approaches to risk ascertainment, although with still generally modest results. Conclusions While a broad range of risk factors has been identified, no individual marker or combination of markers can at this time enable accurate prospective prediction of emerging psychosis for individuals at FHR. We outline the complex and multi-level nature of psychotic illness, the myriad of factors influencing its development, and methodological hurdles to accurate and reliable prediction. Prospects and challenges for future generations of FHR studies are discussed in the context of early detection and intervention strategies. PMID:23693118

Prediction of cardiovascular risk in rheumatoid arthritis: performance of original and adapted SCORE algorithms.

PubMed

Arts, E E A; Popa, C D; Den Broeder, A A; Donders, R; Sandoo, A; Toms, T; Rollefstad, S; Ikdahl, E; Semb, A G; Kitas, G D; Van Riel, P L C M; Fransen, J

2016-04-01

Predictive performance of cardiovascular disease (CVD) risk calculators appears suboptimal in rheumatoid arthritis (RA). A disease-specific CVD risk algorithm may improve CVD risk prediction in RA. The objectives of this study are to adapt the Systematic COronary Risk Evaluation (SCORE) algorithm with determinants of CVD risk in RA and to assess the accuracy of CVD risk prediction calculated with the adapted SCORE algorithm. Data from the Nijmegen early RA inception cohort were used. The primary outcome was first CVD events. The SCORE algorithm was recalibrated by reweighing included traditional CVD risk factors and adapted by adding other potential predictors of CVD. Predictive performance of the recalibrated and adapted SCORE algorithms was assessed and the adapted SCORE was externally validated. Of the 1016 included patients with RA, 103 patients experienced a CVD event. Discriminatory ability was comparable across the original, recalibrated and adapted SCORE algorithms. The Hosmer-Lemeshow test results indicated that all three algorithms provided poor model fit (p<0.05) for the Nijmegen and external validation cohort. The adapted SCORE algorithm mainly improves CVD risk estimation in non-event cases and does not show a clear advantage in reclassifying patients with RA who develop CVD (event cases) into more appropriate risk groups. This study demonstrates for the first time that adaptations of the SCORE algorithm do not provide sufficient improvement in risk prediction of future CVD in RA to serve as an appropriate alternative to the original SCORE. Risk assessment using the original SCORE algorithm may underestimate CVD risk in patients with RA. 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/

Dengue: recent past and future threats

PubMed Central

Rogers, David J.

2015-01-01

This article explores four key questions about statistical models developed to describe the recent past and future of vector-borne diseases, with special emphasis on dengue: (1) How many variables should be used to make predictions about the future of vector-borne diseases?(2) Is the spatial resolution of a climate dataset an important determinant of model accuracy?(3) Does inclusion of the future distributions of vectors affect predictions of the futures of the diseases they transmit?(4) Which are the key predictor variables involved in determining the distributions of vector-borne diseases in the present and future?Examples are given of dengue models using one, five or 10 meteorological variables and at spatial resolutions of from one-sixth to two degrees. Model accuracy is improved with a greater number of descriptor variables, but is surprisingly unaffected by the spatial resolution of the data. Dengue models with a reduced set of climate variables derived from the HadCM3 global circulation model predictions for the 1980s are improved when risk maps for dengue's two main vectors (Aedes aegypti and Aedes albopictus) are also included as predictor variables; disease and vector models are projected into the future using the global circulation model predictions for the 2020s, 2040s and 2080s. The Garthwaite–Koch corr-max transformation is presented as a novel way of showing the relative contribution of each of the input predictor variables to the map predictions. PMID:25688021

9.4 COMPLEX SYSTEM THEORY AND THE TRANSDIAGNOSTIC USE OF EARLY WARNING SIGNALS TO FORESEE THE TYPE OF FUTURE TRANSITIONS IN SYMPTOMS

PubMed Central

Wichers, Marieke; Schreuder, Marieke; Hartman, Catharina; Wigman, Hanneke

2018-01-01

Abstract Background Recently, we showed that assumptions from complex system theory seem applicable in the field of psychiatry. This means that indicators of critical slowing down in the system signal the risk for a critical transition in the near future. In the current study we wanted to explore whether the principle of critical slowing down may also be informative to anticipate on the type of symptoms that individuals are most likely to develop. This is relevant as it may lead to personalized prediction of risk of whether adolescents with mixed complaints are most likely to develop either depression, anxiety, somatic or psychotic symptoms in the near future. For example, we hypothesized that critical slowing down in feeling ‘suspicious’ more strongly indicates risk for a future transition to psychotic symptoms, while critical slowing down in feeling ‘down’ more strongly indicates risk for a transition to depressive symptoms. Methods We examined this in a population of adolescents (most between 15 and 18 years) as adolescents are an at-risk group for the development of psychopathology. At baseline experience sampling was performed for 6 days, 10 measurements a day. Affect items were used to assess autocorrelation as an indicator of ‘critical slowing down’ of the system. At baseline and follow-up SCL-90 questionnaires were administered. In total, 147 adolescents participated both in baseline and follow-up measures and showed increases in at least one of the defined symptom dimensions. We examined whether autocorrelation was positively associated with the size of symptom transition and whether different type of transitions (in depression, anxiety etc.) were differentially predicted by autocorrelations in specific affect states. Results The analyses were done very recently, and findings have not been presented before. We found both shared and specific indicators of risk in the development for transition to various symptom dimensions. First, autocorrelation in ‘feeling suspicious’ appeared to be the strongest signal for all assessed psychopathology dimensions (SCL-90 depression: std beta: 0.185; p <0.001; SCL-90 anxiety: std beta: 0.093; p=0.006; SCL-90 interpersonal sensitivity: std beta: 0.176, p<0.001). Second, we found that the combination of ‘feeling suspicious’ and the affect with the second-highest autocorrelation together predicted the precise type of symptom transition. Thus, the combination of feeling suspicious (std beta: 0.185; p<0.001) and down (std beta: 0.108; p=0.001) predicted larger increases in depressive symptoms one year later on the SCL-90, while the combination of feeling suspicious (std beta: 0.093; p=0.006) with feeling anxious (std beta: 0.086; p=0.014) predicted larger increases in anxiety symptoms a year later on the SCL-90. Discussion These findings support the hypothesis that indicators of slowing down can not only be used to predict risk for a mean level shift in symptoms, but that they can also be informative for the type of symptom transitions at hand. In a next step these findings could be translated to designs measuring personalized early warnings for future direction of symptom shifts, and if successful to clinical implementation of these techniques.

Are Genetic Tests for Atherosclerosis Ready for Routine Clinical Use?

PubMed

Paynter, Nina P; Ridker, Paul M; Chasman, Daniel I

2016-02-19

In this review, we lay out 3 areas currently being evaluated for incorporation of genetic information into clinical practice related to atherosclerosis. The first, familial hypercholesterolemia, is the clearest case for utility of genetic testing in diagnosis and potentially guiding treatment. Already in use for confirmatory testing of familial hypercholesterolemia and for cascade screening of relatives, genetic testing is likely to expand to help establish diagnoses and facilitate research related to most effective therapies, including new agents, such as PCSK9 inhibitors. The second area, adding genetic information to cardiovascular risk prediction for primary prevention, is not currently recommended. Although identification of additional variants may add substantially to prediction in the future, combining known variants has not yet demonstrated sufficient improvement in prediction for incorporation into commonly used risk scores. The third area, pharmacogenetics, has utility for some therapies today. Future utility for pharmacogenetics will wax or wane depending on the nature of available drugs and therapeutic strategies. © 2016 American Heart Association, Inc.

External validation of a simple clinical tool used to predict falls in people with Parkinson disease

PubMed Central

Duncan, Ryan P.; Cavanaugh, James T.; Earhart, Gammon M.; Ellis, Terry D.; Ford, Matthew P.; Foreman, K. Bo; Leddy, Abigail L.; Paul, Serene S.; Canning, Colleen G.; Thackeray, Anne; Dibble, Leland E.

2015-01-01

Background Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. METHODS We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. RESULTS The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76 –0.89), comparable to the developmental study. CONCLUSION The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual’s risk of an impending fall. PMID:26003412

External validation of a simple clinical tool used to predict falls in people with Parkinson disease.

PubMed

Duncan, Ryan P; Cavanaugh, James T; Earhart, Gammon M; Ellis, Terry D; Ford, Matthew P; Foreman, K Bo; Leddy, Abigail L; Paul, Serene S; Canning, Colleen G; Thackeray, Anne; Dibble, Leland E

2015-08-01

Assessment of fall risk in an individual with Parkinson disease (PD) is a critical yet often time consuming component of patient care. Recently a simple clinical prediction tool based only on fall history in the previous year, freezing of gait in the past month, and gait velocity <1.1 m/s was developed and accurately predicted future falls in a sample of individuals with PD. We sought to externally validate the utility of the tool by administering it to a different cohort of 171 individuals with PD. Falls were monitored prospectively for 6 months following predictor assessment. The tool accurately discriminated future fallers from non-fallers (area under the curve [AUC] = 0.83; 95% CI 0.76-0.89), comparable to the developmental study. The results validated the utility of the tool for allowing clinicians to quickly and accurately identify an individual's risk of an impending fall. Copyright © 2015 Elsevier Ltd. All rights reserved.

Mood instability and impulsivity as trait predictors of suicidal thoughts.

PubMed

Peters, Evyn M; Balbuena, Lloyd; Marwaha, Steven; Baetz, Marilyn; Bowen, Rudy

2016-12-01

Impulsivity, the tendency to act quickly without adequate planning or concern for consequences, is a commonly cited risk factor for suicidal thoughts and behaviour. There are many definitions of impulsivity and how it relates to suicidality is not well understood. Mood instability, which describes frequent fluctuations of mood over time, is a concept related to impulsivity that may help explain this relationship. The purpose of this study was to determine whether impulsivity could predict suicidal thoughts after controlling for mood instability. This study utilized longitudinal data from the 2000 Adult Psychiatric Morbidity Survey (N = 2,406). There was a time interval of 18 months between the two waves of the study. Trait impulsivity and mood instability were measured with the Structured Clinical Interview for DSM-IV Axis II Personality Disorders. Logistic regression analyses were used to evaluate baseline impulsivity and mood instability as predictors of future suicidal thoughts. Impulsivity significantly predicted the presence of suicidal thoughts, but this effect became non-significant with mood instability included in the same model. Impulsivity may be a redundant concept when predicting future suicidal thoughts if mood instability is considered. The significance is that research and therapy focusing on mood instability along with impulsivity may be useful in treating the suicidal patient. Mood instability and impulsivity both predict future suicidal thoughts. Impulsivity does not predict suicidal thoughts after controlling for mood instability. Assessing and treating mood instability could be important aspects of suicide prevention and risk management. © 2015 The British Psychological Society.

Disease Risk in a Dynamic Environment: The Spread of Tick-Borne Pathogens in Minnesota, USA

PubMed Central

Robinson, Stacie J.; Neitzel, David F.; Moen, Ronald A.; Craft, Meggan E.; Hamilton, Karin E.; Johnson, Lucinda B.; Mulla, David J.; Munderloh, Ulrike G.; Redig, Patrick T.; Smith, Kirk E.; Turner, Clarence L.; Umber, Jamie K.; Pelican, Katharine M.

2015-01-01

As humans and climate change alter the landscape, novel disease risk scenarios emerge. Understanding the complexities of pathogen emergence and subsequent spread as shaped by landscape heterogeneity is crucial to understanding disease emergence, pinpointing high-risk areas, and mitigating emerging disease threats in a dynamic environment. Tick-borne diseases present an important public health concern and incidence of many of these diseases are increasing in the United States. The complex epidemiology of tick-borne diseases includes strong ties with environmental factors that influence host availability, vector abundance, and pathogen transmission. Here, we used 16 years of case data from the Minnesota Department of Health to report spatial and temporal trends in Lyme disease (LD), human anaplasmosis, and babesiosis. We then used a spatial regression framework to evaluate the impact of landscape and climate factors on the spread of LD. Finally, we use the fitted model, and landscape and climate datasets projected under varying climate change scenarios, to predict future changes in tick-borne pathogen risk. Both forested habitat and temperature were important drivers of LD spread in Minnesota. Dramatic changes in future temperature regimes and forest communities predict rising risk of tick-borne disease. PMID:25281302

Big Data’s Role in Precision Public Health

PubMed Central

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts. PMID:29594091

Big Data's Role in Precision Public Health.

PubMed

Dolley, Shawn

2018-01-01

Precision public health is an emerging practice to more granularly predict and understand public health risks and customize treatments for more specific and homogeneous subpopulations, often using new data, technologies, and methods. Big data is one element that has consistently helped to achieve these goals, through its ability to deliver to practitioners a volume and variety of structured or unstructured data not previously possible. Big data has enabled more widespread and specific research and trials of stratifying and segmenting populations at risk for a variety of health problems. Examples of success using big data are surveyed in surveillance and signal detection, predicting future risk, targeted interventions, and understanding disease. Using novel big data or big data approaches has risks that remain to be resolved. The continued growth in volume and variety of available data, decreased costs of data capture, and emerging computational methods mean big data success will likely be a required pillar of precision public health into the future. This review article aims to identify the precision public health use cases where big data has added value, identify classes of value that big data may bring, and outline the risks inherent in using big data in precision public health efforts.

Disease risk in a dynamic environment: the spread of tick-borne pathogens in Minnesota, USA.

PubMed

Robinson, Stacie J; Neitzel, David F; Moen, Ronald A; Craft, Meggan E; Hamilton, Karin E; Johnson, Lucinda B; Mulla, David J; Munderloh, Ulrike G; Redig, Patrick T; Smith, Kirk E; Turner, Clarence L; Umber, Jamie K; Pelican, Katharine M

2015-03-01

As humans and climate change alter the landscape, novel disease risk scenarios emerge. Understanding the complexities of pathogen emergence and subsequent spread as shaped by landscape heterogeneity is crucial to understanding disease emergence, pinpointing high-risk areas, and mitigating emerging disease threats in a dynamic environment. Tick-borne diseases present an important public health concern and incidence of many of these diseases are increasing in the United States. The complex epidemiology of tick-borne diseases includes strong ties with environmental factors that influence host availability, vector abundance, and pathogen transmission. Here, we used 16 years of case data from the Minnesota Department of Health to report spatial and temporal trends in Lyme disease (LD), human anaplasmosis, and babesiosis. We then used a spatial regression framework to evaluate the impact of landscape and climate factors on the spread of LD. Finally, we use the fitted model, and landscape and climate datasets projected under varying climate change scenarios, to predict future changes in tick-borne pathogen risk. Both forested habitat and temperature were important drivers of LD spread in Minnesota. Dramatic changes in future temperature regimes and forest communities predict rising risk of tick-borne disease.

Lifetime suicide attempts in juvenile assessment center youth.

PubMed

Nolen, Scott; McReynolds, Larkin S; DeComo, Robert E; John, Reni; Keating, Joseph M; Wasserman, Gail A

2008-01-01

To describe suicide risk in youth seen at a Juvenile Assessment Center (JAC), we examined relationships among self-reported lifetime attempts and demographic, justice, and psychiatric data via logistic regression. Similar to other settings, youth reporting lifetime attempts were more likely to be older, female, not living with both parents and currently arrested for a violent or felony crime. Mood, substance use, and behavior disorder each increased prediction substantially. Anxiety Disorder was associated with elevated attempt rates for boys only. JACs need to develop protocols for identifying suicide risk; further, since suicide history predicts future attempts, Anxiety Disordered boys may be at particular risk.

Do self- or parent-reported dietary, physical activity, and sedentary behaviors predict worsening obesity in children?

PubMed

Dorsey, Karen B; Mauldon, Maria; Magraw, Ruth; Yu, Sunkyung; Krumholz, Harlan M

2010-10-01

To determine whether information gathered during routine healthcare visits regarding obesity related risk factors and risk behaviors predicts increases in BMI z-score over time among overweight and obese children. Medical records from 168 overweight and 441 obese patients seen for repeated visits between September 2003 and April 2006 were examined for reported dietary, physical activity, and sedentary behaviors, family history of obesity and diabetes mellitus, documented Acanthosis nigricans, and BMI values. Random-effects regression analysis was done to determine whether demographic, familial, or behavioral data predicted changes in BMI z-score over time. The presence of A nigricans and a family history of obesity were associated with an increase in BMI z-score (beta=0.56, SE=0.09, P<.001 and beta=0.31, SE=0.13, P=.021). These risk factors explained 8% and 7% of the variation in BMI z-score respectively. Self- or parent-reported dietary and physical activity behaviors did not predict change in BMI z-score. Our findings suggest that the risk factors and self- or parent-reported risk behaviors routinely assessed by pediatric clinicians have limited ability to predict future growth trends, demonstrating the difficulty in determining which patients have the greatest risk of progression of obesity. Copyright (c) 2010 Mosby, Inc. All rights reserved.

Paleontological baselines for evaluating extinction risk in the modern oceans

NASA Astrophysics Data System (ADS)

Finnegan, Seth; Anderson, Sean C.; Harnik, Paul G.; Simpson, Carl; Tittensor, Derek P.; Byrnes, Jarrett E.; Finkel, Zoe V.; Lindberg, David R.; Liow, Lee Hsiang; Lockwood, Rowan; Lotze, Heike K.; McClain, Craig R.; McGuire, Jenny L.; O'Dea, Aaron; Pandolfi, John M.

2015-05-01

Marine taxa are threatened by anthropogenic impacts, but knowledge of their extinction vulnerabilities is limited. The fossil record provides rich information on past extinctions that can help predict biotic responses. We show that over 23 million years, taxonomic membership and geographic range size consistently explain a large proportion of extinction risk variation in six major taxonomic groups. We assess intrinsic risk—extinction risk predicted by paleontologically calibrated models—for modern genera in these groups. Mapping the geographic distribution of these genera identifies coastal biogeographic provinces where fauna with high intrinsic risk are strongly affected by human activity or climate change. Such regions are disproportionately in the tropics, raising the possibility that these ecosystems may be particularly vulnerable to future extinctions. Intrinsic risk provides a prehuman baseline for considering current threats to marine biodiversity.

Dealing with unquantifiable uncertainties in landslide modelling for urban risk reduction in developing countries

NASA Astrophysics Data System (ADS)

Almeida, Susana; Holcombe, Liz; Pianosi, Francesca; Wagener, Thorsten

2016-04-01

Landslides have many negative economic and societal impacts, including the potential for significant loss of life and damage to infrastructure. Slope stability assessment can be used to guide decisions about the management of landslide risk, but its usefulness can be challenged by high levels of uncertainty in predicting landslide occurrence. Prediction uncertainty may be associated with the choice of model that is used to assess slope stability, the quality of the available input data, or a lack of knowledge of how future climatic and socio-economic changes may affect future landslide risk. While some of these uncertainties can be characterised by relatively well-defined probability distributions, for other uncertainties, such as those linked to climate change, no probability distribution is available to characterise them. This latter type of uncertainty, often referred to as deep uncertainty, means that robust policies need to be developed that are expected to perform acceptably well over a wide range of future conditions. In our study the impact of deep uncertainty on slope stability predictions is assessed in a quantitative and structured manner using Global Sensitivity Analysis (GSA) and the Combined Hydrology and Stability Model (CHASM). In particular, we use several GSA methods including the Method of Morris, Regional Sensitivity Analysis and Classification and Regression Trees (CART), as well as advanced visualization tools, to assess the combination of conditions that may lead to slope failure. Our example application is a slope in the Caribbean, an area that is naturally susceptible to landslides due to a combination of high rainfall rates during the hurricane season, steep slopes, and highly weathered residual soils. Rapid unplanned urbanisation and changing climate may further exacerbate landslide risk in the future. Our example shows how we can gain useful information in the presence of deep uncertainty by combining physically based models with GSA in a scenario discovery framework.

Risk-Seeking Versus Risk-Avoiding Investments in Noisy Periodic Environments

NASA Astrophysics Data System (ADS)

Navarro-Barrientos, J. Emeterio; Walter, Frank E.; Schweitzer, Frank

We study the performance of various agent strategies in an artificial investment scenario. Agents are equipped with a budget, x(t), and at each time step invest a particular fraction, q(t), of their budget. The return on investment (RoI), r(t), is characterized by a periodic function with different types and levels of noise. Risk-avoiding agents choose their fraction q(t) proportional to the expected positive RoI, while risk-seeking agents always choose a maximum value qmax if they predict the RoI to be positive ("everything on red"). In addition to these different strategies, agents have different capabilities to predict the future r(t), dependent on their internal complexity. Here, we compare "zero-intelligent" agents using technical analysis (such as moving least squares) with agents using reinforcement learning or genetic algorithms to predict r(t). The performance of agents is measured by their average budget growth after a certain number of time steps. We present results of extensive computer simulations, which show that, for our given artificial environment, (i) the risk-seeking strategy outperforms the risk-avoiding one, and (ii) the genetic algorithm was able to find this optimal strategy itself, and thus outperforms other prediction approaches considered.

Predictive modeling of complications.

PubMed

Osorio, Joseph A; Scheer, Justin K; Ames, Christopher P

2016-09-01

Predictive analytic algorithms are designed to identify patterns in the data that allow for accurate predictions without the need for a hypothesis. Therefore, predictive modeling can provide detailed and patient-specific information that can be readily applied when discussing the risks of surgery with a patient. There are few studies using predictive modeling techniques in the adult spine surgery literature. These types of studies represent the beginning of the use of predictive analytics in spine surgery outcomes. We will discuss the advancements in the field of spine surgery with respect to predictive analytics, the controversies surrounding the technique, and the future directions.

Assessing effects of variation in global climate data sets on spatial predictions from climate envelope models

USGS Publications Warehouse

Romañach, Stephanie; Watling, James I.; Fletcher, Robert J.; Speroterra, Carolina; Bucklin, David N.; Brandt, Laura A.; Pearlstine, Leonard G.; Escribano, Yesenia; Mazzotti, Frank J.

2014-01-01

Climate change poses new challenges for natural resource managers. Predictive modeling of species–environment relationships using climate envelope models can enhance our understanding of climate change effects on biodiversity, assist in assessment of invasion risk by exotic organisms, and inform life-history understanding of individual species. While increasing interest has focused on the role of uncertainty in future conditions on model predictions, models also may be sensitive to the initial conditions on which they are trained. Although climate envelope models are usually trained using data on contemporary climate, we lack systematic comparisons of model performance and predictions across alternative climate data sets available for model training. Here, we seek to fill that gap by comparing variability in predictions between two contemporary climate data sets to variability in spatial predictions among three alternative projections of future climate. Overall, correlations between monthly temperature and precipitation variables were very high for both contemporary and future data. Model performance varied across algorithms, but not between two alternative contemporary climate data sets. Spatial predictions varied more among alternative general-circulation models describing future climate conditions than between contemporary climate data sets. However, we did find that climate envelope models with low Cohen's kappa scores made more discrepant spatial predictions between climate data sets for the contemporary period than did models with high Cohen's kappa scores. We suggest conservation planners evaluate multiple performance metrics and be aware of the importance of differences in initial conditions for spatial predictions from climate envelope models.

[How exactly can we predict the prognosis of COPD].

PubMed

Atiş, Sibel; Kanik, Arzu; Ozgür, Eylem Sercan; Eker, Suzan; Tümkaya, Münir; Ozge, Cengiz

2009-01-01

Predictive models play a pivotal role in the provision of accurate and useful probabilistic assessments of clinical outcomes in chronic diseases. This study was aimed to develop a dedicated prognostic index for quantifying progression risk in chronic obstructive pulmonary disease (COPD). Data were collected prospectively from 75 COPD patients during a three years period. A predictive model of progression risk of COPD was developed using Bayesian logistic regression analysis by Markov chain Monte Carlo method. One-year cycles were used for the disease progression in this model. Primary end points for progression were impairment in basal dyspne index (BDI) score, FEV(1) decline, and exacerbation frequency in last three years. Time-varying covariates age, smoking, body mass index (BMI), severity of disease according to GOLD, PaO2, PaCO(2), IC, RV/TLC, DLCO were used under the study. The mean age was 57.1 + or - 8.1. BDI were strongly correlated with exacerbation frequency (p= 0.001) but not with FEV(1) decline. BMI was found to be a predictor factor for impairment in BDI (p= 0.03). The following independent risk factors were significant to predict exacerbation frequency: GOLD staging (OR for GOLD I vs. II and III = 2.3 and 4.0), hypoxemia (OR for mild vs moderate and severe = 2.1 and 5.1) and hyperinflation (OR= 1.6). PaO2 (p= 0.026), IC (p= 0.02) and RV/TLC (p= 0.03) were found to be predictive factors for FEV(1) decline. The model estimated BDI, lung function and exacerbation frequency at the last time point by testing initial data of three years with 95% reliability (p< 0.001). Accordingly, this model was evaluated as confident of 95% for assessing the future status of COPD patients. Using Bayesian predictive models, it was possible to develop a risk-stratification index that accurately predicted progression of COPD. This model can provide decision-making about future in COPD patients with high reliability looking clinical data of beginning.

Predictors of self-rated health: a 12-month prospective study of IT and media workers.

PubMed

Hasson, Dan; Arnetz, Bengt B; Theorell, Töres; Anderberg, Ulla Maria

2006-07-31

The aim of the present study was to determine health-related risk and salutogenic factors and to use these to construct prediction models for future self-rated health (SRH), i.e. find possible characteristics predicting individuals improving or worsening in SRH over time (0-12 months). A prospective study was conducted with measurements (physiological markers and self-ratings) at 0, 6 and 12 months, involving 303 employees (187 men and 116 women, age 23-64) from four information technology and two media companies. There were a multitude of statistically significant cross-sectional correlations (Spearman's Rho) between SRH and other self-ratings as well as physiological markers. Predictors of future SRH were baseline ratings of SRH, self-esteem and social support (logistic regression), and SRH, sleep quality and sense of coherence (linear regression). The results of the present study indicate that baseline SRH and other self-ratings are predictive of future SRH. It is cautiously implied that SRH, self-esteem, social support, sleep quality and sense of coherence might be predictors of future SRH and therefore possibly also of various future health outcomes.

Vitamin D and ferritin correlation with chronic neck pain using standard statistics and a novel artificial neural network prediction model.

PubMed

Eloqayli, Haytham; Al-Yousef, Ali; Jaradat, Raid

2018-02-15

Despite the high prevalence of chronic neck pain, there is limited consensus about the primary etiology, risk factors, diagnostic criteria and therapeutic outcome. Here, we aimed to determine if Ferritin and Vitamin D are modifiable risk factors with chronic neck pain using slandered statistics and artificial intelligence neural network (ANN). Fifty-four patients with chronic neck pain treated between February 2016 and August 2016 in King Abdullah University Hospital and 54 patients age matched controls undergoing outpatient or minor procedures were enrolled. Patients and control demographic parameters, height, weight and single measurement of serum vitamin D, Vitamin B12, ferritin, calcium, phosphorus, zinc were obtained. An ANN prediction model was developed. The statistical analysis reveals that patients with chronic neck pain have significantly lower serum Vitamin D and Ferritin (p-value <.05). 90% of patients with chronic neck pain were females. Multilayer Feed Forward Neural Network with Back Propagation(MFFNN) prediction model were developed and designed based on vitamin D and ferritin as input variables and CNP as output. The ANN model output results show that, 92 out of 108 samples were correctly classified with 85% classification accuracy. Although Iron and vitamin D deficiency cannot be isolated as the sole risk factors of chronic neck pain, they should be considered as two modifiable risk. The high prevalence of chronic neck pain, hypovitaminosis D and low ferritin amongst women is of concern. Bioinformatics predictions with artificial neural network can be of future benefit in classification and prediction models for chronic neck pain. We hope this initial work will encourage a future larger cohort study addressing vitamin D and iron correction as modifiable factors and the application of artificial intelligence models in clinical practice.

Resting-state regional cerebral blood flow during adolescence: associations with initiation of substance use and prediction of future use disorders.

PubMed

Ramage, Amy E; Lin, Ai-Ling; Olvera, Rene L; Fox, Peter T; Williamson, Douglas E

2015-04-01

Adolescence is a period of developmental flux when brain systems are vulnerable to influences of early substance use, which in turn relays increased risk for substance use disorders. Our study intent was to assess adolescent regional cerebral blood flow (rCBF) as it relates to current and future alcohol use. The aim was to identify brain-based predictors for initiation of alcohol use and onset of future substance use disorders. Quantitative rCBF was assessed in 100 adolescents (age 12-15). Prospective behavioral assessments were conducted annually over a three-year follow-up period to characterize onset of alcohol initiation, future drinking patterns and use disorders. Comparisons amongst use groups (i.e., current-, future-, and non-alcohol using adolescents) identified rCBF associated with initiation of alcohol use. Regression by future drinking patterns identified rCBF predictive of heavier drinking. Survival analysis determined whether or not baseline rCBF predicted later development of use disorders. Baseline rCBF was decreased to the parietal cortex and increased to mesolimbic regions in adolescents currently using alcohol as well as those who would use alcohol in the future. Higher baseline rCBF to the left fusiform gyrus and lower rCBF to the right inferior parietal cortex and left cerebellum was associated with future drinking patterns as well as predicted the onset of alcohol and substance use disorders in this cohort. Variations in resting rCBF to regions within reward and default mode or control networks appear to represent trait markers of alcohol use initiation and are predictive of future development of use disorders. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Geo-environmental model for the prediction of potential transmission risk of Dirofilaria in an area with dry climate and extensive irrigated crops. The case of Spain.

PubMed

Simón, Luis; Afonin, Alexandr; López-Díez, Lucía Isabel; González-Miguel, Javier; Morchón, Rodrigo; Carretón, Elena; Montoya-Alonso, José Alberto; Kartashev, Vladimir; Simón, Fernando

2014-03-01

Zoonotic filarioses caused by Dirofilaria immitis and Dirofilaria repens are transmitted by culicid mosquitoes. Therefore Dirofilaria transmission depends on climatic factors like temperature and humidity. In spite of the dry climate of most of the Spanish territory, there are extensive irrigated crops areas providing moist habitats favourable for mosquito breeding. A GIS model to predict the risk of Dirofilaria transmission in Spain, based on temperatures and rainfall data as well as in the distribution of irrigated crops areas, is constructed. The model predicts that potential risk of Dirofilaria transmission exists in all the Spanish territory. Highest transmission risk exists in several areas of Andalucía, Extremadura, Castilla-La Mancha, Murcia, Valencia, Aragón and Cataluña, where moderate/high temperatures coincide with extensive irrigated crops. High risk in Balearic Islands and in some points of Canary Islands, is also predicted. The lowest risk is predicted in Northern cold and scarcely or non-irrigated dry Southeastern areas. The existence of irrigations locally increases transmission risk in low rainfall areas of the Spanish territory. The model can contribute to implement rational preventive therapy guidelines in accordance with the transmission characteristics of each local area. Moreover, the use of humidity-related factors could be of interest in future predictions to be performed in countries with similar environmental characteristics. Copyright © 2014 Elsevier B.V. All rights reserved.

The Science-Policy Link: Stakeholder Reactions to the Uncertainties of Future Sea Level Rise

NASA Astrophysics Data System (ADS)

Plag, H.; Bye, B.

2011-12-01

Policy makers and stakeholders in the coastal zone are equally challenged by the risk of an anticipated rise of coastal Local Sea Level (LSL) as a consequence of future global warming. Many low-lying and often densely populated coastal areas are under risk of increased inundation. More than 40% of the global population is living in or near the coastal zone and this fraction is steadily increasing. A rise in LSL will increase the vulnerability of coastal infrastructure and population dramatically, with potentially devastating consequences for the global economy, society, and environment. Policy makers are faced with a trade-off between imposing today the often very high costs of coastal protection and adaptation upon national economies and leaving the costs of potential major disasters to future generations. They are in need of actionable information that provides guidance for the development of coastal zones resilient to future sea level changes. Part of this actionable information comes from risk and vulnerability assessments, which require information on future LSL changes as input. In most cases, a deterministic approach has been applied based on predictions of the plausible range of future LSL trajectories as input. However, there is little consensus in the scientific community on how these trajectories should be determined, and what the boundaries of the plausible range are. Over the last few years, many publications in Science, Nature and other peer-reviewed scientific journals have revealed a broad range of possible futures and significant epistemic uncertainties and gaps concerning LSL changes. Based on the somewhat diffuse science input, policy and decision makers have made rather different choices for mitigation and adaptation in cases such as Venice, The Netherlands, New York City, and the San Francisco Bay area. Replacing the deterministic, prediction-based approach with a statistical one that fully accounts for the uncertainties and epistemic gaps would provide a different kind of science input to policy makers and stakeholders. Like in many other insurance problems (for example, earthquakes), where deterministic predictions are not possible and decisions have to be made on the basis of statistics and probabilities, the statistical approach to coastal resilience would require stakeholders to make decisions on the basis of probabilities instead of predictions. The science input for informed decisions on adaptation would consist of general probabilities of decadal to century scale sea level changes derived from paleo records, including the probabilities for large and rapid rises. Similar to other problems where the appearance of a hazard is associated with a high risk (like a fire in a house), this approach would also require a monitoring and warning system (a "smoke detector") capable of detecting any onset of a rapid sea level rise.

It's lonely at the top: Biodiversity at risk to loss from climate change

Treesearch

John L. Koprowski; Sandra L. Doumas; Melissa J. Merrick; Brittany Oleson; Erin E. Posthumus; Timothy G. Jessen; R. Nathan Gwinn

2013-01-01

Climate change is a serious immediate and long-term threat to wildlife species. State and federal agencies are working with universities and non-government organizations to predict, plan for, and mitigate such uncertainties in the future. Endemic species may be particularly at-risk as climate-induced changes impact their limited geographic ranges. The Madrean...

DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk.

PubMed

Dayeh, Tasnim; Tuomi, Tiinamaija; Almgren, Peter; Perfilyev, Alexander; Jansson, Per-Anders; de Mello, Vanessa D; Pihlajamäki, Jussi; Vaag, Allan; Groop, Leif; Nilsson, Emma; Ling, Charlotte

2016-07-02

Identification of subjects with a high risk of developing type 2 diabetes (T2D) is fundamental for prevention of the disease. Consequently, it is essential to search for new biomarkers that can improve the prediction of T2D. The aim of this study was to examine whether 5 DNA methylation loci in blood DNA (ABCG1, PHOSPHO1, SOCS3, SREBF1, and TXNIP), recently reported to be associated with T2D, might predict future T2D in subjects from the Botnia prospective study. We also tested if these CpG sites exhibit altered DNA methylation in human pancreatic islets, liver, adipose tissue, and skeletal muscle from diabetic vs. non-diabetic subjects. DNA methylation at the ABCG1 locus cg06500161 in blood DNA was associated with an increased risk for future T2D (OR = 1.09, 95% CI = 1.02-1.16, P-value = 0.007, Q-value = 0.018), while DNA methylation at the PHOSPHO1 locus cg02650017 in blood DNA was associated with a decreased risk for future T2D (OR = 0.85, 95% CI = 0.75-0.95, P-value = 0.006, Q-value = 0.018) after adjustment for age, gender, fasting glucose, and family relation. Furthermore, the level of DNA methylation at the ABCG1 locus cg06500161 in blood DNA correlated positively with BMI, HbA1c, fasting insulin, and triglyceride levels, and was increased in adipose tissue and blood from the diabetic twin among monozygotic twin pairs discordant for T2D. DNA methylation at the PHOSPHO1 locus cg02650017 in blood correlated positively with HDL levels, and was decreased in skeletal muscle from diabetic vs. non-diabetic monozygotic twins. DNA methylation of cg18181703 (SOCS3), cg11024682 (SREBF1), and cg19693031 (TXNIP) was not associated with future T2D risk in subjects from the Botnia prospective study.

Silent Brain Infarction and Risk of Future Stroke: A Systematic Review and Meta-Analysis

PubMed Central

Gupta, Ajay; Giambrone, Ashley E.; Gialdini, Gino; Finn, Caitlin; Delgado, Diana; Gutierrez, Jose; Wright, Clinton; Beiser, Alexa S.; Seshadri, Sudha; Pandya, Ankur; Kamel, Hooman

2016-01-01

Background and Purpose Silent brain infarction (SBI) on magnetic resonance imaging (MRI) has been proposed as a subclinical risk marker for future symptomatic stroke. We performed a systematic review and meta-analysis to summarize the association between MRI-defined SBI and future stroke risk. Methods We searched the medical literature to identify cohort studies involving adults with MRI detection of SBI who were subsequently followed for incident clinically-defined stroke. Study data and quality assessment were recorded in duplicate with disagreements in data extraction resolved by a third reader. Strength association between MRI detected SBI and future symptomatic stroke measured by a hazard ratio (HR). Results The meta-analysis included 13 studies (14,764 subjects) with a mean follow-up ranging from 25.7 to 174 months. SBI predicted the occurrence of stroke with a random effects crude relative risk of 2.94 (95% CI 2.24–3.86, P<0.001; Q=39.65, P<0.001). In the eight studies of 10,427 subjects providing HR adjusted for cardiovascular risk factors, SBI was an independent predictor of incident stroke (HR 2.08 [95% CI 1.69–2.56, P<0.001]; Q=8.99, P=0.25). In a subgroup analysis pooling 9,483 stroke-free individuals from large population-based studies, SBI was present in ~18% of participants and remained a strong predictor of future stroke (HR 2.06 [95% CI 1.64–2.59], p<0.01). Conclusions SBI is present in approximately one in five stroke-free older adults and is associated with a 2-fold increased risk of future stroke. Future studies of in-depth stroke risk evaluations and intensive prevention measures are warranted in patients with clinically unrecognized radiologically evident brain infarctions. PMID:26888534

Classification of suicide attempters in schizophrenia using sociocultural and clinical features: A machine learning approach.

PubMed

Hettige, Nuwan C; Nguyen, Thai Binh; Yuan, Chen; Rajakulendran, Thanara; Baddour, Jermeen; Bhagwat, Nikhil; Bani-Fatemi, Ali; Voineskos, Aristotle N; Mallar Chakravarty, M; De Luca, Vincenzo

2017-07-01

Suicide is a major concern for those afflicted by schizophrenia. Identifying patients at the highest risk for future suicide attempts remains a complex problem for psychiatric interventions. Machine learning models allow for the integration of many risk factors in order to build an algorithm that predicts which patients are likely to attempt suicide. Currently it is unclear how to integrate previously identified risk factors into a clinically relevant predictive tool to estimate the probability of a patient with schizophrenia for attempting suicide. We conducted a cross-sectional assessment on a sample of 345 participants diagnosed with schizophrenia spectrum disorders. Suicide attempters and non-attempters were clearly identified using the Columbia Suicide Severity Rating Scale (C-SSRS) and the Beck Suicide Ideation Scale (BSS). We developed four classification algorithms using a regularized regression, random forest, elastic net and support vector machine models with sociocultural and clinical variables as features to train the models. All classification models performed similarly in identifying suicide attempters and non-attempters. Our regularized logistic regression model demonstrated an accuracy of 67% and an area under the curve (AUC) of 0.71, while the random forest model demonstrated 66% accuracy and an AUC of 0.67. Support vector classifier (SVC) model demonstrated an accuracy of 67% and an AUC of 0.70, and the elastic net model demonstrated and accuracy of 65% and an AUC of 0.71. Machine learning algorithms offer a relatively successful method for incorporating many clinical features to predict individuals at risk for future suicide attempts. Increased performance of these models using clinically relevant variables offers the potential to facilitate early treatment and intervention to prevent future suicide attempts. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluating Fire Risk in the Northeastern United States in the Past, Present, and Future

NASA Astrophysics Data System (ADS)

Miller, D.; Bradley, R. S.

2017-12-01

One poorly understood consequence of climate change is its effects on extreme events such as wildfires. Robust associations between wildfire frequency and climatic variability have been shown to exist, indicating that future climate change may continue to have a significant effect on wildfire activity. The Northeastern United States (NEUS) has seen some of the most infamous and largest historic fires in North America, such as the Miramichi Fire of 1825 and the fires of 1947. Although return intervals for large fires in the NEUS are long (hundreds of years), wildfires have played a critical role in ecosystem development and forest structure in the region. Understanding and predicting fire occurrence and vulnerability in the NEUS, especially in a changing climate, is economically and culturally important yet remains difficult due to human impacts (i.e. fire suppression activities and human disturbance). Thus, an alternative method for investigating fire risk in the NEUS is needed. Here, we present a compilation of meteorological data collected from Automated Surface Observing Systems (ASOS) from the NEUS throughout the 20th century through present day. We use these data to compute fifteen common "fire danger indices" employed in the USA and Canada to investigate changes in the region's fire risk over time, as well as the skill of each of these indices at predicting wildfire activity relative to the historical record of fires in the NEUS. We use dynamically-downscaled regional climate model output for the 21st century to project future wildfire activity based on the fire danger indices capable of capturing historical fire activity in the NEUS. These projections will aid in predicting how fire risk in the NEUS will evolve with anticipated climate change.

How effective are risk assessments/measures for predicting future aggressive behaviour in adults with intellectual disabilities (ID): A systematic review and meta-analysis.

PubMed

Lofthouse, Rachael; Golding, Laura; Totsika, Vasiliki; Hastings, Richard; Lindsay, William

2017-12-01

Risk assessments assist professionals in the identification and management of risk of aggression. The present study aimed to systematically review evidence on the efficacy of assessments for managing the risk of physical aggression in adults with intellectual disabilities (ID). A literature search was conducted using the databases PsycINFO, EMBASE, MEDLINE, Web of Science, and Google Scholar. Electronic and hand searches identified 14 studies that met the inclusion criteria. Standardised mean difference effect sizes Area Under Curve (AUC) were calculated for studies. Random effects subgroup analysis was used to compare different types of risk measures (Actuarial, Structured Professional Judgment and dynamic), and prospective vs. catch-up longitudinal study designs. Overall, evidence of predictive validity was found for risk measures with ID populations: (AUC)=0.724, 95% CI [0.681, 0.768]. There was no variation in the performance of different types of risk measures, or different study design. Risk assessment measures predict the likelihood of aggression in ID population and are comparable to those in mainstream populations. Further meta-analysis is necessary when risk measures are more established in this population. Copyright © 2017 Elsevier Ltd. All rights reserved.

Polygenic risk predicts obesity in both white and black young adults.

PubMed

Domingue, Benjamin W; Belsky, Daniel W; Harris, Kathleen Mullan; Smolen, Andrew; McQueen, Matthew B; Boardman, Jason D

2014-01-01

To test transethnic replication of a genetic risk score for obesity in white and black young adults using a national sample with longitudinal data. A prospective longitudinal study using the National Longitudinal Study of Adolescent Health Sibling Pairs (n = 1,303). Obesity phenotypes were measured from anthropometric assessments when study members were aged 18-26 and again when they were 24-32. Genetic risk scores were computed based on published genome-wide association study discoveries for obesity. Analyses tested genetic associations with body-mass index (BMI), waist-height ratio, obesity, and change in BMI over time. White and black young adults with higher genetic risk scores had higher BMI and waist-height ratio and were more likely to be obese compared to lower genetic risk age-peers. Sibling analyses revealed that the genetic risk score was predictive of BMI net of risk factors shared by siblings. In white young adults only, higher genetic risk predicted increased risk of becoming obese during the study period. In black young adults, genetic risk scores constructed using loci identified in European and African American samples had similar predictive power. Cumulative information across the human genome can be used to characterize individual level risk for obesity. Measured genetic risk accounts for only a small amount of total variation in BMI among white and black young adults. Future research is needed to identify modifiable environmental exposures that amplify or mitigate genetic risk for elevated BMI.

Approaches for predicting long-term sickness absence. Re: Schouten et al. "Screening manual and office workers for risk of long-term sickness absence: cut-off points for the Work Ability Index".

PubMed

van Amelsvoort, Ludovic Gpm; Jansen, Nicole W H; Kant, I Jmert

2015-05-01

We read with much interest the article of Schouten et al (1) on identifying workers with a high risk for future long-term sickness absence using the Work Ability Index (WAI). The ability to identify high-risk workers might facilitate targeted interventions for such workers and, consequently, can reduce sickness absence levels and improve workers' health. Earlier studies by both Tamela et al (2), Kant et al (3), and Lexis et al (4) have demonstrated that such an approach, based on the identification of high-risk workers and a subsequent intervention, can be effectively applied in practice to reduce sickness absence significantly. The reason for our letter on Schouten et al's article is twofold. First, by including workers already on sick leave in a study predicting long-term sick leave will result in an overestimation of the predictive properties of the instrument and biased predictors, especially when also the outcome of interest is included as a factor in the prediction model. Second, we object to the use of the term "screening" when subjects with the condition screened for are included in the study. Reinforced by the inclusion of sickness absence in the prediction model, including workers already on sick leave will shift the focus of the study findings towards the prediction of (re)current sickness absence and workers with a below-average return-to-work rate, rather than the identification of workers at high risk for the onset of future long-term sickness absence. The possibilities for prevention will shift from pure secondary prevention to a mix of secondary and tertiary prevention. As a consequence, the predictors of the model presented in the Schouten et al article can be used as a basis for tailoring neither preventive measures nor interventions. Moreover, including the outcome (sickness absence) as a predictor in the model, especially in a mixed population including workers with and without the condition (on sick leave), will result in biased predictors and an overestimation of the predictive value. A methodological approach of related issues is provided in the works of Glymour et al (5) and Hamilton et al (6). This phenomenon is even more clearly illustrated by the predictive properties of the workability index, as described by Alavinia et al (7, page 328), which reported that "when adjusted for individual characteristics, lifestyle factors, and work characteristics, two dimensions of the WAI were significant predictors for both moderate and long durations of sickness absence: (i) the presence of sickness absence in the past 12 months prior to the medical examination and (ii) experienced limitations due to health problems." So, when applied to the study by Schouten et al (1), this means that most of the predictive value would be related to the factors "sickness absence in the past 12 months". In addition, we object to the use of the term "screening" in the Schouten et al study as it includes workers with the intended outcome (long-term sickness absence). One can identify three separate aims to study the longitudinal association between risk factors and subsequent long-term sickness absence: (i) to establish causal risk factors for long-term sickness absence, often to find clues for primary preventive strategies (beyond the scope here); (ii) to identify high-risk workers who are still at work and might benefit from an intervention before sickness absence occurs (secondary prevention); and (iii) to identify workers on sick leave who might suffer a below-average return-to-work rate or have a high risk for the recurrence of (long-term) sickness absence and might benefit from intensification or optimization of the return-to-work process (tertiary prevention). In this light, one needs to separate screening instruments from predictive instruments and reserve the term "screening" for the situation as defined by Wilson and Junger (8, page 7): "The object of screening for disease is to discover those among the apparently well who are in fact suffering from disease" (ie, situations of secondary prevention). This means that, when applying this definition on long-term sickness absence under the precondition that the individuals are still at work, screening enables the identification of high-risk individuals in the early "stages" of a "disease" that can progress into long-term sickness absence. In the case of the Schouten et al study, the population at risk, as derived from their predictive instrument, consists of workers with and without sickness absence, and as such excludes the use of the term "screening" in this case. To conclude, we have substantiated that, in addition to correct usage of the term "screening", careful selection of the study population, predictors and most importantly the aim of the predictive model are essential in the process of developing predictive instruments aimed at identifying workers at high risk of long-term sickness absence. Two fundamentally different approaches are possible. One approach aims at identifying workers on sick leave with either a below-average chance to return to work an/or a high risk for a successive episode of long-term sickness absence. From a methodological and practical point of view, such an instrument should be developed and validated among workers already on sick leave. A second approach aims at identifying workers who are still at work but at high risk for future long-term sickness absence. To develop and validate such an instrument, a study sample where workers already on sick leave are excluded is a prerequisite. Such instruments fit in a pro-active approach of preventing future sickness absence, where an early intervention can be offered to those workers with an increased risk for future sickness absence.

Risk identification and prediction of coal workers' pneumoconiosis in Kailuan Colliery Group in China: a historical cohort study.

PubMed

Shen, Fuhai; Yuan, Juxiang; Sun, Zhiqian; Hua, Zhengbing; Qin, Tianbang; Yao, Sanqiao; Fan, Xueyun; Chen, Weihong; Liu, Hongbo; Chen, Jie

2013-01-01

Prior to 1970, coal mining technology and prevention measures in China were poor. Mechanized coal mining equipment and advanced protection measures were continuously installed in the mines after 1970. All these improvements may have resulted in a change in the incidence of coal workers' pneumoconiosis (CWP). Therefore, it is important to identify the characteristics of CWP today and trends for the incidence of CWP in the future. A total of 17,023 coal workers from the Kailuan Colliery Group were studied. A life-table method was used to calculate the cumulative incidence rate of CWP and predict the number of new CWP patients in the future. The probability of developing CWP was estimated by a multilayer perceptron artificial neural network for each coal worker without CWP. The results showed that the cumulative incidence rates of CWP for tunneling, mining, combining, and helping workers were 31.8%, 27.5%, 24.2%, and 2.6%, respectively, during the same observation period of 40 years. It was estimated that there would be 844 new CWP cases among 16,185 coal workers without CWP within their life expectancy. There would be 273.1, 273.1, 227.6, and 69.9 new CWP patients in the next <10, 10-, 20-, and 30- years respectively in the study cohort within their life expectancy. It was identified that coal workers whose risk probabilities were over 0.2 were at high risk for CWP, and whose risk probabilities were under 0.1 were at low risk. The present and future incidence trends of CWP remain high among coal workers. We suggest that coal workers at high risk of CWP undergo a physical examination for pneumoconiosis every year, and the coal workers at low risk of CWP be examined every 5 years.

Estimation of Wild Fire Risk Area based on Climate and Maximum Entropy in Korean Peninsular

NASA Astrophysics Data System (ADS)

Kim, T.; Lim, C. H.; Song, C.; Lee, W. K.

2015-12-01

The number of forest fires and accompanying human injuries and physical damages has been increased by frequent drought. In this study, forest fire danger zone of Korea is estimated to predict and prepare for future forest fire hazard regions. The MaxEnt (Maximum Entropy) model is used to estimate the forest fire hazard region which estimates the probability distribution of the status. The MaxEnt model is primarily for the analysis of species distribution, but its applicability for various natural disasters is getting recognition. The detailed forest fire occurrence data collected by the MODIS for past 5 years (2010-2014) is used as occurrence data for the model. Also meteorology, topography, vegetation data are used as environmental variable. In particular, various meteorological variables are used to check impact of climate such as annual average temperature, annual precipitation, precipitation of dry season, annual effective humidity, effective humidity of dry season, aridity index. Consequently, the result was valid based on the AUC(Area Under the Curve) value (= 0.805) which is used to predict accuracy in the MaxEnt model. Also predicted forest fire locations were practically corresponded with the actual forest fire distribution map. Meteorological variables such as effective humidity showed the greatest contribution, and topography variables such as TWI (Topographic Wetness Index) and slope also contributed on the forest fire. As a result, the east coast and the south part of Korea peninsula were predicted to have high risk on the forest fire. In contrast, high-altitude mountain area and the west coast appeared to be safe with the forest fire. The result of this study is similar with former studies, which indicates high risks of forest fire in accessible area and reflects climatic characteristics of east and south part in dry season. To sum up, we estimated the forest fire hazard zone with existing forest fire locations and environment variables and had meaningful result with artificial and natural effect. It is expected to predict future forest fire risk with future climate variables as the climate changes.

Using genetic prediction from known complex disease Loci to guide the design of next-generation sequencing experiments.

PubMed

Jostins, Luke; Levine, Adam P; Barrett, Jeffrey C

2013-01-01

A central focus of complex disease genetics after genome-wide association studies (GWAS) is to identify low frequency and rare risk variants, which may account for an important fraction of disease heritability unexplained by GWAS. A profusion of studies using next-generation sequencing are seeking such risk alleles. We describe how already-known complex trait loci (largely from GWAS) can be used to guide the design of these new studies by selecting cases, controls, or families who are most likely to harbor undiscovered risk alleles. We show that genetic risk prediction can select unrelated cases from large cohorts who are enriched for unknown risk factors, or multiply-affected families that are more likely to harbor high-penetrance risk alleles. We derive the frequency of an undiscovered risk allele in selected cases and controls, and show how this relates to the variance explained by the risk score, the disease prevalence and the population frequency of the risk allele. We also describe a new method for informing the design of sequencing studies using genetic risk prediction in large partially-genotyped families using an extension of the Inside-Outside algorithm for inference on trees. We explore several study design scenarios using both simulated and real data, and show that in many cases genetic risk prediction can provide significant increases in power to detect low-frequency and rare risk alleles. The same approach can also be used to aid discovery of non-genetic risk factors, suggesting possible future utility of genetic risk prediction in conventional epidemiology. Software implementing the methods in this paper is available in the R package Mangrove.

A Retrospective Analysis of Pressure Ulcer Incidence and Modified Braden Scale Score Risk Classifications.

PubMed

Chen, Hong-Lin; Cao, Ying-Juan; Wang, Jing; Huai, Bao-Sha

2015-09-01

The Braden Scale is the most widely used pressure ulcer risk assessment in the world, but the currently used 5 risk classification groups do not accurately discriminate among their risk categories. To optimize risk classification based on Braden Scale scores, a retrospective analysis of all consecutively admitted patients in an acute care facility who were at risk for pressure ulcer development was performed between January 2013 and December 2013. Predicted pressure ulcer incidence first was calculated by logistic regression model based on original Braden score. Risk classification then was modified based on the predicted pressure ulcer incidence and compared between different risk categories in the modified (3-group) classification and the traditional (5-group) classification using chi-square test. Two thousand, six hundred, twenty-five (2,625) patients (mean age 59.8 ± 16.5, range 1 month to 98 years, 1,601 of whom were men) were included in the study; 81 patients (3.1%) developed a pressure ulcer. The predicted pressure ulcer incidence ranged from 0.1% to 49.7%. When the predicted pressure ulcer incidence was greater than 10.0% (high risk), the corresponding Braden scores were less than 11; when the predicted incidence ranged from 1.0% to 10.0% (moderate risk), the corresponding Braden scores ranged from 12 to 16; and when the predicted incidence was less than 1.0% (mild risk), the corresponding Braden scores were greater than 17. In the modified classification, observed pressure ulcer incidence was significantly different between each of the 3 risk categories (P less than 0.05). However, in the traditional classification, the observed incidence was not significantly different between the high-risk category and moderate-risk category (P less than 0.05) and between the mild-risk category and no-risk category (P less than 0.05). If future studies confirm the validity of these findings, pressure ulcer prevention protocols of care based on Braden Scale scores can be simplified.

Upper gastrointestinal bleeding risk scores: Who, when and why?

PubMed Central

Monteiro, Sara; Gonçalves, Tiago Cúrdia; Magalhães, Joana; Cotter, José

2016-01-01

Upper gastrointestinal bleeding (UGIB) remains a significant cause of hospital admission. In order to stratify patients according to the risk of the complications, such as rebleeding or death, and to predict the need of clinical intervention, several risk scores have been proposed and their use consistently recommended by international guidelines. The use of risk scoring systems in early assessment of patients suffering from UGIB may be useful to distinguish high-risks patients, who may need clinical intervention and hospitalization, from low risk patients with a lower chance of developing complications, in which management as outpatients can be considered. Although several scores have been published and validated for predicting different outcomes, the most frequently cited ones are the Rockall score and the Glasgow Blatchford score (GBS). While Rockall score, which incorporates clinical and endoscopic variables, has been validated to predict mortality, the GBS, which is based on clinical and laboratorial parameters, has been studied to predict the need of clinical intervention. Despite the advantages previously reported, their use in clinical decisions is still limited. This review describes the different risk scores used in the UGIB setting, highlights the most important research, explains why and when their use may be helpful, reflects on the problems that remain unresolved and guides future research with practical impact. PMID:26909231

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges

PubMed Central

Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map’s coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions. PMID:27618445

Impacts of Climate Change on Native Landcover: Seeking Future Climatic Refuges.

PubMed

Zanin, Marina; Mangabeira Albernaz, Ana Luisa

2016-01-01

Climate change is a driver for diverse impacts on global biodiversity. We investigated its impacts on native landcover distribution in South America, seeking to predict its effect as a new force driving habitat loss and population isolation. Moreover, we mapped potential future climatic refuges, which are likely to be key areas for biodiversity conservation under climate change scenarios. Climatically similar native landcovers were aggregated using a decision tree, generating a reclassified landcover map, from which 25% of the map's coverage was randomly selected to fuel distribution models. We selected the best geographical distribution models among twelve techniques, validating the predicted distribution for current climate with the landcover map and used the best technique to predict the future distribution. All landcover categories showed changes in area and displacement of the latitudinal/longitudinal centroid. Closed vegetation was the only landcover type predicted to expand its distributional range. The range contractions predicted for other categories were intense, even suggesting extirpation of the sparse vegetation category. The landcover refuges under future climate change represent a small proportion of the South American area and they are disproportionately represented and unevenly distributed, predominantly occupying five of 26 South American countries. The predicted changes, regardless of their direction and intensity, can put biodiversity at risk because they are expected to occur in the near future in terms of the temporal scales of ecological and evolutionary processes. Recognition of the threat of climate change allows more efficient conservation actions.

Developing and validating risk prediction models in an individual participant data meta-analysis

PubMed Central

2014-01-01

Background Risk prediction models estimate the risk of developing future outcomes for individuals based on one or more underlying characteristics (predictors). We review how researchers develop and validate risk prediction models within an individual participant data (IPD) meta-analysis, in order to assess the feasibility and conduct of the approach. Methods A qualitative review of the aims, methodology, and reporting in 15 articles that developed a risk prediction model using IPD from multiple studies. Results The IPD approach offers many opportunities but methodological challenges exist, including: unavailability of requested IPD, missing patient data and predictors, and between-study heterogeneity in methods of measurement, outcome definitions and predictor effects. Most articles develop their model using IPD from all available studies and perform only an internal validation (on the same set of data). Ten of the 15 articles did not allow for any study differences in baseline risk (intercepts), potentially limiting their model’s applicability and performance in some populations. Only two articles used external validation (on different data), including a novel method which develops the model on all but one of the IPD studies, tests performance in the excluded study, and repeats by rotating the omitted study. Conclusions An IPD meta-analysis offers unique opportunities for risk prediction research. Researchers can make more of this by allowing separate model intercept terms for each study (population) to improve generalisability, and by using ‘internal-external cross-validation’ to simultaneously develop and validate their model. Methodological challenges can be reduced by prospectively planned collaborations that share IPD for risk prediction. PMID:24397587

[Risk assessment of carcinogenic and non-carcinogenic effects in the use of food].

PubMed

Frolova, O A; Karpova, M V

2012-01-01

Application of methodology for assessing the risk of diseases associated with consumption of contaminated foods, is aimed at predicting possible changes in the future and helps to create a framework for the prevention of negative effects on public health. The purpose of the study is assessment of health risks formed under the influence of chemical contaminants that pollute the food. Exponential average daily dose of receipt of chemicals in the body, non-carcinogenic and carcinogenic risks were calculated.

Preseason screening of shoulder range of motion and humeral retrotorsion does not predict injury in high school baseball players.

PubMed

Oyama, Sakiko; Hibberd, Elizabeth E; Myers, Joseph B

2017-07-01

Shoulder and elbow injuries are commonplace in high school baseball. Although altered shoulder range of motion (ROM) and humeral retrotorsion angles have been associated with injuries, the efficacy of preseason screening of these characteristics remains controversial. We conducted preseason screenings for shoulder internal and external rotation ROM and humeral retrotorsion on 832 high school baseball players and tracked their exposure and incidence on throwing-related shoulder and elbow injuries during a subsequent season. Poisson regression with robust error variance was used to determine whether preseason screening could identify injury risk in baseball players and whether the injury risk was higher for pitchers compared with players who do not pitch. Shoulder rotation ROM or humeral retrotorsion at preseason did not predict the risk of throwing-related upper extremity injury (P = .15-.89). Injury risk was 3.84 higher for baseball players who pitched compared with those who did not (95% confidence interval, 1.72-8.56; P = .001). Preseason measures of shoulder ROM and humeral retrotorsion may not be effective in identifying players who are at increased injury risk. Because shoulder ROM is a measure that fluctuates under a variety of influences, future study should investigate whether taking multiple measurements during a season can identify at-risk players. The usefulness of preseason screening may also depend on rigor of participation in sports. Future studies should investigate how preseason shoulder characteristics and participation factors (ie, pitch count and frequency, competitive level, pitching in multiple leagues) interact to predict injury risk in baseball players. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Shortened version of the work ability index to identify workers at risk of long-term sickness absence.

PubMed

Schouten, Lianne S; Bültmann, Ute; Heymans, Martijn W; Joling, Catelijne I; Twisk, Jos W R; Roelen, Corné A M

2016-04-01

The Work Ability Index (WAI) identifies non-sicklisted workers at risk of future long-term sickness absence (LTSA). The WAI is a complicated instrument and inconvenient for use in large-scale surveys. We investigated whether shortened versions of the WAI identify non-sicklisted workers at risk of LTSA. Prospective study including two samples of non-sicklisted workers participating in occupational health checks between 2010 and 2012. A heterogeneous development sample (N= 2899) was used to estimate logistic regression coefficients for the complete WAI, a shortened WAI version without the list of diseases, and single-item Work Ability Score (WAS). These three instruments were calibrated for predictions of different (≥2, ≥4 and ≥6 weeks) LTSA durations in a validation sample of non-sicklisted workers (N= 3049) employed at a steel mill, differentiating between manual (N= 1710) and non-manual (N= 1339) workers. The discriminative ability was investigated by receiver operating characteristic analysis. All three instruments under-predicted the LTSA risks in both manual and non-manual workers. The complete WAI discriminated between individuals at high and low risk of LTSA ≥2, ≥4 and ≥6 weeks in manual and non-manual workers. Risk predictions and discrimination by the shortened WAI without the list of diseases were as good as the complete WAI. The WAS showed poorer discrimination in manual and non-manual workers. The WAI without the list of diseases is a good alternative to the complete WAI to identify non-sicklisted workers at risk of future LTSA durations ≥2, ≥4 and ≥6 weeks. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Opioid Attentional Bias and Cue-Elicited Craving Predict Future Risk of Prescription Opioid Misuse Among Chronic Pain Patients*

PubMed Central

Garland, Eric L.; Howard, Matthew O.

2014-01-01

Background Some chronic pain patients receiving long-term opioid analgesic pharmacotherapy are at risk for misusing opioids. Like other addictive behaviors, risk of opioid misuse may be signaled by an attentional bias (AB) towards drug-related cues. The purpose of this study was to examine opioid AB as a potential predictor of opioid misuse among chronic pain patients following behavioral treatment. Methods Chronic pain patients taking long-term opioid analgesics (N = 47) completed a dot probe task designed to assess opioid AB, as well as self-report measures of opioid misuse and pain severity, and then participated in behavioral treatment. Regression analyses examined opioid AB and cue-elicited craving as predictors of opioid misuse at 3-months posttreatment follow-up. Results Patients who scored high on a measure of opioid misuse risk following treatment exhibited significantly greater opioid AB scores than patients at low risk for opioid misuse. Opioid AB for 200 ms cues and cue-elicited craving significantly predicted opioid misuse risk 20 weeks later, even after controlling for pre-treatment opioid dependence diagnosis, opioid misuse, and pain severity (Model R2 = .50). Conclusion Biased initial attentional orienting to prescription opioid cues and cue-elicited craving may reliably signal future opioid misuse risk following treatment. These measures may therefore provide potential prognostic indicators of treatment outcome. PMID:25282309

Traditional Cardiovascular Risk Factors as Predictors of Cardiovascular Events in the U.S. Astronaut Corps

NASA Technical Reports Server (NTRS)

Halm, M. K.; Clark, A.; Wear, M. L.; Murray, J. D.; Polk, J. D.; Amirian, E.

2009-01-01

Risk prediction equations from the Framingham Heart Study are commonly used to predict the absolute risk of myocardial infarction (MI) and coronary heart disease (CHD) related death. Predicting CHD-related events in the U.S. astronaut corps presents a monumental challenge, both because astronauts tend to live healthier lifestyles and because of the unique cardiovascular stressors associated with being trained for and participating in space flight. Traditional risk factors may not hold enough predictive power to provide a useful indicator of CHD risk in this unique population. It is important to be able to identify individuals who are at higher risk for CHD-related events so that appropriate preventive care can be provided. This is of special importance when planning long duration missions since the ability to provide advanced cardiac care and perform medical evacuation is limited. The medical regimen of the astronauts follows a strict set of clinical practice guidelines in an effort to ensure the best care. The purpose of this study was to evaluate the utility of the Framingham risk score (FRS), low-density lipoprotein (LDL) and high-density lipoprotein levels, blood pressure, and resting pulse as predictors of CHD-related death and MI in the astronaut corps, using Cox regression. Of these factors, only two, LDL and pulse at selection, were predictive of CHD events (HR(95% CI)=1.12 (1.00-1.25) and HR(95% CI)=1.70 (1.05-2.75) for every 5-unit increase in LDL and pulse, respectively). Since traditional CHD risk factors may lack the specificity to predict such outcomes in astronauts, the development of a new predictive model, using additional measures such as electron-beam computed tomography and carotid intima-media thickness ultrasound, is planned for the future.

Suicide risk assessment: Trust an implicit probe or listen to the patient?

PubMed

Harrison, Dominique P; Stritzke, Werner G K; Fay, Nicolas; Hudaib, Abdul-Rahman

2018-05-21

Previous research suggests implicit cognition can predict suicidal behavior. This study examined the utility of the death/suicide implicit association test (d/s-IAT) in acute and prospective assessment of suicide risk and protective factors, relative to clinician and patient estimates of future suicide risk. Patients (N = 128; 79 female; 111 Caucasian) presenting to an emergency department were recruited if they reported current suicidal ideation or had been admitted because of an acute suicide attempt. Patients completed the d/s-IAT and self-report measures assessing three death-promoting (e.g., suicide ideation) and two life-sustaining (e.g., zest for life) factors, with self-report measures completed again at 3- and 6-month follow-ups. The clinician and patient provided risk estimates of that patient making a suicide attempt within the next 6 months. Results showed that among current attempters, the d/s-IAT differentiated between first time and multiple attempters; with multiple attempters having significantly weaker self-associations with life relative to death. The d/s-IAT was associated with concurrent suicidal ideation and zest for life, but only predicted the desire to die prospectively at 3 months. By contrast, clinician and patient estimates predicted suicide risk at 3- and 6-month follow-up, with clinician estimates predicting death-promoting factors, and only patient estimates predicting life-sustaining factors. The utility of the d/s-IAT was more pronounced in the assessment of concurrent risk. Prospectively, clinician and patient predictions complemented each other in predicting suicide risk and resilience, respectively. Our findings indicate collaborative rather than implicit approaches add greater value to the management of risk and recovery in suicidal patients. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Intracranial pressure-induced optic nerve sheath response as a predictive biomarker for optic disc edema in astronauts.

PubMed

Wostyn, Peter; De Deyn, Peter Paul

2017-11-01

A significant proportion of the astronauts who spend extended periods in microgravity develop ophthalmic abnormalities. Understanding this syndrome, called visual impairment and intracranial pressure (VIIP), has become a high priority for National Aeronautics and Space Administration, especially in view of future long-duration missions (e.g., Mars missions). Moreover, to ensure selection of astronaut candidates who will be able to complete long-duration missions with low risk of the VIIP syndrome, it is imperative to identify biomarkers for VIIP risk prediction. Here, we hypothesize that the optic nerve sheath response to alterations in intracranial pressure may be a potential predictive biomarker for optic disc edema in astronauts. If confirmed, this biomarker could be used for preflight identification of astronauts at risk for developing VIIP-associated optic disc edema.

Fracture Prediction by Computed Tomography and Finite Element Analysis: Current and Future Perspectives.

PubMed

Johannesdottir, Fjola; Allaire, Brett; Bouxsein, Mary L

2018-05-30

This review critiques the ability of CT-based methods to predict incident hip and vertebral fractures. CT-based techniques with concurrent calibration all show strong associations with incident hip and vertebral fracture, predicting hip and vertebral fractures as well as, and sometimes better than, dual-energy X-ray absorptiometry areal biomass density (DXA aBMD). There is growing evidence for use of routine CT scans for bone health assessment. CT-based techniques provide a robust approach for osteoporosis diagnosis and fracture prediction. It remains to be seen if further technical advances will improve fracture prediction compared to DXA aBMD. Future work should include more standardization in CT analyses, establishment of treatment intervention thresholds, and more studies to determine whether routine CT scans can be efficiently used to expand the number of individuals who undergo evaluation for fracture risk.

Impulsive versus premeditated aggression in the prediction of violent criminal recidivism.

PubMed

Swogger, Marc T; Walsh, Zach; Christie, Michael; Priddy, Brittany M; Conner, Kenneth R

2015-01-01

Past aggression is a potent predictor of future aggression and informs the prediction of violent criminal recidivism. However, aggression is a heterogeneous construct and different types of aggression may confer different levels of risk for future violence. In this prospective study of 91 adults in a pretrial diversion program, we examined (a) premeditated versus impulsive aggression in the prediction of violent recidivism during a one-year follow-up period, and (b) whether either type of aggression would have incremental validity in the prediction of violent recidivism after taking into account frequency of past general aggression. Findings indicate that premeditated, but not impulsive, aggression predicts violent recidivism. Moreover, premeditated aggression remained a predictor of recidivism even with general aggression frequency in the model. Results provide preliminary evidence that the assessment of premeditated aggression provides relevant information for the management of violent offenders. © 2014 Wiley Periodicals, Inc.

Impulsive versus Premeditated Aggression in the Prediction of Violent Criminal Recidivism

PubMed Central

Swogger, Marc T.; Walsh, Zach; Christie, Michael; Priddy, Brittany M.; Conner, Kenneth R.

2015-01-01

Past aggression is a potent predictor of future aggression and informs the prediction of violent criminal recidivism. However, aggression is a heterogeneous construct and different types of aggression may confer different levels of risk for future violence. In this prospective study of 91 adults in a pretrial diversion program, we examined a) premeditated versus impulsive aggression in the prediction of violent recidivism during a one-year follow-up period, and b) whether either type of aggression would have incremental validity in the prediction of violent recidivism after taking into account frequency of past general aggression. Findings indicate that premeditated, but not impulsive, aggression predicts violent recidivism. Moreover, premeditated aggression remained a predictor of recidivism even with general aggression frequency in the model. Results provide preliminary evidence that the assessment of premeditated aggression provides relevant information for the management of violent offenders. PMID:25043811

Climate-driven spatial mismatches between British orchards and their pollinators: increased risks of pollination deficits

PubMed Central

Polce, Chiara; Garratt, Michael P; Termansen, Mette; Ramirez-Villegas, Julian; Challinor, Andrew J; Lappage, Martin G; Boatman, Nigel D; Crowe, Andrew; Endalew, Ayenew Melese; Potts, Simon G; Somerwill, Kate E; Biesmeijer, Jacobus C

2014-01-01

Understanding how climate change can affect crop-pollinator systems helps predict potential geographical mismatches between a crop and its pollinators, and therefore identify areas vulnerable to loss of pollination services. We examined the distribution of orchard species (apples, pears, plums and other top fruits) and their pollinators in Great Britain, for present and future climatic conditions projected for 2050 under the SRES A1B Emissions Scenario. We used a relative index of pollinator availability as a proxy for pollination service. At present, there is a large spatial overlap between orchards and their pollinators, but predictions for 2050 revealed that the most suitable areas for orchards corresponded to low pollinator availability. However, we found that pollinator availability may persist in areas currently used for fruit production, which are predicted to provide suboptimal environmental suitability for orchard species in the future. Our results may be used to identify mitigation options to safeguard orchard production against the risk of pollination failure in Great Britain over the next 50 years; for instance, choosing fruit tree varieties that are adapted to future climatic conditions, or boosting wild pollinators through improving landscape resources. Our approach can be readily applied to other regions and crop systems, and expanded to include different climatic scenarios. PMID:24638986

Ventral Striatum Functional Connectivity as a Predictor of Adolescent Depressive Disorder in a Longitudinal Community-Based Sample.

PubMed

Pan, Pedro Mario; Sato, João R; Salum, Giovanni A; Rohde, Luis A; Gadelha, Ary; Zugman, Andre; Mari, Jair; Jackowski, Andrea; Picon, Felipe; Miguel, Eurípedes C; Pine, Daniel S; Leibenluft, Ellen; Bressan, Rodrigo A; Stringaris, Argyris

2017-11-01

Previous studies have implicated aberrant reward processing in the pathogenesis of adolescent depression. However, no study has used functional connectivity within a distributed reward network, assessed using resting-state functional MRI (fMRI), to predict the onset of depression in adolescents. This study used reward network-based functional connectivity at baseline to predict depressive disorder at follow-up in a community sample of adolescents. A total of 637 children 6-12 years old underwent resting-state fMRI. Discovery and replication analyses tested intrinsic functional connectivity (iFC) among nodes of a putative reward network. Logistic regression tested whether striatal node strength, a measure of reward-related iFC, predicted onset of a depressive disorder at 3-year follow-up. Further analyses investigated the specificity of this prediction. Increased left ventral striatum node strength predicted increased risk for future depressive disorder (odds ratio=1.54, 95% CI=1.09-2.18), even after excluding participants who had depressive disorders at baseline (odds ratio=1.52, 95% CI=1.05-2.20). Among 11 reward-network nodes, only the left ventral striatum significantly predicted depression. Striatal node strength did not predict other common adolescent psychopathology, such as anxiety, attention deficit hyperactivity disorder, and substance use. Aberrant ventral striatum functional connectivity specifically predicts future risk for depressive disorder. This finding further emphasizes the need to understand how brain reward networks contribute to youth depression.

Orbital Debris Modeling

NASA Technical Reports Server (NTRS)

Liou, J. C.

2012-01-01

Presentation outlne: (1) The NASA Orbital Debris (OD) Engineering Model -- A mathematical model capable of predicting OD impact risks for the ISS and other critical space assets (2) The NASA OD Evolutionary Model -- A physical model capable of predicting future debris environment based on user-specified scenarios (3) The NASA Standard Satellite Breakup Model -- A model describing the outcome of a satellite breakup (explosion or collision)

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

PubMed

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

2008-01-01

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

Mandibular bone changes in 24 years and skeletal fracture prediction.

PubMed

Jonasson, G; Sundh, V; Hakeberg, M; Hassani-Nejad, A; Lissner, L; Ahlqwist, M

2013-03-01

The objectives of the investigation were to describe changes in mandibular bone structure with aging and to compare the usefulness of cortical and trabecular bone for fracture prediction. From 1968 to 1993, 1,003 women were examined. With the help of panoramic radiographs, cortex thickness was measured and cortex was categorized as: normal, moderately, or severely eroded. The trabeculation was assessed as sparse, mixed, or dense. Visually, the mandibular compact and trabecular bone transformed gradually during the 24 years. The compact bone became more porous, the intertrabecular spaces increased, and the radiographic image of the trabeculae seemed less mineralized. Cortex thickness increased up to the age of 50 and decreased significantly thereafter. At all examinations, the sparse trabeculation group had more fractures (71-78 %) than the non-sparse group (27-31 %), whereas the severely eroded compact group showed more fractures than the less eroded groups only in 1992/1993, 24 years later. Sparse trabecular pattern was associated with future fractures both in perimenopausal and older women (relative risk (RR), 1.47-4.37) and cortical erosion in older women (RR, 1.35-1.55). RR for future fracture associated with a severely eroded cortex increased to 4.98 for cohort 1930 in 1992/1993. RR for future fracture associated with sparse trabeculation increased to 11.43 for cohort 1922 in 1992/1993. Dental radiographs contain enough information to identify women most at risk of future fracture. When observing sparse mandibular trabeculation, dentists can identify 40-69 % of women at risk for future fractures, depending on participant age at examination.

Predicting Parent-Child Aggression Risk: Cognitive Factors and Their Interaction With Anger.

PubMed

Rodriguez, Christina M

2018-02-01

Several cognitive elements have previously been proposed to elevate risk for physical child abuse. To predict parent-child aggression risk, the current study evaluated the role of approval of parent-child aggression, perceptions of children as poorly behaved, and discipline attributions. Several dimensions of attributions specifically tied to parents' discipline practices were targeted. In addition, anger experienced during discipline episodes was considered a potential moderator of these cognitive processes. Using a largely multiple-indicator approach, a sample of 110 mothers reported on these cognitive and affective aspects that may occur when disciplining their children as well as responding to measures of parent-child aggression risk. Findings suggest that greater approval of parent-child aggression, negative perceptions of their child's behavior, and discipline attributions independently predicted parent-child aggression risk, with anger significantly interacting with mothers' perception of their child as more poorly behaved to exacerbate their parent-child aggression risk. Of the discipline attribution dimensions evaluated, mothers' sense of external locus of control and believing their child deserved their discipline were related to increase parent-child aggression risk. Future work is encouraged to comprehensively evaluate how cognitive and affective components contribute and interact to increase risk for parent-child aggression.

Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics.

PubMed

Rho, Mi Jung; Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Jung, Dong Jin; Kim, Dai-Jin; Choi, In Young

2017-12-27

Background : Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods : Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results : The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions : These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment.

Risk Factors for Internet Gaming Disorder: Psychological Factors and Internet Gaming Characteristics

PubMed Central

Lee, Hyeseon; Lee, Taek-Ho; Cho, Hyun; Kim, Dai-Jin; Choi, In Young

2017-01-01

Background: Understanding the risk factors associated with Internet gaming disorder (IGD) is important to predict and diagnose the condition. The purpose of this study is to identify risk factors that predict IGD based on psychological factors and Internet gaming characteristics; Methods: Online surveys were conducted between 26 November and 26 December 2014. There were 3568 Korean Internet game users among a total of 5003 respondents. We identified 481 IGD gamers and 3087 normal Internet gamers, based on Diagnostic and Statistical Manual for Mental Disorders (DSM-5) criteria. Logistic regression analysis was applied to identify significant risk factors for IGD; Results: The following eight risk factors were found to be significantly associated with IGD: functional and dysfunctional impulsivity (odds ratio: 1.138), belief self-control (1.034), anxiety (1.086), pursuit of desired appetitive goals (1.105), money spent on gaming (1.005), weekday game time (1.081), offline community meeting attendance (2.060), and game community membership (1.393; p < 0.05 for all eight risk factors); Conclusions: These risk factors allow for the prediction and diagnosis of IGD. In the future, these risk factors could also be used to inform clinical services for IGD diagnosis and treatment. PMID:29280953

Extinctions. Paleontological baselines for evaluating extinction risk in the modern oceans.

PubMed

Finnegan, Seth; Anderson, Sean C; Harnik, Paul G; Simpson, Carl; Tittensor, Derek P; Byrnes, Jarrett E; Finkel, Zoe V; Lindberg, David R; Liow, Lee Hsiang; Lockwood, Rowan; Lotze, Heike K; McClain, Craig R; McGuire, Jenny L; O'Dea, Aaron; Pandolfi, John M

2015-05-01

Marine taxa are threatened by anthropogenic impacts, but knowledge of their extinction vulnerabilities is limited. The fossil record provides rich information on past extinctions that can help predict biotic responses. We show that over 23 million years, taxonomic membership and geographic range size consistently explain a large proportion of extinction risk variation in six major taxonomic groups. We assess intrinsic risk-extinction risk predicted by paleontologically calibrated models-for modern genera in these groups. Mapping the geographic distribution of these genera identifies coastal biogeographic provinces where fauna with high intrinsic risk are strongly affected by human activity or climate change. Such regions are disproportionately in the tropics, raising the possibility that these ecosystems may be particularly vulnerable to future extinctions. Intrinsic risk provides a prehuman baseline for considering current threats to marine biodiversity. Copyright © 2015, American Association for the Advancement of Science.

Predicting fibromyalgia, a narrative review: are we better than fools and children?

PubMed

Ablin, J N; Buskila, D

2014-09-01

Fibromyalgia syndrome (FMS) is a common and intriguing condition, manifest by chronic pain and fatigue. Although the pathogenesis of FMS is not yet completely understood, predicting the future development of FMS and chronic pain is a major challenge with great potential advantages, both from an individual as well as an epidemiological standpoint. Current knowledge indicates a genetic underpinning for FMS, and as increasing data are accumulated regarding the genetics involved, the prospect of utilizing these data for prediction becomes ever more attractive. The co-existence of FMS with multiple other functional disorders indicates that the clinical identification of such symptom constellations in a patient can alert the physician to the future development of FMS. Hypermobility syndrome is another clinical (as well as genetic) phenotype that has emerged as a risk factor for the development of FMS. Stressful events, including early life trauma, are also harbingers of the future development of FMS. Functional neuroimaging may help to elucidate the neural processes involved in central sensitization, and may ultimately also evolve into markers of predictive value. Last but not least, obesity and disturbed sleep are clinical (inter-related) features relevant for this spectrum. Future efforts will aim at integrating genetic, clinical and physiological data in the prediction of FMS and chronic pain. © 2014 European Pain Federation - EFIC®

Risk Prediction Models in Psychiatry: Toward a New Frontier for the Prevention of Mental Illnesses.

PubMed

Bernardini, Francesco; Attademo, Luigi; Cleary, Sean D; Luther, Charles; Shim, Ruth S; Quartesan, Roberto; Compton, Michael T

2017-05-01

We conducted a systematic, qualitative review of risk prediction models designed and tested for depression, bipolar disorder, generalized anxiety disorder, posttraumatic stress disorder, and psychotic disorders. Our aim was to understand the current state of research on risk prediction models for these 5 disorders and thus future directions as our field moves toward embracing prediction and prevention. Systematic searches of the entire MEDLINE electronic database were conducted independently by 2 of the authors (from 1960 through 2013) in July 2014 using defined search criteria. Search terms included risk prediction, predictive model, or prediction model combined with depression, bipolar, manic depressive, generalized anxiety, posttraumatic, PTSD, schizophrenia, or psychosis. We identified 268 articles based on the search terms and 3 criteria: published in English, provided empirical data (as opposed to review articles), and presented results pertaining to developing or validating a risk prediction model in which the outcome was the diagnosis of 1 of the 5 aforementioned mental illnesses. We selected 43 original research reports as a final set of articles to be qualitatively reviewed. The 2 independent reviewers abstracted 3 types of data (sample characteristics, variables included in the model, and reported model statistics) and reached consensus regarding any discrepant abstracted information. Twelve reports described models developed for prediction of major depressive disorder, 1 for bipolar disorder, 2 for generalized anxiety disorder, 4 for posttraumatic stress disorder, and 24 for psychotic disorders. Most studies reported on sensitivity, specificity, positive predictive value, negative predictive value, and area under the (receiver operating characteristic) curve. Recent studies demonstrate the feasibility of developing risk prediction models for psychiatric disorders (especially psychotic disorders). The field must now advance by (1) conducting more large-scale, longitudinal studies pertaining to depression, bipolar disorder, anxiety disorders, and other psychiatric illnesses; (2) replicating and carrying out external validations of proposed models; (3) further testing potential selective and indicated preventive interventions; and (4) evaluating effectiveness of such interventions in the context of risk stratification using risk prediction models. © Copyright 2017 Physicians Postgraduate Press, Inc.

Assessing the reliability, predictive and construct validity of historical, clinical and risk management-20 (HCR-20) in Mexican psychiatric inpatients.

PubMed

Sada, Andrea; Robles-García, Rebeca; Martínez-López, Nicolás; Hernández-Ramírez, Rafael; Tovilla-Zarate, Carlos-Alfonso; López-Munguía, Fernando; Suárez-Alvarez, Enrique; Ayala, Xochitl; Fresán, Ana

2016-08-01

Assessing dangerousness to gauge the likelihood of future violent behaviour has become an integral part of clinical mental health practice in forensic and non-forensic psychiatric settings, one of the most effective instruments for this being the Historical, Clinical and Risk Management-20 (HCR-20). To examine the HCR-20 factor structure in Mexican psychiatric inpatients and to obtain its predictive validity and reliability for use in this population. In total, 225 patients diagnosed with psychotic, affective or personality disorders were included. The HCR-20 was applied at hospital admission and violent behaviours were assessed during psychiatric hospitalization using the Overt Aggression Scale (OAS). Construct validity, predictive validity and internal consistency were determined. Violent behaviour remains more severe in patients classified in the high-risk group during hospitalization. Fifteen items displayed adequate communalities in the original designated domains of the HCR-20 and internal consistency of the instruments was high. The HCR-20 is a suitable instrument for predicting violence risk in Mexican psychiatric inpatients.

How to make predictions about future infectious disease risks

PubMed Central

Woolhouse, Mark

2011-01-01

Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the ‘art of the possible’, which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for ‘good practice’ for the development and the use of predictive models. PMID:21624924

Scalar utility theory and proportional processing: what does it actually imply?

PubMed Central

Rosenström, Tom; Wiesner, Karoline; Houston, Alasdair I

2017-01-01

Scalar Utility Theory (SUT) is a model used to predict animal and human choice behaviour in the context of reward amount, delay to reward, and variability in these quantities (risk preferences). This article reviews and extends SUT, deriving novel predictions. We show that, contrary to what has been implied in the literature, (1) SUT can predict both risk averse and risk prone behaviour for both reward amounts and delays to reward depending on experimental parameters, (2) SUT implies violations of several concepts of rational behaviour (e.g. it violates strong stochastic transitivity and its equivalents, and leads to probability matching) and (3) SUT can predict, but does not always predict, a linear relationship between risk sensitivity in choices and coefficient of variation in the decision-making experiment. SUT derives from Scalar Expectancy Theory which models uncertainty in behavioural timing using a normal distribution. We show that the above conclusions also hold for other distributions, such as the inverse Gaussian distribution derived from drift-diffusion models. A straightforward way to test the key assumptions of SUT is suggested and possible extensions, future prospects and mechanistic underpinnings are discussed. PMID:27288541

Can theory predict the process of suicide on entry to prison? Predicting dynamic risk factors for suicide ideation in a high-risk prison population.

PubMed

Slade, Karen; Edelman, Robert

2014-01-01

Each year approximately 110,000 people are imprisoned in England and Wales and new prisoners remain one of the highest risk groups for suicide across the world. The reduction of suicide in prisoners remains difficult as assessments and interventions tend to rely on static risk factors with few theoretical or integrated models yet evaluated. To identify the dynamic factors that contribute to suicide ideation in this population based on Williams and Pollock's (2001) Cry of Pain (CoP) model. New arrivals (N = 198) into prison were asked to complete measures derived from the CoP model plus clinical and prison-specific factors. It was hypothesized that the factors of the CoP model would be predictive of suicide ideation. Support was provided for the defeat and entrapment aspects of the CoP model with previous self-harm, repeated times in prison, and suicide-permissive cognitions also key in predicting suicide ideation for prisoners on entry to prison. An integrated and dynamic model was developed that has utility in predicting suicide in early-stage prisoners. Implications for both theory and practice are discussed along with recommendations for future research.

Scalar utility theory and proportional processing: What does it actually imply?

PubMed

Rosenström, Tom; Wiesner, Karoline; Houston, Alasdair I

2016-09-07

Scalar Utility Theory (SUT) is a model used to predict animal and human choice behaviour in the context of reward amount, delay to reward, and variability in these quantities (risk preferences). This article reviews and extends SUT, deriving novel predictions. We show that, contrary to what has been implied in the literature, (1) SUT can predict both risk averse and risk prone behaviour for both reward amounts and delays to reward depending on experimental parameters, (2) SUT implies violations of several concepts of rational behaviour (e.g. it violates strong stochastic transitivity and its equivalents, and leads to probability matching) and (3) SUT can predict, but does not always predict, a linear relationship between risk sensitivity in choices and coefficient of variation in the decision-making experiment. SUT derives from Scalar Expectancy Theory which models uncertainty in behavioural timing using a normal distribution. We show that the above conclusions also hold for other distributions, such as the inverse Gaussian distribution derived from drift-diffusion models. A straightforward way to test the key assumptions of SUT is suggested and possible extensions, future prospects and mechanistic underpinnings are discussed. Copyright © 2016 Elsevier Ltd. All rights reserved.

Coral bleaching pathways under the control of regional temperature variability

NASA Astrophysics Data System (ADS)

Langlais, C. E.; Lenton, A.; Heron, S. F.; Evenhuis, C.; Sen Gupta, A.; Brown, J. N.; Kuchinke, M.

2017-11-01

Increasing sea surface temperatures (SSTs) are predicted to adversely impact coral populations worldwide through increasing thermal bleaching events. Future bleaching is unlikely to be spatially uniform. Therefore, understanding what determines regional differences will be critical for adaptation management. Here, using a cumulative heat stress metric, we show that characteristics of regional SST determine the future bleaching risk patterns. Incorporating observed information on SST variability, in assessing future bleaching risk, provides novel options for management strategies. As a consequence, the known biases in climate model variability and the uncertainties in regional warming rate across climate models are less detrimental than previously thought. We also show that the thresholds used to indicate reef viability can strongly influence a decision on what constitutes a potential refugia. Observing and understanding the drivers of regional variability, and the viability limits of coral reefs, is therefore critical for making meaningful projections of coral bleaching risk.

Reward-related neural activity and structure predict future substance use in dysregulated youth.

PubMed

Bertocci, M A; Bebko, G; Versace, A; Iyengar, S; Bonar, L; Forbes, E E; Almeida, J R C; Perlman, S B; Schirda, C; Travis, M J; Gill, M K; Diwadkar, V A; Sunshine, J L; Holland, S K; Kowatch, R A; Birmaher, B; Axelson, D A; Frazier, T W; Arnold, L E; Fristad, M A; Youngstrom, E A; Horwitz, S M; Findling, R L; Phillips, M L

2017-06-01

Identifying youth who may engage in future substance use could facilitate early identification of substance use disorder vulnerability. We aimed to identify biomarkers that predicted future substance use in psychiatrically un-well youth. LASSO regression for variable selection was used to predict substance use 24.3 months after neuroimaging assessment in 73 behaviorally and emotionally dysregulated youth aged 13.9 (s.d. = 2.0) years, 30 female, from three clinical sites in the Longitudinal Assessment of Manic Symptoms (LAMS) study. Predictor variables included neural activity during a reward task, cortical thickness, and clinical and demographic variables. Future substance use was associated with higher left middle prefrontal cortex activity, lower left ventral anterior insula activity, thicker caudal anterior cingulate cortex, higher depression and lower mania scores, not using antipsychotic medication, more parental stress, older age. This combination of variables explained 60.4% of the variance in future substance use, and accurately classified 83.6%. These variables explained a large proportion of the variance, were useful classifiers of future substance use, and showed the value of combining multiple domains to provide a comprehensive understanding of substance use development. This may be a step toward identifying neural measures that can identify future substance use disorder risk, and act as targets for therapeutic interventions.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing.

PubMed

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models.

Perception of Risk and Terrorism-Related Behavior Change: Dual Influences of Probabilistic Reasoning and Reality Testing

PubMed Central

Denovan, Andrew; Dagnall, Neil; Drinkwater, Kenneth; Parker, Andrew; Clough, Peter

2017-01-01

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behavior change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behavior change scale. Structural equation modeling examined three progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behavior change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behavior change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behavior change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behavior change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behavior change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behavior change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. PMID:29062288

Health risk factors as predictors of workers' compensation claim occurrence and cost

PubMed Central

Schwatka, Natalie V; Atherly, Adam; Dally, Miranda J; Fang, Hai; vS Brockbank, Claire; Tenney, Liliana; Goetzel, Ron Z; Jinnett, Kimberly; Witter, Roxana; Reynolds, Stephen; McMillen, James; Newman, Lee S

2017-01-01

Objective The objective of this study was to examine the predictive relationships between employee health risk factors (HRFs) and workers' compensation (WC) claim occurrence and costs. Methods Logistic regression and generalised linear models were used to estimate the predictive association between HRFs and claim occurrence and cost among a cohort of 16 926 employees from 314 large, medium and small businesses across multiple industries. First, unadjusted (HRFs only) models were estimated, and second, adjusted (HRFs plus demographic and work organisation variables) were estimated. Results Unadjusted models demonstrated that several HRFs were predictive of WC claim occurrence and cost. After adjusting for demographic and work organisation differences between employees, many of the relationships previously established did not achieve statistical significance. Stress was the only HRF to display a consistent relationship with claim occurrence, though the type of stress mattered. Stress at work was marginally predictive of a higher odds of incurring a WC claim (p<0.10). Stress at home and stress over finances were predictive of higher and lower costs of claims, respectively (p<0.05). Conclusions The unadjusted model results indicate that HRFs are predictive of future WC claims. However, the disparate findings between unadjusted and adjusted models indicate that future research is needed to examine the multilevel relationship between employee demographics, organisational factors, HRFs and WC claims. PMID:27530688

Psychological and Behavioral Risk Factors for Obesity Onset in Adolescent Girls: A Prospective Study

ERIC Educational Resources Information Center

Stice, Eric; Presnell, Katherine; Shaw, Heather; Rohde, Paul

2005-01-01

Because little is known about risk factors for obesity, the authors tested whether certain psychological and behavioral variables predicted future onset of obesity. The authors used data from a prospective study of 496 adolescent girls who completed a baseline assessment at age 11-15 years and 4 annual follow-ups. Self-reported dietary restraint,…

Defence mechanisms: the role of physiology in current and future environmental protection paradigms

PubMed Central

Glover, Chris N

2018-01-01

Abstract Ecological risk assessments principally rely on simplified metrics of organismal sensitivity that do not consider mechanism or biological traits. As such, they are unable to adequately extrapolate from standard laboratory tests to real-world settings, and largely fail to account for the diversity of organisms and environmental variables that occur in natural environments. However, an understanding of how stressors influence organism health can compensate for these limitations. Mechanistic knowledge can be used to account for species differences in basal biological function and variability in environmental factors, including spatial and temporal changes in the chemical, physical and biological milieu. Consequently, physiological understanding of biological function, and how this is altered by stressor exposure, can facilitate proactive, predictive risk assessment. In this perspective article, existing frameworks that utilize physiological knowledge (e.g. biotic ligand models, adverse outcomes pathways and mechanistic effect models), are outlined, and specific examples of how mechanistic understanding has been used to predict risk are highlighted. Future research approaches and data needs for extending the incorporation of physiological information into ecological risk assessments are discussed. Although the review focuses on chemical toxicants in aquatic systems, physical and biological stressors and terrestrial environments are also briefly considered. PMID:29564135

Avoiding Drought Risks and Social Conflict Under Climate Change

NASA Astrophysics Data System (ADS)

Towler, E.; Lazrus, H.; Paimazumder, D.

2014-12-01

Traditional drought research has mainly focused on physical drought risks and less on the cultural processes that also contribute to how drought risks are perceived and managed. However, as society becomes more vulnerable to drought and climate change threatens to increase water scarcity, it is clear that drought research would benefit from a more interdisciplinary approach. To assess avoided drought impacts from reduced climate change, drought risks need to be assessed in the context of both climate prediction as well as improved understanding of socio-cultural processes. To this end, this study explores a risk-based framework to combine physical drought likelihoods with perceived risks from stakeholder interviews. Results are presented from a case study on how stakeholders in south-central Oklahoma perceive drought risks given diverse cultural beliefs, water uses, and uncertainties in future drought prediction. Stakeholder interviews (n=38) were conducted in 2012 to understand drought risks to various uses of water, as well as to measure worldviews from the cultural theory of risk - a theory that explains why people perceive risks differently, potentially leading to conflict over management decisions. For physical drought risk, drought projections are derived from a large ensemble of future climates generated from two RCPs that represent higher and lower emissions trajectories (i.e., RCP8.5 and RCP4.5). These are used to develop a Combined Drought Risk Matrix (CDRM) that characterizes drought risks for different water uses as the products of both physical likelihood (from the climate ensemble) and risk perception (from the interviews). We use the CRDM to explore the avoided drought risks posed to various water uses, as well as to investigate the potential for reduction of conflict over water management.

Risk assessment models to predict caries recurrence after oral rehabilitation under general anaesthesia: a pilot study.

PubMed

Lin, Yai-Tin; Kalhan, Ashish Chetan; Lin, Yng-Tzer Joseph; Kalhan, Tosha Ashish; Chou, Chein-Chin; Gao, Xiao Li; Hsu, Chin-Ying Stephen

2018-05-08

Oral rehabilitation under general anaesthesia (GA), commonly employed to treat high caries-risk children, has been associated with high economic and individual/family burden, besides high post-GA caries recurrence rates. As there is no caries prediction model available for paediatric GA patients, this study was performed to build caries risk assessment/prediction models using pre-GA data and to explore mid-term prognostic factors for early identification of high-risk children prone to caries relapse post-GA oral rehabilitation. Ninety-two children were identified and recruited with parental consent before oral rehabilitation under GA. Biopsychosocial data collection at baseline and the 6-month follow-up were conducted using questionnaire (Q), microbiological assessment (M) and clinical examination (C). The prediction models constructed using data collected from Q, Q + M and Q + M + C demonstrated an accuracy of 72%, 78% and 82%, respectively. Furthermore, of the 83 (90.2%) patients recalled 6 months after GA intervention, recurrent caries was identified in 54.2%, together with reduced bacterial counts, lower plaque index and increased percentage of children toothbrushing for themselves (all P < 0.05). Additionally, meal-time and toothbrushing duration were shown, through bivariate analyses, to be significant prognostic determinants for caries recurrence (both P < 0.05). Risk assessment/prediction models built using pre-GA data may be promising in identifying high-risk children prone to post-GA caries recurrence, although future internal and external validation of predictive models is warranted. © 2018 FDI World Dental Federation.

Credit risk evaluation based on social media.

PubMed

Yang, Yang; Gu, Jing; Zhou, Zongfang

2016-07-01

Social media has been playing an increasingly important role in the sharing of individuals' opinions on many financial issues, including credit risk in investment decisions. This paper analyzes whether these opinions, which are transmitted through social media, can accurately predict enterprises' future credit risk. We consider financial statements oriented evaluation results based on logit and probit approaches as the benchmarks. We then conduct textual analysis to retrieve both posts and their corresponding commentaries published on two of the most popular social media platforms for financial investors in China. Professional advice from financial analysts is also investigated in this paper. We surprisingly find that the opinions extracted from both posts and commentaries surpass opinions of analysts in terms of credit risk prediction. Copyright © 2015 Elsevier Inc. All rights reserved.

Food Reinforcement and Parental Obesity Predict Future Weight Gain in Non-Obese Adolescents

PubMed Central

Epstein, Leonard H.; Yokum, Sonja; Feda, Denise M.; Stice, Eric

2014-01-01

Background Food reinforcement, the extent to which people are willing to work to earn a preferred snack food, and parental obesity are risk factors for weight gain, but there is no research comparing the predictive effects of these factors for adolescent weight gain. Methods 130 non-obese adolescents (M age = 15.2 ± 1.0; M BMI = 20.7 ± 2.0; M zBMI = 0.16 ± 0.64) at differential risk for weight gain based on parental obesity completed baseline food and money reinforcement tasks, and provided zBMI data over 2-yr follow-up. Results The number of obese (BMI ≥ 30) parents (p = 0.007) and high food reinforcement (p = 0.046) were both significant independent predictors of greater zBMI increases, controlling for age, sex, parent education and minority status. Having no obese parents or being low or average in food reinforcement was associated with reductions in zBMI, but those high in food reinforcement showed larger zBMI increases (0.102) than having one obese parent (0.025) but less than having two obese parents (0.177). Discussion Food reinforcement and parental obesity independently predict future weight gain among adolescents. It might be fruitful for obesity prevention programs to target both high risk groups. PMID:25045864

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods.

PubMed

Grossi, Enzo

2006-05-03

In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level.

Fibrinogen concentration and its role in CVD risk in black South Africans--effect of urbanisation.

PubMed

Pieters, Marlien; de Maat, Moniek P M; Jerling, Johann C; Hoekstra, Tiny; Kruger, Annamarie

2011-09-01

The aim of this study was to investigate correlates of fibrinogen concentration in black South Africans, as well as its association with cardiovascular disease (CVD) risk and whether urbanisation influences this association. A total of 1,006 rural and 1,004 urban black South Africans from the PURE study were cross-sectionally analysed. The association of fibrinogen with CVD risk was determined by investigating the association of fibrinogen with other CVD risk markers as well as with predicted CVD risk using the Reynolds Risk score. The rural group had a significantly higher fibrinogen concentration than the urban group, despite higher levels of risk factors and increased predicted CVD risk in the urban group. Increased levels of CVD risk factors were, however, still associated with increased fibrinogen concentration. Fibrinogen correlated significantly, but weakly, with overall predicted CVD risk. This correlation was stronger in the urban than in the rural group. Multiple regression analysis showed that a smaller percentage of the variance in fibrinogen is explained by the traditional CVD risk factors in the rural than in the urban group. In conclusion, fibrinogen is weakly associated with CVD risk (predicted overall risk as well with individual risk factors) in black South Africans, and is related to the degree of urbanisation. Increased fibrinogen concentration, in black South Africans, especially in rural areas, is largely unexplained, and likely not strongly correlated with traditional CVD-related lifestyle and pathophysiological processes. This does, however, not exclude the possibility that once increased, the fibrinogen concentration contributes to future development of CVD.

Hip Strength as a Predictor of Ankle Sprains in Male Soccer Players: A Prospective Study.

PubMed

Powers, Christopher M; Ghoddosi, Navid; Straub, Rachel K; Khayambashi, Khalil

2017-11-01

  Diminished hip-abductor strength has been suggested to increase the risk of noncontact lateral ankle sprains.   To determine prospectively whether baseline hip-abductor strength predicts future noncontact lateral ankle sprains in competitive male soccer players.   Prospective cohort study.   Athletic training facilities and various athletic fields.   Two hundred ten competitive male soccer players.   Before the start of the sport season, isometric hip-abductor strength was measured bilaterally using a handheld dynamometer. Any previous history of ankle sprain, body mass index, age, height, and weight were documented. During the sport season (30 weeks), ankle injury status was recorded by team medical providers. Injured athletes were further classified based on the mechanism of injury. Only data from injured athletes who sustained noncontact lateral ankle sprains were used for analysis. Postseason, logistic regression was used to determine whether baseline hip strength predicted future noncontact lateral ankle sprains. A receiver operating characteristic curve was constructed for hip strength to determine the cutoff value for distinguishing between high-risk and low-risk outcomes.   A total of 25 noncontact lateral ankle sprains were confirmed, for an overall annual incidence of 11.9%. Baseline hip-abductor strength was lower in injured players than in uninjured players ( P = .008). Logistic regression indicated that impaired hip-abductor strength increased the future injury risk (odds ratio = 1.10 [95% confidence interval = 1.02, 1.18], P = .010). The strength cutoff to define high risk was ≤33.8% body weight, as determined by receiver operating characteristic curve analysis. For athletes classified as high risk, the probability of injury increased from 11.9% to 26.7%.   Reduced isometric hip-abductor strength predisposed competitive male soccer players to noncontact lateral ankle sprains.

Designing and operating infrastructure for nonstationary flood risk management

NASA Astrophysics Data System (ADS)

Doss-Gollin, J.; Farnham, D. J.; Lall, U.

2017-12-01

Climate exhibits organized low-frequency and regime-like variability at multiple time scales, causing the risk associated with climate extremes such as floods and droughts to vary in time. Despite broad recognition of this nonstationarity, there has been little theoretical development of ideas for the design and operation of infrastructure considering the regime structure of such changes and their potential predictability. We use paleo streamflow reconstructions to illustrate an approach to the design and operation of infrastructure to address nonstationary flood and drought risk. Specifically, we consider the tradeoff between flood control and conservation storage, and develop design and operation principles for allocating these storage volumes considering both a m-year project planning period and a n-year historical sampling record. As n increases, the potential uncertainty in probabilistic estimates of the return periods associated with the T-year extreme event decreases. As the duration m of the future operation period decreases, the uncertainty associated with the occurrence of the T-year event also increases. Finally, given the quasi-periodic nature of the system it may be possible to offer probabilistic predictions of the conditions in the m-year future period, especially if m is small. In the context of such predictions, one can consider that a m-year prediction may have lower bias, but higher variance, than would be associated with using a stationary estimate from the preceding n years. This bias-variance trade-off, and the potential for considering risk management for multiple values of m, provides an interesting system design challenge. We use wavelet-based simulation models in a Bayesian framework to estimate these biases and uncertainty distributions and devise a risk-optimized decision rule for the allocation of flood and conservation storage. The associated theoretical development also provides a methodology for the sizing of storage for new infrastructure under nonstationarity, and an examination of risk adaptation measures which consider both short term and long term options simultaneously.

Long-Term Worries after Colposcopy: Which Women Are at Increased Risk?

PubMed

Sharp, Linda; Cotton, Seonaidh C; Cruickshank, Margaret E; Gray, Nicola M; Neal, Keith; Rothnie, Kieran; Thornton, Alison J; Walker, Leslie G; Little, Julian

2015-01-01

A colposcopy examination is the main management option for women with an abnormal cervical screening test result. Although some women experience adverse psychological effects after colposcopy, those at greatest risk are unknown. We investigated predictors of worries about cervical cancer, sex, future fertility and general health during 12 to 30 months after colposcopy. We invited 1,515 women, aged 20 to 59 years with low-grade cervical cytology who attended colposcopy to complete questionnaires at recruitment (∼8 weeks after cytology result) and after 12, 18, 24, and 30 months of follow up. Outcomes were worries about having cervical cancer, having sex, future fertility, and general health at any time during follow-up. Factors significantly associated with each outcome were identified using multiple logistic regression. At one or more time points during follow-up, 40% of women reported worries about having cervical cancer, 26% about having sex, 24% about future fertility, and 60% about general health. For all outcomes except sex, worries reported at recruitment were associated with significantly increased risk of worries during follow-up. Significant anxiety at recruitment was associated with all worries during follow-up. Women diagnosed with CIN2+ had significantly higher risks of worries about cervical cancer and future fertility. Management received was associated significantly with worries about cervical cancer and having sex. Younger women significantly more often reported worries about future fertility, whereas women who had children had reduced risk of future fertility worries but increased risk of cervical cancer worries. Clinical, sociodemographic, lifestyle, and psychological factors predicted risk of reporting worries after colposcopy. Copyright © 2015 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

Risk Factors and Biomarkers of Age-Related Macular Degeneration

PubMed Central

Lambert, Nathan G.; Singh, Malkit K.; ElShelmani, Hanan; Mansergh, Fiona C.; Wride, Michael A.; Padilla, Maximilian; Keegan, David; Hogg, Ruth E.; Ambati, Balamurali K.

2016-01-01

A biomarker can be a substance or structure measured in body parts, fluids or products that can affect or predict disease incidence. As age-related macular degeneration (AMD) is the leading cause of blindness in the developed world, much research and effort has been invested in the identification of different biomarkers to predict disease incidence, identify at risk individuals, elucidate causative pathophysiological etiologies, guide screening, monitoring and treatment parameters, and predict disease outcomes. To date, a host of genetic, environmental, proteomic, and cellular targets have been identified as both risk factors and potential biomarkers for AMD. Despite this, their use has been confined to research settings and has not yet crossed into the clinical arena. A greater understanding of these factors and their use as potential biomarkers for AMD can guide future research and clinical practice. This article will discuss known risk factors and novel, potential biomarkers of AMD in addition to their application in both academic and clinical settings. PMID:27156982

Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide.

PubMed

Wang, Zeneng; Tang, W H Wilson; Buffa, Jennifer A; Fu, Xiaoming; Britt, Earl B; Koeth, Robert A; Levison, Bruce S; Fan, Yiying; Wu, Yuping; Hazen, Stanley L

2014-04-01

Recent metabolomics and animal model studies show trimethylamine-N-oxide (TMAO), an intestinal microbiota-dependent metabolite formed from dietary trimethylamine-containing nutrients such as phosphatidylcholine (PC), choline, and carnitine, is linked to coronary artery disease pathogenesis. Our aim was to examine the prognostic value of systemic choline and betaine levels in stable cardiac patients. We examined the relationship between fasting plasma choline and betaine levels and risk of major adverse cardiac events (MACE = death, myocardial infraction, stroke) in relation to TMAO over 3 years of follow-up in 3903 sequential stable subjects undergoing elective diagnostic coronary angiography. In our study cohort, median (IQR) TMAO, choline, and betaine levels were 3.7 (2.4-6.2)μM, 9.8 (7.9-12.2)μM, and 41.1 (32.5-52.1)μM, respectively. Modest but statistically significant correlations were noted between TMAO and choline (r = 0.33, P < 0.001) and less between TMAO and betaine (r = 0.09, P < 0.001). Higher plasma choline and betaine levels were associated with a 1.9-fold and 1.4-fold increased risk of MACE, respectively (Quartiles 4 vs. 1; P < 0.01, each). Following adjustments for traditional cardiovascular risk factors and high-sensitivity C-reactive protein, elevated choline [1.34 (1.03-1.74), P < 0.05], and betaine levels [1.33 (1.03-1.73), P < 0.05] each predicted increased MACE risk. Neither choline nor betaine predicted MACE risk when TMAO was added to the adjustment model, and choline and betaine predicted future risk for MACE only when TMAO was elevated. Elevated plasma levels of choline and betaine are each associated with incident MACE risk independent of traditional risk factors. However, high choline and betaine levels are only associated with higher risk of future MACE with concomitant increase in TMAO.

Prognostic value of choline and betaine depends on intestinal microbiota-generated metabolite trimethylamine-N-oxide

PubMed Central

Wang, Zeneng; Tang, W. H. Wilson; Buffa, Jennifer A.; Fu, Xiaoming; Britt, Earl B.; Koeth, Robert A.; Levison, Bruce S.; Fan, Yiying; Wu, Yuping; Hazen, Stanley L.

2014-01-01

Aims Recent metabolomics and animal model studies show trimethylamine-N-oxide (TMAO), an intestinal microbiota-dependent metabolite formed from dietary trimethylamine-containing nutrients such as phosphatidylcholine (PC), choline, and carnitine, is linked to coronary artery disease pathogenesis. Our aim was to examine the prognostic value of systemic choline and betaine levels in stable cardiac patients. Methods and results We examined the relationship between fasting plasma choline and betaine levels and risk of major adverse cardiac events (MACE = death, myocardial infraction, stroke) in relation to TMAO over 3 years of follow-up in 3903 sequential stable subjects undergoing elective diagnostic coronary angiography. In our study cohort, median (IQR) TMAO, choline, and betaine levels were 3.7 (2.4–6.2)μM, 9.8 (7.9–12.2)μM, and 41.1 (32.5–52.1)μM, respectively. Modest but statistically significant correlations were noted between TMAO and choline (r = 0.33, P < 0.001) and less between TMAO and betaine (r = 0.09, P < 0.001). Higher plasma choline and betaine levels were associated with a 1.9-fold and 1.4-fold increased risk of MACE, respectively (Quartiles 4 vs. 1; P < 0.01, each). Following adjustments for traditional cardiovascular risk factors and high-sensitivity C-reactive protein, elevated choline [1.34 (1.03–1.74), P < 0.05], and betaine levels [1.33 (1.03–1.73), P < 0.05] each predicted increased MACE risk. Neither choline nor betaine predicted MACE risk when TMAO was added to the adjustment model, and choline and betaine predicted future risk for MACE only when TMAO was elevated. Conclusion Elevated plasma levels of choline and betaine are each associated with incident MACE risk independent of traditional risk factors. However, high choline and betaine levels are only associated with higher risk of future MACE with concomitant increase in TMAO. PMID:24497336

Anthropometric measures and absolute cardiovascular risk estimates in the Australian Diabetes, Obesity and Lifestyle (AusDiab) Study.

PubMed

Chen, Lei; Peeters, Anna; Magliano, Dianna J; Shaw, Jonathan E; Welborn, Timothy A; Wolfe, Rory; Zimmet, Paul Z; Tonkin, Andrew M

2007-12-01

Framingham risk functions are widely used for prediction of future cardiovascular disease events. They do not, however, include anthropometric measures of overweight or obesity, now considered a major cardiovascular disease risk factor. We aimed to establish the most appropriate anthropometric index and its optimal cutoff point for use as an ancillary measure in clinical practice when identifying people with increased absolute cardiovascular risk estimates. Analysis of a population-based, cross-sectional survey was carried out. The 1991 Framingham prediction equations were used to compute 5 and 10-year risks of cardiovascular or coronary heart disease in 7191 participants from the Australian Diabetes, Obesity and Lifestyle Study (1999-2000). Receiver operating characteristic curve analysis was used to compare measures of body mass index (BMI), waist circumference, and waist-to-hip ratio in identifying participants estimated to be at 'high', or at 'intermediate or high' absolute risk. After adjustment for BMI and age, waist-to-hip ratio showed stronger correlation with absolute risk estimates than waist circumference. The areas under the receiver operating characteristic curve for waist-to-hip ratio (0.67-0.70 in men, 0.64-0.74 in women) were greater than those for waist circumference (0.60-0.65, 0.59-0.71) or BMI (0.52-0.59, 0.53-0.66). The optimal cutoff points of BMI, waist circumference and waist-to-hip ratio to predict people at 'high', or at 'intermediate or high' absolute risk estimates were 26 kg/m2, 95 cm and 0.90 in men, and 25-26 kg/m2, 80-85 cm and 0.80 in women, respectively. Measurement of waist-to-hip ratio is more useful than BMI or waist circumference in the identification of individuals estimated to be at increased risk for future primary cardiovascular events.

Measuring Gambling Reinforcers, Over Consumption and Fallacies: The Psychometric Properties and Predictive Validity of the Jonsson-Abbott Scale.

PubMed

Jonsson, Jakob; Abbott, Max W; Sjöberg, Anders; Carlbring, Per

2017-01-01

Traditionally, gambling and problem gambling research relies on cross-sectional and retrospective designs. This has compromised identification of temporal relationships and causal inference. To overcome these problems a new questionnaire, the Jonsson-Abbott Scale (JAS), was developed and used in a large, prospective, general population study, The Swedish Longitudinal Gambling Study (Swelogs). The JAS has 11 items and seeks to identify early indicators, examine relationships between indicators and assess their capacity to predict future problem progression. The aims of the study were to examine psychometric properties of the JAS (internal consistency and dimensionality) and predictive validity with respect to increased gambling risk and problem gambling onset. The results are based on repeated interviews with 3818 participants. The response rate from the initial baseline wave was 74%. The original sample consisted of a random, stratified selection from the Swedish population register aged between 16 and 84. The results indicate an acceptable fit of a three-factor solution in a confirmatory factor analysis with 'Over consumption,' 'Gambling fallacies,' and 'Reinforcers' as factors. Reinforcers, Over consumption and Gambling fallacies were significant predictors of gambling risk potential and Gambling fallacies and Over consumption were significant predictors of problem gambling onset (incident cases) at 12 month follow up. When controlled for risk potential measured at baseline, the predictor Over consumption was not significant for gambling risk potential at follow up. For incident cases, Gambling fallacies and Over consumption remained significant when controlled for risk potential. Implications of the results for the development of problem gambling, early detection, prevention, and future research are discussed.

Accuracy of risk scales for predicting repeat self-harm and suicide: a multicentre, population-level cohort study using routine clinical data.

PubMed

Steeg, Sarah; Quinlivan, Leah; Nowland, Rebecca; Carroll, Robert; Casey, Deborah; Clements, Caroline; Cooper, Jayne; Davies, Linda; Knipe, Duleeka; Ness, Jennifer; O'Connor, Rory C; Hawton, Keith; Gunnell, David; Kapur, Nav

2018-04-25

Risk scales are used widely in the management of patients presenting to hospital following self-harm. However, there is evidence that their diagnostic accuracy in predicting repeat self-harm is limited. Their predictive accuracy in population settings, and in identifying those at highest risk of suicide is not known. We compared the predictive accuracy of the Manchester Self-Harm Rule (MSHR), ReACT Self-Harm Rule (ReACT), SAD PERSONS Scale (SPS) and Modified SAD PERSONS Scale (MSPS) in an unselected sample of patients attending hospital following self-harm. Data on 4000 episodes of self-harm presenting to Emergency Departments (ED) between 2010 and 2012 were obtained from four established monitoring systems in England. Episodes were assigned a risk category for each scale and followed up for 6 months. The episode-based repeat rate was 28% (1133/4000) and the incidence of suicide was 0.5% (18/3962). The MSHR and ReACT performed with high sensitivity (98% and 94% respectively) and low specificity (15% and 23%). The SPS and the MSPS performed with relatively low sensitivity (24-29% and 9-12% respectively) and high specificity (76-77% and 90%). The area under the curve was 71% for both MSHR and ReACT, 51% for SPS and 49% for MSPS. Differences in predictive accuracy by subgroup were small. The scales were less accurate at predicting suicide than repeat self-harm. The scales failed to accurately predict repeat self-harm and suicide. The findings support existing clinical guidance not to use risk classification scales alone to determine treatment or predict future risk.

Sick Leave within 5 Years of Whiplash Trauma Predicts Recovery: A Prospective Cohort and Register-Based Study

PubMed Central

Carstensen, Tina Birgitte Wisbech; Fink, Per; Oernboel, Eva; Kasch, Helge; Jensen, Troels Staehelin; Frostholm, Lisbeth

2015-01-01

Background 10–22% of individuals sustaining whiplash trauma develop persistent symptoms resulting in reduced working ability and decreased quality of life, but it is poorly understood why some people do not recover. Various collision and post-collision risk factors have been studied, but little is known about pre-collision risk factors. In particular, the impact of sickness and socioeconomic factors before the collision on recovery is sparsely explored. The aim of this study was to examine if welfare payments received within five years pre-collision predict neck pain and negative change in provisional situation one year post-collision. Methods and Findings 719 individuals with acute whiplash trauma consecutively recruited from emergency departments or primary care after car accidents in Denmark completed questionnaires on socio-demographic and health factors immediately after the collision. After 12 months, a visual analogue scale on neck pain intensity was completed. 3595 matched controls in the general population were sampled, and national public register data on social benefits and any other welfare payments were obtained for participants with acute whiplash trauma and controls from five years pre-collision to 15 months after. Participants with acute whiplash trauma who had received sickness benefit for more than 12 weeks pre-collision had increased odds for negative change in future provisional situation (Odds Ratio (OR) (95% Confidence Interval (CI) = 3.8 (2.1;7.1)) and future neck pain (OR (95%CI) = 3.3 (1.8;6.3)), controlling for other known risk factors. Participants with acute whiplash trauma had weaker attachment to labour market (more weeks of sick leave (χ2(2) = 36.7, p < 0.001) and unemployment (χ2(2) = 12.5, p = 0.002)) pre-collision compared with controls. Experiencing a whiplash trauma raised the odds for future negative change in provisional situation (OR (95%CI) = 3.1 (2.3;4.4)) compared with controls. Conclusions Sick leave before the collision strongly predicted prolonged recovery following whiplash trauma. Participants with acute whiplash trauma had weaker attachment to labour market pre-collision compared with the general population. Neck pain at inclusion predicted future neck pain. Acute whiplash trauma may trigger pre-existing vulnerabilities increasing risk of developing whiplash-associated disorders. PMID:26098860

Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults.

PubMed

Würtz, Peter; Soininen, Pasi; Kangas, Antti J; Rönnemaa, Tapani; Lehtimäki, Terho; Kähönen, Mika; Viikari, Jorma S; Raitakari, Olli T; Ala-Korpela, Mika

2013-03-01

Branched-chain and aromatic amino acids are associated with the risk for future type 2 diabetes; however, the underlying mechanisms remain elusive. We tested whether amino acids predict insulin resistance index in healthy young adults. Circulating isoleucine, leucine, valine, phenylalanine, tyrosine, and six additional amino acids were quantified in 1,680 individuals from the population-based Cardiovascular Risk in Young Finns Study (baseline age 32 ± 5 years; 54% women). Insulin resistance was estimated by homeostasis model assessment (HOMA) at baseline and 6-year follow-up. Amino acid associations with HOMA of insulin resistance (HOMA-IR) and glucose were assessed using regression models adjusted for established risk factors. We further examined whether amino acid profiling could augment risk assessment of insulin resistance (defined as 6-year HOMA-IR >90th percentile) in early adulthood. Isoleucine, leucine, valine, phenylalanine, and tyrosine were associated with HOMA-IR at baseline and for men at 6-year follow-up, while for women only leucine, valine, and phenylalanine predicted 6-year HOMA-IR (P < 0.05). None of the other amino acids were prospectively associated with HOMA-IR. The sum of branched-chain and aromatic amino acid concentrations was associated with 6-year insulin resistance for men (odds ratio 2.09 [95% CI 1.38-3.17]; P = 0.0005); however, including the amino acid score in prediction models did not improve risk discrimination. Branched-chain and aromatic amino acids are markers of the development of insulin resistance in young, normoglycemic adults, with most pronounced associations for men. These findings suggest that the association of branched-chain and aromatic amino acids with the risk for future diabetes is at least partly mediated through insulin resistance.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

Flooding in the future--predicting climate change, risks and responses in urban areas.

PubMed

Ashley, R M; Balmforth, D J; Saul, A J; Blanskby, J D

2005-01-01

Engineering infrastructure is provided at high cost and is expected to have a useful operational life of decades. However, it is clear that the future is uncertain. Traditional approaches to designing and operating urban storm drainage assets have relied on past performance of natural systems and the ability to extrapolate this performance, together with that of the assets across the usable lifetime. Whether or not climate change is going to significantly alter future weather patterns in Europe, it is clear that it is now incumbent on designers and operators of storm drainage systems to prepare for greater uncertainty in the effectiveness of storm drainage systems. A recent U.K. Government study considered the potential effects of climate and socio-economic change in the U.K. in terms of four future scenarios and what the implications are for the performance of existing storm drainage facilities. In this paper the modelling that was undertaken to try to quantify the changes in risk, together with the effectiveness of responses in managing that risk, are described. It shows that flood risks may increase by a factor of almost 30 times and that traditional engineering measures alone are unlikely to be able to provide protection.

Predicted extinction of unique genetic diversity in marine forests of Cystoseira spp.

PubMed

Buonomo, Roberto; Chefaoui, Rosa M; Lacida, Ricardo Bermejo; Engelen, Aschwin H; Serrão, Ester A; Airoldi, Laura

2018-07-01

Climate change is inducing shifts in species ranges across the globe. These can affect the genetic pools of species, including loss of genetic variability and evolutionary potential. In particular, geographically enclosed ecosystems, like the Mediterranean Sea, have a higher risk of suffering species loss and genetic erosion due to barriers to further range shifts and to dispersal. In this study, we address these questions for three habitat-forming seaweed species, Cystoseira tamariscifolia, C. amentacea and C. compressa, throughout their entire ranges in the Atlantic and Mediterranean regions. We aim to 1) describe their population genetic structure and diversity, 2) model the present and predict the future distribution and 3) assess the consequences of predicted future range shifts for their population genetic structure, according to two contrasting future climate change scenarios. A net loss of suitable areas was predicted in both climatic scenarios across the range of distribution of the three species. This loss was particularly severe for C. amentacea in the Mediterranean Sea (less 90% in the most extreme climatic scenario), suggesting that the species could become potentially at extinction risk. For all species, genetic data showed very differentiated populations, indicating low inter-population connectivity, and high and distinct genetic diversity in areas that were predicted to become lost, causing erosion of unique evolutionary lineages. Our results indicated that the Mediterranean Sea is the most threatened region, where future suitable Cystoseira habitats will become more limited. This is likely to have wider ecosystem impacts as there is a lack of species with the same ecological niche and functional role in the Mediterranean. The projected accelerated loss of already fragmented and disturbed populations and the long-term genetic effects highlight the urge for local scale management strategies that sustain the capacity of these habitat-forming species to persist despite climatic impacts while waiting for global emission reductions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reactive stepping behaviour in response to forward loss of balance predicts future falls in community-dwelling older adults.

PubMed

Carty, Christopher P; Cronin, Neil J; Nicholson, Deanne; Lichtwark, Glen A; Mills, Peter M; Kerr, Graham; Cresswell, Andrew G; Barrett, Rod S

2015-01-01

a fall occurs when an individual experiences a loss of balance from which they are unable to recover. Assessment of balance recovery ability in older adults may therefore help to identify individuals at risk of falls. The purpose of this 12-month prospective study was to assess whether the ability to recover from a forward loss of balance with a single step across a range of lean magnitudes was predictive of falls. two hundred and one community-dwelling older adults, aged 65-90 years, underwent baseline testing of sensori-motor function and balance recovery ability followed by 12-month prospective falls evaluation. Balance recovery ability was defined by whether participants required either single or multiple steps to recover from forward loss of balance from three lean magnitudes, as well as the maximum lean magnitude participants could recover from with a single step. forty-four (22%) participants experienced one or more falls during the follow-up period. Maximal recoverable lean magnitude and use of multiple steps to recover at the 15% body weight (BW) and 25%BW lean magnitudes significantly predicted a future fall (odds ratios 1.08-1.26). The Physiological Profile Assessment, an established tool that assesses variety of sensori-motor aspects of falls risk, was also predictive of falls (Odds ratios 1.22 and 1.27, respectively), whereas age, sex, postural sway and timed up and go were not predictive. reactive stepping behaviour in response to forward loss of balance and physiological profile assessment are independent predictors of a future fall in community-dwelling older adults. Exercise interventions designed to improve reactive stepping behaviour may protect against future falls. © The Author 2014. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

The contribution to future flood risk in the Severn Estuary from extreme sea level rise due to ice sheet mass loss

NASA Astrophysics Data System (ADS)

Quinn, N.; Bates, P. D.; Siddall, M.

2013-12-01

The rate at which sea levels will rise in the coming century is of great interest to decision makers tasked with developing mitigation policies to cope with the risk of coastal inundation. Accurate estimates of future sea levels are vital in the provision of effective policy. Recent reports from UK Climate Impacts Programme (UKCIP) suggest that mean sea levels in the UK may rise by as much as 80 cm by 2100; however, a great deal of uncertainty surrounds model predictions, particularly the contribution from ice sheets responding to climatic warming. For this reason, the application of semi-empirical modelling approaches for sea level rise predictions has increased of late, the results from which suggest that the rate of sea level rise may be greater than previously thought, exceeding 1 m by 2100. Furthermore, studies in the Red Sea indicate that rapid sea level rise beyond 1m per century has occurred in the past. In light of such research, the latest UKCIP assessment has included a H++ scenario for sea level rise in the UK of up to 1.9 m which is defined as improbable but, crucially, physically plausible. The significance of such low-probability sea level rise scenarios upon the estimation of future flood risk is assessed using the Somerset levels (UK) as a case study. A simple asymmetric probability distribution is constructed to include sea level rise scenarios of up to 1.9 m by 2100 which are added to a current 1:200 year event water level to force a two-dimensional hydrodynamic model of coastal inundation. From the resulting ensemble predictions an estimation of risk by 2100 is established. The results indicate that although the likelihood of extreme sea level rise due to rapid ice sheet mass loss is low, the resulting hazard can be large, resulting in a significant (27%) increase to the projected annual risk. Furthermore, current defence construction guidelines for the coming century in the UK are expected to account for 95% of the sea level rise distribution presented in this research, while the larger, low probability scenarios beyond this level are estimated to contribute a residual annual risk of approximately £0.45 million. These findings clearly demonstrate that uncertainty in future sea level rise is a vital component of coastal flood risk, and therefore, needs to be accounted for by decision makers when considering mitigation policies related to coastal flooding.

Real-time web-based assessment of total population risk of future emergency department utilization: statewide prospective active case finding study.

PubMed

Hu, Zhongkai; Jin, Bo; Shin, Andrew Y; Zhu, Chunqing; Zhao, Yifan; Hao, Shiying; Zheng, Le; Fu, Changlin; Wen, Qiaojun; Ji, Jun; Li, Zhen; Wang, Yong; Zheng, Xiaolin; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng B

2015-01-13

An easily accessible real-time Web-based utility to assess patient risks of future emergency department (ED) visits can help the health care provider guide the allocation of resources to better manage higher-risk patient populations and thereby reduce unnecessary use of EDs. Our main objective was to develop a Health Information Exchange-based, next 6-month ED risk surveillance system in the state of Maine. Data on electronic medical record (EMR) encounters integrated by HealthInfoNet (HIN), Maine's Health Information Exchange, were used to develop the Web-based surveillance system for a population ED future 6-month risk prediction. To model, a retrospective cohort of 829,641 patients with comprehensive clinical histories from January 1 to December 31, 2012 was used for training and then tested with a prospective cohort of 875,979 patients from July 1, 2012, to June 30, 2013. The multivariate statistical analysis identified 101 variables predictive of future defined 6-month risk of ED visit: 4 age groups, history of 8 different encounter types, history of 17 primary and 8 secondary diagnoses, 8 specific chronic diseases, 28 laboratory test results, history of 3 radiographic tests, and history of 25 outpatient prescription medications. The c-statistics for the retrospective and prospective cohorts were 0.739 and 0.732 respectively. Integration of our method into the HIN secure statewide data system in real time prospectively validated its performance. Cluster analysis in both the retrospective and prospective analyses revealed discrete subpopulations of high-risk patients, grouped around multiple "anchoring" demographics and chronic conditions. With the Web-based population risk-monitoring enterprise dashboards, the effectiveness of the active case finding algorithm has been validated by clinicians and caregivers in Maine. The active case finding model and associated real-time Web-based app were designed to track the evolving nature of total population risk, in a longitudinal manner, for ED visits across all payers, all diseases, and all age groups. Therefore, providers can implement targeted care management strategies to the patient subgroups with similar patterns of clinical histories, driving the delivery of more efficient and effective health care interventions. To the best of our knowledge, this prospectively validated EMR-based, Web-based tool is the first one to allow real-time total population risk assessment for statewide ED visits.

Predicting sun protection behaviors using protection motivation variables.

PubMed

Ch'ng, Joanne W M; Glendon, A Ian

2014-04-01

Protection motivation theory components were used to predict sun protection behaviors (SPBs) using four outcome measures: typical reported behaviors, previous reported behaviors, current sunscreen use as determined by interview, and current observed behaviors (clothing worn) to control for common method bias. Sampled from two SE Queensland public beaches during summer, 199 participants aged 18-29 years completed a questionnaire measuring perceived severity, perceived vulnerability, response efficacy, response costs, and protection motivation (PM). Personal perceived risk (similar to threat appraisal) and response likelihood (similar to coping appraisal) were derived from their respective PM components. Protection motivation predicted all four SPB criterion variables. Personal perceived risk and response likelihood predicted protection motivation. Protection motivation completely mediated the effect of response likelihood on all four criterion variables. Alternative models are considered. Strengths and limitations of the study are outlined and suggestions made for future research.

Optimism/pessimism and future orientation as predictors of suicidal ideation: Are there ethnic differences?

PubMed

Yu, Elizabeth A; Chang, Edward C

2016-10-01

The present study sought to test the generalizability of Chang et al.'s (2013) model, which suggests that optimism/pessimism and future orientation function as additive and interactive predictors of suicidal risk, to specific ethnic minority college student groups (i.e., Asian Americans, African Americans, and Latino Americans). The present study used Chang et al.'s (2013) model to predict suicidal ideation among 81 (34 male and 47 female) Asian-American, 71 (22 male and 49 female) African-American adults, and 83 (34 male and 49 female) Latino-American college students. Our results indicated that this model did not predict suicidal ideation well for Asian-American college students; however, it did work well to predict suicidal ideation for African-American and Latino-American college students. Our findings indicate that optimism/pessimism and future orientation are important positive cognitions involved with suicidal ideation for African-American and Latino-American college students. Further research is needed to better understand the cultural underpinnings of how these positive cognitions work to predict suicide-related outcomes. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

New methods for fall risk prediction.

PubMed

Ejupi, Andreas; Lord, Stephen R; Delbaere, Kim

2014-09-01

Accidental falls are the leading cause of injury-related death and hospitalization in old age, with over one-third of the older adults experiencing at least one fall or more each year. Because of limited healthcare resources, regular objective fall risk assessments are not possible in the community on a large scale. New methods for fall prediction are necessary to identify and monitor those older people at high risk of falling who would benefit from participating in falls prevention programmes. Technological advances have enabled less expensive ways to quantify physical fall risk in clinical practice and in the homes of older people. Recently, several studies have demonstrated that sensor-based fall risk assessments of postural sway, functional mobility, stepping and walking can discriminate between fallers and nonfallers. Recent research has used low-cost, portable and objective measuring instruments to assess fall risk in older people. Future use of these technologies holds promise for assessing fall risk accurately in an unobtrusive manner in clinical and daily life settings.

Examining the predictive validity of low-risk gambling limits with longitudinal data.

PubMed

Currie, Shawn R; Hodgins, David C; Casey, David M; el-Guebaly, Nady; Smith, Garry J; Williams, Robert J; Schopflocher, Don P; Wood, Robert T

2012-02-01

To assess the impact of gambling above the low-risk gambling limits developed by Currie et al. (2006) on future harm. To identify demographic, behavioural, clinical and environmental factors that predict the shift from low- to high-risk gambling habits over time. Longitudinal cohort study of gambling habits in community-dwelling adults. Alberta, Canada. A total of 809 adult gamblers who completed the time 1 and time 2 assessments separated by a 14-month interval. Low-risk gambling limits were defined as gambling no more than three times per month, spending no more than CAN$1000 per year on gambling and spending less than 1% of gross income on gambling. Gambling habits, harm from gambling and gambler characteristics were assessed by the Canadian Problem Gambling Index. Ancillary measures of substance abuse, gambling environment, major depression, impulsivity and personality traits assessed the influence of other risk factors on the escalation of gambling intensity. Gamblers classified as low risk at time 1 and shifted into high-risk gambling by time 2 were two to three times more likely to experience harm compared to gamblers who remained low risk at both assessments. Factors associated with the shift from low- to high-risk gambling behaviour from time 1 to time 2 included male gender, tobacco use, older age, having less education, having friends who gamble and playing electronic gaming machines. An increase in the intensity of gambling behaviour is associated with greater likelihood of future gambling related harm in adults. © 2011 The Authors, Addiction © 2011 Society for the Study of Addiction.

Translating Uncertain Sea Level Projections Into Infrastructure Impacts Using a Bayesian Framework

NASA Astrophysics Data System (ADS)

Moftakhari, Hamed; AghaKouchak, Amir; Sanders, Brett F.; Matthew, Richard A.; Mazdiyasni, Omid

2017-12-01

Climate change may affect ocean-driven coastal flooding regimes by both raising the mean sea level (msl) and altering ocean-atmosphere interactions. For reliable projections of coastal flood risk, information provided by different climate models must be considered in addition to associated uncertainties. In this paper, we propose a framework to project future coastal water levels and quantify the resulting flooding hazard to infrastructure. We use Bayesian Model Averaging to generate a weighted ensemble of storm surge predictions from eight climate models for two coastal counties in California. The resulting ensembles combined with msl projections, and predicted astronomical tides are then used to quantify changes in the likelihood of road flooding under representative concentration pathways 4.5 and 8.5 in the near-future (1998-2063) and mid-future (2018-2083). The results show that road flooding rates will be significantly higher in the near-future and mid-future compared to the recent past (1950-2015) if adaptation measures are not implemented.

Drinking Status Between Ages 50 and 55 for Men From the San Diego Prospective Study Who Developed DSM-IV Alcohol Abuse or Dependence in Prior Follow-Ups.

PubMed

Gonçalves, Priscila Dib; Schuckit, Marc A; Smith, Tom L

2017-07-01

Although alcohol use disorders (AUDs) are prevalent among older individuals, few studies have examined the course and predictors of AUDs from their onset into the person's 50s. This study describes the AUD course from ages 50 to 55 in participants who developed AUDs according to criteria from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), during the San Diego Prospective Study (SDPS). Among the 397 university students in the SDPS who were followed about every 5 years from age 20 (before AUD onset), 165 developed AUDs, 156 of whom were interviewed at age 55. Age 50-55 outcomes were compared regarding age 20-50 characteristics. Variables that differed significantly across outcome groups were evaluated using binary logistic regression analyses predicting each outcome type. Between ages 50 and 55, 16% had low-risk drinking, 36% had high-risk drinking, 38% met DSM-5 AUD criteria, and 10% were abstinent. Baseline predictors of outcome at ages 50-55 included earlier low levels of response to alcohol predicting DSM-5 AUDs and abstinence, higher drinking frequency predicting DSM-5 diagnoses and lower predicting low-risk drinking, higher participation in treatment and/or self-help groups predicting abstinence and lower predicting DSM-5 AUDs, later ages of AUD onset predicting high-risk drinking, and cannabis use disorders predicting abstinent outcomes. Despite the high functioning of these men, few were abstinent or maintained low-risk drinking during the recent 5 years, and 38% met DSM-5 AUD criteria. The data may be helpful to both clinicians and researchers predicting the future course of AUDs in their older patients and research participants.

Prediction and perception of hazards in professional drivers: Does hazard perception skill differ between safe and less-safe fire-appliance drivers?

PubMed

Crundall, David; Kroll, Victoria

2018-05-18

Can hazard perception testing be useful for the emergency services? Previous research has found emergency response drivers' (ERDs) to perform better than controls, however these studies used clips of normal driving. In contrast, the current study filmed footage from a fire-appliance on blue-light training runs through Nottinghamshire, and endeavoured to discriminate between different groups of EDRs based on experience and collision risk. Thirty clips were selected to create two variants of the hazard perception test: a traditional push-button test requiring speeded-responses to hazards, and a prediction test that occludes at hazard onset and provides four possible outcomes for participants to choose between. Three groups of fire-appliance drivers (novices, low-risk experienced and high-risk experienced), and age-matched controls undertook both tests. The hazard perception test only discriminated between controls and all FA drivers, whereas the hazard prediction test was more sensitive, discriminating between high and low-risk experienced fire appliance drivers. Eye movement analyses suggest that the low-risk drivers were better at prioritising the hazardous precursors, leading to better predictive accuracy. These results pave the way for future assessment and training tools to supplement emergency response driver training, while supporting the growing literature that identifies hazard prediction as a more robust measure of driver safety than traditional hazard perception tests. Copyright © 2018 Elsevier Ltd. All rights reserved.

Overcoming Learning Aversion in Evaluating and Managing Uncertain Risks.

PubMed

Cox, Louis Anthony Tony

2015-10-01

Decision biases can distort cost-benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well-documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk-cost-benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk-reducing regulations. Low-regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low-regret learning strategies using regulation of air pollutants with uncertain health effects as an example. © 2015 Society for Risk Analysis.

Self-reported stroke symptoms without a prior diagnosis of stroke or transient ischemic attack: a powerful new risk factor for stroke.

PubMed

Kleindorfer, Dawn; Judd, Suzanne; Howard, Virginia J; McClure, Leslie; Safford, Monika M; Cushman, Mary; Rhodes, David; Howard, George

2011-11-01

Previously in the REasons for Geographic And Racial Differences in Stroke (REGARDS) cohort, we found 18% of the stroke/transient ischemic attack-free study population reported ≥1 stroke symptom at baseline. We sought to evaluate the additional impact of these stroke symptoms on risk for subsequent stroke. REGARDS recruited 30,239 US blacks and whites, aged 45+ years in 2003 to 2007 who are being followed every 6 months for events. All stroke events are physician-verified; those with prior diagnosed stroke or transient ischemic attack are excluded from this analysis. At baseline, participants were asked 6 questions regarding stroke symptoms. Measured stroke risk factors were components of the Framingham Stroke Risk Score. After excluding those with prior stroke or missing data, there were 24,412 participants in this analysis with a median follow-up of 4.4 years. Participants were 39% black, 55% female, and had median age of 64 years. There were 381 physician-verified stroke events. The Framingham Stroke Risk Score explained 72.0% of stroke risk; individual components explained between 0.2% (left ventricular hypertrophy) and 5.7% (age+race) of stroke risk. After adjustment for Framingham Stroke Risk Score factors, stroke symptoms were significantly related to stroke risk: for each stroke symptom reported, the risk of stroke increased by 21% per symptom. Among participants without self-reported stroke or transient ischemic attack, prior stroke symptoms are highly predictive of future stroke events. Compared with Framingham Stroke Risk Score factors, the impact of stroke symptom on the prediction of future stroke was almost as large as the impact of smoking and hypertension and larger than the impact of diabetes and heart disease.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Cortical Thickness Predicts the First Onset of Major Depression in Adolescence

PubMed Central

Foland-Ross, Lara C.; Sacchet, Matthew D.; Prasad, Gautam; Gilbert, Brooke; Thompson, Paul M.; Gotlib, Ian H.

2015-01-01

Given the increasing prevalence of Major Depressive Disorder and recent advances in preventative treatments for this disorder, an important challenge in pediatric neuroimaging is the early identification of individuals at risk for depression. We examined whether machine learning can be used to predict the onset of depression at the individual level. Thirty-three never-disordered adolescents (10–15 years old) underwent structural MRI. Participants were followed for 5 years to monitor the emergence of clinically significant depressive symptoms. We used support vector machines (SVMs) to test whether baseline cortical thickness could reliably distinguish adolescents who develop depression from adolescents who remained free of any Axis I disorder. Accuracies from subsampled cross-validated classification were used to assess classifier performance. Baseline cortical thickness correctly predicted the future onset of depression with an overall accuracy of 70% (69% sensitivity, 70% specificity; p = 0.021). Examination of SVM feature weights indicated that the right medial orbitofrontal, right precentral, left anterior cingulate, and bilateral insular cortex contributed most strongly to this classification. These findings indicate that cortical gray matter structure can predict the subsequent onset of depression. An important direction for future research is to elucidate mechanisms by which these anomalies in gray matter structure increase risk for developing this disorder. PMID:26315399

Cortical thickness predicts the first onset of major depression in adolescence.

PubMed

Foland-Ross, Lara C; Sacchet, Matthew D; Prasad, Gautam; Gilbert, Brooke; Thompson, Paul M; Gotlib, Ian H

2015-11-01

Given the increasing prevalence of Major Depressive Disorder and recent advances in preventative treatments for this disorder, an important challenge in pediatric neuroimaging is the early identification of individuals at risk for depression. We examined whether machine learning can be used to predict the onset of depression at the individual level. Thirty-three never-disordered adolescents (10-15 years old) underwent structural MRI. Participants were followed for 5 years to monitor the emergence of clinically significant depressive symptoms. We used support vector machines (SVMs) to test whether baseline cortical thickness could reliably distinguish adolescents who develop depression from adolescents who remained free of any Axis I disorder. Accuracies from subsampled cross-validated classification were used to assess classifier performance. Baseline cortical thickness correctly predicted the future onset of depression with an overall accuracy of 70% (69% sensitivity, 70% specificity; p=0.021). Examination of SVM feature weights indicated that the right medial orbitofrontal, right precentral, left anterior cingulate, and bilateral insular cortex contributed most strongly to this classification. These findings indicate that cortical gray matter structure can predict the subsequent onset of depression. An important direction for future research is to elucidate mechanisms by which these anomalies in gray matter structure increase risk for developing this disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluation of waist-to-height ratio to predict 5 year cardiometabolic risk in sub-Saharan African adults.

PubMed

Ware, L J; Rennie, K L; Kruger, H S; Kruger, I M; Greeff, M; Fourie, C M T; Huisman, H W; Scheepers, J D W; Uys, A S; Kruger, R; Van Rooyen, J M; Schutte, R; Schutte, A E

2014-08-01

Simple, low-cost central obesity measures may help identify individuals with increased cardiometabolic disease risk, although it is unclear which measures perform best in African adults. We aimed to: 1) cross-sectionally compare the accuracy of existing waist-to-height ratio (WHtR) and waist circumference (WC) thresholds to identify individuals with hypertension, pre-diabetes, or dyslipidaemia; 2) identify optimal WC and WHtR thresholds to detect CVD risk in this African population; and 3) assess which measure best predicts 5-year CVD risk. Black South Africans (577 men, 942 women, aged >30years) were recruited by random household selection from four North West Province communities. Demographic and anthropometric measures were taken. Recommended diagnostic thresholds (WC > 80 cm for women, >94 cm for men; WHtR > 0.5) were evaluated to predict blood pressure, fasting blood glucose, lipids, and glycated haemoglobin measured at baseline and 5 year follow up. Women were significantly more overweight than men at baseline (mean body mass index (BMI) women 27.3 ± 7.4 kg/m(2), men 20.9 ± 4.3 kg/m(2)); median WC women 81.9 cm (interquartile range 61-103), men 74.7 cm (63-87 cm), all P < 0.001). In women, both WC and WHtR significantly predicted all cardiometabolic risk factors after 5 years. In men, even after adjusting WC threshold based on ROC analysis, WHtR better predicted overall 5-year risk. Neither measure predicted hypertension in men. The WHtR threshold of >0.5 appears to be more consistently supported and may provide a better predictor of future cardiometabolic risk in sub-Saharan Africa. Copyright © 2014 Elsevier B.V. All rights reserved.

Health risk factors as predictors of workers' compensation claim occurrence and cost.

PubMed

Schwatka, Natalie V; Atherly, Adam; Dally, Miranda J; Fang, Hai; vS Brockbank, Claire; Tenney, Liliana; Goetzel, Ron Z; Jinnett, Kimberly; Witter, Roxana; Reynolds, Stephen; McMillen, James; Newman, Lee S

2017-01-01

The objective of this study was to examine the predictive relationships between employee health risk factors (HRFs) and workers' compensation (WC) claim occurrence and costs. Logistic regression and generalised linear models were used to estimate the predictive association between HRFs and claim occurrence and cost among a cohort of 16 926 employees from 314 large, medium and small businesses across multiple industries. First, unadjusted (HRFs only) models were estimated, and second, adjusted (HRFs plus demographic and work organisation variables) were estimated. Unadjusted models demonstrated that several HRFs were predictive of WC claim occurrence and cost. After adjusting for demographic and work organisation differences between employees, many of the relationships previously established did not achieve statistical significance. Stress was the only HRF to display a consistent relationship with claim occurrence, though the type of stress mattered. Stress at work was marginally predictive of a higher odds of incurring a WC claim (p<0.10). Stress at home and stress over finances were predictive of higher and lower costs of claims, respectively (p<0.05). The unadjusted model results indicate that HRFs are predictive of future WC claims. However, the disparate findings between unadjusted and adjusted models indicate that future research is needed to examine the multilevel relationship between employee demographics, organisational factors, HRFs and WC claims. 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/.

How are compassion fatigue, burnout, and compassion satisfaction affected by quality of working life? Findings from a survey of mental health staff in Italy.

PubMed

Cetrano, Gaia; Tedeschi, Federico; Rabbi, Laura; Gosetti, Giorgio; Lora, Antonio; Lamonaca, Dario; Manthorpe, Jill; Amaddeo, Francesco

2017-11-21

Quality of working life includes elements such as autonomy, trust, ergonomics, participation, job complexity, and work-life balance. The overarching aim of this study was to investigate if and how quality of working life affects Compassion Fatigue, Burnout, and Compassion Satisfaction among mental health practitioners. Staff working in three Italian Mental Health Departments completed the Professional Quality of Life Scale, measuring Compassion Fatigue, Burnout, and Compassion Satisfaction, and the Quality of Working Life Questionnaire. The latter was used to collect socio-demographics, occupational characteristics and 13 indicators of quality of working life. Multiple regressions controlling for other variables were undertaken to predict Compassion Fatigue, Burnout, and Compassion Satisfaction. Four hundred questionnaires were completed. In bivariate analyses, experiencing more ergonomic problems, perceiving risks for the future, a higher impact of work on life, and lower levels of trust and of perceived quality of meetings were associated with poorer outcomes. Multivariate analysis showed that (a) ergonomic problems and impact of work on life predicted higher levels of both Compassion Fatigue and Burnout; (b) impact of life on work was associated with Compassion Fatigue and lower levels of trust and perceiving more risks for the future with Burnout only; (c) perceived quality of meetings, need of training, and perceiving no risks for the future predicted higher levels of Compassion Satisfaction. In order to provide adequate mental health services, service providers need to give their employees adequate ergonomic conditions, giving special attention to time pressures. Building trustful relationships with management and within the teams is also crucial. Training and meetings are other important targets for potential improvement. Additionally, insecurity about the future should be addressed as it can affect both Burnout and Compassion Satisfaction. Finally, strategies to reduce possible work-life conflicts need to be considered.

The 2006 William Feinberg lecture: shifting the paradigm from stroke to global vascular risk estimation.

PubMed

Sacco, Ralph L

2007-06-01

By the year 2010, it is estimated that 18.1 million people worldwide will die annually because of cardiovascular diseases and stroke. "Global vascular risk" more broadly includes the multiple overlapping disease silos of stroke, myocardial infarction, peripheral arterial disease, and vascular death. Estimation of global vascular risk requires consideration of a variety of variables including demographics, environmental behaviors, and risk factors. Data from multiple studies suggest continuous linear relationships between the physiological vascular risk modulators of blood pressure, lipids, and blood glucose rather than treating these conditions as categorical risk factors. Constellations of risk factors may be more relevant than individual categorical components. Exciting work with novel risk factors may also have predictive value in estimates of global vascular risk. Advances in imaging have led to the measurement of subclinical conditions such as carotid intima-media thickness and subclinical brain conditions such as white matter hyperintensities and silent infarcts. These subclinical measurements may be intermediate stages in the transition from asymptomatic to symptomatic vascular events, appear to be associated with the fundamental vascular risk factors, and represent opportunities to more precisely quantitate disease progression. The expansion of studies in molecular epidemiology and detection of genetic markers underlying vascular risks also promises to extend our precision of global vascular risk estimation. Global vascular risk estimation will require quantitative methods that bundle these multi-dimensional data into more precise estimates of future risk. The power of genetic information coupled with data on demographics, risk-inducing behaviors, vascular risk modulators, biomarkers, and measures of subclinical conditions should provide the most realistic approximation of an individual's future global vascular risk. The ultimate public health benefit, however, will depend on not only identification of global vascular risk but also the realization that we can modify this risk and prove the prediction models wrong.

[Analysis of 14 individuals who requested predictive genetic testing for hereditary neuromuscular diseases].

PubMed

Yoshida, Kunihiro; Tamai, Mariko; Kubota, Takeo; Kawame, Hiroshi; Amano, Naoji; Ikeda, Shu-ichi; Fukushima, Yoshimitsu

2002-02-01

Predictive genetic testing for hereditary neuromuscular diseases is a delicate issue for individuals at risk and their families, as well as for medical staff because these diseases are often late-onset and intractable. Therefore careful pre- and post-test genetic counseling and psychosocial support should be provided along with such genetic testing. The Division of Clinical and Molecular Genetics was established at our hospital in May 1996 to provide skilled professional genetic counseling. Since its establishment, 14 individuals have visited our clinic to request predictive genetic testing for hereditary neuromuscular diseases (4 for myotonic dystrophy, 6 for spinocerebellar ataxia, 3 for Huntington's disease, and 1 for Alzheimer's disease). The main reasons for considering testing were to remove uncertainty about the genetic status and to plan for the future. Nine of 14 individuals requested testing for making decisions about a forthcoming marriage or pregnancy (family planning). Other reasons raised by the individuals included career or financial planning, planning for their own health care, and knowing the risk for their children. At the first genetic counseling session, all of the individuals expressed hopes of not being a gene carrier and of escaping from fear of disease, and seemed not to be mentally well prepared for an increased-risk result. To date, 7 of the 14 individuals have received genetic testing and only one, who underwent predictive genetic testing for spinocerebellar ataxia, was given an increased-risk result. The seven individuals including the one with an increased-risk result, have coped well with their new knowledge about their genetic status after the testing results were disclosed. None of them has expressed regret. In pre-test genetic counseling sessions, we consider it quite important not only to determine the psychological status of the individual, but also to make the individual try to anticipate the changes in his/her life upon receiving an increased-risk or a decreased-risk result. Sufficient time should be taken to build a good relationship between the individual and his/her family and the medical staff during pre-test counseling sessions. This will help the individuals feel satisfied with their own decisions for the future, whether they receive genetic testing or not.

Predicting the onset of psychosis in patients at clinical high risk: practical guide to probabilistic prognostic reasoning.

PubMed

Fusar-Poli, P; Schultze-Lutter, F

2016-02-01

Prediction of psychosis in patients at clinical high risk (CHR) has become a mainstream focus of clinical and research interest worldwide. When using CHR instruments for clinical purposes, the predicted outcome is but only a probability; and, consequently, any therapeutic action following the assessment is based on probabilistic prognostic reasoning. Yet, probabilistic reasoning makes considerable demands on the clinicians. We provide here a scholarly practical guide summarising the key concepts to support clinicians with probabilistic prognostic reasoning in the CHR state. We review risk or cumulative incidence of psychosis in, person-time rate of psychosis, Kaplan-Meier estimates of psychosis risk, measures of prognostic accuracy, sensitivity and specificity in receiver operator characteristic curves, positive and negative predictive values, Bayes' theorem, likelihood ratios, potentials and limits of real-life applications of prognostic probabilistic reasoning in the CHR state. Understanding basic measures used for prognostic probabilistic reasoning is a prerequisite for successfully implementing the early detection and prevention of psychosis in clinical practice. Future refinement of these measures for CHR patients may actually influence risk management, especially as regards initiating or withholding treatment. 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/

Uncertainty: the Curate's egg in financial economics.

PubMed

Pixley, Jocelyn

2014-06-01

Economic theories of uncertainty are unpopular with financial experts. As sociologists, we rightly refuse predictions, but the uncertainties of money are constantly sifted and turned into semi-denial by a financial economics set on somehow beating the future. Picking out 'bits' of the future as 'risk' and 'parts' as 'information' is attractive but socially dangerous, I argue, because money's promises are always uncertain. New studies of uncertainty are reversing sociology's neglect of the unavoidable inability to know the forces that will shape the financial future. © London School of Economics and Political Science 2014.

Cardiovascular risk prediction tools for populations in Asia.

PubMed

Barzi, F; Patel, A; Gu, D; Sritara, P; Lam, T H; Rodgers, A; Woodward, M

2007-02-01

Cardiovascular risk equations are traditionally derived from the Framingham Study. The accuracy of this approach in Asian populations, where resources for risk factor measurement may be limited, is unclear. To compare "low-information" equations (derived using only age, systolic blood pressure, total cholesterol and smoking status) derived from the Framingham Study with those derived from the Asian cohorts, on the accuracy of cardiovascular risk prediction. Separate equations to predict the 8-year risk of a cardiovascular event were derived from Asian and Framingham cohorts. The performance of these equations, and a subsequently "recalibrated" Framingham equation, were evaluated among participants from independent Chinese cohorts. Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US. 172,077 participants from the Asian cohorts; 25,682 participants from Chinese cohorts and 6053 participants from the Framingham Study. In the Chinese cohorts, 542 cardiovascular events occurred during 8 years of follow-up. Both the Asian cohorts and the Framingham equations discriminated cardiovascular risk well in the Chinese cohorts; the area under the receiver-operator characteristic curve was at least 0.75 for men and women. However, the Framingham risk equation systematically overestimated risk in the Chinese cohorts by an average of 276% among men and 102% among women. The corresponding average overestimation using the Asian cohorts equation was 11% and 10%, respectively. Recalibrating the Framingham risk equation using cardiovascular disease incidence from the non-Chinese Asian cohorts led to an overestimation of risk by an average of 4% in women and underestimation of risk by an average of 2% in men. A low-information Framingham cardiovascular risk prediction tool, which, when recalibrated with contemporary data, is likely to estimate future cardiovascular risk with similar accuracy in Asian populations as tools developed from data on local cohorts.

Quantification of increased flood risk due to global climate change for urban river management planning.

PubMed

Morita, M

2011-01-01

Global climate change is expected to affect future rainfall patterns. These changes should be taken into account when assessing future flooding risks. This study presents a method for quantifying the increase in flood risk caused by global climate change for use in urban flood risk management. Flood risk in this context is defined as the product of flood damage potential and the probability of its occurrence. The study uses a geographic information system-based flood damage prediction model to calculate the flood damage caused by design storms with different return periods. Estimation of the monetary damages these storms produce and their return periods are precursors to flood risk calculations. The design storms are developed from modified intensity-duration-frequency relationships generated by simulations of global climate change scenarios (e.g. CGCM2A2). The risk assessment method is applied to the Kanda River basin in Tokyo, Japan. The assessment provides insights not only into the flood risk cost increase due to global warming, and the impact that increase may have on flood control infrastructure planning.

The role of narcissism in health-risk and health-protective behaviors.

PubMed

Hill, Erin M

2016-09-01

This study examined the role of narcissism in health-risk and health-protective behaviors in a sample of 365 undergraduate students. Regression analyses were used to test the influence of narcissism on health behaviors. Narcissism was positively predictive of alcohol use, marijuana use, and risky driving behaviors, and it was associated with an increased likelihood of consistently having a healthy eating pattern. Narcissism was also positively predictive of physical activity. Results are discussed with reference to the potential short-term and long-term health implications and the need for future research on the factors involved in the relationship between narcissism and health behaviors. © The Author(s) 2015.

Symptoms of conduct disorder, oppositional defiant disorder, attention-deficit/hyperactivity disorder, and callous-unemotional traits as unique predictors of psychosocial maladjustment in boys: advancing an evidence base for DSM-V.

PubMed

Pardini, Dustin A; Fite, Paula J

2010-11-01

The incremental utility of symptoms of conduct disorder (CD), oppositional defiant disorder (ODD), attention-deficit/hyperactivity disorder (ADHD), and callous-unemotional (CU) traits for predicting psychosocial outcomes across multiple domains was examined in a community sample of 1,517 boys. Several outcomes were assessed semiannually across a 2-year follow-up, including antisocial behavior, internalizing problems, peer conflict, and academic difficulties. Official criminal charges were also examined across adolescence. CD symptoms emerged as the most robust predictor of future antisocial outcomes. However, ODD symptoms predicted later criminal charges and conduct problems, and CU traits were robustly associated with serious and persistent criminal behavior in boys. Attention-deficit/hyperactivity disorder symptoms predicted increases in oppositional defiant behavior and conduct problems over time and were uniquely related to future academic difficulties. Both ADHD and ODD symptoms predicted social and internalizing problems in boys, whereas CU traits were associated with decreased internalizing problems over time. The current findings have implications for revisions being considered as part of the DSM-V. Specifically, incorporating CU traits into the diagnostic criteria for Disruptive Behavior Disorders (DBD) may help to further delineate boys at risk for severe and persistent delinquency. Although currently prohibited, allowing a diagnosis of ODD when CD is present may provide unique prognostic information about boys who are at risk for future criminal behavior, social problems, and internalizing problems. Copyright © 2010 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

How artificial intelligence tools can be used to assess individual patient risk in cardiovascular disease: problems with the current methods

PubMed Central

Grossi, Enzo

2006-01-01

Background In recent years a number of algorithms for cardiovascular risk assessment has been proposed to the medical community. These algorithms consider a number of variables and express their results as the percentage risk of developing a major fatal or non-fatal cardiovascular event in the following 10 to 20 years Discussion The author has identified three major pitfalls of these algorithms, linked to the limitation of the classical statistical approach in dealing with this kind of non linear and complex information. The pitfalls are the inability to capture the disease complexity, the inability to capture process dynamics, and the wide confidence interval of individual risk assessment. Artificial Intelligence tools can provide potential advantage in trying to overcome these limitations. The theoretical background and some application examples related to artificial neural networks and fuzzy logic have been reviewed and discussed. Summary The use of predictive algorithms to assess individual absolute risk of cardiovascular future events is currently hampered by methodological and mathematical flaws. The use of newer approaches, such as fuzzy logic and artificial neural networks, linked to artificial intelligence, seems to better address both the challenge of increasing complexity resulting from a correlation between predisposing factors, data on the occurrence of cardiovascular events, and the prediction of future events on an individual level. PMID:16672045

Determinants and definition of abdominal obesity as related to risk of diabetes, metabolic syndrome and coronary disease in Turkish men: a prospective cohort study.

PubMed

Onat, Altan; Uyarel, Hüseyin; Hergenç, Gülay; Karabulut, Ahmet; Albayrak, Sinan; Can, Günay

2007-03-01

We aimed to investigate determinants of abdominal obesity and its clinical impact on metabolic syndrome (MS), diabetes (DM) and coronary heart disease (CHD) in men. Prospective evaluation of 1638 male participants (aged 48.5+/-12.3), representative of Turkey's men who have a high prevalence of MS. For components of MS, criteria of NCEP guidelines were adopted, modified for abdominal obesity. Follow-up constituted 9650 person-years. Insulin level (relative risk [RR] 1.40 for doubling), C-reactive protein (CRP) and heavy smoking (protective) were independent predictors of newly developing abdominal obesity. High triglyceride and low HDL-cholesterol were significantly associated already with waist girth quartile II, apolipoprotein B with quartile III. Waist girth significantly predicted future MS from quartile II on, independent of insulin resistance (IR) by homeostatic model assessment, whereby its hazard ratio (HR, 2.6) exceeded double that of HOMA. CRP independently predicted MS. Age-adjusted HR of waist girth (1.59) was significant in predicting DM. Age- and smoking-adjusted top waist quartile conferred significant risk for incident CHD (RR 1.71) but not for overall mortality. As judged by sensitivity and specificity rates for future CHD, DM and MS, abdominal obesity was most appropriately defined with a waist girth of >or=95 cm, and an action level 1 of >or=87 cm was proposed for MS in this population. Serum insulin, CRP levels and (inversely) heavy smoking are predictors for abdominal obesity in Turkish men. Atherogenic dyslipidemia and elevated blood pressure are associated significantly already with modest rises in waist girth adjusted for age and smoking. Abdominal obesity shows substantial independence of IR in the development of MS. Increasing waist girth was predictive of MS, more strongly than of DM. Risk for CHD imparted by abdominal obesity is essentially mediated by risk factors it induces.

Areas of high conservation value at risk by plant invaders in Georgia under climate change.

PubMed

Slodowicz, Daniel; Descombes, Patrice; Kikodze, David; Broennimann, Olivier; Müller-Schärer, Heinz

2018-05-01

Invasive alien plants (IAP) are a threat to biodiversity worldwide. Understanding and anticipating invasions allow for more efficient management. In this regard, predicting potential invasion risks by IAPs is essential to support conservation planning into areas of high conservation value (AHCV) such as sites exhibiting exceptional botanical richness, assemblage of rare, and threatened and/or endemic plant species. Here, we identified AHCV in Georgia, a country showing high plant richness, and assessed the susceptibility of these areas to colonization by IAPs under present and future climatic conditions. We used actual protected areas and areas of high plant endemism (identified using occurrences of 114 Georgian endemic plant species) as proxies for AHCV. Then, we assessed present and future potential distribution of 27 IAPs using species distribution models under four climate change scenarios and stacked single-species potential distribution into a consensus map representing IAPs richness. We evaluated present and future invasion risks in AHCV using IAPs richness as a metric of susceptibility. We show that the actual protected areas cover only 9.4% of the areas of high plant endemism in Georgia. IAPs are presently located at lower elevations around the large urban centers and in western Georgia. We predict a shift of IAPs toward eastern Georgia and higher altitudes and an increased susceptibility of AHCV to IAPs under future climate change. Our study provides a good baseline for decision makers and stakeholders on where and how resources should be invested in the most efficient way to protect Georgia's high plant richness from IAPs.

Communicating asset risk: how name recognition and the format of historic volatility information affect risk perception and investment decisions.

PubMed

Weber, Elke U; Siebenmorgen, Niklas; Weber, Martin

2005-06-01

An experiment examined how the type and presentation format of information about investment options affected investors' expectations about asset risk, returns, and volatility and how these expectations related to asset choice. Respondents were provided with the names of 16 domestic and foreign investment options, with 10-year historical return information for these options, or with both. Historical returns were presented either as a bar graph of returns per year or as a continuous density distribution. Provision of asset names allowed for the investigation of the mechanisms underlying the home bias in investment choice and other asset familiarity effects. Respondents provided their expectations of future returns, volatility, and expected risk, and indicated the options they would choose to invest in. Expected returns closely resembled historical expected values. Risk and volatility perceptions both varied significantly as a function of the type and format of information, but in different ways. Expected returns and perceived risk, not predicted volatility, predicted portfolio decisions.

Predicting Ecstasy Use among Young People at Risk: A Prospective Study of Initially Ecstasy-Naive Subjects

ERIC Educational Resources Information Center

Vervaeke, Hylke K.E.; Benschop, Annemieke; Van Den Brink, Wim; Korf, Dirk J.

2008-01-01

Our aim is to identify predictors of first-time ecstasy use in a prospective study among young people at risk. As part of the multidisciplinary Netherlands XTC Toxicity Study (NeXT), we monitored 188 subjects aged up to 18 years who were ecstasy-naive at baseline but seemed likely to start taking ecstasy in the near future. After an 11- to…

Risk of Obstructive Sleep Apnea and Its Association with Cardiovascular and Noncardiac Vascular Risk in Patients with Rheumatoid Arthritis: A Population-based Study.

PubMed

Wilton, Katelynn M; Matteson, Eric L; Crowson, Cynthia S

2018-01-01

To define the incidence of obstructive sleep apnea (OSA) in patients with rheumatoid arthritis (RA) and determine whether OSA diagnosis predicts future cardiovascular disease (CVD) and noncardiac vascular events. Medical information pertaining to RA, OSA, CVD, and vascular diagnoses was extracted from a comprehensive medical record system for a geographically defined population of 813 patients previously diagnosed with RA and 813 age- and sex-matched comparator subjects. The risk for OSA in persons with RA versus comparators was elevated, although not reaching statistical significance (HR 1.32, 95% CI 0.98-1.77; p = 0.07). Patients with RA were more likely to be diagnosed with OSA if they had traditional risk factors for OSA, including male sex, current smoking status, hypertension, diabetes, dyslipidemia, and increased body mass index. Features of RA disease associated with OSA included large joint swelling and joint surgery. Patients with RA with decreased renal function were also at higher risk of OSA. The increased risk of overall CVD among patients with RA who have OSA was similar to the increased CVD risk associated with OSA in the comparator cohort (interaction p = 0.86). OSA diagnosis was associated with an increased risk of both CVD (HR 1.9, 95% CI 1.08-3.27), and cerebrovascular disease (HR 2.4, 95% CI 1.14-5.26) in patients with RA. Patients with RA may be at increased risk of OSA secondary to both traditional and RA-related risk factors. Diagnosis with OSA predicts future CVD in RA and may provide an opportunity for CVD intervention.

Risk Identification and Prediction of Coal Workers’ Pneumoconiosis in Kailuan Colliery Group in China: A Historical Cohort Study

PubMed Central

Shen, Fuhai; Yuan, Juxiang; Sun, Zhiqian; Hua, Zhengbing; Qin, Tianbang; Yao, Sanqiao; Fan, Xueyun; Chen, Weihong; Liu, Hongbo; Chen, Jie

2013-01-01

Background Prior to 1970, coal mining technology and prevention measures in China were poor. Mechanized coal mining equipment and advanced protection measures were continuously installed in the mines after 1970. All these improvements may have resulted in a change in the incidence of coal workers’ pneumoconiosis (CWP). Therefore, it is important to identify the characteristics of CWP today and trends for the incidence of CWP in the future. Methodology/Principal Findings A total of 17,023 coal workers from the Kailuan Colliery Group were studied. A life-table method was used to calculate the cumulative incidence rate of CWP and predict the number of new CWP patients in the future. The probability of developing CWP was estimated by a multilayer perceptron artificial neural network for each coal worker without CWP. The results showed that the cumulative incidence rates of CWP for tunneling, mining, combining, and helping workers were 31.8%, 27.5%, 24.2%, and 2.6%, respectively, during the same observation period of 40 years. It was estimated that there would be 844 new CWP cases among 16,185 coal workers without CWP within their life expectancy. There would be 273.1, 273.1, 227.6, and 69.9 new CWP patients in the next <10, 10-, 20-, and 30- years respectively in the study cohort within their life expectancy. It was identified that coal workers whose risk probabilities were over 0.2 were at high risk for CWP, and whose risk probabilities were under 0.1 were at low risk. Conclusion/Significance The present and future incidence trends of CWP remain high among coal workers. We suggest that coal workers at high risk of CWP undergo a physical examination for pneumoconiosis every year, and the coal workers at low risk of CWP be examined every 5 years. PMID:24376519

Curiosity predicts smoking experimentation independent of susceptibility in a US national sample.

PubMed

Nodora, Jesse; Hartman, Sheri J; Strong, David R; Messer, Karen; Vera, Lisa E; White, Martha M; Portnoy, David B; Choiniere, Conrad J; Vullo, Genevieve C; Pierce, John P

2014-12-01

To improve smoking prevention efforts, better methods for identifying at-risk youth are needed. The widely used measure of susceptibility to smoking identifies at-risk adolescents; however, it correctly identifies only about one third of future smokers. Adding curiosity about smoking to this susceptibility index may allow us to identify a greater proportion of future smokers while they are still pre-teens. We use longitudinal data from a recent national study on parenting to prevent problem behaviors. Only oldest children between 10 and 13years of age were eligible. Participants were identified by RDD survey and followed for 6years. All baseline never smokers with at least one follow-up assessment were included (n=878). The association of curiosity about smoking with future smoking behavior was assessed. Then, curiosity was added to form an enhanced susceptibility index and sensitivity, specificity and positive predictive value were calculated. Among committed never smokers at baseline, those who were 'definitely not curious' were less likely to progress toward smoking than both those who were 'probably not curious' (ORadj=1.89; 95% CI=1.03-3.47) or 'probably/definitely curious' (ORadj=2.88; 95% CI=1.11-7.45). Incorporating curiosity into the susceptibility index increased the proportion identified as at-risk to smoke from 25.1% to 46.9%. The sensitivity (true positives) for this enhanced susceptibility index for both experimentation and established smoking increased from 37-40% to over 50%, although the positive predictive value did not improve. The addition of curiosity significantly improves the identification and classification of which adolescents will experiment with smoking or become established smokers. Copyright © 2014 Elsevier Ltd. All rights reserved.

BOADICEA breast cancer risk prediction model: updates to cancer incidences, tumour pathology and web interface

PubMed Central

Lee, A J; Cunningham, A P; Kuchenbaecker, K B; Mavaddat, N; Easton, D F; Antoniou, A C

2014-01-01

Background: The Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) is a risk prediction model that is used to compute probabilities of carrying mutations in the high-risk breast and ovarian cancer susceptibility genes BRCA1 and BRCA2, and to estimate the future risks of developing breast or ovarian cancer. In this paper, we describe updates to the BOADICEA model that extend its capabilities, make it easier to use in a clinical setting and yield more accurate predictions. Methods: We describe: (1) updates to the statistical model to include cancer incidences from multiple populations; (2) updates to the distributions of tumour pathology characteristics using new data on BRCA1 and BRCA2 mutation carriers and women with breast cancer from the general population; (3) improvements to the computational efficiency of the algorithm so that risk calculations now run substantially faster; and (4) updates to the model's web interface to accommodate these new features and to make it easier to use in a clinical setting. Results: We present results derived using the updated model, and demonstrate that the changes have a significant impact on risk predictions. Conclusion: All updates have been implemented in a new version of the BOADICEA web interface that is now available for general use: http://ccge.medschl.cam.ac.uk/boadicea/. PMID:24346285

The Bronchiectasis Severity Index. An International Derivation and Validation Study

PubMed Central

Goeminne, Pieter; Aliberti, Stefano; McDonnell, Melissa J.; Lonni, Sara; Davidson, John; Poppelwell, Lucy; Salih, Waleed; Pesci, Alberto; Dupont, Lieven J.; Fardon, Thomas C.; De Soyza, Anthony; Hill, Adam T.

2014-01-01

Rationale: There are no risk stratification tools for morbidity and mortality in bronchiectasis. Identifying patients at risk of exacerbations, hospital admissions, and mortality is vital for future research. Objectives: This study describes the derivation and validation of the Bronchiectasis Severity Index (BSI). Methods: Derivation of the BSI used data from a prospective cohort study (Edinburgh, UK, 2008–2012) enrolling 608 patients. Cox proportional hazard regression was used to identify independent predictors of mortality and hospitalization over 4-year follow-up. The score was validated in independent cohorts from Dundee, UK (n = 218); Leuven, Belgium (n = 253); Monza, Italy (n = 105); and Newcastle, UK (n = 126). Measurements and Main Results: Independent predictors of future hospitalization were prior hospital admissions, Medical Research Council dyspnea score greater than or equal to 4, FEV1 < 30% predicted, Pseudomonas aeruginosa colonization, colonization with other pathogenic organisms, and three or more lobes involved on high-resolution computed tomography. Independent predictors of mortality were older age, low FEV1, lower body mass index, prior hospitalization, and three or more exacerbations in the year before the study. The derived BSI predicted mortality and hospitalization: area under the receiver operator characteristic curve (AUC) 0.80 (95% confidence interval, 0.74–0.86) for mortality and AUC 0.88 (95% confidence interval, 0.84–0.91) for hospitalization, respectively. There was a clear difference in exacerbation frequency and quality of life using the St. George’s Respiratory Questionnaire between patients classified as low, intermediate, and high risk by the score (P < 0.0001 for all comparisons). In the validation cohorts, the AUC for mortality ranged from 0.81 to 0.84 and for hospitalization from 0.80 to 0.88. Conclusions: The BSI is a useful clinical predictive tool that identifies patients at risk of future mortality, hospitalization, and exacerbations across healthcare systems. PMID:24328736

Design and application analysis of prediction system of geo-hazards based on GIS in the Three Gorges Reservoir

NASA Astrophysics Data System (ADS)

Li, Deying; Yin, Kunlong; Gao, Huaxi; Liu, Changchun

2009-10-01

Although the project of the Three Gorges Dam across the Yangtze River in China can utilize this huge potential source of hydroelectric power, and eliminate the loss of life and damage by flood, it also causes environmental problems due to the big rise and fluctuation of the water, such as geo-hazards. In order to prevent and predict geo-hazards, the establishment of prediction system of geo-hazards is very necessary. In order to implement functions of hazard prediction of regional and urban geo-hazard, single geo-hazard prediction, prediction of landslide surge and risk evaluation, logical layers of the system consist of data capturing layer, data manipulation and processing layer, analysis and application layer, and information publication layer. Due to the existence of multi-source spatial data, the research on the multi-source transformation and fusion data should be carried on in the paper. Its applicability of the system was testified on the spatial prediction of landslide hazard through spatial analysis of GIS in which information value method have been applied aims to identify susceptible areas that are possible to future landslide, on the basis of historical record of past landslide, terrain parameter, geology, rainfall and anthropogenic activity. Detailed discussion was carried out on spatial distribution characteristics of landslide hazard in the new town of Badong. These results can be used for risk evaluation. The system can be implemented as an early-warning and emergency management tool by the relevant authorities of the Three Gorges Reservoir in the future.

Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations.

PubMed

Chen, Tianlu; Ni, Yan; Ma, Xiaojing; Bao, Yuqian; Liu, Jiajian; Huang, Fengjie; Hu, Cheng; Xie, Guoxiang; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-02-05

Recent studies revealed strong evidence that branched-chain and aromatic amino acids (BCAAs and AAAs) are closely associated with the risk of developing type 2 diabetes in several Western countries. The aim of this study was to evaluate the potential role of BCAAs and AAAs in predicting the diabetes development in Chinese populations. The serum levels of valine, leucine, isoleucine, tyrosine, and phenylalanine were measured in a longitudinal and a cross sectional studies with a total of 429 Chinese participants at different stages of diabetes development, using an ultra-performance liquid chromatography triple quadruple mass spectrometry platform. The alterations of the five AAs in Chinese populations are well in accordance with previous reports. Early elevation of the five AAs and their combined score was closely associated with future development of diabetes, suggesting an important role of these metabolites as early markers of diabetes. On the other hand, the five AAs were not as good as existing clinical markers in differentiating diabetic patients from their healthy counterparts. Our findings verified the close correlation of BCAAs and AAAs with insulin resistance and future development of diabetes in Chinese populations and highlighted the predictive value of these markers for future development of diabetes.

Branched-chain and aromatic amino acid profiles and diabetes risk in Chinese populations

PubMed Central

Chen, Tianlu; Ni, Yan; Ma, Xiaojing; Bao, Yuqian; Liu, Jiajian; Huang, Fengjie; Hu, Cheng; Xie, Guoxiang; Zhao, Aihua; Jia, Weiping; Jia, Wei

2016-01-01

Recent studies revealed strong evidence that branched-chain and aromatic amino acids (BCAAs and AAAs) are closely associated with the risk of developing type 2 diabetes in several Western countries. The aim of this study was to evaluate the potential role of BCAAs and AAAs in predicting the diabetes development in Chinese populations. The serum levels of valine, leucine, isoleucine, tyrosine, and phenylalanine were measured in a longitudinal and a cross sectional studies with a total of 429 Chinese participants at different stages of diabetes development, using an ultra-performance liquid chromatography triple quadruple mass spectrometry platform. The alterations of the five AAs in Chinese populations are well in accordance with previous reports. Early elevation of the five AAs and their combined score was closely associated with future development of diabetes, suggesting an important role of these metabolites as early markers of diabetes. On the other hand, the five AAs were not as good as existing clinical markers in differentiating diabetic patients from their healthy counterparts. Our findings verified the close correlation of BCAAs and AAAs with insulin resistance and future development of diabetes in Chinese populations and highlighted the predictive value of these markers for future development of diabetes. PMID:26846565

Measuring Gambling Reinforcers, Over Consumption and Fallacies: The Psychometric Properties and Predictive Validity of the Jonsson-Abbott Scale

PubMed Central

Jonsson, Jakob; Abbott, Max W.; Sjöberg, Anders; Carlbring, Per

2017-01-01

Traditionally, gambling and problem gambling research relies on cross-sectional and retrospective designs. This has compromised identification of temporal relationships and causal inference. To overcome these problems a new questionnaire, the Jonsson-Abbott Scale (JAS), was developed and used in a large, prospective, general population study, The Swedish Longitudinal Gambling Study (Swelogs). The JAS has 11 items and seeks to identify early indicators, examine relationships between indicators and assess their capacity to predict future problem progression. The aims of the study were to examine psychometric properties of the JAS (internal consistency and dimensionality) and predictive validity with respect to increased gambling risk and problem gambling onset. The results are based on repeated interviews with 3818 participants. The response rate from the initial baseline wave was 74%. The original sample consisted of a random, stratified selection from the Swedish population register aged between 16 and 84. The results indicate an acceptable fit of a three-factor solution in a confirmatory factor analysis with ‘Over consumption,’ ‘Gambling fallacies,’ and ‘Reinforcers’ as factors. Reinforcers, Over consumption and Gambling fallacies were significant predictors of gambling risk potential and Gambling fallacies and Over consumption were significant predictors of problem gambling onset (incident cases) at 12 month follow up. When controlled for risk potential measured at baseline, the predictor Over consumption was not significant for gambling risk potential at follow up. For incident cases, Gambling fallacies and Over consumption remained significant when controlled for risk potential. Implications of the results for the development of problem gambling, early detection, prevention, and future research are discussed. PMID:29085320

The past, present, and future of cancer incidence in the United States: 1975 through 2020.

PubMed

Weir, Hannah K; Thompson, Trevor D; Soman, Ashwini; Møller, Bjørn; Leadbetter, Steven

2015-06-01

The overall age-standardized cancer incidence rate continues to decline whereas the number of cases diagnosed each year increases. Predicting cancer incidence can help to anticipate future resource needs, evaluate primary prevention strategies, and inform research. Surveillance, Epidemiology, and End Results data were used to estimate the number of cancers (all sites) resulting from changes in population risk, age, and size. The authors projected to 2020 nationwide age-standardized incidence rates and cases (including the top 23 cancers). Since 1975, incident cases increased among white individuals, primarily caused by an aging white population, and among black individuals, primarily caused by an increasing black population. Between 2010 and 2020, it is expected that overall incidence rates (proxy for risk) will decrease slightly among black men and stabilize in other groups. By 2020, the authors predict annual cancer cases (all races, all sites) to increase among men by 24.1% (-3.2% risk and 27.3% age/growth) to >1 million cases, and by 20.6% among women (1.2% risk and 19.4% age/growth) to >900,000 cases. The largest increases are expected for melanoma (white individuals); cancers of the prostate, kidney, liver, and urinary bladder in males; and the lung, breast, uterus, and thyroid in females. Overall, the authors predict cancer incidence rates/risk to stabilize for the majority of the population; however, they expect the number of cancer cases to increase by >20%. A greater emphasis on primary prevention and early detection is needed to counter the effect of an aging and growing population on the burden of cancer. © 2015 American Cancer Society.

The Past, Present, and Future of Cancer Incidence in the United States: 1975 Through 2020

PubMed Central

Weir, Hannah K.; Thompson, Trevor D.; Soman, Ashwini; Møller, Bjørn; Leadbetter, Steven

2015-01-01

BACKGROUND The overall age-standardized cancer incidence rate continues to decline whereas the number of cases diagnosed each year increases. Predicting cancer incidence can help to anticipate future resource needs, evaluate primary prevention strategies, and inform research. METHODS Surveillance, Epidemiology, and End Results data were used to estimate the number of cancers (all sites) resulting from changes in population risk, age, and size. The authors projected to 2020 nationwide age-standardized incidence rates and cases (including the top 23 cancers). RESULTS Since 1975, incident cases increased among white individuals, primarily caused by an aging white population, and among black individuals, primarily caused by an increasing black population. Between 2010 and 2020, it is expected that overall incidence rates (proxy for risk) will decrease slightly among black men and stabilize in other groups. By 2020, the authors predict annual cancer cases (all races, all sites) to increase among men by 24.1% (−3.2% risk and 27.3% age/growth) to >1 million cases, and by 20.6% among women (1.2% risk and 19.4% age/growth) to >900,000 cases. The largest increases are expected for melanoma (white individuals); cancers of the prostate, kidney, liver, and urinary bladder in males; and the lung, breast, uterus, and thyroid in females. CONCLUSIONS Overall, the authors predict cancer incidence rates/risk to stabilize for the majority of the population; however, they expect the number of cancer cases to increase by >20%. A greater emphasis on primary prevention and early detection is needed to counter the effect of an aging and growing population on the burden of cancer. PMID:25649671

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

PubMed

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

2018-01-03

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

Adiposity and hyperglycaemia in pregnancy and related health outcomes in European ethnic minorities of Asian and African origin: a review

PubMed Central

Jenum, Anne Karen; Sommer, Christine; Sletner, Line; Mørkrid, Kjersti; Bærug, Anne; Mosdøl, Annhild

2013-01-01

Background Ethnic minorities in Europe have high susceptibility to type 2 diabetes (T2DM) and, in some groups, also cardiovascular disease (CVD). Pregnancy can be considered a stress test that predicts future morbidity patterns in women and that affects future health of the child. Objective To review ethnic differences in: 1) adiposity, hyperglycaemia, and pre-eclampsia during pregnancy; 2) future risk in the mother of obesity, T2DM and CVD; and 3) prenatal development and possible influences of maternal obesity, hyperglycaemia, and pre-eclampsia on offspring's future disease risk, as relevant for ethnic minorities in Europe of Asian and African origin. Design Literature review. Results Maternal health among ethnic minorities is still sparsely documented. Higher pre-pregnant body mass index (BMI) is found in women of African and Middle Eastern descent, and lower BMI in women from East and South Asia compared with women from the majority population. Within study populations, risk of gestational diabetes mellitus (GDM) is considerably higher in many minority groups, particularly South Asians, than in the majority population. This increased risk is apparent at lower BMI and younger ages. Women of African origin have higher risk of pre-eclampsia. A GDM pregnancy implies approximately seven-fold higher risk of T2DM than normal pregnancies, and both GDM and pre-eclampsia increase later risk of CVD. Asian neonates have lower birth weights, and mostly also African neonates. This may translate into increased risks of later obesity, T2DM, and CVD. Foetal overgrowth can promote the same conditions. Breastfeeding represents a possible strategy to reduce risk of T2DM in both the mother and the child. Conclusions Ethnic minority women in Europe with Asian and African origin and their offspring seem to be at increased risk of T2DM and CVD, both currently and in the future. Pregnancy is an important window of opportunity for short and long-term disease prevention. PMID:23467680

Prediction of cardiovascular disease risk among low-income urban dwellers in metropolitan Kuala Lumpur, Malaysia.

PubMed

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Bulgiba, Awang; Majid, Hazreen Abdul

2015-01-01

We aimed to predict the ten-year cardiovascular disease (CVD) risk among low-income urban dwellers of metropolitan Malaysia. Participants were selected from a cross-sectional survey conducted in Kuala Lumpur. To assess the 10-year CVD risk, we employed the Framingham risk scoring (FRS) models. Significant determinants of the ten-year CVD risk were identified using General Linear Model (GLM). Altogether 882 adults (≥30 years old with no CVD history) were randomly selected. The classic FRS model (figures in parentheses are from the modified model) revealed that 20.5% (21.8%) and 38.46% (38.9%) of respondents were at high and moderate risk of CVD. The GLM models identified the importance of education, occupation, and marital status in predicting the future CVD risk. Our study indicated that one out of five low-income urban dwellers has high chance of having CVD within ten years. Health care expenditure, other illness related costs and loss of productivity due to CVD would worsen the current situation of low-income urban population. As such, the public health professionals and policy makers should establish substantial effort to formulate the public health policy and community-based intervention to minimize the upcoming possible high mortality and morbidity due to CVD among the low-income urban dwellers.

Selective Methicillin-Resistant Staphylococcus Aureus (MRSA) screening of a high risk population does not adequately detect MRSA carriers within a country with low MRSA prevalence.

PubMed

de Wouters, Solange; Daxhelet, Jérémy; Kaminski, Ludovic; Thienpont, Emmanuel; Cornu, Olivier; Yombi, Jean Cyr

2015-12-01

Methicillin-Resistant Staphylococcus Aureus (MRSA) has been widely recognized as a serious problem in hospital settings. The purpose of this study is to evaluate the predictive value of MRSA colonization factors in the detection of MRSA carriers in an orthopedic ward. A systematic MRSA detection strategy was set up to assess the predictive value of MRSA colonization factors among 554 patients undergoing elective knee arthroplasty. In total 116 patients were found positive for Staphylococcus Aureus; among those 110/116 patients were found positive for Methicillin-Sensitive Staphylococcus Aureus (MSSA) and 6/116 for MRSA. Only one patient out of six presented two risk factors according to MRSA risk factors. In this study, no correlation was found between the remaining conventional risk factors, according to Belgian guidelines, defined to target high-risk populations and to identify MRSA carriers. Established criteria for selective MRSA screening do not allow detecting MRSA carriers. The objective of detecting MRSA carriers is not correctly met by the actual applied criteria (Belgian consensus) for a selective screening policy. Future studies should aim at identifying the right risk factors, depending of the country's prevalence of MRSA, to improve the ability to predict the risk of MRSA carriage at hospital admission.

Prediction of Cardiovascular Disease Risk among Low-Income Urban Dwellers in Metropolitan Kuala Lumpur, Malaysia

PubMed Central

Su, Tin Tin; Amiri, Mohammadreza; Mohd Hairi, Farizah; Thangiah, Nithiah; Majid, Hazreen Abdul

2015-01-01

We aimed to predict the ten-year cardiovascular disease (CVD) risk among low-income urban dwellers of metropolitan Malaysia. Participants were selected from a cross-sectional survey conducted in Kuala Lumpur. To assess the 10-year CVD risk, we employed the Framingham risk scoring (FRS) models. Significant determinants of the ten-year CVD risk were identified using General Linear Model (GLM). Altogether 882 adults (≥30 years old with no CVD history) were randomly selected. The classic FRS model (figures in parentheses are from the modified model) revealed that 20.5% (21.8%) and 38.46% (38.9%) of respondents were at high and moderate risk of CVD. The GLM models identified the importance of education, occupation, and marital status in predicting the future CVD risk. Our study indicated that one out of five low-income urban dwellers has high chance of having CVD within ten years. Health care expenditure, other illness related costs and loss of productivity due to CVD would worsen the current situation of low-income urban population. As such, the public health professionals and policy makers should establish substantial effort to formulate the public health policy and community-based intervention to minimize the upcoming possible high mortality and morbidity due to CVD among the low-income urban dwellers. PMID:25821810

Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk - Results from the PROG-IMT collaboration.

PubMed

Lorenz, Matthias W; Gao, Lu; Ziegelbauer, Kathrin; Norata, Giuseppe Danilo; Empana, Jean Philippe; Schmidtmann, Irene; Lin, Hung-Ju; McLachlan, Stela; Bokemark, Lena; Ronkainen, Kimmo; Amato, Mauro; Schminke, Ulf; Srinivasan, Sathanur R; Lind, Lars; Okazaki, Shuhei; Stehouwer, Coen D A; Willeit, Peter; Polak, Joseph F; Steinmetz, Helmuth; Sander, Dirk; Poppert, Holger; Desvarieux, Moise; Ikram, M Arfan; Johnsen, Stein Harald; Staub, Daniel; Sirtori, Cesare R; Iglseder, Bernhard; Beloqui, Oscar; Engström, Gunnar; Friera, Alfonso; Rozza, Francesco; Xie, Wuxiang; Parraga, Grace; Grigore, Liliana; Plichart, Matthieu; Blankenberg, Stefan; Su, Ta-Chen; Schmidt, Caroline; Tuomainen, Tomi-Pekka; Veglia, Fabrizio; Völzke, Henry; Nijpels, Giel; Willeit, Johann; Sacco, Ralph L; Franco, Oscar H; Uthoff, Heiko; Hedblad, Bo; Suarez, Carmen; Izzo, Raffaele; Zhao, Dong; Wannarong, Thapat; Catapano, Alberico; Ducimetiere, Pierre; Espinola-Klein, Christine; Chien, Kuo-Liong; Price, Jackie F; Bergström, Göran; Kauhanen, Jussi; Tremoli, Elena; Dörr, Marcus; Berenson, Gerald; Kitagawa, Kazuo; Dekker, Jacqueline M; Kiechl, Stefan; Sitzer, Matthias; Bickel, Horst; Rundek, Tatjana; Hofman, Albert; Mathiesen, Ellisiv B; Castelnuovo, Samuela; Landecho, Manuel F; Rosvall, Maria; Gabriel, Rafael; de Luca, Nicola; Liu, Jing; Baldassarre, Damiano; Kavousi, Maryam; de Groot, Eric; Bots, Michiel L; Yanez, David N; Thompson, Simon G

2018-01-01

Carotid intima media thickness (CIMT) predicts cardiovascular (CVD) events, but the predictive value of CIMT change is debated. We assessed the relation between CIMT change and events in individuals at high cardiovascular risk. From 31 cohorts with two CIMT scans (total n = 89070) on average 3.6 years apart and clinical follow-up, subcohorts were drawn: (A) individuals with at least 3 cardiovascular risk factors without previous CVD events, (B) individuals with carotid plaques without previous CVD events, and (C) individuals with previous CVD events. Cox regression models were fit to estimate the hazard ratio (HR) of the combined endpoint (myocardial infarction, stroke or vascular death) per standard deviation (SD) of CIMT change, adjusted for CVD risk factors. These HRs were pooled across studies. In groups A, B and C we observed 3483, 2845 and 1165 endpoint events, respectively. Average common CIMT was 0.79mm (SD 0.16mm), and annual common CIMT change was 0.01mm (SD 0.07mm), both in group A. The pooled HR per SD of annual common CIMT change (0.02 to 0.43mm) was 0.99 (95% confidence interval: 0.95-1.02) in group A, 0.98 (0.93-1.04) in group B, and 0.95 (0.89-1.04) in group C. The HR per SD of common CIMT (average of the first and the second CIMT scan, 0.09 to 0.75mm) was 1.15 (1.07-1.23) in group A, 1.13 (1.05-1.22) in group B, and 1.12 (1.05-1.20) in group C. We confirm that common CIMT is associated with future CVD events in individuals at high risk. CIMT change does not relate to future event risk in high-risk individuals.

Idiopathic Pulmonary Fibrosis: Gender-Age-Physiology Index Stage for Predicting Future Lung Function Decline.

PubMed

Salisbury, Margaret L; Xia, Meng; Zhou, Yueren; Murray, Susan; Tayob, Nabihah; Brown, Kevin K; Wells, Athol U; Schmidt, Shelley L; Martinez, Fernando J; Flaherty, Kevin R

2016-02-01

Idiopathic pulmonary fibrosis is a progressive lung disease with variable course. The Gender-Age-Physiology (GAP) Index and staging system uses clinical variables to stage mortality risk. It is unknown whether clinical staging predicts future decline in pulmonary function. We assessed whether the GAP stage predicts future pulmonary function decline and whether interval pulmonary function change predicts mortality after accounting for stage. Patients with idiopathic pulmonary fibrosis (N = 657) were identified retrospectively at three tertiary referral centers, and baseline GAP stages were assessed. Mixed models were used to describe average trajectories of FVC and diffusing capacity of the lung for carbon monoxide (Dlco). Multivariable Cox proportional hazards models were used to assess whether declines in pulmonary function ≥ 10% in 6 months predict mortality after accounting for GAP stage. Over a 2-year period, GAP stage was not associated with differences in yearly lung function decline. After accounting for stage, a 10% decrease in FVC or Dlco over 6 months independently predicted death or transplantation (FVC hazard ratio, 1.37; Dlco hazard ratio, 1.30; both, P ≤ .03). Patients with GAP stage 2 with declining pulmonary function experienced a survival profile similar to patients with GAP stage 3, with 1-year event-free survival of 59.3% (95% CI, 49.4-67.8) vs 56.9% (95% CI, 42.2-69.1). Baseline GAP stage predicted death or lung transplantation but not the rate of future pulmonary function decline. After accounting for GAP stage, a decline of ≥ 10% over 6 months independently predicted death or lung transplantation. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

External Validation of the HERNIAscore: An Observational Study.

PubMed

Cherla, Deepa V; Moses, Maya L; Mueck, Krislynn M; Hannon, Craig; Ko, Tien C; Kao, Lillian S; Liang, Mike K

2017-09-01

The HERNIAscore is a ventral incisional hernia (VIH) risk assessment tool that uses only preoperative variables and predictable intraoperative variables. The aim of this study was to validate and modify, if needed, the HERNIAscore in an external dataset. This was a retrospective observational study of all patients undergoing resection for gastrointestinal malignancy from 2011 through 2015 at a safety-net hospital. The primary end point was clinical postoperative VIH. Patients were stratified into low-risk, medium-risk, and high-risk groups based on HERNIAscore. A revised HERNIAscore was calculated with the addition of earlier abdominal operation as a categorical variable. Cox regression of incisional hernia with stratification by risk class was performed. Incidence rates of clinical VIH formation within each risk class were also calculated. Two hundred and forty-seven patents were enrolled. On Cox regression, in addition to the 3 variables of the HERNIAscore (BMI, COPD, and incision length), earlier abdominal operation was also predictive of VIH. The revised HERNIAscore demonstrated improved predictive accuracy for clinical VIH. Although the original HERNIAscore effectively stratified the risk of an incisional radiographic VIH developing, the revised HERNIAscore provided a statistically significant stratification for both clinical and radiographic VIHs in this patient cohort. We have externally validated and improved the HERNIAscore. The revised HERNIAscore uses BMI, incision length, COPD, and earlier abdominal operation to predict risk of postoperative incisional hernia. Future research should assess methods to prevent incisional hernias in moderate-to-high risk patients. Copyright © 2017 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Human Population Density and Extinction Risk in the World's Carnivores

PubMed Central

Purvis, Andy; Sechrest, Wes; Gittleman, John L; Bielby, Jon; Mace, Georgina M

2004-01-01

Understanding why some species are at high risk of extinction, while others remain relatively safe, is central to the development of a predictive conservation science. Recent studies have shown that a species' extinction risk may be determined by two types of factors: intrinsic biological traits and exposure to external anthropogenic threats. However, little is known about the relative and interacting effects of intrinsic and external variables on extinction risk. Using phylogenetic comparative methods, we show that extinction risk in the mammal order Carnivora is predicted more strongly by biology than exposure to high-density human populations. However, biology interacts with human population density to determine extinction risk: biological traits explain 80% of variation in risk for carnivore species with high levels of exposure to human populations, compared to 45% for carnivores generally. The results suggest that biology will become a more critical determinant of risk as human populations expand. We demonstrate how a model predicting extinction risk from biology can be combined with projected human population density to identify species likely to move most rapidly towards extinction by the year 2030. African viverrid species are particularly likely to become threatened, even though most are currently considered relatively safe. We suggest that a preemptive approach to species conservation is needed to identify and protect species that may not be threatened at present but may become so in the near future. PMID:15252445

A precision medicine approach for psychiatric disease based on repeated symptom scores.

PubMed

Fojo, Anthony T; Musliner, Katherine L; Zandi, Peter P; Zeger, Scott L

2017-12-01

For psychiatric diseases, rich information exists in the serial measurement of mental health symptom scores. We present a precision medicine framework for using the trajectories of multiple symptoms to make personalized predictions about future symptoms and related psychiatric events. Our approach fits a Bayesian hierarchical model that estimates a population-average trajectory for all symptoms and individual deviations from the average trajectory, then fits a second model that uses individual symptom trajectories to estimate the risk of experiencing an event. The fitted models are used to make clinically relevant predictions for new individuals. We demonstrate this approach on data from a study of antipsychotic therapy for schizophrenia, predicting future scores for positive, negative, and general symptoms, and the risk of treatment failure in 522 schizophrenic patients with observations over 8 weeks. While precision medicine has focused largely on genetic and molecular data, the complementary approach we present illustrates that innovative analytic methods for existing data can extend its reach more broadly. The systematic use of repeated measurements of psychiatric symptoms offers the promise of precision medicine in the field of mental health. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Uncertainties in radiation effect predictions for the natural radiation environments of space.

PubMed

McNulty, P J; Stassinopoulos, E G

1994-10-01

Future manned missions beyond low earth orbit require accurate predictions of the risk to astronauts and to critical systems from exposure to ionizing radiation. For low-level exposures, the hazards are dominated by rare single-event phenomena where individual cosmic-ray particles or spallation reactions result in potentially catastrophic changes in critical components. Examples might be a biological lesion leading to cancer in an astronaut or a memory upset leading to an undesired rocket firing. The risks of such events appears to depend on the amount of energy deposited within critical sensitive volumes of biological cells and microelectronic components. The critical environmental information needed to estimate the risks posed by the natural space environments, including solar flares, is the number of times more than a threshold amount of energy for an event will be deposited in the critical microvolumes. These predictions are complicated by uncertainties in the natural environments, particularly the composition of flares, and by the effects of shielding. Microdosimetric data for large numbers of orbits are needed to improve the environmental models and to test the transport codes used to predict event rates.

Uncertainties in radiation effect predictions for the natural radiation environments of space

NASA Technical Reports Server (NTRS)

Mcnulty, P. J.; Stassinopoulos, E. G.

1994-01-01

Future manned missions beyond low earth orbit require accurate predictions of the risk to astronauts and to critical systems from exposure to ionizing radiation. For low-level exposures, the hazards are dominated by rare single-event phenomena where individual cosmic-ray particles or spallation reactions result in potentially catastrophic changes in critical components. Examples might be a biological lesion leading to cancer in an astronaut or a memory upset leading to an undesired rocket firing. The risks of such events appears to depend on the amount of energy deposited within critical sensitive volumes of biological cells and microelectronic components. The critical environmental information needed to estimate the risks posed by the natural space environments, including solar flares, is the number of times more than a threshold amount of energy for an event will be deposited in the critical microvolumes. These predictions are complicated by uncertainties in the natural environments, particularly the composition of flares, and by the effects of shielding. Microdosimetric data for large numbers of orbits are needed to improve the environmental models and to test the transport codes used to predict event rates.

Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models.

PubMed

Bonan, Gordon B; Doney, Scott C

2018-02-02

Many global change stresses on terrestrial and marine ecosystems affect not only ecosystem services that are essential to humankind, but also the trajectory of future climate by altering energy and mass exchanges with the atmosphere. Earth system models, which simulate terrestrial and marine ecosystems and biogeochemical cycles, offer a common framework for ecological research related to climate processes; analyses of vulnerability, impacts, and adaptation; and climate change mitigation. They provide an opportunity to move beyond physical descriptors of atmospheric and oceanic states to societally relevant quantities such as wildfire risk, habitat loss, water availability, and crop, fishery, and timber yields. To achieve this, the science of climate prediction must be extended to a more multifaceted Earth system prediction that includes the biosphere and its resources. Copyright © 2018, American Association for the Advancement of Science.

Longitudinal prediction of language emergence in infants at high and low risk for autism spectrum disorder.

PubMed

Edmunds, Sarah R; Ibañez, Lisa V; Warren, Zachary; Messinger, Daniel S; Stone, Wendy L

2017-02-01

This study used a prospective longitudinal design to examine the early developmental pathways that underlie language growth in infants at high risk (n = 50) and low risk (n = 34) for autism spectrum disorder in the first 18 months of life. While motor imitation and responding to joint attention (RJA) have both been found to predict expressive language in children with autism spectrum disorder and those with typical development, the longitudinal relation between these capacities has not yet been identified. As hypothesized, results revealed that 15-month RJA mediated the association between 12-month motor imitation and 18-month expressive vocabulary, even after controlling for earlier levels of RJA and vocabulary. These results provide new information about the developmental sequencing of skills relevant to language growth that may inform future intervention efforts for children at risk for language delay or other developmental challenges.

Physician-patient and patient-family communication after colonoscopy.

PubMed

Jiménez, Jessica A; Jung, Barbara; Madlensky, Lisa

2012-09-01

A personal or family history of colorectal adenomas increases the risk of colorectal cancer (CRC). We aimed to compare physicians' communication with polyp patients vs. non-polyp patients, assess whether polyps or CRC family history were associated with physician-patient communication, and describe patients' disclosure of colonoscopy and polyp diagnosis to their relatives. Four hundred nine patients completed an online survey regarding physician-patient communication of colonoscopy results, perceived personal and familial risk of polyps and CRC, and disclosure of colonoscopy results to relatives. Six percent of participants reported that their physicians discussed familial risks. Polyp diagnosis and family history predicted physician-patient discussions about familial CRC risks. Polyp diagnosis predicted physician-patient discussions of future surveillance. Twenty-two percent of patients told none of their relatives that they had a colonoscopy. Family history, gender, and education were associated with patient-family communication. There is room for improvement in physician-patient and patient-family communication following colonoscopy.

Impacts of variability in cellulosic biomass yields on energy security.

PubMed

Mullins, Kimberley A; Matthews, H Scott; Griffin, W Michael; Anex, Robert

2014-07-01

The practice of modeling biomass yields on the basis of deterministic point values aggregated over space and time obscures important risks associated with large-scale biofuel use, particularly risks related to drought-induced yield reductions that may become increasingly frequent under a changing climate. Using switchgrass as a case study, this work quantifies the variability in expected yields over time and space through switchgrass growth modeling under historical and simulated future weather. The predicted switchgrass yields across the United States range from about 12 to 19 Mg/ha, and the 80% confidence intervals range from 20 to 60% of the mean. Average yields are predicted to decrease with increased temperatures and weather variability induced by climate change. Feedstock yield variability needs to be a central part of modeling to ensure that policy makers acknowledge risks to energy supplies and develop strategies or contingency plans that mitigate those risks.

Cetacean range and climate in the eastern North Atlantic: future predictions and implications for conservation.

PubMed

Lambert, Emily; Pierce, Graham J; Hall, Karen; Brereton, Tom; Dunn, Timothy E; Wall, Dave; Jepson, Paul D; Deaville, Rob; MacLeod, Colin D

2014-06-01

There is increasing evidence that the distributions of a large number of species are shifting with global climate change as they track changing surface temperatures that define their thermal niche. Modelling efforts to predict species distributions under future climates have increased with concern about the overall impact of these distribution shifts on species ecology, and especially where barriers to dispersal exist. Here we apply a bio-climatic envelope modelling technique to investigate the impacts of climate change on the geographic range of ten cetacean species in the eastern North Atlantic and to assess how such modelling can be used to inform conservation and management. The modelling process integrates elements of a species' habitat and thermal niche, and employs "hindcasting" of historical distribution changes in order to verify the accuracy of the modelled relationship between temperature and species range. If this ability is not verified, there is a risk that inappropriate or inaccurate models will be used to make future predictions of species distributions. Of the ten species investigated, we found that while the models for nine could successfully explain current spatial distribution, only four had a good ability to predict distribution changes over time in response to changes in water temperature. Applied to future climate scenarios, the four species-specific models with good predictive abilities indicated range expansion in one species and range contraction in three others, including the potential loss of up to 80% of suitable white-beaked dolphin habitat. Model predictions allow identification of affected areas and the likely time-scales over which impacts will occur. Thus, this work provides important information on both our ability to predict how individual species will respond to future climate change and the applicability of predictive distribution models as a tool to help construct viable conservation and management strategies. © 2014 John Wiley & Sons Ltd.

Multi-dimensional perspectives of flood risk - using a participatory framework to develop new approaches to flood risk communication

NASA Astrophysics Data System (ADS)

Rollason, Edward; Bracken, Louise; Hardy, Richard; Large, Andy

2017-04-01

Flooding is a major hazard across Europe which, since, 1998 has caused over €52 million in damages and displaced over half a million people. Climate change is predicted to increase the risks posed by flooding in the future. The 2007 EU Flood Directive cemented the use of flood risk maps as a central tool in understanding and communicating flood risk. Following recent flooding in England, an urgent need to integrate people living at risk from flooding into flood management approaches, encouraging flood resilience and the up-take of resilient activities has been acknowledged. The effective communication of flood risk information plays a major role in allowing those at risk to make effective decisions about flood risk and increase their resilience, however, there are emerging concerns over the effectiveness of current approaches. The research presented explores current approaches to flood risk communication in England and the effectiveness of these methods in encouraging resilient actions before and during flooding events. The research also investigates how flood risk communications could be undertaken more effectively, using a novel participatory framework to integrate the perspectives of those living at risk. The research uses co-production between local communities and researchers in the environmental sciences, using a participatory framework to bring together local knowledge of flood risk and flood communications. Using a local competency group, the research explores what those living at risk from flooding want from flood communications in order to develop new approaches to help those at risk understand and respond to floods. Suggestions for practice are refined by the communities to co-produce recommendations. The research finds that current approaches to real-time flood risk communication fail to forecast the significance of predicted floods, whilst flood maps lack detailed information about how floods occur, or use scientific terminology which people at risk find confusing or lacking in realistic grounding. This means users do not have information they find useful to make informed decisions about how to prepare for and respond to floods. Working together with at-risk participants, the research has developed new approaches for communicating flood risk. These approaches focus on understanding flood mechanisms and dynamics, to help participants imagine their flood risk and link potential scenarios to reality, and provide forecasts of predicted flooding at a variety of scales, allowing participants to assess the significance of predicted flooding and make more informed judgments on what action to take in response. The findings presented have significant implications for the way in which flood risk is communicated, changing the focus of mapping from probabilistic future scenarios to understanding flood dynamics and mechanisms. Such ways of communicating flood risk embrace how people would like to see risk communicated, and help those at risk grow their resilience. Communicating in such a way has wider implications for flood modelling and data collection. However, these represent potential opportunities to build more effective local partnerships for assessing and managing flood risks.

Effects of temperature and salinity on the growth of Alexandrium (Dinophyceae) isolates from the Salish Sea

PubMed Central

Bill, Brian D.; Moore, Stephanie K.; Hay, Levi R.; Anderson, Donald M.; Trainer, Vera L.

2016-01-01

Toxin-producing blooms of dinoflagellates in the genus Alexandrium have plagued the inhabitants of the Salish Sea for centuries. Yet the environmental conditions that promote accelerated growth of this organism, a producer of paralytic shellfish toxins, is lacking. This study quantitatively determined the growth response of two Alexandrium isolates to a range of temperatures and salinities, factors that will strongly respond to future climate change scenarios. An empirical equation, derived from observed growth rates describing the temperature and salinity dependence of growth, was used to hindcast bloom risk. Hindcasting was achieved by comparing predicted growth rates, calculated from in situ temperature and salinity data from Quartermaster Harbor, with corresponding Alexandrium cell counts and shellfish toxin data. The greatest bloom risk, defined at μ>0.25 d−1, generally occurred from April through November annually; however, growth rates rarely fell below 0.10 d−1. Except for a few occasions, Alexandrium cells were only observed during the periods of highest bloom risk and paralytic shellfish toxins above the regulatory limit always fell within the periods of predicted bloom occurrence. While acknowledging that Alexandrium growth rates are affected by other abiotic and biotic factors, such as grazing pressure and nutrient availability, the use of this empirical growth function to predict higher risk time frames for blooms and toxic shellfish within the Salish Sea provides the groundwork for a more comprehensive biological model of Alexandrium bloom dynamics in the region and will enhance our ability to forecast blooms in the Salish Sea under future climate change scenarios. PMID:27037588

Predicting Vulnerabilities of North American Shorebirds to Climate Change

PubMed Central

Galbraith, Hector; DesRochers, David W.; Brown, Stephen; Reed, J. Michael

2014-01-01

Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at–risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners–in–Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90%) taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower–risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change. PMID:25268907

Predicting vulnerabilities of North American shorebirds to climate change.

PubMed

Galbraith, Hector; DesRochers, David W; Brown, Stephen; Reed, J Michael

2014-01-01

Despite an increase in conservation efforts for shorebirds, there are widespread declines of many species of North American shorebirds. We wanted to know whether these declines would be exacerbated by climate change, and whether relatively secure species might become at-risk species. Virtually all of the shorebird species breeding in the USA and Canada are migratory, which means climate change could affect extinction risk via changes on the breeding, wintering, and/or migratory refueling grounds, and that ecological synchronicities could be disrupted at multiple sites. To predict the effects of climate change on shorebird extinction risks, we created a categorical risk model complementary to that used by Partners-in-Flight and the U.S. Shorebird Conservation Plan. The model is based on anticipated changes in breeding, migration, and wintering habitat, degree of dependence on ecological synchronicities, migration distance, and degree of specialization on breeding, migration, or wintering habitat. We evaluated 49 species, and for 3 species we evaluated 2 distinct populations each, and found that 47 (90%) taxa are predicted to experience an increase in risk of extinction. No species was reclassified into a lower-risk category, although 6 species had at least one risk factor decrease in association with climate change. The number of species that changed risk categories in our assessment is sensitive to how much of an effect of climate change is required to cause the shift, but even at its least sensitive, 20 species were at the highest risk category for extinction. Based on our results it appears that shorebirds are likely to be highly vulnerable to climate change. Finally, we discuss both how our approach can be integrated with existing risk assessments and potential future directions for predicting change in extinction risk due to climate change.

Are Risky Youth Less Protectable As They Age? The Dynamics of Protection During Adolescence and Young Adulthood

PubMed Central

Krohn, Marvin D.; Lizotte, Alan J.; Phillips, Matthew D.; Schmidt, Nicole M.

2013-01-01

Research on recidivism in criminal justice and desistance in criminology are not integrated. Yet, both fields seem to be moving towards models that look at how positive elements in a person's environment can impact a person's behavior, conditional on different levels of risk. This study builds on this observation by applying interactional theory and the concept of Risk-Needs-Responsivity to theorize that both Needs and Responsivity will change over time in predictable ways. We then use a novel empirical approach with the Rochester Youth Development Study to show that even in late adolescence, individuals who are at risk for violence can be protected from future violence and risky behavior like gun carrying with positive events in their environment and personal life. In young adulthood, fewer people are still at risk for violence, and those who are at risk are harder to protect from future violence and gun carrying. PMID:24363492

Whom to treat? The contribution of vertebral X-rays to risk-based algorithms for fracture prediction. Results from the European Prospective Osteoporosis Study.

PubMed

Kaptoge, S; Armbrecht, G; Felsenberg, D; Lunt, M; Weber, K; Boonen, S; Jajic, I; Stepan, J J; Banzer, D; Reisinger, W; Janott, J; Kragl, G; Scheidt-Nave, C; Felsch, B; Matthis, C; Raspe, H H; Lyritis, G; Póor, G; Nuti, R; Miazgowski, T; Hoszowski, K; Armas, J Bruges; Vaz, A Lopes; Benevolenskaya, L I; Masaryk, P; Cannata, J B; Johnell, O; Reid, D M; Bhalla, A; Woolf, A D; Todd, C J; Cooper, C; Eastell, R; Kanis, J A; O'Neill, T W; Silman, A J; Reeve, J

2006-01-01

Vertebral fracture is a strong risk factor for future spine and hip fractures; yet recent data suggest that only 5-20% of subjects with a spine fracture are identified in primary care. We aimed to develop easily applicable algorithms predicting a high risk of future spine fracture in men and women over 50 years of age. Data was analysed from 5,561 men and women aged 50+ years participating in the European Prospective Osteoporosis Study (EPOS). Lateral thoracic and lumbar spine radiographs were taken at baseline and at an average of 3.8 years later. These were evaluated by an experienced radiologist. The risk of a new (incident) vertebral fracture was modelled as a function of age, number of prevalent vertebral fractures, height loss, sex and other fracture history reported by the subject, including limb fractures occurring between X-rays. Receiver Operating Characteristic (ROC) curves were used to compare the predictive ability of models. In a negative binomial regression model without baseline X-ray data, the risk of incident vertebral fracture significantly increased with age [RR 1.74, 95% CI (1.44, 2.10) per decade], height loss [1.08 (1.04, 1.12) per cm decrease], female sex [1.48 (1.05, 2.09)], and recalled fracture history; [1.65 (1.15, 2.38) to 3.03 (1.66, 5.54)] according to fracture site. Baseline radiological assessment of prevalent vertebral fracture significantly improved the areas subtended by ROC curves from 0.71 (0.67, 0.74) to 0.74 (0.70, 0.77) P=0.013 for predicting 1+ incident fracture; and from 0.74 (0.67, 0.81) to 0.83 (0.76, 0.90) P=0.001 for 2+ incident fractures. Age, sex and height loss remained independently predictive. The relative risk of a new vertebral fracture increased with the number of prevalent vertebral fractures present from 3.08 (2.10, 4.52) for 1 fracture to 9.36 (5.72, 15.32) for 3+. At a specificity of 90%, the model including X-ray data improved the sensitivity for predicting 2+ and 1+ incident fractures by 6 and 4 fold respectively compared with random guessing. At 75% specificity the improvements were 3.2 and 2.4 fold respectively. With the modelling restricted to the subjects who had BMD measurements (n=2,409), the AUC for predicting 1+ vs. 0 incident vertebral fractures improved from 0.72 (0.66, 0.79) to 0.76 (0.71, 0.82) upon adding femoral neck BMD (P=0.010). We conclude that for those with existing vertebral fractures, an accurately read spine X-ray will form a central component in future algorithms for targeting treatment, especially to the most vulnerable. The sensitivity of this approach to identifying vertebral fracture cases requiring anti-osteoporosis treatment, even when X-rays are ordered highly selectively, exceeds by a large margin the current standard of practice as recorded anywhere in the world.

Baseline dental plaque activity, mutans streptococci culture, and future caries experience in children.

PubMed

Hallett, Kerrod B; O'Rourke, Peter K

2013-01-01

The purpose of this study was to evaluate a chairside caries risk assessment protocol utilizing a caries prediction instrument, adenosine triphosphate (ATP) activity in dental plaque, mutans streptococci (MS) culture, and routine dental examination in five- to 10-year-old children at two regional Australian schools with high caries experience. Clinical indicators for future caries were assessed at baseline examination using a standardized prediction instrument. Plaque ATP activity was measured directly in relative light units (RLU) using a bioluminescence meter, and MS culture data were recorded. Each child's dentition was examined clinically and radiographically, and caries experience was recorded using enamel white spot lesions and decayed, missing, and filled surfaces for primary and permanent teeth indices. Univariate one-way analysis of variance between selected clinical indicators, ATP activity, MS count at baseline, and future new caries activity was performed, and a generalized linear model for prediction of new caries activity at 24 months was constructed. Future new caries activity was significantly associated with the presence of visible cavitations, reduced saliva flow, and orthodontic appliances at baseline (R(2)=0.2, P<.001). Baseline plaque adenosine triphosphate activity and mutans streptococci counts were not significantly associated with caries activity at 24 months.

Which forms of child/adolescent externalizing behaviors account for late adolescent risky sexual behavior and substance use?

PubMed

Timmermans, Maartje; van Lier, Pol A C; Koot, Hans M

2008-04-01

Health risk behaviors like substance use (alcohol, tobacco, soft/hard drugs) and risky sexual behavior become more prevalent in adolescence. Children with behavior problems are thought to be prone to engage in health risk behaviors later in life. It is, however, unclear which problems within the externalizing spectrum account for these outcomes. Three hundred and nine children were followed from age 4/5 years to 18 years (14-year follow-up). Level and course of parent-rated opposition, physical aggression, status violations and property violations were used to predict adolescent-reported substance use and risky sexual behavior at age 18 years. Both level and change in physical aggression were unique predictors of all forms of adolescent health risk behavior. Levels of status violations predicted smoking and soft drug use only, while change in property violations predicted each of the health risk behaviors. The links between opposition and health risk behaviors were accounted for by co-occurring problem behaviors. Of externalizing problems, physical aggression is the best predictor of adolescent substance use and risky sexual behavior from childhood onwards. Possible explanations and implications of these findings, and future research directions are discussed.

The PRONE score: an algorithm for predicting doctors’ risks of formal patient complaints using routinely collected administrative data

PubMed Central

Spittal, Matthew J; Bismark, Marie M; Studdert, David M

2015-01-01

Background Medicolegal agencies—such as malpractice insurers, medical boards and complaints bodies—are mostly passive regulators; they react to episodes of substandard care, rather than intervening to prevent them. At least part of the explanation for this reactive role lies in the widely recognised difficulty of making robust predictions about medicolegal risk at the individual clinician level. We aimed to develop a simple, reliable scoring system for predicting Australian doctors’ risks of becoming the subject of repeated patient complaints. Methods Using routinely collected administrative data, we constructed a national sample of 13 849 formal complaints against 8424 doctors. The complaints were lodged by patients with state health service commissions in Australia over a 12-year period. We used multivariate logistic regression analysis to identify predictors of subsequent complaints, defined as another complaint occurring within 2 years of an index complaint. Model estimates were then used to derive a simple predictive algorithm, designed for application at the doctor level. Results The PRONE (Predicted Risk Of New Event) score is a 22-point scoring system that indicates a doctor's future complaint risk based on four variables: a doctor's specialty and sex, the number of previous complaints and the time since the last complaint. The PRONE score performed well in predicting subsequent complaints, exhibiting strong validity and reliability and reasonable goodness of fit (c-statistic=0.70). Conclusions The PRONE score appears to be a valid method for assessing individual doctors’ risks of attracting recurrent complaints. Regulators could harness such information to target quality improvement interventions, and prevent substandard care and patient dissatisfaction. The approach we describe should be replicable in other agencies that handle large numbers of patient complaints or malpractice claims. PMID:25855664

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

PubMed

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

2014-08-01

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

The predictive validity of common risk assessment tools in men with intellectual disabilities and problematic sexual behaviors.

PubMed

Fedoroff, J Paul; Richards, Deborah; Ranger, Rebekah; Curry, Susan

2016-10-01

This CIHR-funded study examined whether certain current risk assessment tools were effective in appraising risk of recidivism in a sample of sex offenders with intellectual disabilities (ID). Fifty men with ID who had engaged in problematic sexual behavior (PSB) were followed for an average of 2.5 years. Recidivism was defined and measured as any illegal or problematic behavior, as well as any problematic but not necessarily illegal behavior. At the beginning of the study, each participant was rated on two risk assessment tools: the Violence Risk Appraisal Guide (VRAG) and the Sex Offender Risk Appraisal Guide (SORAG). During each month of follow-up, participants were also rated on the Short-Dynamic Risk Scale (SDRS), an assessment tool intended to measure the risk of future problematic behaviors. Data was analyzed using t-tests, Cohen's d and area under the curve (AUC) to test predictive validity of the assessment tools. Using the AUC, results showed that the VRAG was predictive of sexual (AUC=0.74), sexual and/or violent (AUC=0.71) and of any criminally chargeable event (AUC=0.69). The SORAG was only significantly predictive of sexual events (AUC=0.70) and the SDRS was predictive of violent events (AUC=0.71). The t-test and Cohen's d analyses, which are less robust to deviations from the assumptions of normal and continuous distribution than AUC, did not yield significant results in each category, and therefore, while the results of this study suggest that the VRAG and the SORAG may be effective tools in measuring the short term risk of sexual recidivism; and the VRAG and SDRS may be effective tools in appraising long term risk of sexual and/or violent recidivism in this population, it should be used with caution. Regardless of the assessment tool used, risk assessments should take into account the differences between sex offenders with and without ID to ensure effective measurement. Copyright © 2016. Published by Elsevier Ltd.

Comparison between frailty index of deficit accumulation and fracture risk assessment tool (FRAX) in prediction of risk of fractures.

PubMed

Li, Guowei; Thabane, Lehana; Papaioannou, Alexandra; Adachi, Jonathan D

2015-08-01

A frailty index (FI) of deficit accumulation could quantify and predict the risk of fractures based on the degree of frailty in the elderly. We aimed to compare the predictive powers between the FI and the fracture risk assessment tool (FRAX) in predicting risk of major osteoporotic fracture (hip, upper arm or shoulder, spine, or wrist) and hip fracture, using the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort. There were 3985 women included in the study, with the mean age of 69.4 years (standard deviation [SD] = 8.89). During the follow-up, there were 149 (3.98%) incident major osteoporotic fractures and 18 (0.48%) hip fractures reported. The FRAX and FI were significantly related to each other. Both FRAX and FI significantly predicted risk of major osteoporotic fracture, with a hazard ratio (HR) of 1.03 (95% confidence interval [CI]: 1.02-1.05) and 1.02 (95% CI: 1.01-1.04) for per-0.01 increment for the FRAX and FI respectively. The HRs were 1.37 (95% CI: 1.19-1.58) and 1.26 (95% CI: 1.12-1.42) for an increase of per-0.10 (approximately one SD) in the FRAX and FI respectively. Similar discriminative ability of the models was found: c-index = 0.62 for the FRAX and c-index = 0.61 for the FI. When cut-points were chosen to trichotomize participants into low-risk, medium-risk and high-risk groups, a significant increase in fracture risk was found in the high-risk group (HR = 2.04, 95% CI: 1.36-3.07) but not in the medium-risk group (HR = 1.23, 95% CI: 0.82-1.84) compared with the low-risk women for the FI, while for FRAX the medium-risk (HR = 2.00, 95% CI: 1.09-3.68) and high-risk groups (HR = 2.61, 95% CI: 1.48-4.58) predicted risk of major osteoporotic fracture significantly only when survival time exceeded 18months (550 days). Similar findings were observed for hip fracture and in sensitivity analyses. In conclusion, the FI is comparable with FRAX in the prediction of risk of future fractures, indicating that measures of frailty status may aid in fracture risk assessment and fracture prevention in the elderly. Further evidence from randomized controlled trials of osteoporosis medication interventions is needed to support the FI and FRAX as validated measures of fracture risk. Copyright © 2015 Elsevier Inc. All rights reserved.

Comparison between frailty index of deficit accumulation and fracture risk assessment tool (FRAX) in prediction of risk of fractures

PubMed Central

Li, Guowei; Thabane, Lehana; Papaioannou, Alexandra; Adachi, Jonathan D.

2016-01-01

A frailty index (FI) of deficit accumulation could quantify and predict the risk of fractures based on the degree of frailty in the elderly. We aimed to compare the predictive powers between the FI and the fracture risk assessment tool (FRAX) in predicting risk of major osteoporotic fracture (hip, upper arm or shoulder, spine, or wrist) and hip fracture, using the data from the Global Longitudinal Study of Osteoporosis in Women (GLOW) 3-year Hamilton cohort. There were 3985 women included in the study, with the mean age of 69.4 years (standard deviation [SD] = 8.89). During the follow-up, there were 149 (3.98%) incident major osteoporotic fractures and 18 (0.48%) hip fractures reported. The FRAX and FI were significantly related to each other. Both FRAX and FI significantly predicted risk of major osteoporotic fracture, with a hazard ratio (HR) of 1.03 (95% confidence interval [CI]: 1.02–1.05) and 1.02 (95% CI: 1.01–1.04) for per-0.01 increment for the FRAX and FI respectively. The HRs were 1.37 (95% CI: 1.19–1.58) and 1.26 (95% CI: 1.12–1.42) for an increase of per-0.10 (approximately one SD) in the FRAX and FI respectively. Similar discriminative ability of the models was found: c-index = 0.62 for the FRAX and c-index = 0.61 for the FI. When cut-points were chosen to trichotomize participants into low-risk, medium-risk and high-risk groups, a significant increase in fracture risk was found in the high-risk group (HR = 2.04, 95% CI: 1.36–3.07) but not in the medium-risk group (HR = 1.23, 95% CI: 0.82–1.84) compared with the low-risk women for the FI, while for FRAX the medium-risk (HR = 2.00, 95% CI: 1.09–3.68) and high-risk groups (HR = 2.61, 95% CI: 1.48–4.58) predicted risk of major osteoporotic fracture significantly only when survival time exceeded 18 months (550 days). Similar findings were observed for hip fracture and in sensitivity analyses. In conclusion, the FI is comparable with FRAX in the prediction of risk of future fractures, indicating that measures of frailty status may aid in fracture risk assessment and fracture prevention in the elderly. Further evidence from randomized controlled trials of osteoporosis medication interventions is needed to support the FI and FRAX as validated measures of fracture risk. PMID:25916552

Use of a Short-Form Balance Confidence Scale to Predict Future Recurrent Falls in People With Parkinson Disease.

PubMed

Cole, Michael H; Rippey, Jodi; Naughton, Geraldine A; Silburn, Peter A

2016-01-01

To assess whether the 16-item Activities-specific Balance Confidence scale (ABC-16) and short-form 6-item Activities-specific Balance Confidence scale (ABC-6) could predict future recurrent falls in people with Parkinson disease (PD) and to validate the robustness of their predictive capacities. Twelve-month prospective cohort study. General community. People with idiopathic PD (N=79). Clinical tests were conducted to assess symptom severity, balance confidence, and medical history. Over the subsequent 12 months, participants recorded any falls on daily fall calendars, which they returned monthly by reply paid post. Logistic regression and receiver operating characteristic analyses estimated the sensitivities and specificities of the ABC-16 and ABC-6 for predicting future recurrent falls in this cohort, and "leave-one-out" validation was used to assess their robustness. Of the 79 patients who completed follow-up, 28 (35.4%) fell more than once during the 12-month period. Both the ABC-16 and ABC-6 were significant predictors of future recurrent falls, and moderate sensitivities (ABC-16: 75.0%; ABC-6: 71.4%) and specificities (ABC-16: 76.5%; ABC-6: 74.5%) were reported for each tool for a cutoff score of 77.5 and 65.8, respectively. The results have significant implications and demonstrate that the ABC-16 and ABC-6 independently identify patients with PD at risk of future recurrent falls. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

NASA Earned Value Management (EVM) Update

NASA Technical Reports Server (NTRS)

Kerby, Jerald

2013-01-01

Earned Value Management (EVM) is an integrated management control system for assessing, understanding and qualifying what a project is achieving with the resoures. EVM integrates technical cost and schedules with risk management. It allows objective assessment and quantification of current project performance, and helps predict future performance-based trents.

Coming Attractions.

ERIC Educational Resources Information Center

Datta, Lois-Ellin

2001-01-01

Forecasts the future of evaluation, predicting an era of stability or expansion for the profession, with increased communication among evaluators and a flowering of evaluation theories. Among the unknowns that give pause are the possibility of underprepared users and the risks of promising more than can be delivered. Some suggestions are made for…

Pregnancy-associated plasma protein-A is a stronger predictor for adverse cardiovascular outcomes after acute coronary syndrome in type-2 diabetes mellitus.

PubMed

Li, Wei-Ping; Neradilek, Moni B; Gu, Fu-Sheng; Isquith, Daniel A; Sun, Zhi-Jun; Wu, Xing; Li, Hong-Wei; Zhao, Xue-Qiao

2017-04-05

The risk prediction of pregnancy-associated plasma protein-A (PAPP-A) for future cardiovascular (CV) events post acute coronary syndrome (ACS) in patients with type-2 diabetes mellitus (T2DM) was investigated in comparison to other risk factors. PAPP-A was measured at hospital admission in 320 consecutive ACS patients (136 with T2DM and 184 without). All patients were followed for 2 years for occurrence of CV death, non-fatal MI or stroke. Effect of PAPP-A on the CV event risk was estimated using Cox regression models. Receiver operating characteristics (ROC) curves were generated to demonstrate the sensitivity and specificity of PAPP-A in predicting CV events. ACS patients with T2DM had higher PAPP-A (19.29 ± 16.36 vs. 13.29 ± 13.90 ng/ml, p < 0.001) and higher rate of CV events 2 years post ACS (27.2 vs. 13.6%, p = 0.002) than those without. Higher levels of PAPP-A were significantly associated with increased risk of CV events during 2-year follow-up [HR = 2.97 for 1 SD increase in log 10 (PAPP-A), 95% CI 2.11-4.18, p < 0.001] in T2DM and (HR = 3.16, 95% CI 2.27-4.39, p < 0.001) in non-T2DM. Among patients with T2DM, PAPP-A showed a larger area under the curve (AUC 0.79) that was significantly more predictive than hsCRP (AUC 0.64), eGFR (AUC 0.66) and LVEF < 50% (AUC 0.52); predictive ability did not improve significantly by including those factors into the model. Patients with T2DM had higher levels of PAPP-A and increased risk of CV events. Elevated PAPP-A compared to other risk factors was a stronger predictor for future CV events 2 years post ACS in patients with T2DM. Trial registration ISRCTN10805074. Registered on 20 January 2017, retrospectively registered.

Predicting suicide with the SAD PERSONS scale.

PubMed

Katz, Cara; Randall, Jason R; Sareen, Jitender; Chateau, Dan; Walld, Randy; Leslie, William D; Wang, JianLi; Bolton, James M

2017-09-01

Suicide is a major public health issue, and a priority requirement is accurately identifying high-risk individuals. The SAD PERSONS suicide risk assessment scale is widely implemented in clinical settings despite limited supporting evidence. This article aims to determine the ability of the SAD PERSONS scale (SPS) to predict future suicide in the emergency department. Five thousand four hundred sixty-two consecutive adults were seen by psychiatry consultation teams in two tertiary emergency departments with linkage to population-based administrative data to determine suicide deaths within 6 months, 1, and 5 years. Seventy-seven (1.4%) individuals died by suicide during the study period. When predicting suicide at 12 months, medium- and high-risk scores on SPS had a sensitivity of 49% and a specificity of 60%; the positive and negative predictive values were 0.9 and 99%, respectively. Half of the suicides at both 6- and 12-month intervals were classified as low risk by SPS at index visit. The area under the curve at 12 months for the Modified SPS was 0.59 (95% confidence interval [CI] range 0.51-0.67). High-risk scores (compared to low risk) were significantly associated with death by suicide over the 5-year study period using the SPS (hazard ratio 2.49; 95% CI 1.34-4.61) and modified version (hazard ratio 2.29; 95% CI 1.24-2.29). Although widely used in educational and clinical settings, these findings do not support the use of the SPS and Modified SPS to predict suicide in adults seen by psychiatric services in the emergency department. © 2017 Wiley Periodicals, Inc.

Predicting Financial Distress and Closure in Rural Hospitals.

PubMed

Holmes, George M; Kaufman, Brystana G; Pink, George H

2017-06-01

Annual rates of rural hospital closure have been increasing since 2010, and hospitals that close have poor financial performance relative to those that remain open. This study develops and validates a latent index of financial distress to forecast the probability of financial distress and closure within 2 years for rural hospitals. Hospital and community characteristics are used to predict the risk of financial distress 2 years in the future. Financial and community data were drawn for 2,466 rural hospitals from 2000 through 2013. We tested and validated a model predicting a latent index of financial distress (FDI), measured by unprofitability, equity decline, insolvency, and closure. Using the predicted FDI score, hospitals are assigned to high, medium-high, medium-low, and low risk of financial distress for use by practitioners. The FDI forecasts 8.01% of rural hospitals to be at high risk of financial distress in 2015, 16.3% as mid-high, 46.8% as mid-low, and 28.9% as low risk. The rate of closure for hospitals in the high-risk category is 4 times the rate in the mid-high category and 28 times that in the mid-low category. The ability of the FDI to discriminate hospitals experiencing financial distress is supported by a c-statistic of .74 in a validation sample. This methodology offers improved specificity and predictive power relative to existing measures of financial distress applied to rural hospitals. This risk assessment tool may inform programs at the federal, state, and local levels that provide funding or support to rural hospitals. © 2016 National Rural Health Association.

Risk approximation in decision making: approximative numeric abilities predict advantageous decisions under objective risk.

PubMed

Mueller, Silke M; Schiebener, Johannes; Delazer, Margarete; Brand, Matthias

2018-01-22

Many decision situations in everyday life involve mathematical considerations. In decisions under objective risk, i.e., when explicit numeric information is available, executive functions and abilities to handle exact numbers and ratios are predictors of objectively advantageous choices. Although still debated, exact numeric abilities, e.g., normative calculation skills, are assumed to be related to approximate number processing skills. The current study investigates the effects of approximative numeric abilities on decision making under objective risk. Participants (N = 153) performed a paradigm measuring number-comparison, quantity-estimation, risk-estimation, and decision-making skills on the basis of rapid dot comparisons. Additionally, a risky decision-making task with exact numeric information was administered, as well as tasks measuring executive functions and exact numeric abilities, e.g., mental calculation and ratio processing skills, were conducted. Approximative numeric abilities significantly predicted advantageous decision making, even beyond the effects of executive functions and exact numeric skills. Especially being able to make accurate risk estimations seemed to contribute to superior choices. We recommend approximation skills and approximate number processing to be subject of future investigations on decision making under risk.

Chemical Risk Assessment: Traditional vs Public Health Perspectives

PubMed Central

Axelrad, Daniel A.; Bahadori, Tina; Bussard, David; Cascio, Wayne E.; Deener, Kacee; Dix, David; Thomas, Russell S.; Kavlock, Robert J.; Burke, Thomas A.

2017-01-01

Preventing adverse health effects of environmental chemical exposure is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and effects of environmentally induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Considering these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease. PMID:28520487

Sexual Behaviors of US Women at Risk of HIV Acquisition: A Longitudinal Analysis of Findings from HPTN 064.

PubMed

Justman, J; Befus, M; Hughes, J; Wang, J; Golin, C E; Adimora, A A; Kuo, I; Haley, D F; Del Rio, C; El-Sadr, W M; Rompalo, A; Mannheimer, S; Soto-Torres, L; Hodder, S

2015-07-01

We describe the sexual behaviors of women at elevated risk of HIV acquisition who reside in areas of high HIV prevalence and poverty in the US. Participants in HPTN 064, a prospective HIV incidence study, provided information about individual sexual behaviors and male sexual partners in the past 6 months at baseline, 6- and 12-months. Independent predictors of consistent or increased temporal patterns for three high-risk sexual behaviors were assessed separately: exchange sex, unprotected anal intercourse (UAI) and concurrent partnerships. The baseline prevalence of each behavior was >30 % among the 2,099 participants, 88 % reported partner(s) with >1 HIV risk characteristic and both individual and partner risk characteristics decreased over time. Less than high school education and food insecurity predicted consistent/increased engagement in exchange sex and UAI, and partner's concurrency predicted participant concurrency. Our results demonstrate how interpersonal and social factors may influence sustained high-risk behavior by individuals and suggest that further study of the economic issues related to HIV risk could inform future prevention interventions.

The joint effects of risk status, gender, early literacy and cognitive skills on the presence of dyslexia among a group of high-risk Chinese children.

PubMed

Wong, Simpson W L; McBride-Chang, Catherine; Lam, Catherine; Chan, Becky; Lam, Fanny W F; Doo, Sylvia

2012-02-01

This study sought to examine factors that are predictive of future developmental dyslexia among a group of 5-year-old Chinese children at risk for dyslexia, including 62 children with a sibling who had been previously diagnosed with dyslexia and 52 children who manifested clinical at-risk factors in aspects of language according to testing by paediatricians. The age-5 performances on various literacy and cognitive tasks, gender and group status (familial risk or language delayed) were used to predict developmental dyslexia 2 years later using logistic regression analysis. Results showed that greater risk of dyslexia was related to slower rapid automatized naming, lower scores on morphological awareness, Chinese character recognition and English letter naming, and gender (boys had more risk). Three logistic equations were generated for estimating individual risk of dyslexia. The strongest models were those that included all print-related variables (including speeded number naming, character recognition and letter identification) and gender, with about 70% accuracy or above. Early identification of those Chinese children at risk for dyslexia can facilitate better dyslexia risk management. Copyright © 2012 John Wiley & Sons, Ltd.

Differing predictive relationships between baseline LDL-C, systolic blood pressure, and cardiovascular outcomes.

PubMed

Deedwania, Prakash C; Pedersen, Terje R; DeMicco, David A; Breazna, Andrei; Betteridge, D John; Hitman, Graham A; Durrington, Paul; Neil, Andrew

2016-11-01

Traditional cardiovascular risk factors, such as hypertension and dyslipidemia, predispose individuals to cardiovascular disease, particularly patients with diabetes. We investigated the predictive value of baseline systolic blood pressure (SBP) and low-density lipoprotein cholesterol (LDL-C) on the risk of vascular outcomes in a large population of patients at high risk of future cardiovascular events. Data were pooled from the TNT (Treating to New Targets), CARDS (Collaborative Atorvastatin Diabetes Study), and IDEAL (Incremental Decrease in End-Points Through Aggressive Lipid Lowering) trials and included a total of 21,727 patients (TNT: 10,001; CARDS: 2838; IDEAL: 8888). The effect of baseline SBP and LDL-C on cardiovascular events, coronary events, and stroke was evaluated using a multivariate Cox proportional-hazards model. Overall, risk of cardiovascular events was significantly higher for patients with higher baseline SBP or LDL-C. Higher baseline SBP was significantly predictive of stroke but not coronary events. Conversely, higher baseline LDL-C was significantly predictive of coronary events but not stroke. Results from the subgroup with diabetes (5408 patients; TNT: 1501; CARDS: 2838; IDEAL: 1069) were broadly consistent with those of the total cohort: baseline SBP and LDL-C were significantly predictive of cardiovascular events overall, with the association to LDL-C predominantly related to an effect on coronary events. However, baseline SBP was not predictive of either coronary or stroke events in the pooled diabetic population. In this cohort of high-risk patients, baseline SBP and LDL-C were significantly predictive of cardiovascular outcomes, but this effect may differ between the cerebrovascular and coronary systems. NCT00327691 (TNT); NCT00327418 (CARDS); NCT00159835 (IDEAL). Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Predicting Rib Fracture Risk With Whole-Body Finite Element Models: Development and Preliminary Evaluation of a Probabilistic Analytical Framework

PubMed Central

Forman, Jason L.; Kent, Richard W.; Mroz, Krystoffer; Pipkorn, Bengt; Bostrom, Ola; Segui-Gomez, Maria

2012-01-01

This study sought to develop a strain-based probabilistic method to predict rib fracture risk with whole-body finite element (FE) models, and to describe a method to combine the results with collision exposure information to predict injury risk and potential intervention effectiveness in the field. An age-adjusted ultimate strain distribution was used to estimate local rib fracture probabilities within an FE model. These local probabilities were combined to predict injury risk and severity within the whole ribcage. The ultimate strain distribution was developed from a literature dataset of 133 tests. Frontal collision simulations were performed with the THUMS (Total HUman Model for Safety) model with four levels of delta-V and two restraints: a standard 3-point belt and a progressive 3.5–7 kN force-limited, pretensioned (FL+PT) belt. The results of three simulations (29 km/h standard, 48 km/h standard, and 48 km/h FL+PT) were compared to matched cadaver sled tests. The numbers of fractures predicted for the comparison cases were consistent with those observed experimentally. Combining these results with field exposure informantion (ΔV, NASS-CDS 1992–2002) suggests a 8.9% probability of incurring AIS3+ rib fractures for a 60 year-old restrained by a standard belt in a tow-away frontal collision with this restraint, vehicle, and occupant configuration, compared to 4.6% for the FL+PT belt. This is the first study to describe a probabilistic framework to predict rib fracture risk based on strains observed in human-body FE models. Using this analytical framework, future efforts may incorporate additional subject or collision factors for multi-variable probabilistic injury prediction. PMID:23169122

On the association between sexual attraction and adolescent risk behavior involvement: Examining mediation and moderation.

PubMed

Busseri, Michael A; Willoughby, Teena; Chalmers, Heather; Bogaert, Anthony F

2008-01-01

On the basis of a large-scale survey of high-school youth, the authors compared adolescents reporting exclusively heterosexual, mostly heterosexual, bisexual, and predominately same-sex attraction based on high-risk involvement across a range of risk behaviors. Bisexual and same-sex attracted groups were characterized by heightened high-risk involvement relative to the other two groups. Mediation analysis was used to determine whether these group disparities were explained by a set of normative predictive factors spanning multiple life domains. Differences among a combined exclusively/mostly heterosexual attraction group and both the bisexual and same-sex attraction groups were attenuated (66% and 50%, respectively) after incorporating the hypothesized intervening predictive factors, providing evidence of partial mediation. Primary mediators included intrapersonal (attitudes toward risk-taking; academic orientation), interpersonal (peer victimization; parental relationships; unstructured activities), and environmental (substance availability) factors. Mediation results were consistent across participant age and sex. Implications, limitations, and directions for future research are discussed. Copyright (c) 2008 APA.

Increasing Potential Risk of a Global Aquatic Invader in Europe in Contrast to Other Continents under Future Climate Change

PubMed Central

Liu, Xuan; Guo, Zhongwei; Ke, Zunwei; Wang, Supen; Li, Yiming

2011-01-01

Background Anthropogenically-induced climate change can alter the current climatic habitat of non-native species and can have complex effects on potentially invasive species. Predictions of the potential distributions of invasive species under climate change will provide critical information for future conservation and management strategies. Aquatic ecosystems are particularly vulnerable to invasive species and climate change, but the effect of climate change on invasive species distributions has been rather neglected, especially for notorious global invaders. Methodology/Principal Findings We used ecological niche models (ENMs) to assess the risks and opportunities that climate change presents for the red swamp crayfish (Procambarus clarkii), which is a worldwide aquatic invasive species. Linking the factors of climate, topography, habitat and human influence, we developed predictive models incorporating both native and non-native distribution data of the crayfish to identify present areas of potential distribution and project the effects of future climate change based on a consensus-forecast approach combining the CCCMA and HADCM3 climate models under two emission scenarios (A2a and B2a) by 2050. The minimum temperature from the coldest month, the human footprint and precipitation of the driest quarter contributed most to the species distribution models. Under both the A2a and B2a scenarios, P. clarkii shifted to higher latitudes in continents of both the northern and southern hemispheres. However, the effect of climate change varied considerately among continents with an expanding potential in Europe and contracting changes in others. Conclusions/Significance Our findings are the first to predict the impact of climate change on the future distribution of a globally invasive aquatic species. We confirmed the complexities of the likely effects of climate change on the potential distribution of globally invasive species, and it is extremely important to develop wide-ranging and effective control measures according to predicted geographical shifts and changes. PMID:21479188

Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation.

PubMed

Teschendorff, Andrew E; Jones, Allison; Fiegl, Heidi; Sargent, Alexandra; Zhuang, Joanna J; Kitchener, Henry C; Widschwendter, Martin

2012-03-27

Recently, it has been proposed that epigenetic variation may contribute to the risk of complex genetic diseases like cancer. We aimed to demonstrate that epigenetic changes in normal cells, collected years in advance of the first signs of morphological transformation, can predict the risk of such transformation. We analyzed DNA methylation (DNAm) profiles of over 27,000 CpGs in cytologically normal cells of the uterine cervix from 152 women in a prospective nested case-control study. We used statistics based on differential variability to identify CpGs associated with the risk of transformation and a novel statistical algorithm called EVORA (Epigenetic Variable Outliers for Risk prediction Analysis) to make predictions. We observed many CpGs that were differentially variable between women who developed a non-invasive cervical neoplasia within 3 years of sample collection and those that remained disease-free. These CpGs exhibited heterogeneous outlier methylation profiles and overlapped strongly with CpGs undergoing age-associated DNA methylation changes in normal tissue. Using EVORA, we demonstrate that the risk of cervical neoplasia can be predicted in blind test sets (AUC = 0.66 (0.58 to 0.75)), and that assessment of DNAm variability allows more reliable identification of risk-associated CpGs than statistics based on differences in mean methylation levels. In independent data, EVORA showed high sensitivity and specificity to detect pre-invasive neoplasia and cervical cancer (AUC = 0.93 (0.86 to 1) and AUC = 1, respectively). We demonstrate that the risk of neoplastic transformation can be predicted from DNA methylation profiles in the morphologically normal cell of origin of an epithelial cancer. Having profiled only 0.1% of CpGs in the human genome, studies of wider coverage are likely to yield improved predictive and diagnostic models with the accuracy needed for clinical application. The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821.

Epigenetic variability in cells of normal cytology is associated with the risk of future morphological transformation

PubMed Central

2012-01-01

Background Recently, it has been proposed that epigenetic variation may contribute to the risk of complex genetic diseases like cancer. We aimed to demonstrate that epigenetic changes in normal cells, collected years in advance of the first signs of morphological transformation, can predict the risk of such transformation. Methods We analyzed DNA methylation (DNAm) profiles of over 27,000 CpGs in cytologically normal cells of the uterine cervix from 152 women in a prospective nested case-control study. We used statistics based on differential variability to identify CpGs associated with the risk of transformation and a novel statistical algorithm called EVORA (Epigenetic Variable Outliers for Risk prediction Analysis) to make predictions. Results We observed many CpGs that were differentially variable between women who developed a non-invasive cervical neoplasia within 3 years of sample collection and those that remained disease-free. These CpGs exhibited heterogeneous outlier methylation profiles and overlapped strongly with CpGs undergoing age-associated DNA methylation changes in normal tissue. Using EVORA, we demonstrate that the risk of cervical neoplasia can be predicted in blind test sets (AUC = 0.66 (0.58 to 0.75)), and that assessment of DNAm variability allows more reliable identification of risk-associated CpGs than statistics based on differences in mean methylation levels. In independent data, EVORA showed high sensitivity and specificity to detect pre-invasive neoplasia and cervical cancer (AUC = 0.93 (0.86 to 1) and AUC = 1, respectively). Conclusions We demonstrate that the risk of neoplastic transformation can be predicted from DNA methylation profiles in the morphologically normal cell of origin of an epithelial cancer. Having profiled only 0.1% of CpGs in the human genome, studies of wider coverage are likely to yield improved predictive and diagnostic models with the accuracy needed for clinical application. Trial registration The ARTISTIC trial is registered with the International Standard Randomised Controlled Trial Number ISRCTN25417821. PMID:22453031

Free and Cued Selective Reminding Identifies Very Mild Dementia in Primary Care

PubMed Central

Grober, Ellen; Sanders, Amy E.; Hall, Charles; Lipton, Richard B.

2010-01-01

The Free and Cued Selective Reminding Test (FCSRT) is used widely to identify very mild dementia; three alternative scoring procedures have been proposed based on free recall, total recall, and cue efficiency. We compared the predictive validity of these scoring procedures for the identification of very mild prevalent dementia (CDR=0.5), of incident dementia and for distinguishing AD and nonAD dementias. We tested 244 elderly African American and Caucasian primary care patients at 18 month intervals using a screening neuropsychological battery that included the FCSRT and a comprehensive diagnostic neuropsychological battery. Median follow-up was 2.6 years. Dementia diagnoses were assigned using standard criteria without access to the results of the screening battery. There were 50 prevalent and 28 incident dementia cases. At scores selected to provide specificities of 90%, free recall was more sensitive to incident and prevalent dementia than the other two measures. Patients with impaired free recall were 15 times more likely to have a prevalent dementia and their risk of future dementia was four times higher than patients with intact free recall. Neither race nor education affected prediction though older patients were at increased risk of future dementia. Total recall was more impaired in AD dementia than in nonAD dementias. The results indicate that using the FCSRT, free recall is best measure for detecting prevalent dementia and predicting future dementia. Total recall impairment supports the diagnosis of AD rather than nonAD dementia. PMID:20683186

Can Rheumatoid Arthritis Be Prevented?

PubMed Central

Deane, Kevin

2013-01-01

The discovery of elevations of rheumatoid arthritis (RA)-related biomarkers prior to the onset of clinically apparent RA raises hopes that individuals who are at risk for future RA can be identified in a preclinical phase of disease that is defined as abnormalities of RA-related immune activity prior to the clinically apparent onset of joint disease. Additionally, there is a growing understanding of the immunologic processes that are occurring in preclinical RA, as well as a growing understanding of risk factors that may be mechanistically related to RA development. Furthermore, there are data supporting that treatment of early RA can lead to drug free remission. Taken as a whole, these findings suggest that it may be possible to use biomarkers and other factors to accurately identify the likelihood and timing of onset of future RA, and intervene with immunomodulatory therapies and/or risk factor modification to prevent the future onset of RA in at-risk individuals. Importantly, several clinical prevention trials for RA have already been tried, and one is underway. However, while our understanding of the growing understanding of the mechanisms and natural history of RA development may be leading us to the implementation of prevention strategies for RA, there are still several challenges to be met. These include developing sufficiently accurate methods of predicting those at high risk for future RA so that clinical trials can be developed based on accurate rates of development of arthritis and subjects can be adequately informed of their risk for disease, identifying the appropriate interventions and biologic targets for optimal prevention, and addressing the psychosocial and economic aspects that are crucial to developing broadly applicable prevention measures for RA. These issues notwithstanding, prevention of RA may be within reach in the near future. PMID:24315049

Predicting Family Burden Following Childhood Traumatic Brain Injury: A Cumulative Risk Approach

PubMed Central

Josie, Katherine Leigh; Peterson, Catherine Cant; Burant, Christopher; Drotar, Dennis; Stancin, Terry; Wade, Shari L.; Yeates, Keith; Taylor, H. Gerry

2015-01-01

Objective To examine the utility of a cumulative risk index (CRI) in predicting the family burden of injury (FBI) over time in families of children with traumatic brain injury (TBI). Participants One hundred eight children with severe or moderate TBI and their families participated in the study. Measures The measures used in the study include the Socioeconomic Composite Index, Life Stressors and Social Resources Inventory—Adult Form, Vineland Adaptive Behavior Scales, Child Behavior Checklist, Children’s Depression Inventory, McMaster Family Assessment Device, Brief Symptom Inventory, and Family Burden of Injury Interview. In addition, information on injury-related risk was obtained via medical charts. Methods Participants were assessed immediately, 6, and 12 months postinjury and at a 4-year extended follow-up. Results Risk variables were dichotomized (ie, high- or low-risk) and summed to create a CRI for each child. The CRI predicted the FBI at all assessments, even after accounting for autocorrelations across repeated assessments. Path coefficients between the outcome measures at each time point were significant, as were all path coefficients from the CRI to family burden at each time point. In addition, all fit indices were above the recommended guidelines, and the χ2 statistic indicated a good fit to the data. Conclusions The current study provides initial support for the utility of a CRI (ie, an index of accumulated risk factors) in predicting family outcomes over time for children with TBI. The time period immediately after injury best predicts the future levels of FBI; however, cumulative risk continues to influence the change across successive postinjury assessments. These results suggest that clinical interventions could be proactive or preventive by intervening with identified “at-risk” subgroups immediately following injury. PMID:19033828

Predicting suicides after outpatient mental health visits in the Army Study to Assess Risk and Resilience in Servicemembers (Army STARRS)

PubMed Central

Kessler, Ronald C.; Stein, Murray B.; Petukhova, Maria V.; Bliese, Paul; Bossarte, Robert M.; Bromet, Evelyn J.; Fullerton, Carol S.; Gilman, Stephen E.; Ivany, Christopher; Lewandowski-Romps, Lisa; Bell, Amy Millikan; Naifeh, James A.; Nock, Matthew K.; Reis, Benjamin Y.; Rosellini, Anthony J.; Sampson, Nancy A.; Zaslavsky, Alan M.; Ursano, Robert J.

2016-01-01

The 2013 U.S. Veterans Administration/Department of Defense Clinical Practice Guidelines (VA/DoD CPG) require comprehensive suicide risk assessments for VA/DoD patients with mental disorders but provide minimal guidance on how to carry out these assessments. Given that clinician-based assessments are known not to be strong predictors of suicide, we investigated whether a precision medicine model using administrative data after outpatient mental health specialty visits could be developed to predict suicides among outpatients. We focused on male non-deployed Regular U.S. Army soldiers because they account for the vast majority of such suicides. Four machine learning classifiers (naïve Bayes, random forests, support vector regression, elastic net penalized regression) were explored. 41.5% of Army suicides in 2004-2009 occurred among the 12.0% of soldiers seen as outpatient by mental health specialists, with risk especially high within 26 weeks of visits. An elastic net classifier with 10-14 predictors optimized sensitivity (45.6% of suicide deaths occurring after the 15% of visits with highest predicted risk). Good model stability was found for a model using 2004-2007 data to predict 2008-2009 suicides, although stability decreased in a model using 2008-2009 data to predict 2010-2012 suicides. The 5% of visits with highest risk included only 0.1% of soldiers (1047.1 suicides/100,000 person-years in the 5 weeks after the visit). This is a high enough concentration of risk to have implications for targeting preventive interventions. An even better model might be developed in the future by including the enriched information on clinician-evaluated suicide risk mandated by the VA/DoD CPG to be recorded. PMID:27431294

The association between retinal vascular geometry changes and diabetic retinopathy and their role in prediction of progression – an exploratory study

PubMed Central

2014-01-01

Background The study describes the relationship of retinal vascular geometry (RVG) to severity of diabetic retinopathy (DR), and its predictive role for subsequent development of proliferative diabetic retinopathy (PDR). Methods The research project comprises of two stages. Firstly, a comparative study of diabetic patients with different grades of DR. (No DR: Minimal non-proliferative DR: Severe non-proliferative DR: PDR) (10:10: 12: 19). Analysed RVG features including vascular widths and branching angles were compared between patient cohorts. A preliminary statistical model for determination of the retinopathy grade of patients, using these features, is presented. Secondly, in a longitudinal predictive study, RVG features were analysed for diabetic patients with progressive DR over 7 years. RVG at baseline was examined to determine risk for subsequent PDR development. Results In the comparative study, increased DR severity was associated with gradual vascular dilatation (p = 0.000), and widening of the bifurcating angle (p = 0.000) with increase in smaller-child-vessel branching angle (p = 0.027). Type 2 diabetes and increased diabetes duration were associated with increased vascular width (p = <0.05 In the predictive study, at baseline, reduced small-child vascular width (OR = 0.73 (95% CI 0.58-0.92)), was predictive of future progression to PDR. Conclusions The study findings suggest that RVG alterations can act as novel markers indicative of progression of DR severity and establishment of PDR. RVG may also have a potential predictive role in determining the risk of future retinopathy progression. PMID:25001248

Future orientation and suicide ideation and attempts in depressed adults ages 50 and over.

PubMed

Hirsch, Jameson K; Duberstein, Paul R; Conner, Kenneth R; Heisel, Marnin J; Beckman, Anthony; Franus, Nathan; Conwell, Yeates

2006-09-01

The objective of this study was to test the hypothesis that future orientation is associated with lower levels of suicide ideation and lower likelihood of suicide attempt in a sample of patients in treatment for major depression. Two hundred two participants (116 female, 57%) ages 50-88 years were recruited from inpatient and outpatient settings. All were diagnosed with major depression using a structured diagnostic interview. Suicide ideation was assessed with the Scale for Suicide Ideation (both current and worst point ratings), and a measure of future orientation was created to assess future expectancies. The authors predicted that greater future orientation would be associated with less current and worst point suicide ideation, and would distinguish current and lifetime suicide attempters from nonattempters. Hypotheses were tested using multivariate logistic regression and linear regression analyses that accounted for age, gender, hopelessness, and depression. As hypothesized, higher future orientation scores were associated with lower current suicidal ideation, less intense suicidal ideation at its worst point, and lower probability of a history of attempted suicide after accounting for covariates. Future orientation was not associated with current attempt status. Future orientation holds promise as a cognitive variable associated with decreased suicide risk; a better understanding of its putative protective role is needed. Treatments designed to enhance future orientation might decrease suicide risk.

Adolescents’ expectations for the future predict health behaviors in early adulthood

PubMed Central

McDade, Thomas W.; Chyu, Laura; Duncan, Greg J.; Hoyt, Lindsay T.; Doane, Leah D.; Adam, Emma K.

2011-01-01

Health-related behaviors in adolescence establish trajectories of risk for obesity and chronic degenerative diseases, and they represent an important pathway through which socio-economic environments shape patterns of morbidity and mortality. Most behaviors that promote health involve making choices that may not pay off until the future, but the factors that predict an individual's investment in future health are not known. In this paper we consider whether expectations for the future in two domains relevant to adolescents in the U.S.—perceived chances of living to middle age and perceived chances of attending college—are associated with an individual's engagement in behaviors that protect health in the long run. We focus on adolescence as an important life stage during which habits formed may shape trajectories of disease risk later in life. We use data from a large, nationally representative sample of American youth (the US National Longitudinal Study of Adolescent Health) to predict levels of physical activity, fast food consumption, and cigarette smoking in young adulthood in relation to perceived life chances in adolescence, controlling for baseline health behaviors and a wide range of potentially confounding factors. We found that adolescents who rated their chances of attending college more highly exercised more frequently and smoked fewer cigarettes in young adulthood. Adolescents with higher expectations of living to age 35 smoked fewer cigarettes as young adults. Parental education was a significant predictor of perceived life chances, as well as health behaviors, but for each outcome the effects of perceived life chances were independent of, and often stronger than, parental education. Perceived life chances in adolescence may therefore play an important role in establishing individual trajectories of health, and in contributing to social gradients in population health. PMID:21764487

Adolescents' expectations for the future predict health behaviors in early adulthood.

PubMed

McDade, Thomas W; Chyu, Laura; Duncan, Greg J; Hoyt, Lindsay T; Doane, Leah D; Adam, Emma K

2011-08-01

Health-related behaviors in adolescence establish trajectories of risk for obesity and chronic degenerative diseases, and they represent an important pathway through which socio-economic environments shape patterns of morbidity and mortality. Most behaviors that promote health involve making choices that may not pay off until the future, but the factors that predict an individual's investment in future health are not known. In this paper we consider whether expectations for the future in two domains relevant to adolescents in the U.S.-perceived chances of living to middle age and perceived chances of attending college-are associated with an individual's engagement in behaviors that protect health in the long run. We focus on adolescence as an important life stage during which habits formed may shape trajectories of disease risk later in life. We use data from a large, nationally representative sample of American youth (the US National Longitudinal Study of Adolescent Health) to predict levels of physical activity, fast food consumption, and cigarette smoking in young adulthood in relation to perceived life chances in adolescence, controlling for baseline health behaviors and a wide range of potentially confounding factors. We found that adolescents who rated their chances of attending college more highly exercised more frequently and smoked fewer cigarettes in young adulthood. Adolescents with higher expectations of living to age 35 smoked fewer cigarettes as young adults. Parental education was a significant predictor of perceived life chances, as well as health behaviors, but for each outcome the effects of perceived life chances were independent of, and often stronger than, parental education. Perceived life chances in adolescence may therefore play an important role in establishing individual trajectories of health, and in contributing to social gradients in population health. Copyright © 2011 Elsevier Ltd. All rights reserved.

Close Approach Prediction Analysis of the Earth Science Constellation with the Fengyun-1C Debris

NASA Technical Reports Server (NTRS)

Duncan, Matthew; Rand, David K.

2008-01-01

Routine satellite operations for the Earth Science Constellation (ESC) include collision risk assessment between members of the constellation and other orbiting space objects. Each day, close approach predictions are generated by a U.S. Department of Defense Joint Space Operations Center Orbital Safety Analyst using the high accuracy Space Object Catalog maintained by the Air Force's 1" Space Control Squadron. Prediction results and other ancillary data such as state vector information are sent to NASAJGoddard Space Flight Center's (GSFC's) Collision Risk Assessment analysis team for review. Collision analysis is performed and the GSFC team works with the ESC member missions to develop risk reduction strategies as necessary. This paper presents various close approach statistics for the ESC. The ESC missions have been affected by debris from the recent anti-satellite test which destroyed the Chinese Fengyun- 1 C satellite. The paper also presents the percentage of close approach events induced by the Fengyun-1C debris, and presents analysis results which predict the future effects on the ESC caused by this event. Specifically, the Fengyun-1C debris is propagated for twenty years using high-performance computing technology and close approach predictions are generated for the ESC. The percent increase in the total number of conjunction events is considered to be an estimate of the collision risk due to the Fengyun-1C break- UP.

Prediction, Communication and Urban policies. Is there enough space for three faces on a single medal?

NASA Astrophysics Data System (ADS)

Miozzo, D.; Ferraris, L.; Altamura, M.

2012-04-01

There are two possible answers to the question that this session poses (why predict?): Firstly, because scientists like to play God and envisage a future where the chaotic unfolding of atmospheric physics will be reviled by numerical weather prediction models. Secondly, because policy makers realised, in the last years, that the development of our unsustainable society made it impossible to tackle the "risk reduction problem" by solving its dilemma at the root and de-constructing in favour of a cutback of risk exposure. In synthesis the desire of omnipotence of science and the excessively costly future prospected by politicians made us believe that predicting natural hazards is un indispensable tile of a much more complex jigsaw. Civil Protection (CP) measures, those for which most of the predictions are needed, are however entangled within complex societal schemes. A perfect CP system, with perfect soi-disent predictions, is useless if not applied and disseminated through a long term policy of civic education. The entire population needs to became part of this educational stream aiming to a shared and participated empowerment of society. If on the one hand we have society and science on the other hand we have economy and urban policies. The economy deriving from the construction sector is in some countries seen as an indispensable asset for national financial stability. Furthermore the current economical crisis is slowing the adoption of vital risk-reduction interventions: to the same extent as in the aftermath of the Second World War, employment and very short termed economical strategies are overtaking strict urban planning and environmental rules. Thus the availability of funds intended towards the protection of the population has greatly decreased whilst, on the other hand, more buildings are being constructed in areas of great risk. Not only our landscapes are being radically changed but, in the long term, we are exponentially augmenting the exposure of the population to extreme events. This work wants to convey on these themes bringing forward the example of the recent flash flood which took place in Genoa (Liguria Region, Italy, November 2011). It will show how CP plans were present and how they precisely identified the vulnerable areas where unfortunately six women died. Forecasts were consistent to the unfolding of events and CP alerts were diffusely issued two days before the event, however the population was unaware of what was going to happen. To this aspect also the aforementioned faulty urban planning perpetrated in more than fifty years must be taken into account. Going back to the initial question, why do we predict? A realistic answer could be: because we cannot do anything else. It is time for policy makers to rethink completely the scheme of priorities of our society. Are we willing to annihilate the safety of our cities in the near future just to live one more year on the verge of bankruptcy? If things will not change in the near future we are afraid that these questions will be retrospectively answered by our sons and daughters.

Work ability as prognostic risk marker of disability pension: single-item work ability score versus multi-item work ability index.

PubMed

Roelen, Corné A M; van Rhenen, Willem; Groothoff, Johan W; van der Klink, Jac J L; Twisk, Jos W R; Heymans, Martijn W

2014-07-01

Work ability predicts future disability pension (DP). A single-item work ability score (WAS) is emerging as a measure for work ability. This study compared single-item WAS with the multi-item work ability index (WAI) in its ability to identify workers at risk of DP. This prospective cohort study comprised 11 537 male construction workers, who completed the WAI at baseline and reported DP after a mean 2.3 years of follow-up. WAS and WAI were calibrated for DP risk predictions with the Hosmer-Lemeshow (H-L) test and their ability to discriminate between high- and low-risk construction workers was investigated with the area under the receiver operating characteristic curve (AUC). At follow-up, 336 (3%) construction workers reported DP. Both WAS [odds ratio (OR) 0.72, 95% confidence interval (95% CI) 0.66-0.78] and WAI (OR 0.57, 95% CI 0.52-0.63) scores were associated with DP at follow-up. The WAS showed miscalibration (H-L model χ (�)=10.60; df=3; P=0.01) and poorly discriminated between high- and low-risk construction workers (AUC 0.67, 95% CI 0.64-0.70). In contrast, calibration (H-L model χ �=8.20; df=8; P=0.41) and discrimination (AUC 0.78, 95% CI 0.75-0.80) were both adequate for the WAI. Although associated with the risk of future DP, the single-item WAS poorly identified male construction workers at risk of DP. We recommend using the multi-item WAI to screen for risk of DP in occupational health practice.

Novel sensing technology in fall risk assessment in older adults: a systematic review.

PubMed

Sun, Ruopeng; Sosnoff, Jacob J

2018-01-16

Falls are a major health problem for older adults with significant physical and psychological consequences. A first step of successful fall prevention is to identify those at risk of falling. Recent advancement in sensing technology offers the possibility of objective, low-cost and easy-to-implement fall risk assessment. The objective of this systematic review is to assess the current state of sensing technology on providing objective fall risk assessment in older adults. A systematic review was conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis statement (PRISMA). Twenty-two studies out of 855 articles were systematically identified and included in this review. Pertinent methodological features (sensing technique, assessment activities, outcome variables, and fall discrimination/prediction models) were extracted from each article. Four major sensing technologies (inertial sensors, video/depth camera, pressure sensing platform and laser sensing) were reported to provide accurate fall risk diagnostic in older adults. Steady state walking, static/dynamic balance, and functional mobility were used as the assessment activity. A diverse range of diagnostic accuracy across studies (47.9% - 100%) were reported, due to variation in measured kinematic/kinetic parameters and modelling techniques. A wide range of sensor technologies have been utilized in fall risk assessment in older adults. Overall, these devices have the potential to provide an accurate, inexpensive, and easy-to-implement fall risk assessment. However, the variation in measured parameters, assessment tools, sensor sites, movement tasks, and modelling techniques, precludes a firm conclusion on their ability to predict future falls. Future work is needed to determine a clinical meaningful and easy to interpret fall risk diagnosis utilizing sensing technology. Additionally, the gap between functional evaluation and user experience to technology should be addressed.

Self-Reported Stroke Symptoms Without a Prior Diagnosis of Stroke or TIA: A Powerful New Risk Factor for Stroke

PubMed Central

Kleindorfer, Dawn; Judd, Suzanne; Howard, Virginia J.; McClure, Leslie; Safford, Monika M.; Cushman, Mary; Rhodes, David; Howard, George

2011-01-01

Background and Purpose Previously in the REasons for Geographic And Racial Differences in Stroke (REGARDS) cohort, we found 18% of the stroke/TIA-free study population reported ≥ 1 stroke symptom (SS) at baseline. We sought to evaluate the additional impact of these stroke symptoms (SS) on risk for subsequent stroke. Methods REGARDS recruited 30,239 U.S. blacks and whites, aged 45+ in 2003–7, who are being followed every 6 months for events. All stroke events are physician-verified; those with prior diagnosed stroke or TIA are excluded from this analysis. At baseline, participants were asked six questions regarding stroke symptoms. Measured stroke risk factors were components of the Framingham Stroke Risk Score (FSRS). Results After excluding those with prior stroke or missing data, there were 24,412 participants in this analysis, with a median follow-up of 4.4 years. Participants were 39% black, 55% female, and had median age of 64 years. There were 381 physician-verified stroke events. The FSRS explained 72.0% of stroke risk; individual components explained between 0.2% (LVH) and 5.7% (age + race) of stroke risk. After adjustment for FSRS factors, SS were significantly related to stroke risk: for each SS reported, the risk of stroke increased by 21% per symptom. Discussion Among participants without self-reported stroke or TIA, prior SS are highly predictive of future stroke events. Compared to FSRS factors, the impact of SS on the prediction of future stroke was almost as large as the impact of smoking and hypertension, and larger than the impact of diabetes and heart disease. PMID:21921283

[Forensic assessment of violence risk].

PubMed

Pujol Robinat, Amadeo; Mohíno Justes, Susana; Gómez-Durán, Esperanza L

2014-03-01

Over the last 20 years there have been steps forward in the field of scientific research on prediction and handling different violent behaviors. In this work we go over the classic concept of "criminal dangerousness" and the more current of "violence risk assessment". We analyze the evolution of such assessment from the practice of non-structured clinical expert opinion to current actuarial methods and structured clinical expert opinion. Next we approach the problem of assessing physical violence risk analyzing the HCR-20 (Assessing Risk for Violence) and we also review the classic and complex subject of the relation between mental disease and violence. One of the most problematic types of violence, difficult to assess and predict, is sexual violence. We study the different actuarial and sexual violence risk prediction instruments and in the end we advise an integral approach to the problem. We also go through partner violence risk assessment, describing the most frequently used scales, especially SARA (Spouse Assault Risk Assessment) and EPV-R. Finally we give practical advice on risk assessment, emphasizing the importance of having maximum information about the case, carrying out a clinical examination, psychopathologic exploration and the application of one of the described risk assessment scales. We'll have to express an opinion about the dangerousness/risk of future violence from the subject and some recommendations on the conduct to follow and the most advisable treatment. Copyright © 2014 Elsevier España, S.L. All rights reserved.

A comparison of imputation techniques for handling missing predictor values in a risk model with a binary outcome.

PubMed

Ambler, Gareth; Omar, Rumana Z; Royston, Patrick

2007-06-01

Risk models that aim to predict the future course and outcome of disease processes are increasingly used in health research, and it is important that they are accurate and reliable. Most of these risk models are fitted using routinely collected data in hospitals or general practices. Clinical outcomes such as short-term mortality will be near-complete, but many of the predictors may have missing values. A common approach to dealing with this is to perform a complete-case analysis. However, this may lead to overfitted models and biased estimates if entire patient subgroups are excluded. The aim of this paper is to investigate a number of methods for imputing missing data to evaluate their effect on risk model estimation and the reliability of the predictions. Multiple imputation methods, including hotdecking and multiple imputation by chained equations (MICE), were investigated along with several single imputation methods. A large national cardiac surgery database was used to create simulated yet realistic datasets. The results suggest that complete case analysis may produce unreliable risk predictions and should be avoided. Conditional mean imputation performed well in our scenario, but may not be appropriate if using variable selection methods. MICE was amongst the best performing multiple imputation methods with regards to the quality of the predictions. Additionally, it produced the least biased estimates, with good coverage, and hence is recommended for use in practice.

Machine learning derived risk prediction of anorexia nervosa.

PubMed

Guo, Yiran; Wei, Zhi; Keating, Brendan J; Hakonarson, Hakon

2016-01-20

Anorexia nervosa (AN) is a complex psychiatric disease with a moderate to strong genetic contribution. In addition to conventional genome wide association (GWA) studies, researchers have been using machine learning methods in conjunction with genomic data to predict risk of diseases in which genetics play an important role. In this study, we collected whole genome genotyping data on 3940 AN cases and 9266 controls from the Genetic Consortium for Anorexia Nervosa (GCAN), the Wellcome Trust Case Control Consortium 3 (WTCCC3), Price Foundation Collaborative Group and the Children's Hospital of Philadelphia (CHOP), and applied machine learning methods for predicting AN disease risk. The prediction performance is measured by area under the receiver operating characteristic curve (AUC), indicating how well the model distinguishes cases from unaffected control subjects. Logistic regression model with the lasso penalty technique generated an AUC of 0.693, while Support Vector Machines and Gradient Boosted Trees reached AUC's of 0.691 and 0.623, respectively. Using different sample sizes, our results suggest that larger datasets are required to optimize the machine learning models and achieve higher AUC values. To our knowledge, this is the first attempt to assess AN risk based on genome wide genotype level data. Future integration of genomic, environmental and family-based information is likely to improve the AN risk evaluation process, eventually benefitting AN patients and families in the clinical setting.

Cross-cultural and site-based influences on demographic, well-being, and social network predictors of risk perception in hazard and disaster settings in Ecuador and Mexico: predictors of risk perception in hazard and disaster settings in Ecuador and Mexico.

PubMed

Jones, Eric C; Faas, Albert J; Murphy, Arthur D; Tobin, Graham A; Whiteford, Linda M; McCarty, Christopher

2013-03-01

Although virtually all comparative research about risk perception focuses on which hazards are of concern to people in different culture groups, much can be gained by focusing on predictors of levels of risk perception in various countries and places. In this case, we examine standard and novel predictors of risk perception in seven sites among communities affected by a flood in Mexico (one site) and volcanic eruptions in Mexico (one site) and Ecuador (five sites). We conducted more than 450 interviews with questions about how people feel at the time (after the disaster) regarding what happened in the past, their current concerns, and their expectations for the future. We explore how aspects of the context in which people live have an effect on how strongly people perceive natural hazards in relationship with demographic, well-being, and social network factors. Generally, our research indicates that levels of risk perception for past, present, and future aspects of a specific hazard are similar across these two countries and seven sites. However, these contexts produced different predictors of risk perception-in other words, there was little overlap between sites in the variables that predicted the past, present, or future aspects of risk perception in each site. Generally, current stress was related to perception of past danger of an event in the Mexican sites, but not in Ecuador; network variables were mainly important for perception of past danger (rather than future or present danger), although specific network correlates varied from site to site across the countries.

Climate-Induced Range Shifts and Possible Hybridisation Consequences in Insects

PubMed Central

Sánchez-Guillén, Rosa Ana; Muñoz, Jesús; Rodríguez-Tapia, Gerardo; Feria Arroyo, T. Patricia; Córdoba-Aguilar, Alex

2013-01-01

Many ectotherms have altered their geographic ranges in response to rising global temperatures. Current range shifts will likely increase the sympatry and hybridisation between recently diverged species. Here we predict future sympatric distributions and risk of hybridisation in seven Mediterranean ischnurid damselfly species (I. elegans, I. fountaineae, I. genei, I. graellsii, I. pumilio, I. saharensis and I. senegalensis). We used a maximum entropy modelling technique to predict future potential distribution under four different Global Circulation Models and a realistic emissions scenario of climate change. We carried out a comprehensive data compilation of reproductive isolation (habitat, temporal, sexual, mechanical and gametic) between the seven studied species. Combining the potential distribution and data of reproductive isolation at different instances (habitat, temporal, sexual, mechanical and gametic), we infer the risk of hybridisation in these insects. Our findings showed that all but I. graellsii will decrease in distributional extent and all species except I. senegalensis are predicted to have northern range shifts. Models of potential distribution predicted an increase of the likely overlapping ranges for 12 species combinations, out of a total of 42 combinations, 10 of which currently overlap. Moreover, the lack of complete reproductive isolation and the patterns of hybridisation detected between closely related ischnurids, could lead to local extinctions of native species if the hybrids or the introgressed colonising species become more successful. PMID:24260411

Pathways between self-esteem and depression in couples.

PubMed

Johnson, Matthew D; Galambos, Nancy L; Finn, Christine; Neyer, Franz J; Horne, Rebecca M

2017-04-01

Guided by concepts from a relational developmental perspective, this study examined intra- and interpersonal associations between self-esteem and depressive symptoms in a sample of 1,407 couples surveyed annually across 6 years in the Panel Analysis of Intimate Relations and Family Dynamics (pairfam) study. Autoregressive cross-lagged model results demonstrated that self-esteem predicted future depressive symptoms for male partners at all times, replicating the vulnerability model for men (low self-esteem is a risk factor for future depression). Additionally, a cross-partner association emerged between symptoms of depression: Higher depressive symptoms in one partner were associated with higher levels of depression in the other partner one year later. Finally, supportive dyadic coping, the support that partners reported providing to one another in times of stress, was tested as a potential interpersonal mediator of pathways between self-esteem and depression. Female partners' higher initial levels of self-esteem predicted male partners' subsequent reports of increased supportive dyadic coping, which, in turn, predicted higher self-esteem and fewer symptoms of depression among female partners in the future. Male partners' initially higher symptoms of depression predicted less frequent supportive dyadic coping subsequently reported by female partners, which was associated with increased feelings of depression in the future. Couple relations represent an important contextual factor that may be implicated in the developmental pathways connecting self-esteem and symptoms of depression. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Children's School Readiness: Implications for Eliminating Future Disparities in Health and Education

ERIC Educational Resources Information Center

Pagani, Linda S.; Fitzpatrick, Caroline

2014-01-01

Background: School-entry characteristics predict adult educational attainment, which forecasts dispositions toward disease prevention. Health and education risks can also be transmitted from one generation to the next. As such, school readiness forecasts a set of intertwined biopsychosocial trajectories that can influence the developmental…

Monitoring and predicting shrink potential and future processing quality of potato tubers

USDA-ARS?s Scientific Manuscript database

Long-term storage of potato tubers increases risks, which are often attributed to shrink and quality loss. To minimize shrink and ensure high quality tubers, producers must closely monitor the condition of the crop during storage and make necessary adjustments to management plans. Evaluation procedu...

Child Health, Maternal Marital and Socioeconomic Factors, and Maternal Health

ERIC Educational Resources Information Center

Garbarski, Dana; Witt, Whitney P.

2013-01-01

Although maternal socioeconomic status and health predict in part children's future health and socioeconomic prospects, it is possible that the intergenerational association flows in the other direction such that child health affects maternal outcomes. Previous research demonstrates that poor child health increases the risk of adverse maternal…

Multi-hazard risk analysis using the FP7 RASOR Platform

NASA Astrophysics Data System (ADS)

Koudogbo, Fifamè N.; Duro, Javier; Rossi, Lauro; Rudari, Roberto; Eddy, Andrew

2014-10-01

Climate change challenges our understanding of risk by modifying hazards and their interactions. Sudden increases in population and rapid urbanization are changing exposure to risk around the globe, making impacts harder to predict. Despite the availability of operational mapping products, there is no single tool to integrate diverse data and products across hazards, update exposure data quickly and make scenario-based predictions to support both short and long-term risk-related decisions. RASOR (Rapid Analysis and Spatialization Of Risk) will develop a platform to perform multi-hazard risk analysis for the full cycle of disaster management, including targeted support to critical infrastructure monitoring and climate change impact assessment. A scenario-driven query system simulates future scenarios based on existing or assumed conditions and compares them with historical scenarios. RASOR will thus offer a single work environment that generates new risk information across hazards, across data types (satellite EO, in-situ), across user communities (global, local, climate, civil protection, insurance, etc.) and across the world. Five case study areas are considered within the project, located in Haiti, Indonesia, Netherlands, Italy and Greece. Initially available over those demonstration areas, RASOR will ultimately offer global services to support in-depth risk assessment and full-cycle risk management.

Conversation and compliance: role of interpersonal discussion and social norms in public communication campaigns.

PubMed

Frank, Lauren B; Chatterjee, Joyee S; Chaudhuri, Sonal T; Lapsansky, Charlotte; Bhanot, Anurudra; Murphy, Sheila T

2012-01-01

This study explores the role of interpersonal discussion and social norms in a public health campaign, the BBC Condom Normalization Campaign, designed to promote conversation and change the public perception of condom use in India. Drawing upon the integrative model of behavioral prediction, attitudes, self-efficacy, subjective norms, and descriptive norms were predicted to relate to behavioral intentions to use condoms. It is important to note that the valence of discussion was hypothesized to relate to each of these more proximal predictors. The authors used structural equation modeling to test the model on 3 separate samples of Indian men between the ages of 15 and 49 years: (a) high-risk men who had sex with nonspouses; (b) low-risk, sexually inactive, unmarried men; and (c) low-risk, monogamous, married men. Results were similar for low- and high-risk audiences, with valence of discussion about condoms predicting condom-related attitudes, self-efficacy, and subjective and descriptive social norms with respect to condom use, which, in turn, predicted behavioral intent to use condoms. These findings underscore the need to take not only the frequency but also the valence of interpersonal discussion into account when assessing the effect of health campaigns. Implications for theory and design of future public communication campaigns are explored.

Non-animal approaches for toxicokinetics in risk evaluations of food chemicals.

PubMed

Punt, Ans; Peijnenburg, Ad A C M; Hoogenboom, Ron L A P; Bouwmeester, Hans

2017-01-01

The objective of the present work was to review the availability and predictive value of non-animal toxicokinetic approaches and to evaluate their current use in European risk evaluations of food contaminants, additives and food contact materials, as well as pesticides and medicines. Results revealed little use of quantitative animal or human kinetic data in risk evaluations of food chemicals, compared with pesticides and medicines. Risk evaluations of medicines provided sufficient in vivo kinetic data from different species to evaluate the predictive value of animal kinetic data for humans. These data showed a relatively poor correlation between the in vivo bioavailability in rats and dogs versus that in humans. In contrast, in vitro (human) kinetic data have been demonstrated to provide adequate predictions of the fate of compounds in humans, using appropriate in vitro-in vivo scalers and by integration of in vitro kinetic data with in silico kinetic modelling. Even though in vitro kinetic data were found to be occasionally included within risk evaluations of food chemicals, particularly results from Caco-2 absorption experiments and in vitro data on gut-microbial conversions, only minor use of in vitro methods for metabolism and quantitative in vitro-in vivo extrapolation methods was identified. Yet, such quantitative predictions are essential in the development of alternatives to animal testing as well as to increase human relevance of toxicological risk evaluations. Future research should aim at further improving and validating quantitative alternative methods for kinetics, thereby increasing regulatory acceptance of non-animal kinetic data.

Can sensation of cold hands predict Raynaud's phenomenon or paraesthesia?

PubMed

Carlsson, D; Wahlström, J; Burström, L; Hagberg, M; Lundström, R; Pettersson, H; Nilsson, T

2018-05-10

Raynaud's phenomenon and neurosensory symptoms are common after hand-arm vibration exposure. Knowledge of early signs of vibration injuries is needed. To investigate the risk of developing Raynaud's phenomenon and paraesthesia in relation to sensation of cold hands in a cohort of male employees at an engineering plant. We followed a cohort of male manual and office workers at an engineering plant in Sweden for 21 years. At baseline (1987 and 1992) and each follow-up (1992, 1997, 2002, 2008), we assessed sensation of cold, Raynaud's phenomenon and paraesthesia in the hands using questionnaires and measured vibration exposure. We calculated risk estimates with univariate and multiple logistic regression analyses and adjusted for vibration exposure and tobacco usage. There were 241 study participants. During the study period, 21 individuals developed Raynaud's phenomenon and 43 developed paraesthesia. When adjusting the risk of developing Raynaud's phenomenon for vibration exposure and tobacco use, the odds ratios were between 6.0 and 6.3 (95% CI 2.2-17.0). We observed no increased risk for paraesthesia in relation to a sensation of cold hands. A sensation of cold hands was a risk factor for Raynaud's phenomenon. At the individual level, reporting a sensation of cold hands did not appear to be useful information to predict future development of Raynaud's phenomenon given a weak to moderate predictive value. For paraesthesia, the sensation of cold was not a risk factor and there was no predictive value at the individual level.

Pleural mesothelioma and lung cancer risks in relation to occupational history and asbestos lung burden

PubMed Central

Gilham, Clare; Rake, Christine; Burdett, Garry; Nicholson, Andrew G; Davison, Leslie; Franchini, Angelo; Carpenter, James; Hodgson, John; Darnton, Andrew; Peto, Julian

2016-01-01

Background We have conducted a population-based study of pleural mesothelioma patients with occupational histories and measured asbestos lung burdens in occupationally exposed workers and in the general population. The relationship between lung burden and risk, particularly at environmental exposure levels, will enable future mesothelioma rates in people born after 1965 who never installed asbestos to be predicted from their asbestos lung burdens. Methods Following personal interview asbestos fibres longer than 5 µm were counted by transmission electron microscopy in lung samples obtained from 133 patients with mesothelioma and 262 patients with lung cancer. ORs for mesothelioma were converted to lifetime risks. Results Lifetime mesothelioma risk is approximately 0.02% per 1000 amphibole fibres per gram of dry lung tissue over a more than 100-fold range, from 1 to 4 in the most heavily exposed building workers to less than 1 in 500 in most of the population. The asbestos fibres counted were amosite (75%), crocidolite (18%), other amphiboles (5%) and chrysotile (2%). Conclusions The approximate linearity of the dose–response together with lung burden measurements in younger people will provide reasonably reliable predictions of future mesothelioma rates in those born since 1965 whose risks cannot yet be seen in national rates. Burdens in those born more recently will indicate the continuing occupational and environmental hazards under current asbestos control regulations. Our results confirm the major contribution of amosite to UK mesothelioma incidence and the substantial contribution of non-occupational exposure, particularly in women. PMID:26715106

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes.

PubMed

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities' preparedness and response capabilities and to mitigate future consequences. An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model's algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties.

Spatial vulnerability of Australian urban populations to extreme heat events

NASA Astrophysics Data System (ADS)

Loughnan, Margaret; Tapper, Nigel; Phan, Thu; Lynch, Kellie; McInnes, Judith

2013-04-01

Extreme heat events pose a risk to the health of all individuals, especially the elderly and the chronically ill, and are associated with an increased demand for healthcare services. In order to address this problem, policy makers' need information about temperatures above which mortality and morbidity of the exposed population is likely to increase, where the vulnerable groups in the community are located, and how the risks from extreme heat events are likely to change in the future. This study identified threshold temperatures for all Australian capital cities, developed a spatial index of population vulnerability, and used climate model output to predict changes in the number of days exceeding temperature thresholds in the future, as well as changes in risk related to changes in urban density and an ageing population. The study has shown that daily maximum and minimum temperatures from the Bureau of Meteorology forecasts can be used to calculate temperature thresholds for heat alert days. The key risk factors related to adverse health outcomes were found to be areas with intense urban heat islands, areas with higher proportions of older people, and areas with ethnic communities. Maps of spatial vulnerability have been developed to provide information to assist emergency managers, healthcare professionals, and ancillary services develop heatwave preparedness plans at a local scale that target vulnerable groups and address heat-related health risks. The numbers of days exceeding current heat thresholds are predicted to increase over the next 20 to 40 years in all Australian capital cities.

C-reactive protein and other markers of inflammation in hemodialysis patients

PubMed Central

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies. PMID:24009946

C-reactive protein and other markers of inflammation in hemodialysis patients.

PubMed

Heidari, Behzad

2013-01-01

Hemodialysis patients are at greater risk of cardiovascular disease. Higher than expected cardiovascular morbidity and mortality in this population has been attributed to dislipidemia as well as inflammation. The causes of inflammation in hemodialysis patients are multifactorial. Several markers were used for the detection of inflammatory reaction in patients with chronic renal disease. These markers can be used for the prediction of future cardiovascular events. Among the several parameters of inflammatory markers, serum, CRP is well known and its advantages for the detection of inflammation and its predictor ability has been evaluated in several studies. This review addressed the associated factors and markers of inflammation in hemodialysis patients. In addition, their ability in predicting future atherosclerosis and effect of treatment has been reviewed. However, this context particularly in using CRP as a prediction marker of inflammation and morbidity requires further studies.

Prediction of Ischemic Heart Disease and Stroke in Survivors of Childhood Cancer.

PubMed

Chow, Eric J; Chen, Yan; Hudson, Melissa M; Feijen, Elizabeth A M; Kremer, Leontien C; Border, William L; Green, Daniel M; Meacham, Lillian R; Mulrooney, Daniel A; Ness, Kirsten K; Oeffinger, Kevin C; Ronckers, Cécile M; Sklar, Charles A; Stovall, Marilyn; van der Pal, Helena J; van Dijk, Irma W E M; van Leeuwen, Flora E; Weathers, Rita E; Robison, Leslie L; Armstrong, Gregory T; Yasui, Yutaka

2018-01-01

Purpose We aimed to predict individual risk of ischemic heart disease and stroke in 5-year survivors of childhood cancer. Patients and Methods Participants in the Childhood Cancer Survivor Study (CCSS; n = 13,060) were observed through age 50 years for the development of ischemic heart disease and stroke. Siblings (n = 4,023) established the baseline population risk. Piecewise exponential models with backward selection estimated the relationships between potential predictors and each outcome. The St Jude Lifetime Cohort Study (n = 1,842) and the Emma Children's Hospital cohort (n = 1,362) were used to validate the CCSS models. Results Ischemic heart disease and stroke occurred in 265 and 295 CCSS participants, respectively. Risk scores based on a standard prediction model that included sex, chemotherapy, and radiotherapy (cranial, neck, and chest) exposures achieved an area under the curve and concordance statistic of 0.70 and 0.70 for ischemic heart disease and 0.63 and 0.66 for stroke, respectively. Validation cohort area under the curve and concordance statistics ranged from 0.66 to 0.67 for ischemic heart disease and 0.68 to 0.72 for stroke. Risk scores were collapsed to form statistically distinct low-, moderate-, and high-risk groups. The cumulative incidences at age 50 years among CCSS low-risk groups were < 5%, compared with approximately 20% for high-risk groups ( P < .001); cumulative incidence was only 1% for siblings ( P < .001 v low-risk survivors). Conclusion Information available to clinicians soon after completion of childhood cancer therapy can predict individual risk for subsequent ischemic heart disease and stroke with reasonable accuracy and discrimination through age 50 years. These models provide a framework on which to base future screening strategies and interventions.

Sleep and youth suicidal behavior: a neglected field.

PubMed

Liu, Xianchen; Buysse, Daniel J

2006-05-01

Sleep undergoes substantial changes during adolescence and suicide risk begins to increase during this period as well. This review focuses on recent literature on the relationship between sleep and suicidal behavior and proposes directions for future research. Adolescent sleep is characterized by widespread sleep restriction, irregular sleep schedules, daytime sleepiness, and elevated risk for sleep disturbances. More research on adolescent sleep and psychosocial impairment, psychiatric disorders, and suicidal behavior has been conducted. Suicidal psychiatric patients had more sleep disturbances including insomnia, hypersomnia, or nightmares than nonsuicidal patients. Shorter rapid eye movement latency and increased rapid eye movement activity have been noted to be a marker of suicidality in psychiatric patients. Epidemiological studies have demonstrated that insomnia, nightmares, and sleep insufficiency are associated with elevated risk for suicide. Although the link between insomnia and suicidal behavior appears to be mediated by depression, existing data suggest an independent predictive role of nightmares in future suicidal behavior. Sleep loss or disturbances are likely to signal an increased risk of future suicidal action in adolescents. Large-scale prospective studies and neurobiological studies are needed for a better understanding of the complex relationship between sleep, psychopathology, and youth suicidal behavior.

Geography of current and future global mammal extinction risk

PubMed Central

Shoemaker, Kevin T.; Weinstein, Ben; Costa, Gabriel C.; Brooks, Thomas M.; Ceballos, Gerardo; Radeloff, Volker C.; Rondinini, Carlo; Graham, Catherine H.

2017-01-01

Identifying which species are at greatest risk, what makes them vulnerable, and where they are distributed are central goals for conservation science. While knowledge of which factors influence extinction risk is increasingly available for some taxonomic groups, a deeper understanding of extinction correlates and the geography of risk remains lacking. Here, we develop a predictive random forest model using both geospatial and mammalian species’ trait data to uncover the statistical and geographic distributions of extinction correlates. We also explore how this geography of risk may change under a rapidly warming climate. We found distinctive macroecological relationships between species-level risk and extinction correlates, including the intrinsic biological traits of geographic range size, body size and taxonomy, and extrinsic geographic settings such as seasonality, habitat type, land use and human population density. Each extinction correlate exhibited ranges of values that were especially associated with risk, and the importance of different risk factors was not geographically uniform across the globe. We also found that about 10% of mammals not currently recognized as at-risk have biological traits and occur in environments that predispose them towards extinction. Southeast Asia had the most actually and potentially threatened species, underscoring the urgent need for conservation in this region. Additionally, nearly 40% of currently threatened species were predicted to experience rapid climate change at 0.5 km/year or more. Biological and environmental correlates of mammalian extinction risk exhibit distinct statistical and geographic distributions. These results provide insight into species-level patterns and processes underlying geographic variation in extinction risk. They also offer guidance for future conservation research focused on specific geographic regions, or evaluating the degree to which species-level patterns mirror spatial variation in the pressures faced by populations within the ranges of individual species. The added impacts from climate change may increase the susceptibility of at-risk species to extinction and expand the regions where mammals are most vulnerable globally. PMID:29145486

Geography of current and future global mammal extinction risk.

PubMed

Davidson, Ana D; Shoemaker, Kevin T; Weinstein, Ben; Costa, Gabriel C; Brooks, Thomas M; Ceballos, Gerardo; Radeloff, Volker C; Rondinini, Carlo; Graham, Catherine H

2017-01-01

Identifying which species are at greatest risk, what makes them vulnerable, and where they are distributed are central goals for conservation science. While knowledge of which factors influence extinction risk is increasingly available for some taxonomic groups, a deeper understanding of extinction correlates and the geography of risk remains lacking. Here, we develop a predictive random forest model using both geospatial and mammalian species' trait data to uncover the statistical and geographic distributions of extinction correlates. We also explore how this geography of risk may change under a rapidly warming climate. We found distinctive macroecological relationships between species-level risk and extinction correlates, including the intrinsic biological traits of geographic range size, body size and taxonomy, and extrinsic geographic settings such as seasonality, habitat type, land use and human population density. Each extinction correlate exhibited ranges of values that were especially associated with risk, and the importance of different risk factors was not geographically uniform across the globe. We also found that about 10% of mammals not currently recognized as at-risk have biological traits and occur in environments that predispose them towards extinction. Southeast Asia had the most actually and potentially threatened species, underscoring the urgent need for conservation in this region. Additionally, nearly 40% of currently threatened species were predicted to experience rapid climate change at 0.5 km/year or more. Biological and environmental correlates of mammalian extinction risk exhibit distinct statistical and geographic distributions. These results provide insight into species-level patterns and processes underlying geographic variation in extinction risk. They also offer guidance for future conservation research focused on specific geographic regions, or evaluating the degree to which species-level patterns mirror spatial variation in the pressures faced by populations within the ranges of individual species. The added impacts from climate change may increase the susceptibility of at-risk species to extinction and expand the regions where mammals are most vulnerable globally.

Spatiotemporal Analysis of Malaria in Urban Ahmedabad (Gujarat), India: Identification of Hot Spots and Risk Factors for Targeted Intervention

PubMed Central

Parizo, Justin; Sturrock, Hugh J. W.; Dhiman, Ramesh C.; Greenhouse, Bryan

2016-01-01

The world population, especially in developing countries, has experienced a rapid progression of urbanization over the last half century. Urbanization has been accompanied by a rise in cases of urban infectious diseases, such as malaria. The complexity and heterogeneity of the urban environment has made study of specific urban centers vital for urban malaria control programs, whereas more generalizable risk factor identification also remains essential. Ahmedabad city, India, is a large urban center located in the state of Gujarat, which has experienced a significant Plasmodium vivax and Plasmodium falciparum disease burden. Therefore, a targeted analysis of malaria in Ahmedabad city was undertaken to identify spatiotemporal patterns of malaria, risk factors, and methods of predicting future malaria cases. Malaria incidence in Ahmedabad city was found to be spatially heterogeneous, but temporally stable, with high spatial correlation between species. Because of this stability, a prediction method utilizing historic cases from prior years and seasons was used successfully to predict which areas of Ahmedabad city would experience the highest malaria burden and could be used to prospectively target interventions. Finally, spatial analysis showed that normalized difference vegetation index, proximity to water sources, and location within Ahmedabad city relative to the dense urban core were the best predictors of malaria incidence. Because of the heterogeneity of urban environments and urban malaria itself, the study of specific large urban centers is vital to assist in allocating resources and informing future urban planning. PMID:27382081

A Further Look at the Prediction of Weapons Effectiveness in Suppressive Fire

DTIC Science & Technology

1979-05-01

official Oeciertmirit Of the .,m’y politiOn. unless 11) designated by other authorized documents. . I tiny~ flggq rr- SECURITY CLASSIFICAT ION OF THIS PAGE...presents the results of an investigation originally designed to determine what aspects of the auditory signatures of passing projectiles are perceived as...suppression is based on a future risk, while reactive suppression is based on a current risk. Nay-or 2 0 implies that weapons designers need more

Burnout in Japanese residents and its associations with temperament and character.

PubMed

Miyoshi, Ryoei; Matsuo, Hisae; Takeda, Ryuichiro; Komatsu, Hiroyuki; Abe, Hiroshi; Ishida, Yasushi

2016-12-01

High risk of burnout in healthcare workers has long been recognized. However, there are no methods to predict vulnerability to burnout. We examined whether temperament and character are associated with burnout and depressive state in residents by using the Temperament and Character Inventory (TCI). The TCI was used for residents at the beginning of clinical training and then the Maslach Burnout Inventory-General Survey (MBI-GS) and the Self-Rating Depression Scale (SDS) were administered at the beginning of clinical training and after four and ten months. Participants were 85 residents who started clinical training after graduating from the University of Miyazaki Hospital in April 2012 and 2013. After ten months, 23.5% of participants were newly identified with burnout using the MBI-GS and 15.3% of participants were newly diagnosed with depressive state using the SDS. We found that residents with high Cooperativeness were significantly more prone to burnout and that residents with high Harm Avoidance and low Self-Directedness were significantly more prone to depressive states. Our results suggest that the TCI can predict not only the risk for future depressive state but also the risk for future burnout. We feel it is important for the resident education system to identify residents with these temperament and character traits and to help high-risk residents avoid burnout and depressive state. Copyright © 2016 Elsevier B.V. All rights reserved.

Childhood obesity as a predictor of morbidity in adulthood: a systematic review and meta-analysis.

PubMed

Llewellyn, A; Simmonds, M; Owen, C G; Woolacott, N

2016-01-01

Obese children are at higher risk of being obese as adults, and adult obesity is associated with an increased risk of morbidity. This systematic review and meta-analysis investigates the ability of childhood body mass index (BMI) to predict obesity-related morbidities in adulthood. Thirty-seven studies were included. High childhood BMI was associated with an increased incidence of adult diabetes (OR 1.70; 95% CI 1.30-2.22), coronary heart disease (CHD) (OR 1.20; 95% CI 1.10-1.31) and a range of cancers, but not stroke or breast cancer. The accuracy of childhood BMI when predicting any adult morbidity was low. Only 31% of future diabetes and 22% of future hypertension and CHD occurred in children aged 12 or over classified as being overweight or obese. Only 20% of all adult cancers occurred in children classified as being overweight or obese. Childhood obesity is associated with moderately increased risks of adult obesity-related morbidity, but the increase in risk is not large enough for childhood BMI to be a good predictor of the incidence of adult morbidities. This is because the majority of adult obesity-related morbidity occurs in adults who were of healthy weight in childhood. Therefore, targeting obesity reduction solely at obese or overweight children may not substantially reduce the overall burden of obesity-related disease in adulthood. © 2015 World Obesity.

Bone mineral content and areal density, but not bone area, predict an incident fracture risk: a comparative study in a UK prospective cohort.

PubMed

Curtis, E M; Harvey, N C; D'Angelo, S; Cooper, C S; Ward, K A; Taylor, P; Pearson, G; Cooper, C

2016-12-01

We studied a prospective UK cohort of women aged 20 to 80 years, assessed by dual-energy X-ray absorptiometry (DXA) at baseline. Bone mineral content (BMC) and areal bone mineral density (aBMD), but not bone area (BA), at femoral neck, lumbar spine and the whole body sites were similarly predictive of incident fractures. Low aBMD, measured by DXA, is a well-established risk factor for future fracture, but little is known about the performance characteristics of other DXA measures such as BA and BMC in fracture prediction. We therefore investigated the predictive value of BA, BMC and aBMD for incident fracture in a prospective cohort of UK women. In this study, 674 women aged 20-80 years, recruited from four GP practices in Southampton, underwent DXA assessment (proximal femur, lumbar spine, total body) between 1991 and 1993. All women were contacted in 1998-1999 with a validated postal questionnaire to collect information on incident fractures and potential confounding factors including medication use. Four hundred forty-three women responded, and all fractures were confirmed by the assessment of images and radiology reports by a research nurse. Cox proportional hazard models were used to explore the risk of incident fracture, and the results are expressed as hazard ratio (HR) per 1 SD decrease in the predictor and 95% CI. Associations were adjusted for age, BMI, alcohol consumption, smoking, HRT, medications and history of fracture. Fifty-five women (12%) reported a fracture. In fully adjusted models, femoral neck BMC and aBMD were similarly predictive of incident fracture. Femoral neck BMC: HR/SD = 1.64 (95%CI: 1.19, 2.26; p = 0.002); femoral neck aBMD: HR/SD = 1.76 (95%CI: 1.19, 2.60; p = 0.005). In contrast, femoral neck BA was not associated with incident fracture, HR/SD = 1.15 (95%CI: 0.88, 1.50; p = 0.32). Similar results were found with bone indices at the lumbar spine and the whole body. In conclusion, BMC and aBMD appear to predict incident fracture with similar HR/SD, even after adjustment for body size. In contrast, BA only weakly predicted the future fracture. These findings support the use of DXA aBMD in fracture risk assessment, but also suggest that factors which specifically influence BMC will have a relevance to the risk of the incident fracture.

Public Response to a Near-Miss Nuclear Accident Scenario Varying in Causal Attributions and Outcome Uncertainty.

PubMed

Cui, Jinshu; Rosoff, Heather; John, Richard S

2018-05-01

Many studies have investigated public reactions to nuclear accidents. However, few studies focused on more common events when a serious accident could have happened but did not. This study evaluated public response (emotional, cognitive, and behavioral) over three phases of a near-miss nuclear accident. Simulating a loss-of-coolant accident (LOCA) scenario, we manipulated (1) attribution for the initial cause of the incident (software failure vs. cyber terrorist attack vs. earthquake), (2) attribution for halting the incident (fail-safe system design vs. an intervention by an individual expert vs. a chance coincidence), and (3) level of uncertainty (certain vs. uncertain) about risk of a future radiation leak after the LOCA is halted. A total of 773 respondents were sampled using a 3 × 3 × 2 between-subjects design. Results from both MANCOVA and structural equation modeling (SEM) indicate that respondents experienced more negative affect, perceived more risk, and expressed more avoidance behavioral intention when the near-miss event was initiated by an external attributed source (e.g., earthquake) compared to an internally attributed source (e.g., software failure). Similarly, respondents also indicated greater negative affect, perceived risk, and avoidance behavioral intentions when the future impact of the near-miss incident on people and the environment remained uncertain. Results from SEM analyses also suggested that negative affect predicted risk perception, and both predicted avoidance behavior. Affect, risk perception, and avoidance behavior demonstrated high stability (i.e., reliability) from one phase to the next. © 2017 Society for Risk Analysis.

Review of fall risk assessment in geriatric populations using inertial sensors

PubMed Central

2013-01-01

Background Falls are a prevalent issue in the geriatric population and can result in damaging physical and psychological consequences. Fall risk assessment can provide information to enable appropriate interventions for those at risk of falling. Wearable inertial-sensor-based systems can provide quantitative measures indicative of fall risk in the geriatric population. Methods Forty studies that used inertial sensors to evaluate geriatric fall risk were reviewed and pertinent methodological features were extracted; including, sensor placement, derived parameters used to assess fall risk, fall risk classification method, and fall risk classification model outcomes. Results Inertial sensors were placed only on the lower back in the majority of papers (65%). One hundred and thirty distinct variables were assessed, which were categorized as position and angle (7.7%), angular velocity (11.5%), linear acceleration (20%), spatial (3.8%), temporal (23.1%), energy (3.8%), frequency (15.4%), and other (14.6%). Fallers were classified using retrospective fall history (30%), prospective fall occurrence (15%), and clinical assessment (32.5%), with 22.5% using a combination of retrospective fall occurrence and clinical assessments. Half of the studies derived models for fall risk prediction, which reached high levels of accuracy (62-100%), specificity (35-100%), and sensitivity (55-99%). Conclusions Inertial sensors are promising sensors for fall risk assessment. Future studies should identify fallers using prospective techniques and focus on determining the most promising sensor sites, in conjunction with determination of optimally predictive variables. Further research should also attempt to link predictive variables to specific fall risk factors and investigate disease populations that are at high risk of falls. PMID:23927446

Predicting the patterns of change in spring onset and false springs in China during the twenty-first century

NASA Astrophysics Data System (ADS)

Zhu, Likai; Meng, Jijun; Li, Feng; You, Nanshan

2017-10-01

Spring onset has generally shifted earlier in China over the past several decades in response to the warming climate. However, future changes in spring onset and false springs, which will have profound effects on ecosystems, are still not well understood. Here, we used the extended form of the Spring Indices model (SI-x) to project changes in the first leaf and first bloom dates, and predicted false springs for the historical (1950-2005) and future (2006-2100) periods based on the downscaled daily maximum/minimum temperatures under two emission scenarios from 21 General Circulation Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5). On average, first leaf and first bloom in China were projected to occur 21 and 23 days earlier, respectively, by the end of the twenty-first century in the Representative Concentration Pathway (RCP) 8.5 scenario. Areas with greater earlier shifts in spring onset were in the warm temperate zone, as well as the north and middle subtropical zones of China. Early false spring risk increased rapidly in the warm temperate and north subtropical zones, while that declined in the cold temperate zone. Relative to early false spring risk, late false spring risk showed a common increase with smaller magnitude in the RCP 8.5 scenario but might cause greater damage to ecosystems because plants tend to become more vulnerable to the later occurrence of a freeze event. We conclude that future climate warming will continue to cause earlier occurrence of spring onset in general, but might counterintuitively increase plant damage risk in natural and agricultural systems of the warm temperate and subtropical China.

Utility of high density lipoprotein particle concentration in predicting future major adverse cardiovascular events among patients undergoing angiography.

PubMed

May, Heidi T; Anderson, Jeffrey L; Winegar, Deborah A; Rollo, Jeffrey; Connelly, Margery A; Otvos, James D; Muhlestein, Joseph B

2016-10-01

HDL-C is recognized to be inversely associated with cardiovascular (CV) risk. However, attenuation of the association of HDL-C with CV risk may occur after adjustment for other lipoprotein parameters and in various disease states, especially in the setting of acute coronary syndrome (ACS). Recently, the number of HDL particles (HDL-P) has been suggested to improve CV risk prediction. Patients (n=2999) in the Intermountain Heart Collaborative Study who underwent angiography and had lipoprotein particle measurements determined by nuclear magnetic resonance (NMR) spectroscopy were studied. Multivariable Cox hazard regression was utilized to evaluate the association of HDL-C, HDL-P, and HDL-P subclasses with future major adverse CV events (MACE: death, myocardial infarction, heart failure, and stroke). Patients averaged 64±12years, 66% male, 26% diabetic, and 42% ACS. At angiography, 65% of patients were diagnosed with coronary artery disease (CAD). HDL-C and HDL-P averaged 41±13mg/dL and 28±8μmol/L, respectively. HDL-P (HR=0.903, p=0.001), but not HDL-C (HR=0.947, p=0.102) was significantly associated with MACE. In a model that included all HDL-P subclasses, both small (HR=0.862, p<0.0001) and medium (HR=0.922, p=0.020) were associated with CV risk, but not large HDL-P (HR=1.0042, p=0.185). Small HDL-P continued to be associated with all of the individual components of MACE, but not stroke. In this study of patients undergoing angiography, HDL-P was a strong, independent predictor of future MACE, with the smaller HDL-P accounting for this association. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Predicting the patterns of change in spring onset and false springs in China during the twenty-first century.

PubMed

Zhu, Likai; Meng, Jijun; Li, Feng; You, Nanshan

2017-10-28

Spring onset has generally shifted earlier in China over the past several decades in response to the warming climate. However, future changes in spring onset and false springs, which will have profound effects on ecosystems, are still not well understood. Here, we used the extended form of the Spring Indices model (SI-x) to project changes in the first leaf and first bloom dates, and predicted false springs for the historical (1950-2005) and future (2006-2100) periods based on the downscaled daily maximum/minimum temperatures under two emission scenarios from 21 General Circulation Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5). On average, first leaf and first bloom in China were projected to occur 21 and 23 days earlier, respectively, by the end of the twenty-first century in the Representative Concentration Pathway (RCP) 8.5 scenario. Areas with greater earlier shifts in spring onset were in the warm temperate zone, as well as the north and middle subtropical zones of China. Early false spring risk increased rapidly in the warm temperate and north subtropical zones, while that declined in the cold temperate zone. Relative to early false spring risk, late false spring risk showed a common increase with smaller magnitude in the RCP 8.5 scenario but might cause greater damage to ecosystems because plants tend to become more vulnerable to the later occurrence of a freeze event. We conclude that future climate warming will continue to cause earlier occurrence of spring onset in general, but might counterintuitively increase plant damage risk in natural and agricultural systems of the warm temperate and subtropical China.

Increased pulse wave velocity in patients with acute lacunar infarction doubled the risk of future ischemic stroke.

PubMed

Saji, Naoki; Murotani, Kenta; Shimizu, Hirotaka; Uehara, Toshiyuki; Kita, Yasushi; Toba, Kenji; Sakurai, Takashi

2017-04-01

The aim of this study was to determine whether pulse wave velocity (PWV), a marker of vascular endothelial impairment and arteriosclerosis, predicts future ischemic stroke in patients who developed acute lacunar infarction. Patients with a first-ever ischemic stroke due to acute lacunar infarction were enrolled in this study. An oscillometric device (Form PWV/ABI; Omron Colin, Tokyo, Japan) was used to measure brachial-ankle PWV 1 week after stroke onset. Patients were followed for at least 5 years. The main end point of the study was recurrent ischemic stroke. Event-free survival was analyzed using Kaplan-Meier plots and log-rank tests. The risk of recurrent ischemic stroke was estimated using the Cox proportional-hazards model. Of the 156 patients (61% male, mean age: 69.2±11.3 years) assessed in this study, 29 developed recurrent ischemic stroke. The median brachial-ankle PWV value was 20.4 m s -1 . Patients with high PWV values had a greater risk of recurrent ischemic stroke than patients with low PWV values (28% vs. 15%, P=0.08). Kaplan-Meier curve analysis showed that patients with high PWV values had a less favorable (that is, free of recurrent ischemic stroke) survival time (P=0.015). A multivariate Cox proportional-hazards model identified high PWV as an independent predictor of recurrent ischemic stroke after adjusting for age, sex and blood pressure (hazard ratio 2.35, 95% confidence interval, 1.02-5.70, P=0.044). In patients with acute lacunar infarction, a high PWV predicts a twofold greater risk of future ischemic stroke, independent of patient age, sex and blood pressure levels.

IDENTIFYING AREAS WITH A HIGH RISK OF HUMAN INFECTION WITH THE AVIAN INFLUENZA A (H7N9) VIRUS IN EAST ASIA

PubMed Central

Fuller, Trevon; Havers, Fiona; Xu, Cuiling; Fang, Li-Qun; Cao, Wu-Chun; Shu, Yuelong; Widdowson, Marc-Alain; Smith, Thomas B.

2014-01-01

Summary Objectives The rapid emergence, spread, and disease severity of avian influenza A(H7N9) in China has prompted concerns about a possible pandemic and regional spread in the coming months. The objective of this study was to predict the risk of future human infections with H7N9 in China and neighboring countries by assessing the association between H7N9 cases at sentinel hospitals and putative agricultural, climatic, and demographic risk factors. Methods This cross-sectional study used the locations of H7N9 cases and negative cases from China’s influenza-like illness surveillance network. After identifying H7N9 risk factors with logistic regression, we used Geographic Information Systems (GIS) to construct predictive maps of H7N9 risk across Asia. Results Live bird market density was associated with human H7N9 infections reported in China from March-May 2013. Based on these cases, our model accurately predicted the virus’ spread into Guangxi autonomous region in February 2014. Outside China, we find there is a high risk that the virus will spread to northern Vietnam, due to the import of poultry from China. Conclusions Our risk map can focus efforts to improve surveillance in poultry and humans, which may facilitate early identification and treatment of human cases. PMID:24642206

Examining overgeneral autobiographical memory as a risk factor for adolescent depression.

PubMed

Rawal, Adhip; Rice, Frances

2012-05-01

Identifying risk factors for adolescent depression is an important research aim. Overgeneral autobiographical memory (OGM) is a feature of adolescent depression and a candidate cognitive risk factor for future depression. However, no study has ascertained whether OGM predicts the onset of adolescent depressive disorder. OGM was investigated as a predictor of depressive disorder and symptoms in a longitudinal study of high-risk adolescents. In addition, cross-sectional associations between OGM and current depression and OGM differences between depressed adolescents with different clinical outcomes were examined over time. A 1-year longitudinal study of adolescents at familial risk for depression (n = 277, 10-18 years old) was conducted. Autobiographical memory was assessed at baseline. Clinical interviews assessed diagnostic status at baseline and follow-up. Currently depressed adolescents showed an OGM bias compared with adolescents with no disorder and those with anxiety or externalizing disorders. OGM to negative cues predicted the onset of depressive disorder and depressive symptoms at follow-up in adolescents free from depressive disorder at baseline. This effect was independent of the contribution of age, IQ, and baseline depressive symptoms. OGM did not predict onset of anxiety or externalizing disorders. Adolescents with depressive disorder at both assessments were not more overgeneral than adolescents who recovered from depressive disorder over the follow-up period. OGM to negative cues predicted the onset of depressive disorder (but not other disorders) and depressive symptoms over time in adolescents at familial risk for depression. Results are consistent with OGM as a risk factor for depression. Copyright © 2012 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

The impact of birth weight on cardiovascular disease risk in the Women's Health Initiative

PubMed Central

Smith, CJ; Ryckman, KK; Barnabei, Vanessa M.; Howard, Barbara; Isasi, Carmen R.; Sarto, Gloria; Tom, Sarah E.; Van Horn, Linda; Wallace, Robert; Robinson, Jennifer G

2016-01-01

Background and Aims Cardiovascular disease (CVD) is among the leading causes of morbidity and mortality worldwide. Traditional risk factors predict 75-80% of an individual's risk of incident CVD. However, the role of early life experiences in future disease risk is gaining attention. The Barker hypothesis proposes fetal origins of adult disease, with consistent evidence demonstrating the deleterious consequences of birth weight outside the normal range. In this study, we investigate the role of birth weight in CVD risk prediction. Methods and Results The Women's Health Initiative (WHI) represents a large national cohort of post-menopausal women with 63 815 participants included in this analysis. Univariable proportional hazards regression analyses evaluated the association of 4 self-reported birth weight categories against 3 CVD outcome definitions, which included indicators of coronary heart disease, ischemic stroke, coronary revascularization, carotid artery disease and peripheral arterial disease. The role of birth weight was also evaluated for prediction of CVD events in the presence of traditional risk factors using 3 existing CVD risk prediction equations: one body mass index (BMI)-based and two laboratory-based models. Low birth weight (LBW) (< 6 lbs.) was significantly associated with all CVD outcome definitions in univariable analyses (HR=1.086, p=0.009). LBW was a significant covariate in the BMI-based model (HR=1.128, p<0.0001) but not in the lipid-based models. Conclusion LBW (<6 lbs.) is independently associated with CVD outcomes in the WHI cohort. This finding supports the role of the prenatal and postnatal environment in contributing to the development of adult chronic disease. PMID:26708645

Risk-cost-benefit analysis of atrazine in drinking water from agricultural activities and policy implications

NASA Astrophysics Data System (ADS)

Tesfamichael, Aklilu A.; Caplan, Arthur J.; Kaluarachchi, Jagath J.

2005-05-01

This study provides an improved methodology for investigating the trade-offs between the health risks and economic benefits of using atrazine in the agricultural sector by incorporating public attitude to pesticide management in the analysis. Regression models are developed to predict finished water atrazine concentration in high-risk community water supplies in the United States. The predicted finished water atrazine concentrations are then used in a health risk assessment. The computed health risks are compared with the total economic surplus in the U.S. corn market for different atrazine application rates using estimated demand and supply functions developed in this work. Analysis of different scenarios with consumer price premiums for chemical-free and reduced-chemical corn indicate that if the society is willing to pay a price premium, risks can be reduced without a large reduction in the total economic surplus and net benefits may be higher. The results also show that this methodology provides an improved scientific framework for future decision making and policy evaluation in pesticide management.

Resilient parenting of children at developmental risk across middle childhood.

PubMed

Ellingsen, Ruth; Baker, Bruce L; Blacher, Jan; Crnic, Keith

2014-06-01

This paper focuses on factors that might influence positive parenting during middle childhood when a parent faces formidable challenges defined herein as "resilient parenting." Data were obtained from 162 families at child age 5 and 8 years. Using an adapted ABCX model, we examined three risk domains (child developmental delay, child ADHD/ODD diagnosis, and low family income) and three protective factors (mother's education, health, and optimism). The outcome of interest was positive parenting as coded from mother-child interactions. We hypothesized that each of the risk factors would predict poorer parenting and that higher levels of each protective factor would buffer the risk-parenting relationship. Positive parenting scores decreased across levels of increasing risk. Maternal optimism appeared to be a protective factor for resilient parenting concurrently at age 5 and predictively to age 8, as well as a predictor of positive change in parenting from age 5 to age 8, above and beyond level of risk. Maternal education and health were not significantly protective for positive parenting. Limitations, future directions, and implications for intervention are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Resilient Parenting of Children at Developmental Risk Across Middle Childhood

PubMed Central

Baker, Bruce L.; Blacher, Jan; Crnic, Keith

2015-01-01

This paper focuses on factors that might influence positive parenting during middle childhood when a parent faces formidable challenges defined herein as “resilient parenting.” Data were obtained from 162 families at child age 5 and 8 years. Using an adapted ABCX model, we examined three risk domains (child developmental delay, child ADHD/ODD diagnosis, and low family income) and three protective factors (mother’s education, health, and optimism). The outcome of interest was positive parenting as coded from mother-child interactions. We hypothesized that each of the risk factors would predict poorer parenting and that higher levels of each protective factor would buffer the risk-parenting relationship. Positive parenting scores decreased across levels of increasing risk. Maternal optimism appeared to be a protective factor for resilient parenting concurrently at age 5 and predictively to age 8, as well as a predictor of positive change in parenting from age 5 to age 8, above and beyond level of risk. Maternal education and health were not significantly protective for positive parenting. Limitations, future directions, and implications for intervention are discussed. PMID:24713516

Predicting the distributions of predator (snow leopard) and prey (blue sheep) under climate change in the Himalaya.

PubMed

Aryal, Achyut; Shrestha, Uttam Babu; Ji, Weihong; Ale, Som B; Shrestha, Sujata; Ingty, Tenzing; Maraseni, Tek; Cockfield, Geoff; Raubenheimer, David

2016-06-01

Future climate change is likely to affect distributions of species, disrupt biotic interactions, and cause spatial incongruity of predator-prey habitats. Understanding the impacts of future climate change on species distribution will help in the formulation of conservation policies to reduce the risks of future biodiversity losses. Using a species distribution modeling approach by MaxEnt, we modeled current and future distributions of snow leopard (Panthera uncia) and its common prey, blue sheep (Pseudois nayaur), and observed the changes in niche overlap in the Nepal Himalaya. Annual mean temperature is the major climatic factor responsible for the snow leopard and blue sheep distributions in the energy-deficient environments of high altitudes. Currently, about 15.32% and 15.93% area of the Nepal Himalaya are suitable for snow leopard and blue sheep habitats, respectively. The bioclimatic models show that the current suitable habitats of both snow leopard and blue sheep will be reduced under future climate change. The predicted suitable habitat of the snow leopard is decreased when blue sheep habitats is incorporated in the model. Our climate-only model shows that only 11.64% (17,190 km(2)) area of Nepal is suitable for the snow leopard under current climate and the suitable habitat reduces to 5,435 km(2) (reduced by 24.02%) after incorporating the predicted distribution of blue sheep. The predicted distribution of snow leopard reduces by 14.57% in 2030 and by 21.57% in 2050 when the predicted distribution of blue sheep is included as compared to 1.98% reduction in 2030 and 3.80% reduction in 2050 based on the climate-only model. It is predicted that future climate may alter the predator-prey spatial interaction inducing a lower degree of overlap and a higher degree of mismatch between snow leopard and blue sheep niches. This suggests increased energetic costs of finding preferred prey for snow leopards - a species already facing energetic constraints due to the limited dietary resources in its alpine habitat. Our findings provide valuable information for extension of protected areas in future.

Risk Preferences and Predictions about Others: No Association with 2D:4D Ratio

PubMed Central

Lima de Miranda, Katharina; Neyse, Levent; Schmidt, Ulrich

2018-01-01

Prenatal androgen exposure affects the brain development of the fetus which may facilitate certain behaviors and decision patterns in the later life. The ratio between the lengths of second and the fourth fingers (2D:4D) is a negative biomarker of the ratio between prenatal androgen and estrogen exposure and men typically have lower ratios than women. In line with the typical findings suggesting that women are more risk averse than men, several studies have also shown negative relationships between 2D:4D and risk taking although the evidence is not conclusive. Previous studies have also reported that both men and women believe women are more risk averse than men. In the current study, we re-test the relationship between 2D:4D and risk preferences in a German student sample and also investigate whether the 2D:4D ratio is associated with people’s perceptions about others’ risk preferences. Following an incentivized risk elicitation task, we asked all participants their predictions about (i) others’ responses (without sex specification), (ii) men’s responses, and (iii) women’s responses; then measured their 2D:4D ratios. In line with the previous findings, female participants in our sample were more risk averse. While both men and women underestimated other participants’ (non sex-specific) and women’s risky decisions on average, their predictions about men were accurate. We also found evidence for the false consensus effect, as risky choices are positively correlated with predictions about other participants’ risky choices. The 2D:4D ratio was not directly associated either with risk preferences or the predictions of other participants’ choices. An unexpected finding was that women with mid-range levels of 2D:4D estimated significantly larger sex differences in participants’ decisions. This finding needs further testing in future studies. PMID:29472846

Assessing the pollution risk of a groundwater source field at western Laizhou Bay under seawater intrusion

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

Zeng, Xiankui; Wu, Jichun; Wang, Dong, E-mail: wangdong@nju.edu.cn

Coastal areas have great significance for human living, economy and society development in the world. With the rapid increase of pressures from human activities and climate change, the safety of groundwater resource is under the threat of seawater intrusion in coastal areas. The area of Laizhou Bay is one of the most serious seawater intruded areas in China, since seawater intrusion phenomenon was firstly recognized in the middle of 1970s. This study assessed the pollution risk of a groundwater source filed of western Laizhou Bay area by inferring the probability distribution of groundwater Cl{sup −} concentration. The numerical model ofmore » seawater intrusion process is built by using SEAWAT4. The parameter uncertainty of this model is evaluated by Markov Chain Monte Carlo (MCMC) simulation, and DREAM{sub (ZS)} is used as sampling algorithm. Then, the predictive distribution of Cl{sup -} concentration at groundwater source field is inferred by using the samples of model parameters obtained from MCMC. After that, the pollution risk of groundwater source filed is assessed by the predictive quantiles of Cl{sup -} concentration. The results of model calibration and verification demonstrate that the DREAM{sub (ZS)} based MCMC is efficient and reliable to estimate model parameters under current observation. Under the condition of 95% confidence level, the groundwater source point will not be polluted by seawater intrusion in future five years (2015–2019). In addition, the 2.5% and 97.5% predictive quantiles show that the Cl{sup −} concentration of groundwater source field always vary between 175 mg/l and 200 mg/l. - Highlights: • The parameter uncertainty of seawater intrusion model is evaluated by MCMC. • Groundwater source field won’t be polluted by seawater intrusion in future 5 years. • The pollution risk is assessed by the predictive quantiles of Cl{sup −} concentration.« less

Attitudes to mesalamine questionnaire: a novel tool to predict mesalamine nonadherence in patients with IBD.

PubMed

Moss, Alan C; Lillis, Yvonne; Edwards George, Jessica B; Choudhry, Niteesh K; Berg, Anders H; Cheifetz, Adam S; Horowitz, Gary; Leffler, Dan A

2014-12-01

Poor adherence to mesalamine is common and driven by a combination of lifestyle and behavioral factors, as well as health beliefs. We sought to develop a valid tool to identify barriers to patient adherence and predict those at risk for future nonadherence. A 10-item survey was developed from patient-reported barriers to adherence. The survey was administered to 106 patients with ulcerative colitis who were prescribed mesalamine, and correlated with prospectively collected 12-month pharmacy refills (medication possession ratio (MPR)), urine levels of salicylates, and self-reported adherence (Morisky Medication Adherence Scale (MMAS)-8). From the initial 10-item survey, 8 items correlated highly with the MMAS-8 score at enrollment. Computer-generated randomization produced a derivation cohort of 60 subjects and a validation cohort of 46 subjects to assess the survey items in their ability to predict future adherence. Two items from the patient survey correlated with objective measures of long-term adherence: their belief in the importance of maintenance mesalamine even when in remission and their concerns about side effects. The additive score based on these two items correlated with 12-month MPR in both the derivation and validation cohorts (P<0.05). Scores on these two items were associated with a higher risk of being nonadherent over the subsequent 12 months (relative risk (RR) =2.2, 95% confidence interval=1.5-3.5, P=0.04). The area under the curve for the performance of this 2-item tool was greater than that of the 10-item MMAS-8 score for predicting MPR scores over 12 months (area under the curve 0.7 vs. 0.5). Patients' beliefs about the need for maintenance mesalamine and their concerns about side effects influence their adherence to mesalamine over time. These concerns could easily be raised in practice to identify patients at risk of nonadherence (Clinical Trial number NCT01349504).

Football Players' Perceptions of Future Risk of Concussion and Concussion-Related Health Outcomes.

PubMed

Baugh, Christine M; Kroshus, Emily; Kiernan, Patrick T; Mendel, David; Meehan, William P

2017-02-15

Concussion is increasingly recognized as a risk of participation in contact and collision sports. There have been few examinations of athletes' perceptions of their susceptibility to concussion or concussion-related health consequences. We examine college football players' perceptions of their risk of sustaining a concussion and concussion-related health consequences in their future, whether these perceptions change over time, and how concussion history is related to perceived future risk of concussion and concussion-related health consequences. A survey was administered to National Collegiate Athletic Association Division I Football Championship Series athletes on 10 teams in 2013 and to nine of those teams in 2014. Athletes answered questions assessing their perceptions of concussion and potential concussion-related health consequences. Approximately 40% of athletes believed there was a strong possibility that they would sustain a concussion in the future, while approximately one-in-four thought a concussion would make them miss a few games. About one-in-10 athletes predicted dementia, Alzheimer's disease, or chronic traumatic encephalopathy would develop from concussions. These beliefs were stronger among athletes who had sustained previous concussions. Across the two years studied, athletes' perceptions of the risk of concussion and missing a few games because of concussion decreased significantly. Overall, a substantial proportion of college football players believe they will have long-term health consequences as a result of sustaining sport-related concussions. The true incidence and prevalence of many of these outcomes are unknown. Further research is needed to determine whether athletes have an accurate perception of the risks of these outcomes developing.

Football Players' Perceptions of Future Risk of Concussion and Concussion-Related Health Outcomes

PubMed Central

Kroshus, Emily; Kiernan, Patrick T.; Mendel, David; Meehan, William P.

2017-01-01

Abstract Concussion is increasingly recognized as a risk of participation in contact and collision sports. There have been few examinations of athletes' perceptions of their susceptibility to concussion or concussion-related health consequences. We examine college football players' perceptions of their risk of sustaining a concussion and concussion-related health consequences in their future, whether these perceptions change over time, and how concussion history is related to perceived future risk of concussion and concussion-related health consequences. A survey was administered to National Collegiate Athletic Association Division I Football Championship Series athletes on 10 teams in 2013 and to nine of those teams in 2014. Athletes answered questions assessing their perceptions of concussion and potential concussion-related health consequences. Approximately 40% of athletes believed there was a strong possibility that they would sustain a concussion in the future, while approximately one-in-four thought a concussion would make them miss a few games. About one-in-10 athletes predicted dementia, Alzheimer's disease, or chronic traumatic encephalopathy would develop from concussions. These beliefs were stronger among athletes who had sustained previous concussions. Across the two years studied, athletes' perceptions of the risk of concussion and missing a few games because of concussion decreased significantly. Overall, a substantial proportion of college football players believe they will have long-term health consequences as a result of sustaining sport-related concussions. The true incidence and prevalence of many of these outcomes are unknown. Further research is needed to determine whether athletes have an accurate perception of the risks of these outcomes developing. PMID:27526721

Assessing habitat risk from human activities to inform coastal and marine spatial planning: a demonstration in Belize

NASA Astrophysics Data System (ADS)

Arkema, Katie K.; Verutes, Gregory; Bernhardt, Joanna R.; Clarke, Chantalle; Rosado, Samir; Canto, Maritza; Wood, Spencer A.; Ruckelshaus, Mary; Rosenthal, Amy; McField, Melanie; de Zegher, Joann

2014-11-01

Integrated coastal and ocean management requires transparent and accessible approaches for understanding the influence of human activities on marine environments. Here we introduce a model for assessing the combined risk to habitats from multiple ocean uses. We apply the model to coral reefs, mangrove forests and seagrass beds in Belize to inform the design of the country’s first Integrated Coastal Zone Management (ICZM) Plan. Based on extensive stakeholder engagement, review of existing legislation and data collected from diverse sources, we map the current distribution of coastal and ocean activities and develop three scenarios for zoning these activities in the future. We then estimate ecosystem risk under the current and three future scenarios. Current levels of risk vary spatially among the nine coastal planning regions in Belize. Empirical tests of the model are strong—three-quarters of the measured data for coral reef health lie within the 95% confidence interval of interpolated model data and 79% of the predicted mangrove occurrences are associated with observed responses. The future scenario that harmonizes conservation and development goals results in a 20% reduction in the area of high-risk habitat compared to the current scenario, while increasing the extent of several ocean uses. Our results are a component of the ICZM Plan for Belize that will undergo review by the national legislature in 2015. This application of our model to marine spatial planning in Belize illustrates an approach that can be used broadly by coastal and ocean planners to assess risk to habitats under current and future management scenarios.

Religiosity and Risky Sexual Behaviors among an African American Church-based Population

PubMed Central

Hawes, Starlyn M.; Berkley-Patton, Jannette Y.

2014-01-01

African Americans are disproportionately burdened by STDs and HIV in the US. This study examined the relationships between demographics, religiosity, and sexual risk behaviors among 255 adult African American church-based participants. Although participants were highly religious, they reported an average of seven lifetime sex partners and most inconsistently used condoms. Several demographic variables and religiosity significantly predicted lifetime HIV-related risk factors. Taken together, findings indicated that this population is at risk for HIV. Future research should continue to identify correlates of risky sexual behavior among African American parishioners to facilitate the development of HIV risk reduction interventions in their church settings. PMID:23054481

Stress testing hydrologic models using bottom-up climate change assessment

NASA Astrophysics Data System (ADS)

Stephens, C.; Johnson, F.; Marshall, L. A.

2017-12-01

Bottom-up climate change assessment is a promising approach for understanding the vulnerability of a system to potential future changes. The technique has been utilised successfully in risk-based assessments of future flood severity and infrastructure vulnerability. We find that it is also an ideal tool for assessing hydrologic model performance in a changing climate. In this study, we applied bottom-up climate change to compare the performance of two different hydrologic models (an event-based and a continuous model) under increasingly severe climate change scenarios. This allowed us to diagnose likely sources of future prediction error in the two models. The climate change scenarios were based on projections for southern Australia, which indicate drier average conditions with increased extreme rainfall intensities. We found that the key weakness in using the event-based model to simulate drier future scenarios was the model's inability to dynamically account for changing antecedent conditions. This led to increased variability in model performance relative to the continuous model, which automatically accounts for the wetness of a catchment through dynamic simulation of water storages. When considering more intense future rainfall events, representation of antecedent conditions became less important than assumptions around (non)linearity in catchment response. The linear continuous model we applied may underestimate flood risk in a future climate with greater extreme rainfall intensity. In contrast with the recommendations of previous studies, this indicates that continuous simulation is not necessarily the key to robust flood modelling under climate change. By applying bottom-up climate change assessment, we were able to understand systematic changes in relative model performance under changing conditions and deduce likely sources of prediction error in the two models.

Plasma Lipidomic Profiles Improve on Traditional Risk Factors for the Prediction of Cardiovascular Events in Type 2 Diabetes Mellitus.

PubMed

Alshehry, Zahir H; Mundra, Piyushkumar A; Barlow, Christopher K; Mellett, Natalie A; Wong, Gerard; McConville, Malcolm J; Simes, John; Tonkin, Andrew M; Sullivan, David R; Barnes, Elizabeth H; Nestel, Paul J; Kingwell, Bronwyn A; Marre, Michel; Neal, Bruce; Poulter, Neil R; Rodgers, Anthony; Williams, Bryan; Zoungas, Sophia; Hillis, Graham S; Chalmers, John; Woodward, Mark; Meikle, Peter J

2016-11-22

Clinical lipid measurements do not show the full complexity of the altered lipid metabolism associated with diabetes mellitus or cardiovascular disease. Lipidomics enables the assessment of hundreds of lipid species as potential markers for disease risk. Plasma lipid species (310) were measured by a targeted lipidomic analysis with liquid chromatography electrospray ionization-tandem mass spectrometry on a case-cohort (n=3779) subset from the ADVANCE trial (Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation). The case-cohort was 61% male with a mean age of 67 years. All participants had type 2 diabetes mellitus with ≥1 additional cardiovascular risk factors, and 35% had a history of macrovascular disease. Weighted Cox regression was used to identify lipid species associated with future cardiovascular events (nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death) and cardiovascular death during a 5-year follow-up period. Multivariable models combining traditional risk factors with lipid species were optimized with the Akaike information criteria. C statistics and NRIs were calculated within a 5-fold cross-validation framework. Sphingolipids, phospholipids (including lyso- and ether- species), cholesteryl esters, and glycerolipids were associated with future cardiovascular events and cardiovascular death. The addition of 7 lipid species to a base model (14 traditional risk factors and medications) to predict cardiovascular events increased the C statistic from 0.680 (95% confidence interval [CI], 0.678-0.682) to 0.700 (95% CI, 0.698-0.702; P<0.0001) with a corresponding continuous NRI of 0.227 (95% CI, 0.219-0.235). The prediction of cardiovascular death was improved with the incorporation of 4 lipid species into the base model, showing an increase in the C statistic from 0.740 (95% CI, 0.738-0.742) to 0.760 (95% CI, 0.757-0.762; P<0.0001) and a continuous net reclassification index of 0.328 (95% CI, 0.317-0.339). The results were validated in a subcohort with type 2 diabetes mellitus (n=511) from the LIPID trial (Long-Term Intervention With Pravastatin in Ischemic Disease). The improvement in the prediction of cardiovascular events, above traditional risk factors, demonstrates the potential of plasma lipid species as biomarkers for cardiovascular risk stratification in diabetes mellitus. URL: https://clinicaltrials.gov. Unique identifier: NCT00145925. © 2016 American Heart Association, Inc.

Chemical Risk Assessment: Traditional vs Public Health ...

EPA Pesticide Factsheets

Preventing adverse health impacts from exposures to environmental chemicals is fundamental to protecting individual and public health. When done efficiently and properly, chemical risk assessment enables risk management actions that minimize the incidence and impacts of environmentally-induced diseases related to chemical exposure. However, traditional chemical risk assessment is faced with multiple challenges with respect to predicting and preventing disease in human populations, and epidemiological studies increasingly report observations of adverse health effects at exposure levels predicted from animal studies to be safe for humans. This discordance reinforces concerns about the adequacy of contemporary risk assessment practices (Birnbaum, Burke, & Jones, 2016) for protecting public health. It is becoming clear that to protect public health more effectively, future risk assessments will need to use the full range of available data, draw on innovative methods to integrate diverse data streams, and consider health endpoints that also reflect the range of subtle effects and morbidities observed in human populations. Given these factors, there is a need to reframe chemical risk assessment to be more clearly aligned with the public health goal of minimizing environmental exposures associated with disease. Preventing adverse health impacts from exposures to environmental chemicals is fundamental to protecting individual and public health. Chemical risk assessments

Sleep characteristics, body mass index, and risk for hypertension in young adolescents.

PubMed

Peach, Hannah; Gaultney, Jane F; Reeve, Charlie L

2015-02-01

Inadequate sleep has been identified as a risk factor for a variety of health consequences. For example, short sleep durations and daytime sleepiness, an indicator of insufficient sleep and/or poor sleep quality, have been identified as risk factors for hypertension in the adult population. However, less evidence exists regarding whether these relationships hold within child and early adolescent samples and what factors mediate the relationship between sleep and risk for hypertension. Using data from the Study of Early Child Care and Youth Development, the present study examined body mass index (BMI) as a possible mediator for the effects of school-night sleep duration, weekend night sleep duration, and daytime sleepiness on risk for hypertension in a sample of sixth graders. The results demonstrated gender-specific patterns. Among boys, all three sleep characteristics predicted BMI and yielded significant indirect effects on risk for hypertension. Oppositely, only daytime sleepiness predicted BMI among girls and yielded a significant indirect effect on risk for hypertension. The findings provide clarification for the influence of sleep on the risk for hypertension during early adolescence and suggest a potential need for gender-specific designs in future research and application endeavors.

Longitudinal Pathways from Cumulative Contextual Risk at Birth to School Functioning in Adolescence: Analysis of Mediation Effects and Gender Moderation.

PubMed

January, Stacy-Ann A; Mason, W Alex; Savolainen, Jukka; Solomon, Starr; Chmelka, Mary B; Miettunen, Jouko; Veijola, Juha; Moilanen, Irma; Taanila, Anja; Järvelin, Marjo-Riitta

2017-01-01

Children and adolescents exposed to multiple contextual risks are more likely to have academic difficulties and externalizing behavior problems than those who experience fewer risks. This study used data from the Northern Finland Birth Cohort 1986 (a population-based study; N = 6961; 51 % female) to investigate (a) the impact of cumulative contextual risk at birth on adolescents' academic performance and misbehavior in school, (b) learning difficulties and/or externalizing behavior problems in childhood as intervening mechanisms in the association of cumulative contextual risk with functioning in adolescence, and (c) potential gender differences in the predictive associations of cumulative contextual risk at birth with functioning in childhood or adolescence. The results of the structural equation modeling analysis suggested that exposure to cumulative contextual risk at birth had negative associations with functioning 16 years later, and academic difficulties and externalizing behavior problems in childhood mediated some of the predictive relations. Gender, however, did not moderate any of the associations. Therefore, the findings of this study have implications for the prevention of learning and conduct problems in youth and future research on the impact of cumulative risk exposure.

Longitudinal Pathways from Cumulative Contextual Risk at Birth to School Functioning in Adolescence: Analysis of Mediation Effects and Gender Moderation

PubMed Central

January, Stacy-Ann A.; Mason, W. Alex; Savolainen, Jukka; Solomon, Starr; Chmelka, Mary B.; Miettunen, Jouko; Veijola, Juha; Moilanen, Irma; Taanila, Anja; Järvelin, Marjo-Riitta

2016-01-01

Children and adolescents exposed to multiple contextual risks are more likely to have academic difficulties and externalizing behavior problems than those who experience fewer risks. This study used data from the Northern Finland Birth Cohort 1986 (a population-based study; N = 6,961; 51% female) to investigate (a) the impact of cumulative contextual risk at birth on adolescents’ academic performance and misbehavior in school, (b) learning difficulties and/or externalizing behavior problems in childhood as intervening mechanisms in the association of cumulative contextual risk with functioning in adolescence, and (c) potential gender differences in the predictive associations of cumulative contextual risk at birth with functioning in childhood or adolescence. The results of the structural equation modeling analysis suggested that exposure to cumulative contextual risk at birth had negative associations with functioning 16 years later, and academic difficulties and externalizing behavior problems in childhood mediated some of the predictive relations. Gender, however, did not moderate any of the associations. Therefore, the findings of this study have implications for the prevention of learning and conduct problems in youth and future research on the impact of cumulative risk exposure. PMID:27665276

A resilience perspective to water risk management: case-study application of the adaptation tipping point method

NASA Astrophysics Data System (ADS)

Gersonius, Berry; Ashley, Richard; Jeuken, Ad; Nasruddin, Fauzy; Pathirana, Assela; Zevenbergen, Chris

2010-05-01

In a context of high uncertainty about hydrological variables due to climate change and other factors, the development of updated risk management approaches is as important as—if not more important than—the provision of improved data and forecasts of the future. Traditional approaches to adaptation attempt to manage future water risks to cities with the use of the predict-then-adapt method. This method uses hydrological change projections as the starting point to identify adaptive strategies, which is followed by analysing the cause-effect chain based on some sort of Pressures-State-Impact-Response (PSIR) scheme. The predict-then-adapt method presumes that it is possible to define a singular (optimal) adaptive strategy according to a most likely or average projection of future change. A key shortcoming of the method is, however, that the planning of water management structures is typically decoupled from forecast uncertainties and is, as such, inherently inflexible. This means that there is an increased risk of under- or over-adaptation, resulting in either mal-functioning or unnecessary costs. Rather than taking a traditional approach, responsible water risk management requires an alternative approach to adaptation that recognises and cultivates resiliency for change. The concept of resiliency relates to the capability of complex socio-technical systems to make aspirational levels of functioning attainable despite the occurrence of possible changes. Focusing on resiliency does not attempt to reduce uncertainty associated with future change, but rather to develop better ways of managing it. This makes it a particularly relevant perspective for adaptation to long-term hydrological change. Although resiliency is becoming more refined as a theory, the application of the concept to water risk management is still in an initial phase. Different methods are used in practice to support the implementation of a resilience-focused approach. Typically these approaches start the identification and analysis of adaptive strategies at the end of PSIR scheme: impact and examine whether, and for how long, current risk management strategies will continue to be effective under different future conditions. The most noteworthy application of this approach is the adaptation tipping point method. Adaptation tipping points (ATP) are defined as the points where the magnitude of change is such that the current risk management strategy can no longer meet its objectives. In the ATP method, policy objectives, determining aspirational functioning, are taken as the starting point. Also, the current measures to achieve these objectives are described. This is followed by a sensitivity analysis to determine the optimal and critical boundary conditions (state). Lastly, the state is related to pressures in terms of future change. It should be noted that in the ATP method the driver for adopting a new risk management strategy is not future change as such, but rather failing to meet the policy objectives. In the current paper, the ATP method is applied to the case study of an existing stormwater system in Dordrecht (the Netherlands). This application shows the potential of the ATP method to reduce the complexity of implementing a resilience-focused approach to water risk management. It is expected that this will help foster greater practical relevance of resilience as a perspective for the planning of water management structures.

Non-traditional Serum Lipid Variables and Recurrent Stroke Risk

PubMed Central

Park, Jong-Ho; Lee, Juneyoung; Ovbiagele, Bruce

2014-01-01

Background and Purpose Expert consensus guidelines recommend low-density lipoprotein cholesterol (LDL-C) as the primary serum lipid target for recurrent stroke risk reduction. However, mounting evidence suggests that other lipid parameters might be additional therapeutic targets or at least also predict cardiovascular risk. Little is known about the effects of non-traditional lipid variables on recurrent stroke risk. Methods We analyzed the Vitamin Intervention for Stroke Prevention study database comprising 3680 recent (<120 days) ischemic stroke patients followed up for 2 years. Independent associations of baseline serum lipid variables with recurrent ischemic stroke (primary outcome) and the composite endpoint of ischemic stroke/coronary heart disease (CHD)/vascular death (secondary outcomes) were assessed. Results Of all variables evaluated, only triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C) ratio was consistently and independently related to both outcomes: compared with the lowest quintile, the highest TG/HDL-C ratio quintile was associated with stroke (adjusted hazard ratio, 1.56; 95% CI, 1.05−2.32) and stroke/CHD/vascular death (1.39; 1.05−1.83), including adjustment for lipid modifier use. Compared with the lowest quintile, the highest total cholesterol/HDL-C ratio quintile was associated with stroke/CHD/vascular death (1.45; 1.03−2.03). LDL-C/HDL-C ratio, non-HDL-C, elevated TG alone, and low HDL-C alone were not independently linked to either outcome. Conclusions Of various non-traditional lipid variables, elevated baseline TG/HDL-C and TC/HDL-C ratios predict future vascular risk after a stroke, but only elevated TG/HDL-C ratio is related to risk of recurrent stroke. Future studies should assess the role of TG/HDL as a potential therapeutic target for global vascular risk reduction after stroke. PMID:25236873

Postoperative Mortality after Liver Resection for Perihilar Cholangiocarcinoma: Development of a Risk Score and Importance of Biliary Drainage of the Future Liver Remnant

PubMed Central

Wiggers, Jimme K; Koerkamp, Bas Groot; Cieslak, Kasia P; Doussot, Alexandre; van Klaveren, David; Allen, Peter J; Besselink, Marc G; Busch, Olivier R; D’Angelica, Michael I; DeMatteo, Ronald P; Gouma, Dirk J; Kingham, T Peter; van Gulik, Thomas M; Jarnagin, William R

2016-01-01

Background Liver surgery for perihilar cholangiocarcinoma (PHC) is associated with postoperative mortality ranging from 5% to 18%. The aim of this study was to develop a preoperative risk score for postoperative mortality after liver resection for PHC, and to assess the effect of biliary drainage of the future liver remnant (FLR). Study design A consecutive series of 287 patients submitted to major liver resection for presumed PHC between 1997 and 2014 at two Western centers was analyzed; 228 patients (79%) underwent preoperative drainage for jaundice. FLR volumes were calculated with CT volumetry, and completeness of FLR drainage was assessed on imaging. Logistic regression was used to develop a mortality risk score. Results Postoperative mortality at 90-days was 14%, and was independently predicted by age (Odds ratio [OR] per 10 years 2.1), preoperative cholangitis (OR 4.1), FLR volume below 30% (OR 2.9), portal vein reconstruction (OR 2.3), and incomplete FLR drainage in patients with FLR volume below 50% (OR 2.8). The risk score showed good discrimination (AUC 0.75 after bootstrap validation), and ranking patients in tertiles identified three (low-intermediate-high) risk subgroups with predicted mortalities of 2%, 11%, and 37%. No postoperative mortality was observed in 33 undrained patients with FLR volumes above 50%, including 10 jaundiced patients (median bilirubin level 11 mg/dL). Conclusions The mortality risk score for patients with resectable PHC can be used for patient counseling and identification of modifiable risk factors, which include FLR volume, FLR drainage status, and preoperative cholangitis. We found no evidence to support preoperative biliary drainage in patients with an FLR volume above 50%. PMID:27063572

The value of a registry negative urine pregnancy test for the prediction of a future unintended pregnancy among young women.

PubMed

Rottenstreich, Misgav; Grisaru-Granovsky, Sorina; Rottenstreich, Amihai

2018-06-01

Performance of urine pregnancy test in general adolescents' clinic reflects caregiver or woman's concern that there might be a pregnancy. We aimed to assess whether young-unmarried women in whom a negative urine pregnancy test was registered would be at increased risk of a future unintended pregnancy. The study cohort included consecutive women drafted by the Israeli military between 2013 and 2015. The risk of unintended pregnancy was compared between women with a negative urine pregnancy test (n = 2774), the study group, and those in whom urine pregnancy test was not carried out (n = 126,659), the control group. During the study period, 2147 (1.7%) women experienced an unintended pregnancy. The risk of unintended pregnancy was significantly higher in patients in whom a past pregnancy test was negative 4.3% (n = 118), as compared with the control group 1.6% (n = 2028) (odds ratio [OR], 2.7; 95% confidence interval [CI], 2.23-3.26). In multivariate analysis history of a negative pregnancy test results was an independent predictor for a future unintended pregnancy (adjusted OR, 2.0; 95% CI, 1.63-2.52). A history of a negative pregnancy test among young conscripted women is a significant risk indicator for a future unintended pregnancy. Directed efforts should be made in this particular vulnerable group of patients.

Drivers and hotspots of extinction risk in marine mammals.

PubMed

Davidson, Ana D; Boyer, Alison G; Kim, Hwahwan; Pompa-Mansilla, Sandra; Hamilton, Marcus J; Costa, Daniel P; Ceballos, Gerardo; Brown, James H

2012-02-28

The world's oceans are undergoing profound changes as a result of human activities. However, the consequences of escalating human impacts on marine mammal biodiversity remain poorly understood. The International Union for the Conservation of Nature (IUCN) identifies 25% of marine mammals as at risk of extinction, but the conservation status of nearly 40% of marine mammals remains unknown due to insufficient data. Predictive models of extinction risk are crucial to informing present and future conservation needs, yet such models have not been developed for marine mammals. In this paper, we: (i) used powerful machine-learning and spatial-modeling approaches to understand the intrinsic and extrinsic drivers of marine mammal extinction risk; (ii) used this information to predict risk across all marine mammals, including IUCN "Data Deficient" species; and (iii) conducted a spatially explicit assessment of these results to understand how risk is distributed across the world's oceans. Rate of offspring production was the most important predictor of risk. Additional predictors included taxonomic group, small geographic range area, and small social group size. Although the interaction of both intrinsic and extrinsic variables was important in predicting risk, overall, intrinsic traits were more important than extrinsic variables. In addition to the 32 species already on the IUCN Red List, our model identified 15 more species, suggesting that 37% of all marine mammals are at risk of extinction. Most at-risk species occur in coastal areas and in productive regions of the high seas. We identify 13 global hotspots of risk and show how they overlap with human impacts and Marine Protected Areas.

Technology-based interpersonal victimization: predictors of patterns of victimization over time.

PubMed

Korchmaros, Josephine D; Mitchell, Kimberly J; Ybarra, Michele L

2014-05-01

The objective of this study was to identify factors that could predict youth's future technology-based interpersonal victimization and the pattern of that future victimization over time. Data from Growing up With Media, a national, longitudinal, online study were analyzed. At baseline, participants (N = 1,018) were 10- to 15-year-old English speakers who had used the Internet at least once in the last 6 months. Twenty-nine percent reported repeat technology-based interpersonal victimization over a 2-year period (re-victimized group); 10% were victims during only Year 1 (desisted victimized group); and 17% reported victimization during only Year 2 (later victimized group). Of the individual risk factors examined, prior technology-based interpersonal victimization and current amount of Internet use had the strongest overall associations with pattern of technology-based interpersonal victimization over the subsequent 2-year period. There was substantial overlap among the individual risk factors. Thus, they could be thought of more simply in terms of four latent risk and three individual risk factors. On average, across these seven risk factors, repeat victims had the greatest average risk score (0.21) and the not victimized group had the lowest (-0.16). Repeat victims were more likely to be female and older and had more prior experience with problem behaviors, substance use, and negative parent-child relationships as compared with the other three groups. Being female, prior experience with problem behavior, prior substance use, and prior negative parent-child relationships were also associated with frequency of technology-based interpersonal victimization in the near (Year 1) and more distant (Year 2) future. Many of these risk factors related to technology-based victimization over time are malleable, suggesting opportunities for effective targeting of future prevention efforts.

The Individual Health Discount Rate in Patients with Ulcerative Colitis

PubMed Central

Waljee, Akbar K.; Morris, Arden M.; Waljee, Jennifer F.; Higgins, Peter D.R.

2015-01-01

Background In cost-effectiveness analysis, discount rates are used in calculating the value of future costs and benefits. However, standard discount rates may not accurately describe the decision-making of patients with Ulcerative Colitis (UC). These patients often choose the long-term risks of immunosuppressive therapy over the short-term risks of colectomy, demonstrating very high discount rates for future health. In this study, we aimed to measure the discount rate in UC patients and identify variables associated with the discount rate. Methods We surveyed patients with UC and patients who were post-colectomy for UC to measure their valuations of UC and colectomy health states. We used Standard Gamble(SG) and Time-Trade-Off(TTO) methods to assess current and future health state valuations, and calculated the discount rate. Results Participants included 150 subjects with UC and 150 subjects who were post-colectomy for UC. Discount rates varied widely (20.6%–100%) with an overall median rate of 55.0%, which was significantly higher than the standard rate of 5%. Older age and male gender and predicted high discount rates (aversion to immediate risk in favor of distant future risk). For each additional decade of age, patients’ expected discount rate increased by 0.77%. Female gender was the only predictor of very low discount rates. Female patients’ discount rates averaged 8.1% less than age-matched males. Conclusions The accepted discount rate of 5% grossly underestimates UC patients’ preference for long-term over short-term risk. This might explain UC patients’ frequent choice of the long-term risks of immunosuppressive medical therapy over the short-term risks of colectomy. PMID:21560195

Plaque Echolucency and Stroke Risk in Asymptomatic Carotid Stenosis: A Systematic Review and Meta-Analysis

PubMed Central

Gupta, Ajay; Kesavabhotla, Kartik; Baradaran, Hediyeh; Kamel, Hooman; Pandya, Ankur; Giambrone, Ashley E.; Wright, Drew; Pain, Kevin J.; Mtui, Edward E.; Suri, Jasjit S.; Sanelli, Pina C.; Mushlin, Alvin I.

2014-01-01

Background and Purpose Ultrasonographic plaque echolucency has been studied as a stroke risk marker in carotid atherosclerotic disease. We performed a systematic review and meta-analysis to summarize the association between ultrasound determined carotid plaque echolucency and future ipsilateral stroke risk. Methods We searched the medical literature for studies evaluating the association between carotid plaque echolucency and future stroke in asymptomatic patients. We included prospective observational studies with stroke outcome ascertainment after baseline carotid plaque echolucency assessment. We performed a meta-analysis and assessed study heterogeneity and publication bias. We also performed subgroup analyses limited to patients with stenosis ≥50%, studies in which plaque echolucency was determined via subjective visual interpretation, studies with a relatively lower risk of bias, and studies published after the year 2000. Results We analyzed data from 7 studies on 7557 subjects with a mean follow up of 37.2 months. We found a significant positive relationship between predominantly echolucent (compared to predominantly echogenic) plaques and the risk of future ipsilateral stroke across all stenosis severities (0-99%) (relative risk [RR], 2.31, 95% CI, 1.58-3.39, P<.001) and in subjects with ≥50% stenosis (RR, 2.61 95% CI, 1.47-4.63, P=.001). A statistically significant increased RR for future stroke was preserved in all additional subgroup analyses. No statistically significant heterogeneity or publication bias was present in any of the meta-analyses. Conclusions The presence of ultrasound-determined carotid plaque echolucency provides predictive information in asymptomatic carotid artery stenosis beyond luminal stenosis. However, the magnitude of the increased risk is not sufficient on its own to identify patients likely to benefit from surgical revascularization. PMID:25406150

External Validation and Recalibration of Risk Prediction Models for Acute Traumatic Brain Injury among Critically Ill Adult Patients in the United Kingdom

PubMed Central

Griggs, Kathryn A.; Prabhu, Gita; Gomes, Manuel; Lecky, Fiona E.; Hutchinson, Peter J. A.; Menon, David K.; Rowan, Kathryn M.

2015-01-01

Abstract This study validates risk prediction models for acute traumatic brain injury (TBI) in critical care units in the United Kingdom and recalibrates the models to this population. The Risk Adjustment In Neurocritical care (RAIN) Study was a prospective, observational cohort study in 67 adult critical care units. Adult patients admitted to critical care following acute TBI with a last pre-sedation Glasgow Coma Scale score of less than 15 were recruited. The primary outcomes were mortality and unfavorable outcome (death or severe disability, assessed using the Extended Glasgow Outcome Scale) at six months following TBI. Of 3626 critical care unit admissions, 2975 were analyzed. Following imputation of missing outcomes, mortality at six months was 25.7% and unfavorable outcome 57.4%. Ten risk prediction models were validated from Hukkelhoven and colleagues, the Medical Research Council (MRC) Corticosteroid Randomisation After Significant Head Injury (CRASH) Trial Collaborators, and the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) group. The model with the best discrimination was the IMPACT “Lab” model (C index, 0.779 for mortality and 0.713 for unfavorable outcome). This model was well calibrated for mortality at six months but substantially under-predicted the risk of unfavorable outcome. Recalibration of the models resulted in small improvements in discrimination and excellent calibration for all models. The risk prediction models demonstrated sufficient statistical performance to support their use in research and audit but fell below the level required to guide individual patient decision-making. The published models for unfavorable outcome at six months had poor calibration in the UK critical care setting and the models recalibrated to this setting should be used in future research. PMID:25898072

Clinical predictors of conversion to bipolar disorder in a prospective longitudinal familial high-risk sample: focus on depressive features.

PubMed

Frankland, Andrew; Roberts, Gloria; Holmes-Preston, Ellen; Perich, Tania; Levy, Florence; Lenroot, Rhoshel; Hadzi-Pavlovic, Dusan; Breakspear, Michael; Mitchell, Philip B

2017-11-07

Identifying clinical features that predict conversion to bipolar disorder (BD) in those at high familial risk (HR) would assist in identifying a more focused population for early intervention. In total 287 participants aged 12-30 (163 HR with a first-degree relative with BD and 124 controls (CONs)) were followed annually for a median of 5 years. We used the baseline presence of DSM-IV depressive, anxiety, behavioural and substance use disorders, as well as a constellation of specific depressive symptoms (as identified by the Probabilistic Approach to Bipolar Depression) to predict the subsequent development of hypo/manic episodes. At baseline, HR participants were significantly more likely to report ⩾4 Probabilistic features (40.4%) when depressed than CONs (6.7%; p < .05). Nineteen HR subjects later developed either threshold (n = 8; 4.9%) or subthreshold (n = 11; 6.7%) hypo/mania. The presence of ⩾4 Probabilistic features was associated with a seven-fold increase in the risk of 'conversion' to threshold BD (hazard ratio = 6.9, p < .05) above and beyond the fourteen-fold increase in risk related to major depressive episodes (MDEs) per se (hazard ratio = 13.9, p < .05). Individual depressive features predicting conversion were psychomotor retardation and ⩾5 MDEs. Behavioural disorders only predicted conversion to subthreshold BD (hazard ratio = 5.23, p < .01), while anxiety and substance disorders did not predict either threshold or subthreshold hypo/mania. This study suggests that specific depressive characteristics substantially increase the risk of young people at familial risk of BD going on to develop future hypo/manic episodes and may identify a more targeted HR population for the development of early intervention programs.

External Validation and Recalibration of Risk Prediction Models for Acute Traumatic Brain Injury among Critically Ill Adult Patients in the United Kingdom.

PubMed

Harrison, David A; Griggs, Kathryn A; Prabhu, Gita; Gomes, Manuel; Lecky, Fiona E; Hutchinson, Peter J A; Menon, David K; Rowan, Kathryn M

2015-10-01

This study validates risk prediction models for acute traumatic brain injury (TBI) in critical care units in the United Kingdom and recalibrates the models to this population. The Risk Adjustment In Neurocritical care (RAIN) Study was a prospective, observational cohort study in 67 adult critical care units. Adult patients admitted to critical care following acute TBI with a last pre-sedation Glasgow Coma Scale score of less than 15 were recruited. The primary outcomes were mortality and unfavorable outcome (death or severe disability, assessed using the Extended Glasgow Outcome Scale) at six months following TBI. Of 3626 critical care unit admissions, 2975 were analyzed. Following imputation of missing outcomes, mortality at six months was 25.7% and unfavorable outcome 57.4%. Ten risk prediction models were validated from Hukkelhoven and colleagues, the Medical Research Council (MRC) Corticosteroid Randomisation After Significant Head Injury (CRASH) Trial Collaborators, and the International Mission for Prognosis and Analysis of Clinical Trials in TBI (IMPACT) group. The model with the best discrimination was the IMPACT "Lab" model (C index, 0.779 for mortality and 0.713 for unfavorable outcome). This model was well calibrated for mortality at six months but substantially under-predicted the risk of unfavorable outcome. Recalibration of the models resulted in small improvements in discrimination and excellent calibration for all models. The risk prediction models demonstrated sufficient statistical performance to support their use in research and audit but fell below the level required to guide individual patient decision-making. The published models for unfavorable outcome at six months had poor calibration in the UK critical care setting and the models recalibrated to this setting should be used in future research.

A big data analysis of the relationship between future thinking and decision-making.

PubMed

Thorstad, Robert; Wolff, Phillip

2018-02-20

We use big data methods to investigate how decision-making might depend on future sightedness (that is, on how far into the future people's thoughts about the future extend). In study 1, we establish a link between future thinking and decision-making at the population level in showing that US states with citizens having relatively far future sightedness, as reflected in their tweets, take fewer risks than citizens in states having relatively near future sightedness. In study 2, we analyze people's tweets to confirm a connection between future sightedness and decision-making at the individual level in showing that people with long future sightedness are more likely to choose larger future rewards over smaller immediate rewards. In study 3, we show that risk taking decreases with increases in future sightedness as reflected in people's tweets. The ability of future sightedness to predict decisions suggests that future sightedness is a relatively stable cognitive characteristic. This implication was supported in an analysis of tweets by over 38,000 people that showed that future sightedness has both state and trait characteristics (study 4). In study 5, we provide evidence for a potential mechanism by which future sightedness can affect decisions in showing that far future sightedness can make the future seem more connected to the present, as reflected in how people refer to the present, past, and future in their tweets over the course of several minutes. Our studies show how big data methods can be applied to naturalistic data to reveal underlying psychological properties and processes.

Identifying Essential Features of Juvenile Psychopathy in the Prediction of Later Antisocial Behavior: Is There an Additive, Synergistic, or Curvilinear Role for Fearless Dominance?

PubMed Central

Vize, Colin E.; Lynam, Donald R.; Lamkin, Joanna; Miller, Joshua D; Pardini, Dustin

2015-01-01

Despite years of research, and inclusion of psychopathy DSM-5, there remains debate over the fundamental components of psychopathy. Although there is agreement about traits related to Agreeableness and Conscientiousness, there is less agreement about traits related to Fearless Dominance (FD) or Boldness. The present paper uses proxies of FD and Self-centered Impulsivity (SCI) to examine the contribution of FD-related traits to the predictive utility of psychopathy in a large, longitudinal, sample of boys to test four possibilities: FD 1. assessed earlier is a risk factor, 2. interacts with other risk-related variables to predict later psychopathy, 3. interacts with SCI interact to predict outcomes, and 4. bears curvilinear relations to outcomes. SCI received excellent support as a measure of psychopathy in adolescence; however, FD was unrelated to criteria in all tests. It is suggested that FD be dropped from psychopathy and that future research focus on Agreeableness and Conscientiousness. PMID:27347448

Conservation Risks: When Will Rhinos be Extinct?

PubMed

Haas, Timothy C; Ferreira, Sam M

2016-08-01

We develop a risk intelligence system for biodiversity enterprises. Such enterprises depend on a supply of endangered species for their revenue. Many of these enterprises, however, cannot purchase a supply of this resource and are largely unable to secure the resource against theft in the form of poaching. Because replacements are not available once a species becomes extinct, insurance products are not available to reduce the risk exposure of these enterprises to an extinction event. For many species, the dynamics of anthropogenic impacts driven by economic as well as noneconomic values of associated wildlife products along with their ecological stressors can help meaningfully predict extinction risks. We develop an agent/individual-based economic-ecological model that captures these effects and apply it to the case of South African rhinos. Our model uses observed rhino dynamics and poaching statistics. It seeks to predict rhino extinction under the present scenario. This scenario has no legal horn trade, but allows live African rhino trade and legal hunting. Present rhino populations are small and threatened by a rising onslaught of poaching. This present scenario and associated dynamics predicts continued decline in rhino population size with accelerated extinction risks of rhinos by 2036. Our model supports the computation of extinction risks at any future time point. This capability can be used to evaluate the effectiveness of proposed conservation strategies at reducing a species' extinction risk. Models used to compute risk predictions, however, need to be statistically estimated. We point out that statistically fitting such models to observations will involve massive numbers of observations on consumer behavior and time-stamped location observations on thousands of animals. Finally, we propose Big Data algorithms to perform such estimates and to interpret the fitted model's output.

Predictors of incident heart failure in patients after an acute coronary syndrome: The LIPID heart failure risk-prediction model.

PubMed

Driscoll, Andrea; Barnes, Elizabeth H; Blankenberg, Stefan; Colquhoun, David M; Hunt, David; Nestel, Paul J; Stewart, Ralph A; West, Malcolm J; White, Harvey D; Simes, John; Tonkin, Andrew

2017-12-01

Coronary heart disease is a major cause of heart failure. Availability of risk-prediction models that include both clinical parameters and biomarkers is limited. We aimed to develop such a model for prediction of incident heart failure. A multivariable risk-factor model was developed for prediction of first occurrence of heart failure death or hospitalization. A simplified risk score was derived that enabled subjects to be grouped into categories of 5-year risk varying from <5% to >20%. Among 7101 patients from the LIPID study (84% male), with median age 61years (interquartile range 55-67years), 558 (8%) died or were hospitalized because of heart failure. Older age, history of claudication or diabetes mellitus, body mass index>30kg/m 2 , LDL-cholesterol >2.5mmol/L, heart rate>70 beats/min, white blood cell count, and the nature of the qualifying acute coronary syndrome (myocardial infarction or unstable angina) were associated with an increase in heart failure events. Coronary revascularization was associated with a lower event rate. Incident heart failure increased with higher concentrations of B-type natriuretic peptide >50ng/L, cystatin C>0.93nmol/L, D-dimer >273nmol/L, high-sensitivity C-reactive protein >4.8nmol/L, and sensitive troponin I>0.018μg/L. Addition of biomarkers to the clinical risk model improved the model's C statistic from 0.73 to 0.77. The net reclassification improvement incorporating biomarkers into the clinical model using categories of 5-year risk was 23%. Adding a multibiomarker panel to conventional parameters markedly improved discrimination and risk classification for future heart failure events. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Suicide Among Soldiers: A Review of Psychosocial Risk and Protective Factors

PubMed Central

Nock, Matthew K.; Deming, Charlene A.; Fullerton, Carol S.; Gilman, Stephen E.; Goldenberg, Matthew; Kessler, Ronald C.; McCarroll, James E.; McLaughlin, Katie A.; Peterson, Christopher; Schoenbaum, Michael; Stanley, Barbara; Ursano, Robert J.

2014-01-01

Suicide is difficult to predict and prevent and remains a leading cause of death worldwide. Although soldiers historically have had a suicide rate well below that of the general population, the suicide rate among members of the U.S. Army has increased markedly over the past several years and now exceeds that of the general population. This paper reviews psychosocial factors known to be associated with the increased risk of suicidal behavior in general and describes how some of these factors may be especially important in understanding suicide among soldiers. Moving forward, the prevention of suicide requires additional research aimed at: (a) better describing when, where, and among whom suicidal behavior occurs, (b) using exploratory studies to discover new risk and protective factors, (c) developing new methods of predicting suicidal behavior that synthesize information about modifiable risk and protective factors from multiple domains, and (d) understanding the mechanisms and pathways through which suicidal behavior develops. Although the scope and severity of this problem is daunting, the increasing attention and dedication to this issue by the Armed Forces, scientists, and society provide hope for our ability to better predict and prevent these tragic outcomes in the future. PMID:23631542

Spatial model for risk prediction and sub-national prioritization to aid poliovirus eradication in Pakistan.

PubMed

Mercer, Laina D; Safdar, Rana M; Ahmed, Jamal; Mahamud, Abdirahman; Khan, M Muzaffar; Gerber, Sue; O'Leary, Aiden; Ryan, Mike; Salet, Frank; Kroiss, Steve J; Lyons, Hil; Upfill-Brown, Alexander; Chabot-Couture, Guillaume

2017-10-11

Pakistan is one of only three countries where poliovirus circulation remains endemic. For the Pakistan Polio Eradication Program, identifying high risk districts is essential to target interventions and allocate limited resources. Using a hierarchical Bayesian framework we developed a spatial Poisson hurdle model to jointly model the probability of one or more paralytic polio cases, and the number of cases that would be detected in the event of an outbreak. Rates of underimmunization, routine immunization, and population immunity, as well as seasonality and a history of cases were used to project future risk of cases. The expected number of cases in each district in a 6-month period was predicted using indicators from the previous 6-months and the estimated coefficients from the model. The model achieves an average of 90% predictive accuracy as measured by area under the receiver operating characteristic (ROC) curve, for the past 3 years of cases. The risk of poliovirus has decreased dramatically in many of the key reservoir areas in Pakistan. The results of this model have been used to prioritize sub-national areas in Pakistan to receive additional immunization activities, additional monitoring, or other special interventions.

The evolving field of prognostication and risk stratification in MDS: Recent developments and future directions.

PubMed

Lee, Eun-Ju; Podoltsev, Nikolai; Gore, Steven D; Zeidan, Amer M

2016-01-01

The clinical course of patients with myelodysplastic syndromes (MDS) is characterized by wide variability reflecting the underlying genetic and biological heterogeneity of the disease. Accurate prediction of outcomes for individual patients is an integral part of the evidence-based risk/benefit calculations that are necessary for tailoring the aggressiveness of therapeutic interventions. While several prognostication tools have been developed and validated for risk stratification, each of these systems has limitations. The recent progress in genomic sequencing techniques has led to discoveries of recurrent molecular mutations in MDS patients with independent impact on relevant clinical outcomes. Reliable assays of these mutations have already entered the clinic and efforts are currently ongoing to formally incorporate mutational analysis into the existing clinicopathologic risk stratification tools. Additionally, mutational analysis holds promise for going beyond prognostication to therapeutic selection and individualized treatment-specific prediction of outcomes; abilities that would revolutionize MDS patient care. Despite these exciting developments, the best way of incorporating molecular testing for use in prognostication and prediction of outcomes in clinical practice remains undefined and further research is warranted. Copyright © 2015 Elsevier Ltd. All rights reserved.

Use of BMI as the marker of adiposity in a metabolic syndrome severity score: Derivation and validation in predicting long-term disease outcomes.

PubMed

Gurka, Matthew J; Filipp, Stephanie L; Musani, Solomon K; Sims, Mario; DeBoer, Mark D

2018-06-01

Estimates of adiposity in evaluating the metabolic syndrome (MetS) have traditionally utilized measures of waist circumference (WC), whereas body mass index (BMI) is more commonly used clinically. Our objective was to determine if a MetS severity Z-score employing BMI as its measure of adiposity (MetS-Z-BMI) would perform similarly to a WC-based score (MetS-Z-WC) in predicting future disease. To formulate the MetS-Z-BMI, we performed confirmatory factor analysis on a sex- and race/ethnicity-specific basis on MetS-related data for 6870 adult participants of the National Health and Nutrition Survey 1999-2010. We then validated this score and compared it to MetS-Z-WC in assessing correlations with future coronary heart disease (CHD) and Type 2 diabetes mellitus (T2DM) using Cox proportional hazard analysis of 13,094 participants of the Atherosclerosis Risk in Communities study and Jackson Heart Study. Loading factors, which represent the relative contribution of each component to the latent MetS factor, were lower for BMI than for WC in formulating the two respective scores (MetS-Z-BMI and MetS-Z-WC). Nevertheless, MetS-Z-BMI and MetS-Z-WC exhibited similar hazard ratios (HR) toward future disease. For each one standard-deviation-unit increase in MetS-Z-BMI, HR for CHD was 1.76 (95% confidence interval [CI]: 1.65, 1.88) and HR for T2DM was 3.39 (CI 3.16, 3.63) (both p < 0.0001). There were no meaningful differences between the MetS-Z-WC and MetS-Z-BMI scores in their associations with future CHD and T2DM. A MetS severity Z-score utilizing BMI as its measure of adiposity operated similarly to a WC-based score in predicting future CHD and T2DM, suggesting overall similarity in MetS-based risk as estimated by both measures of adiposity. This indicates potential clinical usefulness of MetS-Z-BMI in assessing and following MetS-related risk over time. Copyright © 2018 Elsevier Inc. All rights reserved.

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

PubMed

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

2013-03-15

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

Predicting Drinking Onset with Discrete-Time Survival Analysis in Offspring from the San Diego Prospective Study

PubMed Central

Trim, Ryan S.; Schuckit, Marc A.; Smith, Tom L.

2009-01-01

Previous research has shown that an early onset of drinking is associated with a range of problematic drinking outcomes in adulthood. However, earlier drinking is also linked to additional characteristics that themselves predict alcohol problems including male gender, a family history (FH) of alcoholism, age, race, parental alcoholism, depression symptoms, prior drug use, and conduct problems. This study tested the relationship between the age of first drink (AFD) and a range of risk factors that predict the onset of alcohol use. Participants were offspring from the San Diego Prospective Study (SDPS) who were at least 15 years old at the time of their most recent interview (n=147). Discrete-time survival analysis (DTSA) was used to relate multiple characteristics to the hazard function of alcohol onset across a relevant age range. The results demonstrated the predicted relationships to AFD for conduct problems, male gender, prior marijuana use, and a FH of alcoholism, even when these characteristics were estimated together. Furthermore, an interaction occurred such that offspring with both conduct problems and marijuana use were at substantially higher risk for alcohol use onset during this time period than would be predicted from the effect of these two risk factors alone. However, age at interview, ethnicity, parent education, and depressive symptoms did not predict the pattern of onset of drinking. Implications for future research and prevention efforts are discussed. PMID:19959300

A prediction tool incorporating the biomarker S-100B for patient selection for completion lymph node dissection in stage III melanoma.

PubMed

Damude, S; Wevers, K P; Murali, R; Kruijff, S; Hoekstra, H J; Bastiaannet, E

2017-09-01

Completion lymph node dissection (CLND) in sentinel node (SN)-positive melanoma patients is accompanied with morbidity, while about 80% yield no additional metastases in non-sentinel nodes (NSNs). A prediction tool for NSN involvement could be of assistance in patient selection for CLND. This study investigated which parameters predict NSN-positivity, and whether the biomarker S-100B improves the accuracy of a prediction model. Recorded clinicopathologic factors were tested for their association with NSN-positivity in 110 SN-positive patients who underwent CLND. A prediction model was developed with multivariable logistic regression, incorporating all predictive factors. Five models were compared for their predictive power by calculating the Area Under the Curve (AUC). A weighted risk score, 'S-100B Non-Sentinel Node Risk Score' (SN-SNORS), was derived for the model with the highest AUC. Besides, a nomogram was developed as visual representation. NSN-positivity was present in 24 (21.8%) patients. Sex, ulceration, number of harvested SNs, number of positive SNs, and S-100B value were independently associated with NSN-positivity. The AUC for the model including all these factors was 0.78 (95%CI 0.69-0.88). SN-SNORS was the sum of scores for the five parameters. Scores of ≤9.5, 10-11.5, and ≥12 were associated with low (0%), intermediate (21.0%) and high (43.2%) risk of NSN involvement. A prediction tool based on five parameters, including the biomarker S-100B, showed accurate risk stratification for NSN-involvement in SN-positive melanoma patients. If validated in future studies, this tool could help to identify patients with low risk for NSN-involvement. Copyright © 2017 Elsevier Ltd, BASO ~ The Association for Cancer Surgery, and the European Society of Surgical Oncology. All rights reserved.

Overwintering of herbaceous plants in a changing climate. Still more questions than answers.

PubMed

Rapacz, Marcin; Ergon, Ashild; Höglind, Mats; Jørgensen, Marit; Jurczyk, Barbara; Ostrem, Liv; Rognli, Odd Arne; Tronsmo, Anne Marte

2014-08-01

The increase in surface temperature of the Earth indicates a lower risk of exposure for temperate grassland and crop to extremely low temperatures. However, the risk of low winter survival rate, especially in higher latitudes may not be smaller, due to complex interactions among different environmental factors. For example, the frequency, degree and length of extreme winter warming events, leading to snowmelt during winter increased, affecting the risks of anoxia, ice encasement and freezing of plants not covered with snow. Future climate projections suggest that cold acclimation will occur later in autumn, under shorter photoperiod and lower light intensity, which may affect the energy partitioning between the elongation growth, accumulation of organic reserves and cold acclimation. Rising CO2 levels may also disturb the cold acclimation process. Predicting problems with winter pathogens is also very complex, because climate change may greatly influence the pathogen population and because the plant resistance to these pathogens is increased by cold acclimation. All these factors, often with contradictory effects on winter survival, make plant overwintering viability under future climates an open question. Close cooperation between climatologists, ecologists, plant physiologists, geneticists and plant breeders is strongly required to predict and prevent possible problems. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Prospective study of risk factors for suicidal behavior in individuals with anxiety disorders.

PubMed

Uebelacker, L A; Weisberg, R; Millman, M; Yen, S; Keller, M

2013-07-01

Anxiety disorders are very common and increase risk for suicide attempts. Little is known about predictors of increased risk specifically among individuals with anxiety disorders. The purpose of this study was to investigate whether specific anxiety disorders and other co-morbid psychiatric disorders, physical health, or work or social functioning increased the future likelihood of a suicide attempts among individuals with anxiety disorders. Method In this prospective study, 676 individuals with an anxiety disorder were followed for an average of 12 years. As hypothesized, we found that post-traumatic stress disorder, major depressive disorder (MDD), intermittent depressive disorder (IDD), epilepsy, pain, and poor work and social functioning all predicted a shorter time to a suicide attempt in univariate analyses. In multivariate analyses, baseline MDD and IDD were independent predictors of time to suicide attempt, even when controlling for a past history of suicide attempt. No specific anxiety disorder was an independent predictor of time to attempt in this anxiety-disordered sample. Adding baseline physical health variables and social functioning did not improve the ability of the model to predict time to suicide attempt. Mood disorders and past history of suicide attempts are the most powerful predictors of a future suicide attempt in this sample of individuals, all of whom have an anxiety disorder.

Development of a Single High Fat Meal Challenge to Unmask Latent Cardiopulmonary Effects of Air Pollution Exposure in Rats

EPA Science Inventory

Stress tests are used clinically to determine the presence of underlying disease and predict future cardiovascular risk. In previous studies, we used treadmill exercise stress in rats to unmask the priming effects of air pollution inhalation. Other day-to-day activities stress th...

The influence of mortality and socioeconomic status on risk and delayed rewards: a life history theory approach.

PubMed

Griskevicius, Vladas; Tybur, Joshua M; Delton, Andrew W; Robertson, Theresa E

2011-06-01

Why do some people take risks and live for the present, whereas others avoid risks and save for the future? The evolutionary framework of life history theory predicts that preferences for risk and delay in gratification should be influenced by mortality and resource scarcity. A series of experiments examined how mortality cues influenced decisions involving risk preference (e.g., $10 for sure vs. 50% chance of $20) and temporal discounting (e.g., $5 now vs. $10 later). The effect of mortality depended critically on whether people grew up in a relatively resource-scarce or resource-plentiful environment. For individuals who grew up relatively poor, mortality cues led them to value the present and gamble for big immediate rewards. Conversely, for individuals who grew up relatively wealthy, mortality cues led them to value the future and avoid risky gambles. Overall, mortality cues appear to propel individuals toward diverging life history strategies as a function of childhood socioeconomic status, suggesting important implications for how environmental factors influence economic decisions and risky behaviors. 2011 APA, all rights reserved

[The Basic-Symptom Concept and its Influence on Current International Research on the Prediction of Psychoses].

PubMed

Schultze-Lutter, F

2016-12-01

The early detection of psychoses has become increasingly relevant in research and clinic. Next to the ultra-high risk (UHR) approach that targets an immediate risk of developing frank psychosis, the basic symptom approach that targets the earliest possible detection of the developing disorder is being increasingly used worldwide. The present review gives an introduction to the development and basic assumptions of the basic symptom concept, summarizes the results of studies on the specificity of basic symptoms for psychoses in different age groups as well as on studies of their psychosis-predictive value, and gives an outlook on future results. Moreover, a brief introduction to first recent imaging studies is given that supports one of the main assumptions of the basic symptom concept, i. e., that basic symptoms are the most immediate phenomenological expression of the cerebral aberrations underlying the development of psychosis. From this, it is concluded that basic symptoms might be able to provide important information on future neurobiological research on the etiopathology of psychoses. © Georg Thieme Verlag KG Stuttgart · New York.

Next-generation prognostic assessment for diffuse large B-cell lymphoma

PubMed Central

Staton, Ashley D; Kof, Jean L; Chen, Qiushi; Ayer, Turgay; Flowers, Christopher R

2015-01-01

Current standard of care therapy for diffuse large B-cell lymphoma (DLBCL) cures a majority of patients with additional benefit in salvage therapy and autologous stem cell transplant for patients who relapse. The next generation of prognostic models for DLBCL aims to more accurately stratify patients for novel therapies and risk-adapted treatment strategies. This review discusses the significance of host genetic and tumor genomic alterations seen in DLBCL, clinical and epidemiologic factors, and how each can be integrated into risk stratification algorithms. In the future, treatment prediction and prognostic model development and subsequent validation will require data from a large number of DLBCL patients to establish sufficient statistical power to correctly predict outcome. Novel modeling approaches can augment these efforts. PMID:26289217

Next-generation prognostic assessment for diffuse large B-cell lymphoma.

PubMed

Staton, Ashley D; Koff, Jean L; Chen, Qiushi; Ayer, Turgay; Flowers, Christopher R

2015-01-01

Current standard of care therapy for diffuse large B-cell lymphoma (DLBCL) cures a majority of patients with additional benefit in salvage therapy and autologous stem cell transplant for patients who relapse. The next generation of prognostic models for DLBCL aims to more accurately stratify patients for novel therapies and risk-adapted treatment strategies. This review discusses the significance of host genetic and tumor genomic alterations seen in DLBCL, clinical and epidemiologic factors, and how each can be integrated into risk stratification algorithms. In the future, treatment prediction and prognostic model development and subsequent validation will require data from a large number of DLBCL patients to establish sufficient statistical power to correctly predict outcome. Novel modeling approaches can augment these efforts.

The Number of Sexual Partners and Health-Risking Sexual Behavior: Prediction from High School Entry to High School Exit

PubMed Central

Van Ryzin, Mark J.; Johnson, Amber B.; Leve, Leslie D.; Hyoun, Kim K.

2013-01-01

Precursors to adolescent health-risking sexual behavior (HRSB) were examined in a normative sample of 373 adolescents (48.0% female, n = 178). Using a variable-oriented approach, we regressed the number of sexual partners at high school exit (age 17) on parental monitoring, association with delinquent peers, romantic relationship status, problem behavior, physical maturity, and tobacco and alcohol use at high school entry (age 14); all emerged as significant predictors except alcohol use and physical maturity (we found sex differences in physical maturity and romantic relationship status, with females being more advanced in both areas). Sexual experimentation at high school entry served to partially or fully mediate the impact of these factors. A person-oriented approach, using a broader measure of HRSB, found three subgroups of adolescents: abstainers, low-risk-takers, and high-risk-takers. Results predicting membership in these groups generally followed those from the variable-oriented analysis. Implications for the prevention of HRSB and future research directions are discussed. PMID:20703789

The number of sexual partners and health-risking sexual behavior: prediction from high school entry to high school exit.

PubMed

Van Ryzin, Mark J; Johnson, Amber B; Leve, Leslie D; Kim, Hyoun K

2011-10-01

Precursors to adolescent health-risking sexual behavior (HRSB) were examined in a normative sample of 373 adolescents (48.0% female, n = 178). Using a variable-oriented approach, we regressed the number of sexual partners at high school exit (age 17) on parental monitoring, association with delinquent peers, romantic relationship status, problem behavior, physical maturity, and tobacco and alcohol use at high school entry (age 14); all emerged as significant predictors except alcohol use and physical maturity (we found sex differences in physical maturity and romantic relationship status, with females being more advanced in both areas). Sexual experimentation at high school entry served to partially or fully mediate the impact of these factors. A person-oriented approach, using a broader measure of HRSB, found three subgroups of adolescents: abstainers, low-risk-takers, and high-risk-takers. Results predicting membership in these groups generally followed those from the variable-oriented analysis. Implications for the prevention of HRSB and future research directions are discussed.

Climate change. Accelerating extinction risk from climate change.

PubMed

Urban, Mark C

2015-05-01

Current predictions of extinction risks from climate change vary widely depending on the specific assumptions and geographic and taxonomic focus of each study. I synthesized published studies in order to estimate a global mean extinction rate and determine which factors contribute the greatest uncertainty to climate change-induced extinction risks. Results suggest that extinction risks will accelerate with future global temperatures, threatening up to one in six species under current policies. Extinction risks were highest in South America, Australia, and New Zealand, and risks did not vary by taxonomic group. Realistic assumptions about extinction debt and dispersal capacity substantially increased extinction risks. We urgently need to adopt strategies that limit further climate change if we are to avoid an acceleration of global extinctions. Copyright © 2015, American Association for the Advancement of Science.

An emission-weighted proximity model for air pollution exposure assessment.

PubMed

Zou, Bin; Wilson, J Gaines; Zhan, F Benjamin; Zeng, Yongnian

2009-08-15

Among the most common spatial models for estimating personal exposure are Traditional Proximity Models (TPMs). Though TPMs are straightforward to configure and interpret, they are prone to extensive errors in exposure estimates and do not provide prospective estimates. To resolve these inherent problems with TPMs, we introduce here a novel Emission Weighted Proximity Model (EWPM) to improve the TPM, which takes into consideration the emissions from all sources potentially influencing the receptors. EWPM performance was evaluated by comparing the normalized exposure risk values of sulfur dioxide (SO(2)) calculated by EWPM with those calculated by TPM and monitored observations over a one-year period in two large Texas counties. In order to investigate whether the limitations of TPM in potential exposure risk prediction without recorded incidence can be overcome, we also introduce a hybrid framework, a 'Geo-statistical EWPM'. Geo-statistical EWPM is a synthesis of Ordinary Kriging Geo-statistical interpolation and EWPM. The prediction results are presented as two potential exposure risk prediction maps. The performance of these two exposure maps in predicting individual SO(2) exposure risk was validated with 10 virtual cases in prospective exposure scenarios. Risk values for EWPM were clearly more agreeable with the observed concentrations than those from TPM. Over the entire study area, the mean SO(2) exposure risk from EWPM was higher relative to TPM (1.00 vs. 0.91). The mean bias of the exposure risk values of 10 virtual cases between EWPM and 'Geo-statistical EWPM' are much smaller than those between TPM and 'Geo-statistical TPM' (5.12 vs. 24.63). EWPM appears to more accurately portray individual exposure relative to TPM. The 'Geo-statistical EWPM' effectively augments the role of the standard proximity model and makes it possible to predict individual risk in future exposure scenarios resulting in adverse health effects from environmental pollution.

Using Implicit and Explicit Measures to Predict Nonsuicidal Self-Injury Among Adolescent Inpatients.

PubMed

Cha, Christine B; Augenstein, Tara M; Frost, Katherine H; Gallagher, Katie; D'Angelo, Eugene J; Nock, Matthew K

2016-01-01

To examine the use of implicit and explicit measures to predict adolescent nonsuicidal self-injury (NSSI) before, during, and after inpatient hospitalization. Participants were 123 adolescent psychiatric inpatients who completed measures at hospital admission and discharge. The implicit measure (Self-Injury Implicit Association Test [SI-IAT]) and one of the explicit measures pertained to the NSSI method of cutting. Patients were interviewed at multiple time points at which they reported whether they had engaged in NSSI before their hospital stay, during their hospital stay, and within 3 months after discharge. At baseline, SI-IAT scores differentiated past-year self-injurers and noninjurers (t121 = 4.02, p < .001, d = 0.73). These SI-IAT effects were stronger among patients who engaged in cutting (versus noncutting NSSI methods). Controlling for NSSI history and prospective risk factors, SI-IAT scores predicted patients' subsequent cutting behavior during their hospital stay (odds ratio (OR) = 8.19, CI = 1.56-42.98, p < .05). Patients' explicit self-report uniquely predicted hospital-based and postdischarge cutting, even after controlling for SI-IAT scores (ORs = 1.82-2.34, CIs = 1.25-3.87, p values <.01). Exploratory analyses revealed that in specific cases in which patients explicitly reported low likelihood of NSSI, SI-IAT scores still predicted hospital-based cutting. The SI-IAT is an implicit measure that is outcome-specific, a short-term predictor above and beyond NSSI history, and potentially helpful in cases in which patients at risk for NSSI explicitly report that they would not do so in the future. Ultimately, both implicit and explicit measures can help to predict future incidents of cutting among adolescent inpatients. Copyright © 2016 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Clinical Adoption of Prognostic Biomarkers The Case for Heart Failure

PubMed Central

Kalogeropoulos, Andreas P.; Georgiopoulou, Vasiliki V.; Butler, Javed

2013-01-01

The recent explosion of scientific knowledge and technological progress has led to the discovery of a large array of circulating molecules commonly referred to as biomarkers. Biomarkers in heart failure research have been used to provide pathophysiological insights, aid in establishing the diagnosis, refine prognosis, guide management, and target treatment. However, beyond diagnostic applications of natriuretic peptides, there are currently few widely recognized applications for biomarkers in heart failure. This represents a remarkable discordance considering the number of molecules that have been shown to correlate with outcomes, refine risk prediction, or track disease severity in heart failure in the past decade. In this article, we use a broad framework proposed for cardiovascular risk markers to summarize the current state of biomarker development for heart failure patients. We utilize this framework to identify the challenges of biomarker adoption for risk prediction, disease management, and treatment selection for heart failure and suggest considerations for future research. PMID:22824105

Conscientiousness, career success, and longevity: a lifespan analysis.

PubMed

Kern, Margaret L; Friedman, Howard S; Martin, Leslie R; Reynolds, Chandra A; Luong, Gloria

2009-04-01

Markers of executive functioning, such as prudent planning for the future and impulse control, are related to conscientiousness and may be central to both occupational success and health outcomes. The aim of the study was to examine relations among conscientiousness, career success, and mortality risk across a 65-year period. Using data derived from 693 male participants in the Terman Life Cycle Study, we examined associations among childhood personality, midlife objective career success, and lifelong mortality risk through 2006. Conscientiousness and career success each predicted lower mortality risk (N = 693, relative hazard (rh) = 0.82 [95% confidence interval = 0.74, 0.91] and rh = 0.80 [0.71, 0.91], respectively), with both shared and unique variance. Importantly, childhood personality moderated the success-longevity link; conscientiousness was most relevant for least successful individuals. Conscientiousness and career success predicted longevity, but not in a straightforward manner. Findings highlight the importance of lifespan processes.

Measuring Burden of Unhealthy Behaviours Using a Multivariable Predictive Approach: Life Expectancy Lost in Canada Attributable to Smoking, Alcohol, Physical Inactivity, and Diet.

PubMed

Manuel, Douglas G; Perez, Richard; Sanmartin, Claudia; Taljaard, Monica; Hennessy, Deirdre; Wilson, Kumanan; Tanuseputro, Peter; Manson, Heather; Bennett, Carol; Tuna, Meltem; Fisher, Stacey; Rosella, Laura C

2016-08-01

Behaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by developing, validating, and applying a multivariable predictive model for risk of all-cause death. A predictive algorithm for 5 y risk of death-the Mortality Population Risk Tool (MPoRT)-was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model. The MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 [95% CI: 0.867-0.881]; females 0.875 [0.868-0.882]) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation). Multivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population.

Measuring Burden of Unhealthy Behaviours Using a Multivariable Predictive Approach: Life Expectancy Lost in Canada Attributable to Smoking, Alcohol, Physical Inactivity, and Diet

PubMed Central

Perez, Richard; Taljaard, Monica; Hennessy, Deirdre; Wilson, Kumanan; Tanuseputro, Peter; Bennett, Carol; Tuna, Meltem; Fisher, Stacey; Rosella, Laura C.

2016-01-01

Background Behaviours such as smoking, poor diet, physical inactivity, and unhealthy alcohol consumption are leading risk factors for death. We assessed the Canadian burden attributable to these behaviours by developing, validating, and applying a multivariable predictive model for risk of all-cause death. Methods A predictive algorithm for 5 y risk of death—the Mortality Population Risk Tool (MPoRT)—was developed and validated using the 2001 to 2008 Canadian Community Health Surveys. There were approximately 1 million person-years of follow-up and 9,900 deaths in the development and validation datasets. After validation, MPoRT was used to predict future mortality and estimate the burden of smoking, alcohol, physical inactivity, and poor diet in the presence of sociodemographic and other risk factors using the 2010 national survey (approximately 90,000 respondents). Canadian period life tables were generated using predicted risk of death from MPoRT. The burden of behavioural risk factors attributable to life expectancy was estimated using hazard ratios from the MPoRT risk model. Findings The MPoRT 5 y mortality risk algorithms were discriminating (C-statistic: males 0.874 [95% CI: 0.867–0.881]; females 0.875 [0.868–0.882]) and well calibrated in all 58 predefined subgroups. Discrimination was maintained or improved in the validation cohorts. For the 2010 Canadian population, unhealthy behaviour attributable life expectancy lost was 6.0 years for both men and women (for men 95% CI: 5.8 to 6.3 for women 5.8 to 6.2). The Canadian life expectancy associated with health behaviour recommendations was 17.9 years (95% CI: 17.7 to 18.1) greater for people with the most favourable risk profile compared to those with the least favourable risk profile (88.2 years versus 70.3 years). Smoking, by itself, was associated with 32% to 39% of the difference in life expectancy across social groups (by education achieved or neighbourhood deprivation). Conclusions Multivariable predictive algorithms such as MPoRT can be used to assess health burdens for sociodemographic groups or for small changes in population exposure to risks, thereby addressing some limitations of more commonly used measurement approaches. Unhealthy behaviours have a substantial collective burden on the life expectancy of the Canadian population. PMID:27529741

Predicting acute contact toxicity of pesticides in honeybees (Apis mellifera) through a k-nearest neighbor model.

PubMed

Como, F; Carnesecchi, E; Volani, S; Dorne, J L; Richardson, J; Bassan, A; Pavan, M; Benfenati, E

2017-01-01

Ecological risk assessment of plant protection products (PPPs) requires an understanding of both the toxicity and the extent of exposure to assess risks for a range of taxa of ecological importance including target and non-target species. Non-target species such as honey bees (Apis mellifera), solitary bees and bumble bees are of utmost importance because of their vital ecological services as pollinators of wild plants and crops. To improve risk assessment of PPPs in bee species, computational models predicting the acute and chronic toxicity of a range of PPPs and contaminants can play a major role in providing structural and physico-chemical properties for the prioritisation of compounds of concern and future risk assessments. Over the last three decades, scientific advisory bodies and the research community have developed toxicological databases and quantitative structure-activity relationship (QSAR) models that are proving invaluable to predict toxicity using historical data and reduce animal testing. This paper describes the development and validation of a k-Nearest Neighbor (k-NN) model using in-house software for the prediction of acute contact toxicity of pesticides on honey bees. Acute contact toxicity data were collected from different sources for 256 pesticides, which were divided into training and test sets. The k-NN models were validated with good prediction, with an accuracy of 70% for all compounds and of 65% for highly toxic compounds, suggesting that they might reliably predict the toxicity of structurally diverse pesticides and could be used to screen and prioritise new pesticides. Copyright © 2016 Elsevier Ltd. All rights reserved.

Do causal concentration-response functions exist? A critical review of associational and causal relations between fine particulate matter and mortality.

PubMed

Cox, Louis Anthony Tony

2017-08-01

Concentration-response (C-R) functions relating concentrations of pollutants in ambient air to mortality risks or other adverse health effects provide the basis for many public health risk assessments, benefits estimates for clean air regulations, and recommendations for revisions to existing air quality standards. The assumption that C-R functions relating levels of exposure and levels of response estimated from historical data usefully predict how future changes in concentrations would change risks has seldom been carefully tested. This paper critically reviews literature on C-R functions for fine particulate matter (PM2.5) and mortality risks. We find that most of them describe historical associations rather than valid causal models for predicting effects of interventions that change concentrations. The few papers that explicitly attempt to model causality rely on unverified modeling assumptions, casting doubt on their predictions about effects of interventions. A large literature on modern causal inference algorithms for observational data has been little used in C-R modeling. Applying these methods to publicly available data from Boston and the South Coast Air Quality Management District around Los Angeles shows that C-R functions estimated for one do not hold for the other. Changes in month-specific PM2.5 concentrations from one year to the next do not help to predict corresponding changes in average elderly mortality rates in either location. Thus, the assumption that estimated C-R relations predict effects of pollution-reducing interventions may not be true. Better causal modeling methods are needed to better predict how reducing air pollution would affect public health.

Emotional predictors of bowel screening: the avoidance-promoting role of fear, embarrassment, and disgust.

PubMed

Reynolds, Lisa M; Bissett, Ian P; Consedine, Nathan S

2018-05-03

Despite considerable efforts to address practical barriers, colorectal cancer screening numbers are often low. People do not always act rationally, and investigating emotions may offer insight into the avoidance of screening. The current work assessed whether fear, embarrassment, and disgust predicted colorectal cancer screening avoidance. A community sample (N = 306) aged 45+ completed a questionnaire assessing colorectal cancer screening history and the extent that perceptions of cancer risk, colorectal cancer knowledge, doctor discussions, and a specifically developed scale, the Emotional Barriers to Bowel Screening (EBBS), were associated with previous screening behaviours and anticipated bowel health decision-making. Step-wise logistic regression models revealed that a decision to delay seeking healthcare in the hypothetical presence of bowel symptoms was less likely in people who had discussed risk with their doctor, whereas greater colorectal cancer knowledge and greater fear of a negative outcome predicted greater likelihood of delay. Having previously provided a faecal sample was predicted by discussions about risk with a doctor, older age, and greater embarrassment, whereas perceptions of lower risk predicted a lower likelihood. Likewise, greater insertion disgust predicted a lower likelihood of having had an invasive bowel screening test in the previous 5 years. Alongside medical and demographic factors, fear, embarrassment and disgust are worthy of consideration in colorectal cancer screening. Understanding how specific emotions impact screening decisions and behaviour is an important direction for future work and has potential to inform screening development and communications in bowel health.

Early Prediction of Cancer Progression by Depth-Resolved Nanoscale Mapping of Nuclear Architecture from Unstained Tissue Specimens.

PubMed

Uttam, Shikhar; Pham, Hoa V; LaFace, Justin; Leibowitz, Brian; Yu, Jian; Brand, Randall E; Hartman, Douglas J; Liu, Yang

2015-11-15

Early cancer detection currently relies on screening the entire at-risk population, as with colonoscopy and mammography. Therefore, frequent, invasive surveillance of patients at risk for developing cancer carries financial, physical, and emotional burdens because clinicians lack tools to accurately predict which patients will actually progress into malignancy. Here, we present a new method to predict cancer progression risk via nanoscale nuclear architecture mapping (nanoNAM) of unstained tissue sections based on the intrinsic density alteration of nuclear structure rather than the amount of stain uptake. We demonstrate that nanoNAM detects a gradual increase in the density alteration of nuclear architecture during malignant transformation in animal models of colon carcinogenesis and in human patients with ulcerative colitis, even in tissue that appears histologically normal according to pathologists. We evaluated the ability of nanoNAM to predict "future" cancer progression in patients with ulcerative colitis who did and did not develop colon cancer up to 13 years after their initial colonoscopy. NanoNAM of the initial biopsies correctly classified 12 of 15 patients who eventually developed colon cancer and 15 of 18 who did not, with an overall accuracy of 85%. Taken together, our findings demonstrate great potential for nanoNAM in predicting cancer progression risk and suggest that further validation in a multicenter study with larger cohorts may eventually advance this method to become a routine clinical test. ©2015 American Association for Cancer Research.

Patients’ Opinions about Knowing Their Risk for Depression and What to Do about It. The PredictD-Qualitative Study

PubMed Central

Bellón, Juan Á.; Moreno-Peral, Patricia; Moreno-Küstner, Berta; Motrico, Emma; Aiarzagüena, José M.; Fernández, Anna; Fernández-Alonso, Carmen; Montón-Franco, Carmen; Rodríguez-Bayón, Antonina; Ballesta-Rodríguez, María Isabel; Rüntel-Geidel, Ariadne; Payo-Gordón, Janire; Serrano-Blanco, Antoni; Oliván-Blázquez, Bárbara; Araujo, Luz; Muñoz-García, María del Mar; King, Michael; Nazareth, Irwin; Amezcua, Manuel

2014-01-01

Background The predictD study developed and validated a risk algorithm for predicting the onset of major depression in primary care. We aimed to explore the opinion of patients about knowing their risk for depression and the values and criteria upon which these opinions are based. Methods A maximum variation sample of patients was taken, stratified by city, age, gender, immigrant status, socio-economic status and lifetime depression. The study participants were 52 patients belonging to 13 urban health centres in seven different cities around Spain. Seven Focus Groups (FGs) were given held with primary care patients, one for each of the seven participating cities. Results The results showed that patients generally welcomed knowing their risk for depression. Furthermore, in light of available evidence several patients proposed potential changes in their lifestyles to prevent depression. Patients generally preferred to ask their General Practitioners (GPs) for advice, though mental health specialists were also mentioned. They suggested that GPs undertake interventions tailored to each patient, from a “patient-centred” approach, with certain communication skills, and giving advice to help patients cope with the knowledge that they are at risk of becoming depressed. Conclusions Patients are pleased to be informed about their risk for depression. We detected certain beliefs, attitudes, values, expectations and behaviour among the patients that were potentially useful for future primary prevention programmes on depression. PMID:24646951

Patients' opinions about knowing their risk for depression and what to do about it. The predictD-qualitative study.

PubMed

Bellón, Juan Á; Moreno-Peral, Patricia; Moreno-Küstner, Berta; Motrico, Emma; Aiarzagüena, José M; Fernández, Anna; Fernández-Alonso, Carmen; Montón-Franco, Carmen; Rodríguez-Bayón, Antonina; Ballesta-Rodríguez, María Isabel; Runte-Geidel, Ariadne; Rüntel-Geidel, Ariadne; Payo-Gordón, Janire; Serrano-Blanco, Antoni; Oliván-Blázquez, Bárbara; Araujo, Luz; Muñoz-García, María del Mar; King, Michael; Nazareth, Irwin; Amezcua, Manuel

2014-01-01

The predictD study developed and validated a risk algorithm for predicting the onset of major depression in primary care. We aimed to explore the opinion of patients about knowing their risk for depression and the values and criteria upon which these opinions are based. A maximum variation sample of patients was taken, stratified by city, age, gender, immigrant status, socio-economic status and lifetime depression. The study participants were 52 patients belonging to 13 urban health centres in seven different cities around Spain. Seven Focus Groups (FGs) were given held with primary care patients, one for each of the seven participating cities. The results showed that patients generally welcomed knowing their risk for depression. Furthermore, in light of available evidence several patients proposed potential changes in their lifestyles to prevent depression. Patients generally preferred to ask their General Practitioners (GPs) for advice, though mental health specialists were also mentioned. They suggested that GPs undertake interventions tailored to each patient, from a "patient-centred" approach, with certain communication skills, and giving advice to help patients cope with the knowledge that they are at risk of becoming depressed. Patients are pleased to be informed about their risk for depression. We detected certain beliefs, attitudes, values, expectations and behaviour among the patients that were potentially useful for future primary prevention programmes on depression.

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

PubMed

Yehya, Nadir; Wong, Hector R

2018-01-01

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

Breastfeeding duration and offspring conduct problems: The moderating role of genetic risk.

PubMed

Jackson, Dylan B

2016-10-01

A sizable body of research has examined associations between breastfeeding and various facets of offspring development, including childhood behavioral problems. Notwithstanding the number of studies on the topic, breastfeeding has not consistently been linked to child misbehaviors. Moreover, empirical examinations of whether breastfeeding is differentially predictive of conduct problems among individuals with varying degrees of genetic risk are lacking. The present study examines whether a short duration of breastfeeding and genetic risk interact to predict conduct problems during childhood. A genetically informative design is employed to examine a subsample of twins from the Early Childhood Longitudinal Study: Birth Cohort (ECLS-B), a nationally representative sample of American children. The findings suggest that a shorter duration of breastfeeding only enhances the risk of offspring conduct problems among children who possess high levels of genetic risk. Conversely, longer breastfeeding durations were found to protect against childhood behavioral problems when genetic risk was high. Indicators of genetic risk may help to distinguish individuals whose behavioral development is most sensitive to the duration of breastfeeding. Future research should seek to replicate and extend these findings by considering genetic factors as potential markers of differential susceptibility to breastfeeding duration. Copyright © 2016 Elsevier Ltd. All rights reserved.

Basic disturbances of information processing in psychosis prediction.

PubMed

Bodatsch, Mitja; Klosterkötter, Joachim; Müller, Ralf; Ruhrmann, Stephan

2013-01-01

The basic symptoms (BS) approach provides a valid instrument in predicting psychosis onset and represents moreover a significant heuristic framework for research. The term "basic symptoms" denotes subtle changes of cognition and perception in the earliest and prodromal stages of psychosis development. BS are thought to correspond to disturbances of neural information processing. Following the heuristic implications of the BS approach, the present paper aims at exploring disturbances of information processing, revealed by functional magnetic resonance imaging (fMRI) and electro-encephalographic as characteristics of the at-risk state of psychosis. Furthermore, since high-risk studies employing ultra-high-risk criteria revealed non-conversion rates commonly exceeding 50%, thus warranting approaches that increase specificity, the potential contribution of neural information processing disturbances to psychosis prediction is reviewed. In summary, the at-risk state seems to be associated with information processing disturbances. Moreover, fMRI investigations suggested that disturbances of language processing domains might be a characteristic of the prodromal state. Neurophysiological studies revealed that disturbances of sensory processing may assist psychosis prediction in allowing for a quantification of risk in terms of magnitude and time. The latter finding represents a significant advancement since an estimation of the time to event has not yet been achieved by clinical approaches. Some evidence suggests a close relationship between self-experienced BS and neural information processing. With regard to future research, the relationship between neural information processing disturbances and different clinical risk concepts warrants further investigations. Thereby, a possible time sequence in the prodromal phase might be of particular interest.

Exploring a new bilateral focal density asymmetry based image marker to predict breast cancer risk

NASA Astrophysics Data System (ADS)

Aghaei, Faranak; Mirniaharikandehei, Seyedehnafiseh; Hollingsworth, Alan B.; Wang, Yunzhi; Qiu, Yuchen; Liu, Hong; Zheng, Bin

2017-03-01

Although breast density has been widely considered an important breast cancer risk factor, it is not very effective to predict risk of developing breast cancer in a short-term or harboring cancer in mammograms. Based on our recent studies to build short-term breast cancer risk stratification models based on bilateral mammographic density asymmetry, we in this study explored a new quantitative image marker based on bilateral focal density asymmetry to predict the risk of harboring cancers in mammograms. For this purpose, we assembled a testing dataset involving 100 positive and 100 negative cases. In each of positive case, no any solid masses are visible on mammograms. We developed a computer-aided detection (CAD) scheme to automatically detect focal dense regions depicting on two bilateral mammograms of left and right breasts. CAD selects one focal dense region with the maximum size on each image and computes its asymmetrical ratio. We used this focal density asymmetry as a new imaging marker to divide testing cases into two groups of higher and lower focal density asymmetry. The first group included 70 cases in which 62.9% are positive, while the second group included 130 cases in which 43.1% are positive. The odds ratio is 2.24. As a result, this preliminary study supported the feasibility of applying a new focal density asymmetry based imaging marker to predict the risk of having mammography-occult cancers. The goal is to assist radiologists more effectively and accurately detect early subtle cancers using mammography and/or other adjunctive imaging modalities in the future.

Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change.

PubMed

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-10-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates.

Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change

PubMed Central

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-01-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. PMID:26501958

Dietary Sodium Consumption Predicts Future Blood Pressure and Incident Hypertension in the Japanese Normotensive General Population

PubMed Central

Takase, Hiroyuki; Sugiura, Tomonori; Kimura, Genjiro; Ohte, Nobuyuki; Dohi, Yasuaki

2015-01-01

Background Although there is a close relationship between dietary sodium and hypertension, the concept that persons with relatively high dietary sodium are at increased risk of developing hypertension compared with those with relatively low dietary sodium has not been studied intensively in a cohort. Methods and Results We conducted an observational study to investigate whether dietary sodium intake predicts future blood pressure and the onset of hypertension in the general population. Individual sodium intake was estimated by calculating 24-hour urinary sodium excretion from spot urine in 4523 normotensive participants who visited our hospital for a health checkup. After a baseline examination, they were followed for a median of 1143 days, with the end point being development of hypertension. During the follow-up period, hypertension developed in 1027 participants (22.7%). The risk of developing hypertension was higher in those with higher rather than lower sodium intake (hazard ratio 1.25, 95% CI 1.04 to 1.50). In multivariate Cox proportional hazards regression analysis, baseline sodium intake and the yearly change in sodium intake during the follow-up period (as continuous variables) correlated with the incidence of hypertension. Furthermore, both the yearly increase in sodium intake and baseline sodium intake showed significant correlations with the yearly increase in systolic blood pressure in multivariate regression analysis after adjustment for possible risk factors. Conclusions Both relatively high levels of dietary sodium intake and gradual increases in dietary sodium are associated with future increases in blood pressure and the incidence of hypertension in the Japanese general population. PMID:26224048

Prediction of Cardiovascular Disease by the Framingham-REGICOR Equation in the High-Risk PREDIMED Cohort: Impact of the Mediterranean Diet Across Different Risk Strata.

PubMed

Amor, Antonio J; Serra-Mir, Mercè; Martínez-González, Miguel A; Corella, Dolores; Salas-Salvadó, Jordi; Fitó, Montserrat; Estruch, Ramón; Serra-Majem, Lluis; Arós, Fernando; Babio, Nancy; Ros, Emilio; Ortega, Emilio

2017-03-13

The usefulness of cardiovascular disease (CVD) predictive equations in different populations is debatable. We assessed the efficacy of the Framingham-REGICOR scale, validated for the Spanish population, to identify future CVD in participants, who were predefined as being at high-risk in the PREvención con DIeta MEDiterránea (PREDIMED) study-a nutrition-intervention primary prevention trial-and the impact of adherence to the Mediterranean diet on CVD across risk categories. In a post hoc analysis, we assessed the CVD predictive value of baseline estimated risk in 5966 PREDIMED participants (aged 55-74 years, 57% women; 48% with type 2 diabetes mellitus). Major CVD events, the primary PREDIMED end point, were an aggregate of myocardial infarction, stroke, and cardiovascular death. Multivariate-adjusted Cox regression was used to calculate hazard ratios for major CVD events and effect modification from the Mediterranean diet intervention across risk strata (low, moderate, high, very high). The Framingham-REGICOR classification of PREDIMED participants was 25.1% low risk, 44.5% moderate risk, and 30.4% high or very high risk. During 6-year follow-up, 188 major CVD events occurred. Hazard ratios for major CVD events increased in parallel with estimated risk (2.68, 4.24, and 6.60 for moderate, high, and very high risk), particularly in men (7.60, 13.16, and 15.85, respectively, versus 2.16, 2.28, and 3.51, respectively, in women). Yet among those with low or moderate risk, 32.2% and 74.3% of major CVD events occurred in men and women, respectively. Mediterranean diet adherence was associated with CVD risk reduction regardless of risk strata ( P >0.4 for interaction). Incident CVD increased in parallel with estimated risk in the PREDIMED cohort, but most events occurred in non-high-risk categories, particularly in women. Until predictive tools are improved, promotion of the Mediterranean diet might be useful to reduce CVD independent of baseline risk. URL: http://www.Controlled-trials.com. Unique identifier: ISRCTN35739639. © 2017 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Appropriate Use of Effective Dose in Radiation Protection and Risk Assessment.

PubMed

Fisher, Darrell R; Fahey, Frederic H

2017-08-01

Effective dose was introduced by the ICRP for the single, over-arching purpose of setting limits for radiation protection. Effective dose is a derived quantity or mathematical construct and not a physical, measurable quantity. The formula for calculating effective dose to a reference model incorporates terms to account for all radiation types, organ and tissue radiosensitivities, population groups, and multiple biological endpoints. The properties and appropriate applications of effective dose are not well understood by many within and outside the health physics profession; no other quantity in radiation protection has been more confusing or misunderstood. According to ICRP Publication 103, effective dose is to be used for "prospective dose assessment for planning and optimization in radiological protection, and retrospective demonstration of compliance for regulatory purposes." In practice, effective dose has been applied incorrectly to predict cancer risk among exposed persons. The concept of effective dose applies generally to reference models only and not to individual subjects. While conceived to represent a measure of cancer risk or heritable detrimental effects, effective dose is not predictive of future cancer risk. The formula for calculating effective dose incorporates committee-selected weighting factors for radiation quality and organ sensitivity; however, the organ weighting factors are averaged across all ages and both genders and thus do not apply to any specific individual or radiosensitive subpopulations such as children and young women. Further, it is not appropriate to apply effective dose to individual medical patients because patient-specific parameters may vary substantially from the assumptions used in generalized models. Also, effective dose is not applicable to therapeutic uses of radiation, as its mathematical underpinnings pertain only to observed late (stochastic) effects of radiation exposure and do not account for short-term adverse tissue reactions. The weighting factors incorporate substantial uncertainties, and linearity of the dose-response function at low dose is uncertain and highly disputed. Since effective dose is not predictive of future cancer incidence, it follows that effective dose should never be used to estimate future cancer risk from specific sources of radiation exposure. Instead, individual assessments of potential detriment should only be based on organ or tissue radiation absorbed dose, together with best scientific understanding of the corresponding dose-response relationships.

Rib fractures predict incident limb fractures: results from the European prospective osteoporosis study.

PubMed

Ismail, A A; Silman, A J; Reeve, J; Kaptoge, S; O'Neill, T W

2006-01-01

Population studies suggest that rib fractures are associated with a reduction in bone mass. While much is known about the predictive risk of hip, spine and distal forearm fracture on the risk of future fracture, little is known about the impact of rib fracture. The aim of this study was to determine whether a recalled history of rib fracture was associated with an increased risk of future limb fracture. Men and women aged 50 years and over were recruited from population registers in 31 European centres for participation in a screening survey of osteoporosis (European Prospective Osteoporosis Study). Subjects were invited to complete an interviewer-administered questionnaire that included questions about previous fractures including rib fracture, the age of their first fracture and also the level of trauma. Lateral spine radiographs were performed and the presence of vertebral deformity was determined morphometrically. Following the baseline survey, subjects were followed prospectively by annual postal questionnaire to determine the occurrence of clinical fractures. The subjects included 6,344 men, with a mean age of 64.2 years, and 6,788 women, with a mean age of 63.6 years, who were followed for a median of 3 years (range 0.4-5.9 years), of whom 135 men (2.3%) and 101 women (1.6%) reported a previous low trauma rib fracture. In total, 138 men and 391 women sustained a limb fracture during follow-up. In women, after age adjustment, those with a recalled history of low trauma rib fracture had an increased risk of sustaining 'any' limb fracture [relative hazard (RH)=2.3; 95% CI 1.3, 4.0]. When stratified by fracture type the predictive risk was more marked for hip (RH=7.7; 95% CI 2.3, 25.9) and humerus fracture (RH=4.5; 95% CI 1.4, 14.6) than other sites (RH=1.6; 95% CI 0.6, 4.3). Additional adjustment for prevalent vertebral deformity and previous (non-rib) low trauma fractures at other sites slightly reduced the strength of the association between rib fracture and subsequent limb fracture. In men, after age adjustment, there was a small though non-significant association between recalled history of rib fracture and future limb fracture. Our data highlight the importance of rib fracture as a marker of bone fragility in women.

Radiation-induced valvular heart disease.

PubMed

Gujral, Dorothy M; Lloyd, Guy; Bhattacharyya, Sanjeev

2016-02-15

Radiation to the mediastinum is a key component of treatment with curative intent for a range of cancers including Hodgkin's lymphoma and breast cancer. Exposure to radiation is associated with a risk of radiation-induced heart valve damage characterised by valve fibrosis and calcification. There is a latent interval of 10-20 years between radiation exposure and development of clinically significant heart valve disease. Risk is related to radiation dose received, interval from exposure and use of concomitant chemotherapy. Long-term outlook and the risk of valve surgery are related to the effects of radiation on mediastinal structures including pulmonary fibrosis and pericardial constriction. Dose prediction models to predict the risk of heart valve disease in the future and newer radiation techniques to reduce the radiation dose to the heart are being developed. Surveillance strategies for this cohort of cancer survivors at risk of developing significant heart valve complications are required. 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/

Prediction of Future Epilepsy in Neonates With Hypoxic-Ischemic Encephalopathy Who Received Selective Head Cooling.

PubMed

McDonough, Tiffani L; Paolicchi, Juliann M; Heier, Linda A; Das, Nikkan; Engel, Murray; Perlman, Jeffrey M; Grinspan, Zachary M

2017-06-01

Epilepsy outcomes after therapeutic hypothermia for neonates with hypoxic-ischemic encephalopathy are understudied. The authors used multivariable logistic regression to predict epilepsy in neonates after selective head cooling. Sensitivity analyses used magnetic resonance imaging (MRI) and electroencephalogram (EEG) interpretations by different clinicians. Fifty neonates had 2-year follow-up. Nine developed epilepsy. Predictors included pH ≤6.8 on day of birth (adjusted odds ratio [OR] 19 [95% confidence interval (CI) 1-371]), burst suppression on EEG on day 4 (8.2 [1.3-59]), and MRI deep gray matter injury (OR 33 [2.4-460]). These factors stratify neonates into low (0-1 factors; 3% [0%-14%] risk), medium (2 factors; 56% [21%-86%] risk), and high-risk groups (3 factors; 100% [29%-100%] risk) for epilepsy. The stratification was robust to varying clinical interpretations of the MRI and EEG. Neonates with hypoxic-ischemic encephalopathy who undergo selective head cooling appear at risk of epilepsy if they have 2 to 3 identified factors. If validated, this rule may help counsel families and identify children for close clinical follow-up.

Sex of the baby and future maternal risk of Type 2 diabetes in women who had gestational diabetes.

PubMed

Retnakaran, R; Shah, B R

2016-07-01

Women who develop gestational diabetes mellitus have a chronic defect in the secretion of insulin by the pancreatic β cells that underlies both their diagnostic hyperglycaemia in pregnancy and their elevated lifetime risk of developing Type 2 diabetes in the future. It has recently emerged that carrying a male fetus is associated with poorer maternal β-cell function and an increased risk of gestational diabetes, whereas the development of gestational diabetes when carrying a girl (as compared with a boy) predicts a comparatively higher risk of early progression to Type 2 diabetes before any subsequent pregnancy. In this context, we sought to determine the impact of fetal sex on the long-term risk of Type 2 diabetes in women with gestational diabetes. Using population-based administrative databases, we identified all women in Ontario, Canada, with a singleton live-birth first pregnancy complicated by gestational diabetes between April 2000 and March 2010 (n = 23 363). We compared the risk of subsequent Type 2 diabetes after pregnancy in those who carried a girl (n = 11 229) vs. those who carried a boy (n = 12 134). Over median 5.5 years follow-up, 5483 women (23.5%) were diagnosed with diabetes. Compared with those who carried a boy, women who had a girl had an elevated risk of subsequently developing diabetes (adjusted hazard ratio = 1.06, 95% CI 1.01-1.12). Among women with gestational diabetes, those who are carrying a girl have a slightly higher overall future risk of Type 2 diabetes. © 2015 Diabetes UK.

Aeroallergen sensitization predicts acute chest syndrome in children with sickle cell anaemia.

PubMed

Willen, Shaina M; Rodeghier, Mark; Strunk, Robert C; Bacharier, Leonard B; Rosen, Carol L; Kirkham, Fenella J; DeBaun, Michael R; Cohen, Robyn T

2018-02-01

Asthma is associated with higher rates of acute chest syndrome (ACS) and vaso-occlusive pain episodes among children with sickle cell anaemia (SCA). Aeroallergen sensitization is a risk factor for asthma. We hypothesized that aeroallergen sensitization is associated with an increased incidence of hospitalizations for ACS and pain. Participants in a multicentre, longitudinal cohort study, aged 4-18 years with SCA, underwent skin prick testing to ten aeroallergens. ACS and pain episodes were collected from birth until the end of the follow-up period. The number of positive skin tests were tested for associations with prospective rates of ACS and pain. Multivariable models demonstrated additive effects of having positive skin tests on future rates of ACS (incidence rate ratio (IRR) for each positive test 1·23, 95% confidence interval [CI] 1·11-1·36, P < 0·001). Aeroallergen sensitization was not associated with future pain (IRR 1·14, 95%CI 0·97-1·33, P = 0·11). Our study demonstrated that children with SCA and aeroallergen sensitization are at increased risk for future ACS. Future research is needed to determine whether identification of specific sensitizations and allergen avoidance and treatment reduce the risk of ACS for children with SCA. © 2018 John Wiley & Sons Ltd.

An Integrated and Interdisciplinary Model for Predicting the Risk of Injury and Death in Future Earthquakes

PubMed Central

Shapira, Stav; Novack, Lena; Bar-Dayan, Yaron; Aharonson-Daniel, Limor

2016-01-01

Background A comprehensive technique for earthquake-related casualty estimation remains an unmet challenge. This study aims to integrate risk factors related to characteristics of the exposed population and to the built environment in order to improve communities’ preparedness and response capabilities and to mitigate future consequences. Methods An innovative model was formulated based on a widely used loss estimation model (HAZUS) by integrating four human-related risk factors (age, gender, physical disability and socioeconomic status) that were identified through a systematic review and meta-analysis of epidemiological data. The common effect measures of these factors were calculated and entered to the existing model’s algorithm using logistic regression equations. Sensitivity analysis was performed by conducting a casualty estimation simulation in a high-vulnerability risk area in Israel. Results the integrated model outcomes indicated an increase in the total number of casualties compared with the prediction of the traditional model; with regard to specific injury levels an increase was demonstrated in the number of expected fatalities and in the severely and moderately injured, and a decrease was noted in the lightly injured. Urban areas with higher populations at risk rates were found more vulnerable in this regard. Conclusion The proposed model offers a novel approach that allows quantification of the combined impact of human-related and structural factors on the results of earthquake casualty modelling. Investing efforts in reducing human vulnerability and increasing resilience prior to an occurrence of an earthquake could lead to a possible decrease in the expected number of casualties. PMID:26959647

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.

PubMed

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng

2015-09-22

The increasing rate of health care expenditures in the United States has placed a significant burden on the nation's economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. In the HealthInfoNet, Maine's health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient's next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree-based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study

PubMed Central

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank

2015-01-01

Background The increasing rate of health care expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. Objective This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. Methods In the HealthInfoNet, Maine’s health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient’s next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree–based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Results Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. Conclusions The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes. PMID:26395541

Sensor-derived physical activity parameters can predict future falls in people with dementia

PubMed Central

Schwenk, Michael; Hauer, Klaus; Zieschang, Tania; Englert, Stefan; Mohler, Jane; Najafi, Bijan

2014-01-01

Background There is a need for simple clinical tools that can objectively assess fall risk in people with dementia. Wearable sensors seem to have potential for fall prediction, however, there has been limited work performed in this important area. Objective To explore the validity of sensor-derived physical activity (PA) parameters for predicting future falls in people with dementia. To compare sensor-based fall risk assessment with conventional fall risk measures. Methods A cohort study of people with confirmed dementia discharged from a geriatric rehabilitation ward. PA was quantified using 24-hour motion-sensor monitoring at the beginning of the study. PA parameters (percentage of walking, standing, sitting, lying; duration of single walking, standing, and sitting bouts) were extracted using specific algorithms. Conventional assessment included performance-based tests (Timed-up-and-go test, Performance-Oriented-Mobility-Assessment, 5-chair stand) and questionnaires (cognition, ADL-status, fear of falling, depression, previous faller). Outcome measures were fallers (at least one fall in the 3-month follow-up period) versus non-fallers. Results Seventy-seven people were included in the study (age 81.8 ± 6.3; community dwelling 88%, institutionalized 12%). Surprisingly, fallers and non-fallers did not differ on any conventional assessment (p= 0.069–0.991), except for ‘previous faller’ (p= 0.006). Interestingly, several PA parameters discriminated between groups. The ‘walking bouts average duration’, ‘longest walking bout duration’ and ‘walking bouts duration variability’ were lower in fallers, compared to non-fallers (p= 0.008–0.027). The ‘standing bouts average duration’ was higher in fallers (p= 0.050). Two variables, ‘walking bouts average duration’ [odds ratio (OR) 0.79, p= 0.012] and ‘previous faller’ [OR 4.44, p= 0.007] were identified as independent predictors for falls. The OR for a ‘walking bouts average duration’ of less than 15 seconds for predicting fallers was 6.30 (p= 0.020). Combining ‘walking bouts average duration’ and ‘previous faller’ improved fall prediction [OR 7.71, p< 0.001, sensitivity/specificity 72%/76%]. Discussion Results demonstrate that sensor-derived PA parameters are independent predictors of fall risk and may have higher diagnostic accuracy in persons with dementia compared to conventional fall risk measures. Our findings highlight the potential of telemonitoring technology for estimating fall risk. Results should be confirmed in a larger study and by measuring PA over a longer time period. PMID:25171300

Sensor-derived physical activity parameters can predict future falls in people with dementia.

PubMed

Schwenk, Michael; Hauer, Klaus; Zieschang, Tania; Englert, Stefan; Mohler, Jane; Najafi, Bijan

2014-01-01

There is a need for simple clinical tools that can objectively assess the fall risk in people with dementia. Wearable sensors seem to have the potential for fall prediction; however, there has been limited work performed in this important area. To explore the validity of sensor-derived physical activity (PA) parameters for predicting future falls in people with dementia. To compare sensor-based fall risk assessment with conventional fall risk measures. This was a cohort study of people with confirmed dementia discharged from a geriatric rehabilitation ward. PA was quantified using 24-hour motion-sensor monitoring at the beginning of the study. PA parameters (percentage of walking, standing, sitting, and lying; duration of single walking, standing, and sitting bouts) were extracted using specific algorithms. Conventional assessment included performance-based tests (Timed Up and Go Test, Performance-Oriented Mobility Assessment, 5-chair stand) and questionnaires (cognition, ADL status, fear of falling, depression, previous faller). Outcome measures were fallers (at least one fall in the 3-month follow-up period) versus non-fallers. 77 people were included in the study (age 81.8 ± 6.3; community-dwelling 88%, institutionalized 12%). Surprisingly, fallers and non-fallers did not differ on any conventional assessment (p = 0.069-0.991), except for 'previous faller' (p = 0.006). Interestingly, several PA parameters discriminated between the groups. The 'walking bout average duration', 'longest walking bout duration' and 'walking bout duration variability' were lower in fallers, compared to non-fallers (p = 0.008-0.027). The 'standing bout average duration' was higher in fallers (p = 0.050). Two variables, 'walking bout average duration' [odds ratio (OR) 0.79, p = 0.012] and 'previous faller' (OR 4.44, p = 0.007) were identified as independent predictors for falls. The OR for a 'walking bout average duration' <15 s for predicting fallers was 6.30 (p = 0.020). Combining 'walking bout average duration' and 'previous faller' improved fall prediction (OR 7.71, p < 0.001, sensitivity/specificity 72%/76%). RESULTS demonstrate that sensor-derived PA parameters are independent predictors of the fall risk and may have higher diagnostic accuracy in persons with dementia compared to conventional fall risk measures. Our findings highlight the potential of telemonitoring technology for estimating the fall risk. RESULTS should be confirmed in a larger study and by measuring PA over a longer period of time. © 2014 S. Karger AG, Basel.