Evidence for a relationship between trait gratitude and prosocial behaviour.

PubMed

Yost-Dubrow, Rachel; Dunham, Yarrow

2018-03-01

Prosocial behaviour towards unrelated others is communally beneficial but can be individually costly. The emotion of gratitude mitigates this cost by encouraging direct as well as "upstream" reciprocity, thereby facilitating cooperation. A widely used method for measuring trait gratitude is the Gratitude Questionnaire (GQ6) [McCullough, M., Emmons, R., & Tsang, J. (2002). The grateful disposition: A conceptual and empirical topography. Journal of Personality and Social Psychology, 82, 112-127. Retrieved from https://doi.org/10.1037/0022-3514.82.1.112 ]. Here we undertake an assessment of the external validity of the GQ6 by examining its relationship with two incentivized economic games that serve as face valid indices of generosity and reciprocity. In two studies (total N = 501) we find that trait gratitude as measured by the GQ6 predicts greater donations in a charity donation task as well as greater transfers and returns in an incentivized trust game. These results support the hypothesis that individuals with higher trait gratitude are more generous and trusting on average, and provide initial evidence as to the predictive validity of the GQ6.

Facultative Stabilization Pond: Measuring Biological Oxygen Demand using Mathematical Approaches

NASA Astrophysics Data System (ADS)

Wira S, Ihsan; Sunarsih, Sunarsih

2018-02-01

Pollution is a man-made phenomenon. Some pollutants which discharged directly to the environment could create serious pollution problems. Untreated wastewater will cause contamination and even pollution on the water body. Biological Oxygen Demand (BOD) is the amount of oxygen required for the oxidation by bacteria. The higher the BOD concentration, the greater the organic matter would be. The purpose of this study was to predict the value of BOD contained in wastewater. Mathematical modeling methods were chosen in this study to depict and predict the BOD values contained in facultative wastewater stabilization ponds. Measurements of sampling data were carried out to validate the model. The results of this study indicated that a mathematical approach can be applied to predict the BOD contained in the facultative wastewater stabilization ponds. The model was validated using Absolute Means Error with 10% tolerance limit, and AME for model was 7.38% (< 10%), so the model is valid. Furthermore, a mathematical approach can also be applied to illustrate and predict the contents of wastewater.

Job Design and Ethnic Differences in Working Women’s Physical Activity

PubMed Central

Grzywacz, Joseph G.; Crain, A. Lauren; Martinson, Brian C.; Quandt, Sara A.

2014-01-01

Objective To document the role job control and schedule control play in shaping women’s physical activity, and how it delineates educational and racial variability in associations of job and social control with physical activity. Methods Prospective data were obtained from a community-based sample of working women (N = 302). Validated instruments measured job control and schedule control. Steps per day were assessed using New Lifestyles 800 activity monitors. Results Greater job control predicted more steps per day, whereas greater schedule control predicted fewer steps. Small indirect associations between ethnicity and physical activity were observed among women with a trade school degree or less but not for women with a college degree. Conclusions Low job control created barriers to physical activity among working women with a trade school degree or less. Greater schedule control predicted less physical activity, suggesting women do not use time “created” by schedule flexibility for personal health enhancement. PMID:24034681

Job design and ethnic differences in working women's physical activity.

PubMed

Grzywacz, Joseph G; Crain, A Lauren; Martinson, Brian C; Quandt, Sara A

2014-01-01

To document the role job control and schedule control play in shaping women's physical activity, and how it delineates educational and racial variability in associations of job and social control with physical activity. Prospective data were obtained from a community-based sample of working women (N = 302). Validated instruments measured job control and schedule control. Steps per day were assessed using New Lifestyles 800 activity monitors. Greater job control predicted more steps per day, whereas greater schedule control predicted fewer steps. Small indirect associations between ethnicity and physical activity were observed among women with a trade school degree or less but not for women with a college degree. Low job control created barriers to physical activity among working women with a trade school degree or less. Greater schedule control predicted less physical activity, suggesting women do not use time "created" by schedule flexibility for personal health enhancement.

COARSE PM EMISSIONS MODEL DEVELOPMENT AND INVENTORY VALIDATION

EPA Science Inventory

The proposed research will contribute to our understanding of the sources and controlling variables of coarse PM. This greater understanding, along with an increase in our ability to predict these emissions, will enable more efficient pollution control strategy development. Ad...

Predicting functional outcomes among college drinkers: reliability and predictive validity of the Young Adult Alcohol Consequences Questionnaire.

PubMed

Read, Jennifer P; Merrill, Jennifer E; Kahler, Christopher W; Strong, David R

2007-11-01

Heavy drinking and associated consequences are widespread among U.S. college students. Recently, Read et al. (Read, J. P., Kahler, C. W., Strong, D., & Colder, C. R. (2006). Development and preliminary validation of the Young Adult Alcohol Consequences Questionnaire. Journal of Studies on Alcohol, 67, 169-178) developed the Young Adult Alcohol Consequences Questionnaire (YAACQ) to assess the broad range of consequences that may result from heavy drinking in the college milieu. In the present study, we sought to add to the psychometric validation of this measure by employing a prospective design to examine the test-retest reliability, concurrent validity, and predictive validity of the YAACQ. We also sought to examine the utility of the YAACQ administered early in the semester in the prediction of functional outcomes later in the semester, including the persistence of heavy drinking, and academic functioning. Ninety-two college students (48 females) completed a self-report assessment battery during the first weeks of the Fall semester, and approximately one week later. Additionally, 64 subjects (37 females) participated at an optional third time point at the end of the semester. Overall, the YAACQ demonstrated strong internal consistency, test-retest reliability, and concurrent and predictive validity. YAACQ scores also were predictive of both drinking frequency, and "binge" drinking frequency. YAACQ total scores at baseline were an early indicator of academic performance later in the semester, with greater number of total consequences experienced being negatively associated with end-of-semester grade point average. Specific YAACQ subscale scores (Impaired Control, Dependence Symptoms, Blackout Drinking) showed unique prediction of persistent drinking and academic outcomes.

Validity of Medical Student Questionnaire Data in Prediction of Rural Practice Choice and Its Association With Service Orientation.

PubMed

Shannon, C Ken; Jackson, Jodie

2015-01-01

The validity of medical student projection of, and predictors for, rural practice and the association of a measure of service orientation, projected practice accessibility to the indigent, were investigated. West Virginia (WV) medical student online pre- and postrural rotation questionnaire data were collected during the time period 2001-2009. Of the 1,517 respondent students, submissions by 1,271 met the time interval criterion for inclusion in analyses. Subsequent WV licensing data were available for 461 in 2013. These 2 databases were used to assess for validity of projection of rural practice, for predictors of rural practice, and for student projected accessibility of the future practice to indigent patients. There were statistically significant associations between both pre- and postrotation projections of rural practice and subsequent rural practice. The most significant independent predictors of rural practice were student rural background, reported primary care intent, prediction of rural practice and projection of greater accessibility of the future practice to indigent patients. For scoring of practice access, there were trends for higher scoring by rural students and rural practitioners, with greater pre-post increases for those with urban hometowns. This study demonstrates the utility of medical student questionnaires for projections of numbers of future rural physicians. It suggests that students with a rural background, rural practice intent, or greater service orientation are more likely to enter rural practice. It also suggests that students, particularly those with urban hometowns, are influenced by rural rotation experiences in forecasting greater practice accessibility and in entering rural practice. © 2015 National Rural Health Association.

Prediction of Curve Progression in Idiopathic Scoliosis: Validation of the Sanders Skeletal Maturity Staging System.

PubMed

Sitoula, Prakash; Verma, Kushagra; Holmes, Laurens; Gabos, Peter G; Sanders, James O; Yorgova, Petya; Neiss, Geraldine; Rogers, Kenneth; Shah, Suken A

2015-07-01

Retrospective case series. This study aimed to validate the Sanders Skeletal Maturity Staging System and to assess its correlation to curve progression in idiopathic scoliosis. The Sanders Skeletal Maturity Staging System has been used to predict curve progression in idiopathic scoliosis. This study intended to validate that initial study with a larger sample size. We retrospectively reviewed 1100 consecutive patients with idiopathic scoliosis between 2005 and 2011. Girls aged 8 to 14 years (<2 yr postmenarche) and boys aged 10 to 16 years who had obtained at least 1 hand and spine radiograph on the same day for evaluation of skeletal age and scoliosis curve magnitude were followed to skeletal maturity (Risser stage 5 or fully capped Risser stage 4), curve progression to 50° or greater, or spinal fusion. Patients with nonidiopathic curves were excluded. There were 161 patients: 131 girls (12.3 ± 1.2 yr) and 30 boys (13.9 ± 1.1 yr). The distribution of patients within Sanders stage (SS) 1 through 7 was 7, 28, 41, 45, 7, 31, and 2 patients, respectively; modified Lenke curve types 1 to 6 were 26, 12, 63, 5, 38, and 17 patients, respectively. All patients in SS2 with initial Cobb angles of 25° or greater progressed, and patients in SS1 and SS3 with initial Cobb angles of 35° or greater progressed. Similarly, all patients with initial Cobb angles of 40° or greater progressed except those in SS7. Conversely, none of the patients with initial Cobb angles of 15° or less or those in SS5, SS6, and SS7 with initial Cobb angles of 30° or less progressed. Predictive progression of 67%, 50%, 43%, 27%, and 60% was observed for subgroups SS1/30°, SS2/20°, SS3/30°, SS4/30°, and SS6/35° respectively. This larger cohort shows a strong predictive correlation between SS and initial Cobb angle for probability of curve progression in idiopathic scoliosis. 3.

Feasibility of developing LSI microcircuit reliability prediction models

NASA Technical Reports Server (NTRS)

Ryerson, C. M.

1972-01-01

In the proposed modeling approach, when any of the essential key factors are not known initially, they can be approximated in various ways with a known impact on the accuracy of the final predictions. For example, on any program where reliability predictions are started at interim states of project completion, a-priori approximate estimates of the key factors are established for making preliminary predictions. Later these are refined for greater accuracy as subsequent program information of a more definitive nature becomes available. Specific steps to develop, validate and verify these new models are described.

Predicting the need for massive transfusion in trauma patients: the Traumatic Bleeding Severity Score.

PubMed

Ogura, Takayuki; Nakamura, Yoshihiko; Nakano, Minoru; Izawa, Yoshimitsu; Nakamura, Mitsunobu; Fujizuka, Kenji; Suzukawa, Masayuki; Lefor, Alan T

2014-05-01

The ability to easily predict the need for massive transfusion may improve the process of care, allowing early mobilization of resources. There are currently no clear criteria to activate massive transfusion in severely injured trauma patients. The aims of this study were to create a scoring system to predict the need for massive transfusion and then to validate this scoring system. We reviewed the records of 119 severely injured trauma patients and identified massive transfusion predictors using statistical methods. Each predictor was converted into a simple score based on the odds ratio in a multivariate logistic regression analysis. The Traumatic Bleeding Severity Score (TBSS) was defined as the sum of the component scores. The predictive value of the TBSS for massive transfusion was then validated, using data from 113 severely injured trauma patients. Receiver operating characteristic curve analysis was performed to compare the results of TBSS with the Trauma-Associated Severe Hemorrhage score and the Assessment of Blood Consumption score. In the development phase, five predictors of massive transfusion were identified, including age, systolic blood pressure, the Focused Assessment with Sonography for Trauma scan, severity of pelvic fracture, and lactate level. The maximum TBSS is 57 points. In the validation study, the average TBSS in patients who received massive transfusion was significantly greater (24.2 [6.7]) than the score of patients who did not (6.2 [4.7]) (p < 0.01). The area under the receiver operating characteristic curve, sensitivity, and specificity for a TBSS greater than 15 points was 0.985 (significantly higher than the other scoring systems evaluated at 0.892 and 0.813, respectively), 97.4%, and 96.2%, respectively. The TBSS is simple to calculate using an available iOS application and is accurate in predicting the need for massive transfusion. Additional multicenter studies are needed to further validate this scoring system and further assess its utility. Prognostic study, level III.

The Self-Description Inventory+, Part 1: Factor Structure and Convergent Validity Analyses

DTIC Science & Technology

2013-07-01

measures 12 scales of personality. The current report examines the possibility of replacing the EQ with a Five Factor Model ( FFM ) measure of...Checklist. Our results show that the SDI + has scales that are intercorrelated in a manner consistent with the FFM (Experiment 1), a factor structure...met the criteria showing it to be an FFM instrument, we will conduct concurrent validity research to determine if the SDI+ has greater predictive

Joint use of over- and under-sampling techniques and cross-validation for the development and assessment of prediction models.

PubMed

Blagus, Rok; Lusa, Lara

2015-11-04

Prediction models are used in clinical research to develop rules that can be used to accurately predict the outcome of the patients based on some of their characteristics. They represent a valuable tool in the decision making process of clinicians and health policy makers, as they enable them to estimate the probability that patients have or will develop a disease, will respond to a treatment, or that their disease will recur. The interest devoted to prediction models in the biomedical community has been growing in the last few years. Often the data used to develop the prediction models are class-imbalanced as only few patients experience the event (and therefore belong to minority class). Prediction models developed using class-imbalanced data tend to achieve sub-optimal predictive accuracy in the minority class. This problem can be diminished by using sampling techniques aimed at balancing the class distribution. These techniques include under- and oversampling, where a fraction of the majority class samples are retained in the analysis or new samples from the minority class are generated. The correct assessment of how the prediction model is likely to perform on independent data is of crucial importance; in the absence of an independent data set, cross-validation is normally used. While the importance of correct cross-validation is well documented in the biomedical literature, the challenges posed by the joint use of sampling techniques and cross-validation have not been addressed. We show that care must be taken to ensure that cross-validation is performed correctly on sampled data, and that the risk of overestimating the predictive accuracy is greater when oversampling techniques are used. Examples based on the re-analysis of real datasets and simulation studies are provided. We identify some results from the biomedical literature where the incorrect cross-validation was performed, where we expect that the performance of oversampling techniques was heavily overestimated.

Why stop self-injuring? Development of the reasons to stop self-injury questionnaire.

PubMed

Turner, Brianna J; Chapman, Alexander L; Gratz, Kim L

2014-01-01

We developed a measure of reasons to refrain from nonsuicidal self-injury (NSSI), the Reasons to Stop Self-Injury Questionnaire (RSSIQ), and examined how such reasons are associated with vulnerability versus resiliency for NSSI. Following qualitative item generation, we explored the factor structure, reliability, and convergent validity of the RSSIQ in 218 self-injuring undergraduates. In Study 2, we confirmed the hierarchical factor structure in 146 self-injuring individuals. In Study 3, we examined the incremental predictive validity of the RSSIQ. These studies resulted in a 40-item inventory with nine subscales and two higher-order factors. Resiliency-related reasons to stop NSSI were associated with greater hopefulness, social support, and adaptive coping, and prospectively protected against NSSI 3 months later, while vulnerability-related reasons were associated with greater psychopathology and dysfunctional coping, and predicted more chronic and severe NSSI. These studies, and the RSSIQ, can enhance the assessment and treatment of NSSI by clarifying motivations to stop NSSI.

The Influence of Age and Sexual Drive on the Predictive Validity of the Juvenile Sex Offender Assessment Protocol-Revised.

PubMed

Wijetunga, Charity; Martinez, Ricardo; Rosenfeld, Barry; Cruise, Keith

2018-01-01

The Juvenile Sex Offender Assessment Protocol-Revised (J-SOAP-II) is the most commonly used measure in the assessment of recidivism risk among juveniles who have committed sexual offenses (JSOs), but mixed support exists for its predictive validity. This study compared the predictive validity of the J-SOAP-II across two offender characteristics, age and sexual drive, in a sample of 156 JSOs who had been discharged from a correctional facility or a residential treatment program. The J-SOAP-II appeared to be a better predictor of sexual recidivism for younger JSOs (14-16 years old) than for older ones (17-19 years old), with significant differences found for the Dynamic Summary Scale and Scale III (Intervention). In addition, several of the measure's scales significantly predicted sexual recidivism for JSOs with a clear pattern of sexualized behavior but not for those without such a pattern, indicating that the J-SOAP-II may have greater clinical utility for JSOs with heightened sexual drive. The implications of these findings are discussed.

Assessment of Clinical Criteria for Sepsis

PubMed Central

Seymour, Christopher W.; Liu, Vincent X.; Iwashyna, Theodore J.; Brunkhorst, Frank M.; Rea, Thomas D.; Scherag, André; Rubenfeld, Gordon; Kahn, Jeremy M.; Shankar-Hari, Manu; Singer, Mervyn; Deutschman, Clifford S.; Escobar, Gabriel J.; Angus, Derek C.

2016-01-01

IMPORTANCE The Third International Consensus Definitions Task Force defined sepsis as “life-threatening organ dysfunction due to a dysregulated host response to infection.” The performance of clinical criteria for this sepsis definition is unknown. OBJECTIVE To evaluate the validity of clinical criteria to identify patients with suspected infection who are at risk of sepsis. DESIGN, SETTINGS, AND POPULATION Among 1.3 million electronic health record encounters from January 1, 2010, to December 31, 2012, at 12 hospitals in southwestern Pennsylvania, we identified those with suspected infection in whom to compare criteria. Confirmatory analyses were performed in 4 data sets of 706 399 out-of-hospital and hospital encounters at 165 US and non-US hospitals ranging from January 1, 2008, until December 31, 2013. EXPOSURES Sequential [Sepsis-related] Organ Failure Assessment (SOFA) score, systemic inflammatory response syndrome (SIRS) criteria, Logistic Organ Dysfunction System (LODS) score, and a new model derived using multivariable logistic regression in a split sample, the quick Sequential [Sepsis-related] Organ Failure Assessment (qSOFA) score (range, 0–3 points, with 1 point each for systolic hypotension [≤100 mm Hg], tachypnea [≥22/min], or altered mentation). MAIN OUTCOMES AND MEASURES For construct validity, pairwise agreement was assessed. For predictive validity, the discrimination for outcomes (primary: in-hospital mortality; secondary: in-hospital mortality or intensive care unit [ICU] length of stay ≥3 days) more common in sepsis than uncomplicated infection was determined. Results were expressed as the fold change in outcome over deciles of baseline risk of death and area under the receiver operating characteristic curve (AUROC). RESULTS In the primary cohort, 148 907 encounters had suspected infection (n = 74 453 derivation; n = 74 454 validation), of whom 6347 (4%) died. Among ICU encounters in the validation cohort (n = 7932 with suspected infection, of whom 1289 [16%] died), the predictive validity for in-hospital mortality was lower for SIRS (AUROC = 0.64; 95% CI, 0.62–0.66) and qSOFA (AUROC = 0.66; 95% CI, 0.64–0.68) vs SOFA (AUROC = 0.74; 95% CI, 0.73–0.76; P < .001 for both) or LODS (AUROC = 0.75; 95% CI, 0.73–0.76; P < .001 for both). Among non-ICU encounters in the validation cohort (n = 66 522 with suspected infection, of whom 1886 [3%] died), qSOFA had predictive validity (AUROC = 0.81; 95% CI, 0.80–0.82) that was greater than SOFA (AUROC = 0.79; 95% CI, 0.78–0.80; P < .001) and SIRS (AUROC = 0.76; 95% CI, 0.75–0.77; P < .001). Relative to qSOFA scores lower than 2, encounters with qSOFA scores of 2 or higher had a 3- to 14-fold increase in hospital mortality across baseline risk deciles. Findings were similar in external data sets and for the secondary outcome. CONCLUSIONS AND RELEVANCE Among ICU encounters with suspected infection, the predictive validity for in-hospital mortality of SOFA was not significantly different than the more complex LODS but was statistically greater than SIRS and qSOFA, supporting its use in clinical criteria for sepsis. Among encounters with suspected infection outside of the ICU, the predictive validity for in-hospital mortality of qSOFA was statistically greater than SOFA and SIRS, supporting its use as a prompt to consider possible sepsis. PMID:26903335

A MELD-based model to determine risk of mortality among patients with acute variceal bleeding.

PubMed

Reverter, Enric; Tandon, Puneeta; Augustin, Salvador; Turon, Fanny; Casu, Stefania; Bastiampillai, Ravin; Keough, Adam; Llop, Elba; González, Antonio; Seijo, Susana; Berzigotti, Annalisa; Ma, Mang; Genescà, Joan; Bosch, Jaume; García-Pagán, Joan Carles; Abraldes, Juan G

2014-02-01

Patients with cirrhosis with acute variceal bleeding (AVB) have high mortality rates (15%-20%). Previously described models are seldom used to determine prognoses of these patients, partially because they have not been validated externally and because they include subjective variables, such as bleeding during endoscopy and Child-Pugh score, which are evaluated inconsistently. We aimed to improve determination of risk for patients with AVB. We analyzed data collected from 178 patients with cirrhosis (Child-Pugh scores of A, B, and C: 15%, 57%, and 28%, respectively) and esophageal AVB who received standard therapy from 2007 through 2010. We tested the performance (discrimination and calibration) of previously described models, including the model for end-stage liver disease (MELD), and developed a new MELD calibration to predict the mortality of patients within 6 weeks of presentation with AVB. MELD-based predictions were validated in cohorts of patients from Canada (n = 240) and Spain (n = 221). Among study subjects, the 6-week mortality rate was 16%. MELD was the best model in terms of discrimination; it was recalibrated to predict the 6-week mortality rate with logistic regression (logit, -5.312 + 0.207 • MELD; bootstrapped R(2), 0.3295). MELD values of 19 or greater predicted 20% or greater mortality, whereas MELD scores less than 11 predicted less than 5% mortality. The model performed well for patients from Canada at all risk levels. In the Spanish validation set, in which all patients were treated with banding ligation, MELD predictions were accurate up to the 20% risk threshold. We developed a MELD-based model that accurately predicts mortality among patients with AVB, based on objective variables available at admission. This model could be useful to evaluate the efficacy of new therapies and stratify patients in randomized trials. Copyright © 2014 AGA Institute. Published by Elsevier Inc. All rights reserved.

Linear bubble plume model for hypolimnetic oxygenation: Full-scale validation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Singleton, V. L.; Gantzer, P.; Little, J. C.

2007-02-01

An existing linear bubble plume model was improved, and data collected from a full-scale diffuser installed in Spring Hollow Reservoir, Virginia, were used to validate the model. The depth of maximum plume rise was simulated well for two of the three diffuser tests. Temperature predictions deviated from measured profiles near the maximum plume rise height, but predicted dissolved oxygen profiles compared very well with observations. A sensitivity analysis was performed. The gas flow rate had the greatest effect on predicted plume rise height and induced water flow rate, both of which were directly proportional to gas flow rate. Oxygen transfer within the hypolimnion was independent of all parameters except initial bubble radius and was inversely proportional for radii greater than approximately 1 mm. The results of this work suggest that plume dynamics and oxygen transfer can successfully be predicted for linear bubble plumes using the discrete-bubble approach.

Environmental fate model for ultra-low-volume insecticide applications used for adult mosquito management

USGS Publications Warehouse

Schleier, Jerome J.; Peterson, Robert K.D.; Irvine, Kathryn M.; Marshall, Lucy M.; Weaver, David K.; Preftakes, Collin J.

2012-01-01

One of the more effective ways of managing high densities of adult mosquitoes that vector human and animal pathogens is ultra-low-volume (ULV) aerosol applications of insecticides. The U.S. Environmental Protection Agency uses models that are not validated for ULV insecticide applications and exposure assumptions to perform their human and ecological risk assessments. Currently, there is no validated model that can accurately predict deposition of insecticides applied using ULV technology for adult mosquito management. In addition, little is known about the deposition and drift of small droplets like those used under conditions encountered during ULV applications. The objective of this study was to perform field studies to measure environmental concentrations of insecticides and to develop a validated model to predict the deposition of ULV insecticides. The final regression model was selected by minimizing the Bayesian Information Criterion and its prediction performance was evaluated using k-fold cross validation. Density of the formulation and the density and CMD interaction coefficients were the largest in the model. The results showed that as density of the formulation decreases, deposition increases. The interaction of density and CMD showed that higher density formulations and larger droplets resulted in greater deposition. These results are supported by the aerosol physics literature. A k-fold cross validation demonstrated that the mean square error of the selected regression model is not biased, and the mean square error and mean square prediction error indicated good predictive ability.

The social perception of emotional abilities: expanding what we know about observer ratings of emotional intelligence.

PubMed

Elfenbein, Hillary Anger; Barsade, Sigal G; Eisenkraft, Noah

2015-02-01

We examine the social perception of emotional intelligence (EI) through the use of observer ratings. Individuals frequently judge others' emotional abilities in real-world settings, yet we know little about the properties of such ratings. This article examines the social perception of EI and expands the evidence to evaluate its reliability and cross-judge agreement, as well as its convergent, divergent, and predictive validity. Three studies use real-world colleagues as observers and data from 2,521 participants. Results indicate significant consensus across observers about targets' EI, moderate but significant self-observer agreement, and modest but relatively consistent discriminant validity across the components of EI. Observer ratings significantly predicted interdependent task performance, even after controlling for numerous factors. Notably, predictive validity was greater for observer-rated than for self-rated or ability-tested EI. We discuss the minimal associations of observer ratings with ability-tested EI, study limitations, future directions, and practical implications. PsycINFO Database Record (c) 2015 APA, all rights reserved.

Biomarkers for Early Detection of Clinically Relevant Prostate Cancer. A Multi-Institutional Validation Trial

DTIC Science & Technology

2016-10-01

Study (PASS). We are in the process of evaluating these three biomarker panels in tissue, blood, and urine samples with well annotated clinical and...impacting both the initial choice of therapy and decision-making during AS. The objective of the study is to utilize analytically validated assays that...predict reclassification from Gleason 6 cancer to Gleason 7 or greater. The analysis plan was determined before specimens were selected for the study

Evaluation of Mixed-Phase Microphysics Within Winter Storms using Field Data and In Situ Observations

NASA Technical Reports Server (NTRS)

Colle, Brian A.; Yu, Ruyi; Molthan, Andrew L.; Nesbitt, Stephen

2014-01-01

It is hypothesized that microphysical predictions have greater uncertainties/errors when there are complex interactions that result from mixedphased processes like riming. Use Global Precipitation Measurement (GPM) Mission ground validation studies in Ontario, Canada to verify and improve parameterizations

Project on the Good Physician: Further Evidence for the Validity of a Moral Intuitionist Model of Virtuous Caring.

PubMed

Leffel, G Michael; Oakes Mueller, Ross A; Ham, Sandra A; Karches, Kyle E; Curlin, Farr A; Yoon, John D

2018-01-19

In the Project on the Good Physician, the authors propose a moral intuitionist model of virtuous caring that places the virtues of Mindfulness, Empathic Compassion, and Generosity at the heart of medical character education. Hypothesis 1a: The virtues of Mindfulness, Empathic Compassion, and Generosity will be positively associated with one another (convergent validity). Hypothesis 1b: The virtues of Mindfulness and Empathic Compassion will explain variance in the action-related virtue of Generosity beyond that predicted by Big Five personality traits alone (discriminant validity). Hypothesis 1c: Virtuous students will experience greater well-being ("flourishing"), as measured by four indices of well-being: life meaning, life satisfaction, vocational identity, and vocational calling (predictive validity). Hypothesis 1d: Students who self-report higher levels of the virtues will be nominated by their peers for the Gold Humanism Award (predictive validity). Hypothesis 2a-2c: Neuroticism and Burnout will be positively associated with each other and inversely associated with measures of virtue and well-being. The authors used data from a 2011 nationally representative sample of U.S. medical students (n = 499) in which medical virtues (Mindfulness, Empathic Compassion, and Generosity) were measured using scales adapted from existing instruments with validity evidence. Supporting the predictive validity of the model, virtuous students were recognized by their peers to be exemplary doctors, and they were more likely to have higher ratings on measures of student well-being. Supporting the discriminant validity of the model, virtues predicted prosocial behavior (Generosity) more than personality traits alone, and students higher in the virtue of Mindfulness were less likely to be high in Neuroticism and Burnout. Data from this descriptive-correlational study offered additional support for the validity of the moral intuitionist model of virtuous caring. Applied to medical character education, medical school programs should consider designing educational experiences that intentionally emphasize the cultivation of virtue.

Developing and implementing the use of predictive models for estimating water quality at Great Lakes beaches

USGS Publications Warehouse

Francy, Donna S.; Brady, Amie M.G.; Carvin, Rebecca B.; Corsi, Steven R.; Fuller, Lori M.; Harrison, John H.; Hayhurst, Brett A.; Lant, Jeremiah; Nevers, Meredith B.; Terrio, Paul J.; Zimmerman, Tammy M.

2013-01-01

Predictive models have been used at beaches to improve the timeliness and accuracy of recreational water-quality assessments over the most common current approach to water-quality monitoring, which relies on culturing fecal-indicator bacteria such as Escherichia coli (E. coli.). Beach-specific predictive models use environmental and water-quality variables that are easily and quickly measured as surrogates to estimate concentrations of fecal-indicator bacteria or to provide the probability that a State recreational water-quality standard will be exceeded. When predictive models are used for beach closure or advisory decisions, they are referred to as “nowcasts.” During the recreational seasons of 2010-12, the U.S. Geological Survey (USGS), in cooperation with 23 local and State agencies, worked to improve existing nowcasts at 4 beaches, validate predictive models at another 38 beaches, and collect data for predictive-model development at 7 beaches throughout the Great Lakes. This report summarizes efforts to collect data and develop predictive models by multiple agencies and to compile existing information on the beaches and beach-monitoring programs into one comprehensive report. Local agencies measured E. coli concentrations and variables expected to affect E. coli concentrations such as wave height, turbidity, water temperature, and numbers of birds at the time of sampling. In addition to these field measurements, equipment was installed by the USGS or local agencies at or near several beaches to collect water-quality and metrological measurements in near real time, including nearshore buoys, weather stations, and tributary staff gages and monitors. The USGS worked with local agencies to retrieve data from existing sources either manually or by use of tools designed specifically to compile and process data for predictive-model development. Predictive models were developed by use of linear regression and (or) partial least squares techniques for 42 beaches that had at least 2 years of data (2010-11 and sometimes earlier) and for 1 beach that had 1 year of data. For most models, software designed for model development by the U.S. Environmental Protection Agency (Virtual Beach) was used. The selected model for each beach was based on a combination of explanatory variables including, most commonly, turbidity, day of the year, change in lake level over 24 hours, wave height, wind direction and speed, and antecedent rainfall for various time periods. Forty-two predictive models were validated against data collected during an independent year (2012) and compared to the current method for assessing recreational water quality-using the previous day’s E. coli concentration (persistence model). Goals for good predictive-model performance were responses that were at least 5 percent greater than the persistence model and overall correct responses greater than or equal to 80 percent, sensitivities (percentage of exceedances of the bathing-water standard that were correctly predicted by the model) greater than or equal to 50 percent, and specificities (percentage of nonexceedances correctly predicted by the model) greater than or equal to 85 percent. Out of 42 predictive models, 24 models yielded over-all correct responses that were at least 5 percent greater than the use of the persistence model. Predictive-model responses met the performance goals more often than the persistence-model responses in terms of overall correctness (28 versus 17 models, respectively), sensitivity (17 versus 4 models), and specificity (34 versus 25 models). Gaining knowledge of each beach and the factors that affect E. coli concentrations is important for developing good predictive models. Collection of additional years of data with a wide range of environmental conditions may also help to improve future model performance. The USGS will continue to work with local agencies in 2013 and beyond to develop and validate predictive models at beaches and improve existing nowcasts, restructuring monitoring activities to accommodate future uncertainties in funding and resources.

Chaotic time series prediction for prenatal exposure to polychlorinated biphenyls in umbilical cord blood using the least squares SEATR model

NASA Astrophysics Data System (ADS)

Xu, Xijin; Tang, Qian; Xia, Haiyue; Zhang, Yuling; Li, Weiqiu; Huo, Xia

2016-04-01

Chaotic time series prediction based on nonlinear systems showed a superior performance in prediction field. We studied prenatal exposure to polychlorinated biphenyls (PCBs) by chaotic time series prediction using the least squares self-exciting threshold autoregressive (SEATR) model in umbilical cord blood in an electronic waste (e-waste) contaminated area. The specific prediction steps basing on the proposal methods for prenatal PCB exposure were put forward, and the proposed scheme’s validity was further verified by numerical simulation experiments. Experiment results show: 1) seven kinds of PCB congeners negatively correlate with five different indices for birth status: newborn weight, height, gestational age, Apgar score and anogenital distance; 2) prenatal PCB exposed group at greater risks compared to the reference group; 3) PCBs increasingly accumulated with time in newborns; and 4) the possibility of newborns suffering from related diseases in the future was greater. The desirable numerical simulation experiments results demonstrated the feasibility of applying mathematical model in the environmental toxicology field.

Chaotic time series prediction for prenatal exposure to polychlorinated biphenyls in umbilical cord blood using the least squares SEATR model

PubMed Central

Xu, Xijin; Tang, Qian; Xia, Haiyue; Zhang, Yuling; Li, Weiqiu; Huo, Xia

2016-01-01

Chaotic time series prediction based on nonlinear systems showed a superior performance in prediction field. We studied prenatal exposure to polychlorinated biphenyls (PCBs) by chaotic time series prediction using the least squares self-exciting threshold autoregressive (SEATR) model in umbilical cord blood in an electronic waste (e-waste) contaminated area. The specific prediction steps basing on the proposal methods for prenatal PCB exposure were put forward, and the proposed scheme’s validity was further verified by numerical simulation experiments. Experiment results show: 1) seven kinds of PCB congeners negatively correlate with five different indices for birth status: newborn weight, height, gestational age, Apgar score and anogenital distance; 2) prenatal PCB exposed group at greater risks compared to the reference group; 3) PCBs increasingly accumulated with time in newborns; and 4) the possibility of newborns suffering from related diseases in the future was greater. The desirable numerical simulation experiments results demonstrated the feasibility of applying mathematical model in the environmental toxicology field. PMID:27118260

Differential Lung Toxicity of Biomass Smoke from Smoldering and Flaming Phases Following Acute Inhalation Exposure

EPA Science Inventory

We previously demonstrated that, on a mass basis, lung toxicity associated with particulate matter (PM) from flaming smoke aspirated into mouse lungs is greater than smoldering PM. This finding however has to be validated in inhalation studies to better predict real-world exposu...

Predictive Validity of a Cigarette Purchase Task in a Randomized Controlled Trial of Contingent Vouchers for Smoking in Individuals With Substance Use Disorders

PubMed Central

Mackillop, James; Murphy, Cara M.; Martin, Rosemarie A.; Stojek, Monika; Tidey, Jennifer W.; Colby, Suzanne M.

2016-01-01

Abstract Introduction: A cigarette purchase task (CPT) is a behavioral economic measure of the reinforcing value of smoking in monetary terms (ie, cigarette demand). This study investigated whether cigarette demand predicted response to contingent monetary rewards for abstinence among individuals with substance use disorders. It also sought to replicate evidence for greater price sensitivity at whole-dollar pack price transitions (ie, left-digit effects). Methods: Participants ( N = 338) were individuals in residential substance use disorder treatment who participated in a randomized controlled trial that compared contingent vouchers to noncontingent vouchers for smoking abstinence. Baseline demand indices were used to predict number of abstinent days during the 14-day voucher period (after the reduction lead-in) and at 1 and 3 months afterward. Results: Demand indices correlated with measures of smoking and nicotine dependence. As measured by elasticity, intensity and Omax , higher demand significantly predicted fewer abstinent exhaled carbon monoxide readings during voucher period for individuals in the noncontingent vouchers condition. Breakpoint exhibited a trend-level association with abstinent exhaled carbon monoxide readings. Demand indices did not predict abstinence in the contingent vouchers group, and did not predict abstinence at 1- and 3-month follow-ups. Left-digit price transitions were associated with significantly greater reductions in consumption. Conclusions: The association of cigarette demand with smoking behavior only in the group for whom abstinence was not incentivized indicates that CPT assesses the value of smoking more than the value of money per se and that vouchers counteract the effects of the intrinsic reinforcing value of cigarettes. Results provide initial short-term evidence of predictive validity for the CPT indices. Implications: This study provides the first evidence of the validity of the CPT for predicting early response to brief advice for smoking cessation plus nicotine replacement in smokers with substance dependence. However, demand for cigarettes did not predict voucher-based treatment response, indicating that incentives serve as a powerful motivator not to smoke that acts in opposition to the intrinsic reinforcing value of cigarettes and that the indices reflect the value of smoking more than the value of money per se. PMID:26498173

Adaptation and validation of the Diabetes Management Self-Efficacy Scale to Brazilian Portuguese 1

PubMed Central

Pace, Ana Emilia; Gomes, Lilian Cristiane; Bertolin, Daniela Comelis; Loureiro, Helena Maria Almeira Macedo; Bijl, Jaap Van Der; Shortridge-Baggett, Lillie M.

2017-01-01

Objective: to perform the cultural adaptation and validation of the Diabetes Management Self-efficacy Scale for Patients with Type 2 Diabetes Mellitus with a Brazilian population sample. Method: cross-sectional methodological study in which the adaptation and validation process included the stages recommended in the literature. Construct validity and reliability were assessed with 200 adults with type 2 diabetes mellitus. Results: the items indicated by the panel of judges and by the target population were adjusted in the cultural adaptation to improve clarity and understanding. The instrument's four factors remained in the confirmatory factor analysis with factor loadings of items greater than 0.30, except for factor 4; convergent validity, verified by the multitrait-multimethod analysis, presented inter-item correlations from 0.37 to 0.92, while for discriminant validity, 100% of the items presented greater correlation in their own factors. Cronbach's coefficient alpha for the total scale was 0.78, ranging from 0.57 to 0.86 among factors. Conclusion: semantic, cultural, conceptual and idiomatic equivalences were achieved and the instrument's Brazilian version also presented psychometric properties that showed evidence of reliability and validity. Thus, it can be applied both in clinical practice and research. Self-efficacy is useful for planning and assessing educational interventions, as well as predicting behavior modification in self-care. PMID:28562700

Predictive Validity of Delay Discounting Behavior in Adolescence: A Longitudinal Twin Study

PubMed Central

Isen, Joshua D.; Sparks, Jordan C.; Iacono, William G.

2014-01-01

A standard assumption in the delay discounting literature is that individuals who exhibit steeper discounting of hypothetical rewards also experience greater difficulty deferring gratification to real-world rewards. There is ample cross-sectional evidence that delay discounting paradigms reflect a variety of maladaptive psychosocial outcomes, including substance use pathology. We sought to determine whether a computerized assessment of hypothetical delay discounting (HDD) taps into behavioral impulsivity in a community sample of adolescent twins (N = 675). Using a longitudinal design, we hypothesized that greater HDD at age 14–15 predicts real-world impulsive choices and risk for substance use disorders in late adolescence. We also examined the genetic and environmental structure of HDD performance. Individual differences in HDD behavior showed moderate heritability, and were prospectively associated with real-world temporal discounting at age 17–18. Contrary to expectations, HDD was not consistently related to substance use or trait impulsivity. Although a significant association between HDD behavior and past substance use emerged in males, this effect was mediated by cognitive ability. In both sexes, HDD failed to predict a comprehensive index of substance use problems and behavioral disinhibition in late adolescence. In sum, we present some of the first evidence that HDD performance is heritable and predictive of real-world temporal discounting of rewards. Nevertheless, HDD might not serve as a valid marker of substance use disorder risk in younger adolescents, particularly females. PMID:24999868

Concurrent and prognostic utility of subtyping anorexia nervosa along dietary and negative affect dimensions.

PubMed

Forbush, Kelsie T; Hagan, Kelsey E; Salk, Rachel H; Wildes, Jennifer E

2017-03-01

Bulimia nervosa can be reliably classified into subtypes based on dimensions of dietary restraint and negative affect. Community and clinical studies have shown that dietary-negative affect subtypes have greater test-retest reliability and concurrent and predictive validity compared to subtypes based on the Diagnostic and Statistical Manual of Mental Disorders (DSM). Although dietary-negative affect subtypes have shown utility for characterizing eating disorders that involve binge eating, this framework may have broader implications for understanding restrictive eating disorders. The purpose of this study was to test the concurrent and predictive validity of dietary-negative affect subtypes among patients with anorexia nervosa (AN; N = 194). Latent profile analysis was used to identify subtypes of AN based on dimensions of dietary restraint and negative affect. Chi-square and multivariate analysis of variance were used to characterize baseline differences between identified subtypes. Structural equation modeling was used to test whether dietary-negative affect subtypes would outperform DSM categories in predicting clinically relevant outcomes. Results supported a 2-profile model that replicated dietary-negative affect subtypes: Latent Profile 1 (n = 68) had clinically elevated scores on restraint only; Latent Profile 2 (n = 126) had elevated scores on both restraint and negative affect. Validation analyses showed that membership in the dietary-negative affect profile was associated with greater lifetime psychiatric comorbidity and psychosocial impairment compared to the dietary class. Dietary-negative affect subtypes only outperformed DSM categories in predicting quality-of-life impairment at 1-year follow-up. Findings highlight the clinical utility of subtyping AN based on dietary restraint and negative affect for informing future treatment-matching or personalized medicine strategies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Cryogenic Boil-Off Reduction System Testing

NASA Technical Reports Server (NTRS)

Plachta, David W.; Johnson, Wesley L.; Feller, Jeffery

2014-01-01

The Cryogenic Boil-Off Reduction System was tested with LH2 and LOX in a vacuum chamber to simulate space vacuum and the temperatures of low Earth orbit. Testing was successful and results validated the scaling study model that predicts active cooling reduces upper stage cryogenic propulsion mass for loiter periods greater than 2 weeks.

Contrasting Predictions of the Extended Comparator Hypothesis and Acquisition-Focused Models of Learning Concerning Retrospective Revaluation

PubMed Central

McConnell, Bridget L.; Urushihara, Kouji; Miller, Ralph R.

2009-01-01

Three conditioned suppression experiments with rats investigated contrasting predictions made by the extended comparator hypothesis and acquisition-focused models of learning, specifically, modified SOP and the revised Rescorla-Wagner model, concerning retrospective revaluation. Two target cues (X and Y) were partially reinforced using a stimulus relative validity design (i.e., AX-Outcome/ BX-No outcome/ CY-Outcome/ DY-No outcome), and subsequently one of the companion cues for each target was extinguished in compound (BC-No outcome). In Experiment 1, which used spaced trials for relative validity training, greater suppression was observed to target cue Y for which the excitatory companion cue had been extinguished relative to target cue X for which the nonexcitatory companion cue had been extinguished. Experiment 2 replicated these results in a sensory preconditioning preparation. Experiment 3 massed the trials during relative validity training, and the opposite pattern of data was observed. The results are consistent with the predictions of the extended comparator hypothesis. Furthermore, this set of experiments is unique in being able to differentiate between these models without invoking higher-order comparator processes. PMID:20141324

Can we predict 4-year graduation in podiatric medical school using admission data?

PubMed

Sesodia, Sanjay; Molnar, David; Shaw, Graham P

2012-01-01

This study examined the predictive ability of educational background and demographic variables, available at the admission stage, to identify applicants who will graduate in 4 years from podiatric medical school. A logistic regression model was used to identify two predictors of 4-year graduation: age at matriculation and total Medical College Admission Test score. The model was cross-validated using a second independent sample from the same population. Cross-validation gives greater confidence that the results could be more generally applied. Total Medical College Admission Test score was the strongest predictor of 4-year graduation, with age at matriculation being a statistically significant but weaker predictor. Despite the model's capacity to predict 4-year graduation better than random assignment, a sufficient amount of error in prediction remained, suggesting that important predictors are missing from the model. Furthermore, the high rate of false-positives makes it inappropriate to use age and Medical College Admission Test score as admission screens in an attempt to eliminate attrition by not accepting at-risk students.

Differences in SEM-AVS and ERM-ERL predictions of sediment impacts from metals in two US Virgin Islands marinas.

PubMed

Hinkey, Lynne M; Zaidi, Baqar R

2007-02-01

Two US Virgin Islands marinas were examined for potential metal impacts by comparing sediment chemistry data with two sediment quality guideline (SQG) values: the ratio of simultaneously extractable metals to acid volatile sulfides (SEM-AVS), and effects range-low and -mean (ERL-ERM) values. ERL-ERMs predicted the marina/boatyard complex (IBY: 2118 microg/g dry weight total metals, two exceeded ERMs) would have greater impacts than the marina with no boatyard (CBM: 231 microg/g dry weight total metals, no ERMs exceeded). The AVS-SEM method predicted IBY would have fewer effects due to high AVS-forming metal sulfide complexes, reducing trace metal bioavailability. These contradictory predictions demonstrate the importance of validating the results of either of these methods with other toxicity measures before making any management or regulatory decisions regarding boating and marina impacts. This is especially important in non-temperate areas where sediment quality guidelines have not been validated.

Identification and location tasks rely on different mental processes: a diffusion model account of validity effects in spatial cueing paradigms with emotional stimuli.

PubMed

Imhoff, Roland; Lange, Jens; Germar, Markus

2018-02-22

Spatial cueing paradigms are popular tools to assess human attention to emotional stimuli, but different variants of these paradigms differ in what participants' primary task is. In one variant, participants indicate the location of the target (location task), whereas in the other they indicate the shape of the target (identification task). In the present paper we test the idea that although these two variants produce seemingly comparable cue validity effects on response times, they rest on different underlying processes. Across four studies (total N = 397; two in the supplement) using both variants and manipulating the motivational relevance of cue content, diffusion model analyses revealed that cue validity effects in location tasks are primarily driven by response biases, whereas the same effect rests on delay due to attention to the cue in identification tasks. Based on this, we predict and empirically support that a symmetrical distribution of valid and invalid cues would reduce cue validity effects in location tasks to a greater extent than in identification tasks. Across all variants of the task, we fail to replicate the effect of greater cue validity effects for arousing (vs. neutral) stimuli. We discuss the implications of these findings for best practice in spatial cueing research.

Wrestlers' minimal weight: anthropometry, bioimpedance, and hydrostatic weighing compared.

PubMed

Oppliger, R A; Nielsen, D H; Vance, C G

1991-02-01

The need for accurate assessment of minimal wrestling weight among interscholastic wrestlers has been well documented. Previous research has demonstrated the validity of anthropometric methods for this purpose, but little research has examined the validity of bioelectrical impedance (BIA) measurements. Comparisons between BIA systems has received limited attention. With these two objectives, we compared the prediction of minimal weight (MW) among 57 interscholastic wrestlers using three anthropometric methods (skinfolds (SF) and two skeletal dimensions equations) and three BIA systems (Berkeley Medical Research (BMR), RJL, and Valhalla (VAL]. All methods showed high correlations (r values greater than 0.92) with hydrostatic weighting (HW) and between methods (r values greater than 0.90). The standard errors of estimate (SEE) were relatively small for all methods, especially for SF and the three BIA systems (SEE less than 0.70 kg). The total errors of prediction (E) for RJL and VAL (E = 4.4 and 3.9 kg) were significantly larger than observed nonsignificant BMR and SF values (E = 2.3 and 1.8 kg, respectively). Significant mean differences were observed between HW, RJL, VAL, and the two skeletal dimensions equations, but nonsignificant differences were observed between HW, BMR, and SF. BMR differed significantly from the RJL and VAL systems. The results suggest that RJL and VAL have potential application for this subpopulation. Prediction equation refinement with the addition of selected anthropometric measurement or moderating variables may enhance their utility. However, within the scope of our study, SF and BMR BIA appear to be the most valid methods for determining MW in interscholastic wrestlers.

Examining subtypes of behavior problems among 3-year-old children, Part I: investigating validity of subtypes and biological risk-factors.

PubMed

Harvey, Elizabeth A; Friedman-Weieneth, Julie L; Goldstein, Lauren H; Sherman, Alison H

2007-02-01

This study examined 3-year-old children who were classified as hyperactive (HYP), oppositional-defiant (OD), hyperactive and oppositional defiant (HYP/OD), and non-problem based on mothers' reports of behavior. Using fathers,' teachers,' and observers' ratings of children's behavior, concurrent validity was excellent for the HYP/OD group, moderate for the HYP group, and poor for the OD group. As predicted, both the HYP/OD and HYP groups reported more prenatal/perinatal birth complications and a greater family history of hyperactivity than did non-problem children. Furthermore, the HYP/OD group showed a greater family history of conduct disorder and oppositional defiant disorder (ODD) symptoms than did non-problem children; however, the HYP group also showed a greater family history of ODD than did non-problem children. Results suggest that as early as age 3, these behavior subtypes appear to be linked to biologically-based risk-factors in ways that are consistent with theories of the development of ADHD.

Genomic prediction of reproduction traits for Merino sheep.

PubMed

Bolormaa, S; Brown, D J; Swan, A A; van der Werf, J H J; Hayes, B J; Daetwyler, H D

2017-06-01

Economically important reproduction traits in sheep, such as number of lambs weaned and litter size, are expressed only in females and later in life after most selection decisions are made, which makes them ideal candidates for genomic selection. Accurate genomic predictions would lead to greater genetic gain for these traits by enabling accurate selection of young rams with high genetic merit. The aim of this study was to design and evaluate the accuracy of a genomic prediction method for female reproduction in sheep using daughter trait deviations (DTD) for sires and ewe phenotypes (when individual ewes were genotyped) for three reproduction traits: number of lambs born (NLB), litter size (LSIZE) and number of lambs weaned. Genomic best linear unbiased prediction (GBLUP), BayesR and pedigree BLUP analyses of the three reproduction traits measured on 5340 sheep (4503 ewes and 837 sires) with real and imputed genotypes for 510 174 SNPs were performed. The prediction of breeding values using both sire and ewe trait records was validated in Merino sheep. Prediction accuracy was evaluated by across sire family and random cross-validations. Accuracies of genomic estimated breeding values (GEBVs) were assessed as the mean Pearson correlation adjusted by the accuracy of the input phenotypes. The addition of sire DTD into the prediction analysis resulted in higher accuracies compared with using only ewe records in genomic predictions or pedigree BLUP. Using GBLUP, the average accuracy based on the combined records (ewes and sire DTD) was 0.43 across traits, but the accuracies varied by trait and type of cross-validations. The accuracies of GEBVs from random cross-validations (range 0.17-0.61) were higher than were those from sire family cross-validations (range 0.00-0.51). The GEBV accuracies of 0.41-0.54 for NLB and LSIZE based on the combined records were amongst the highest in the study. Although BayesR was not significantly different from GBLUP in prediction accuracy, it identified several candidate genes which are known to be associated with NLB and LSIZE. The approach provides a way to make use of all data available in genomic prediction for traits that have limited recording. © 2017 Stichting International Foundation for Animal Genetics.

Validating older adults' reports of less mind-wandering: An examination of eye movements and dispositional influences.

PubMed

Frank, David J; Nara, Brent; Zavagnin, Michela; Touron, Dayna R; Kane, Michael J

2015-06-01

The Control Failures × Concerns theory perspective proposes that mind-wandering occurs, in part, because of failures to inhibit distracting thoughts from entering consciousness (McVay & Kane, 2012). Despite older adults (OAs) exhibiting poorer inhibition, they report less mind-wandering than do young adults (YAs). Proposed explanations include (a) that OAs' thought reports are less valid due to an unawareness of, or reluctance to report, task-unrelated thoughts (TUTs) and (b) that dispositional factors protect OAs from mind-wandering. The primary goal of the current study was to test the validity of thought reports via eye-tracking. A secondary goal was to examine whether OAs' greater mindfulness (Splevins, Smith, & Simpson, 2009) or more positive mood (Carstensen, Isaacowitz, & Charles, 1999) protects them from TUTs. We found that eye movement patterns predicted OAs' TUT reports and YAs' task-related interference (TRI, or thoughts about one's performance) reports. Additionally, poor comprehension was associated with more TUTs in both age groups and more TRI in YAs. These results support the validity of OAs' thought reports. Concerning the second aim of the study, OAs' greater tendency to observe their surroundings (a facet of mindfulness) was related to increased TRI, and OAs' more positive mood and greater motivation partially mediated age differences in TUTs. OAs' reduced TUT reports appear to be genuine and potentially related to dispositional factors. (c) 2015 APA, all rights reserved.

New Measures Assessing Predictors of Academic Persistence for Historically Underrepresented Racial/Ethnic Undergraduates in Science

ERIC Educational Resources Information Center

Byars-Winston, Angela; Rogers, Jenna; Branchaw, Janet; Pribbenow, Christine; Hanke, Ryan; Pfund, Christine

2016-01-01

An important step in broadening participation of historically underrepresented (HU) racial/ethnic groups in the sciences is the creation of measures validated with these groups that will allow for greater confidence in the results of investigations into factors that predict their persistence. This study introduces new measures of theoretically…

Exploring Methods for Developing Behaviorally Anchored Rating Scales for Evaluating Structured Interview Performance. Research Report. ETS RR-17-28

ERIC Educational Resources Information Center

Kell, Harrison J.; Martin-Raugh, Michelle P.; Carney, Lauren M.; Inglese, Patricia A.; Chen, Lei; Feng, Gary

2017-01-01

Behaviorally anchored rating scales (BARS) are an essential component of structured interviews. Use of BARS to evaluate interviewees' performance is associated with greater predictive validity and reliability and less bias. BARS are time-consuming and expensive to construct, however. This report explores the feasibility of gathering participants'…

Potential functional variants associated with age at puberty in a validation population of swine

USDA-ARS?s Scientific Manuscript database

Puberty in pigs is defined as age at first estrus and gilts that have an earlier age at puberty are more likely to have greater sow lifetime productivity. Because age at puberty is predictive for sow longevity and lifetime productivity, but not routinely measured in commercial herds, it would be ben...

Development and practical implications of the Exercise Resourcefulness Inventory.

PubMed

Fast, Hilary V; Kennett, Deborah J

2015-05-01

To determine the validity and reliability of the Exercise Resourcefulness Inventory (ERI) designed to assess the self-regulatory strategies used to promote regular exercise. In Study 1, the inventory's relationship with other established scales in the exercise behavior change field was examined. In Study 2, the test-retest reliability and predictive validity of the ERI was established by having participants from Study 1 complete the inventory a second time. Internal consistency, and convergent, discriminant, and concurrent validity were supported in both studies. The test-retest correlation of the ERI was .80. As well, participants scoring higher on the ERI in Study 1 were more likely to be at a higher stage of change in Study 2, and greater increases in exercise resourcefulness over time were predictive of advancement to higher stages of change. ERI is a reliable and valid measure to assess the self-regulatory strategies used to promote regular exercise. Facilitators may want to tailor exercise programs for individuals scoring lower in resourcefulness to prevent them from relapsing. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Hardiness scales in Iranian managers: evidence of incremental validity in relationships with the five factor model and with organizational and psychological adjustment.

PubMed

Ghorbani, Nima; Watson, P J

2005-06-01

This study examined the incremental validity of Hardiness scales in a sample of Iranian managers. Along with measures of the Five Factor Model and of Organizational and Psychological Adjustment, Hardiness scales were administered to 159 male managers (M age = 39.9, SD = 7.5) who had worked in their organizations for 7.9 yr. (SD=5.4). Hardiness predicted greater Job Satisfaction, higher Organization-based Self-esteem, and perceptions of the work environment as being less stressful and constraining. Hardiness also correlated positively with Assertiveness, Emotional Stability, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness and negatively with Depression, Anxiety, Perceived Stress, Chance External Control, and a Powerful Others External Control. Evidence of incremental validity was obtained when the Hardiness scales supplemented the Five Factor Model in predicting organizational and psychological adjustment. These data documented the incremental validity of the Hardiness scales in a non-Western sample and thus confirmed once again that Hardiness has a relevance that extends beyond the culture in which it was developed.

Habitat models to predict wetland bird occupancy influenced by scale, anthropogenic disturbance, and imperfect detection

USGS Publications Warehouse

Glisson, Wesley J.; Conway, Courtney J.; Nadeau, Christopher P.; Borgmann, Kathi L.

2017-01-01

Understanding species–habitat relationships for endangered species is critical for their conservation. However, many studies have limited value for conservation because they fail to account for habitat associations at multiple spatial scales, anthropogenic variables, and imperfect detection. We addressed these three limitations by developing models for an endangered wetland bird, Yuma Ridgway's rail (Rallus obsoletus yumanensis), that examined how the spatial scale of environmental variables, inclusion of anthropogenic disturbance variables, and accounting for imperfect detection in validation data influenced model performance. These models identified associations between environmental variables and occupancy. We used bird survey and spatial environmental data at 2473 locations throughout the species' U.S. range to create and validate occupancy models and produce predictive maps of occupancy. We compared habitat-based models at three spatial scales (100, 224, and 500 m radii buffers) with and without anthropogenic disturbance variables using validation data adjusted for imperfect detection and an unadjusted validation dataset that ignored imperfect detection. The inclusion of anthropogenic disturbance variables improved the performance of habitat models at all three spatial scales, and the 224-m-scale model performed best. All models exhibited greater predictive ability when imperfect detection was incorporated into validation data. Yuma Ridgway's rail occupancy was negatively associated with ephemeral and slow-moving riverine features and high-intensity anthropogenic development, and positively associated with emergent vegetation, agriculture, and low-intensity development. Our modeling approach accounts for common limitations in modeling species–habitat relationships and creating predictive maps of occupancy probability and, therefore, provides a useful framework for other species.

Operationalization and Validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) Fall Risk Algorithm in a Nationally Representative Sample

PubMed Central

Lohman, Matthew C.; Crow, Rebecca S.; DiMilia, Peter R.; Nicklett, Emily J.; Bruce, Martha L.; Batsis, John A.

2017-01-01

Background Preventing falls and fall-related injuries among older adults is a public health priority. The Stopping Elderly Accidents, Deaths, and Injuries (STEADI) tool was developed to promote fall risk screening and encourage coordination between clinical and community-based fall prevention resources; however, little is known about the tool’s predictive validity or adaptability to survey data. Methods Data from five annual rounds (2011–2015) of the National Health and Aging Trends Study (NHATS), a representative cohort of adults age 65 and older in the US. Analytic sample respondents (n=7,392) were categorized at baseline as having low, moderate, or high fall risk according to the STEADI algorithm adapted for use with NHATS data. Logistic mixed-effects regression was used to estimate the association between baseline fall risk and subsequent falls and mortality. Analyses incorporated complex sampling and weighting elements to permit inferences at a national level. Results Participants classified as having moderate and high fall risk had 2.62 (95% CI: 2.29, 2.99) and 4.76 (95% CI: 3.51, 6.47) times greater odds of falling during follow-up compared to those with low risk, respectively, controlling for sociodemographic and health related risk factors for falls. High fall risk was also associated with greater likelihood of falling multiple times annually but not with greater risk of mortality. Conclusion The adapted STEADI clinical fall risk screening tool is a valid measure for predicting future fall risk using survey cohort data. Further efforts to standardize screening for fall risk and to coordinate between clinical and community-based fall prevention initiatives are warranted. PMID:28947669

The COPD Helplessness Index

PubMed Central

Katz, Patricia P.; Yelin, Edward H.; Iribarren, Carlos; Knight, Sara J.; Blanc, Paul D.; Eisner, Mark D.

2010-01-01

Background: Psychologic factors affect how patients with COPD respond to attempts to improve their self-management skills. Learned helplessness may be one such factor, but there is no validated measure of helplessness in COPD. Methods: We administered a new COPD Helplessness Index (CHI) to 1,202 patients with COPD. Concurrent validity was assessed through association of the CHI with established psychosocial measures and COPD severity. The association of helplessness with incident COPD exacerbations was then examined by following subjects over a median 2.1 years, defining COPD exacerbations as COPD-related hospitalizations or ED visits. Results: The CHI demonstrated internal consistency (Cronbach α = 0.75); factor analysis was consistent with the CHI representing a single construct. Greater CHI-measured helplessness correlated with greater COPD severity assessed by the BODE (Body-mass, Obstruction, Dyspnea, Exercise) Index (r = 0.34; P < .001). Higher CHI scores were associated with worse generic (Short Form-12, Physical Component Summary Score) and respiratory-specific (Airways Questionnaire 20) health-related quality of life, greater depressive symptoms, and higher anxiety (all P < .001). Controlling for sociodemographics and smoking status, helplessness was prospectively associated with incident COPD exacerbations (hazard ratio = 1.31; P < .001). After also controlling for the BODE Index, helplessness remained predictive of COPD exacerbations among subjects with BODE Index ≤ median (hazard ratio = 1.35; P = .01), but not among subjects with higher BODE Index values (hazard ratio = 0.93; P = .34). Conclusions: The CHI is an internally consistent and valid measure, concurrently associated with health status and predictively associated with COPD exacerbations. The CHI may prove a useful tool in analyzing differential clinical responses mediated by patient-centered attributes. PMID:19837823

MiRNA Expression Analysis of Pretreatment Biopsies Predicts the Pathological Response of Esophageal Squamous Cell Carcinomas to Neoadjuvant Chemoradiotherapy.

PubMed

Wen, Jing; Luo, Kongjia; Liu, Hui; Liu, Shiliang; Lin, Guangrong; Hu, Yi; Zhang, Xu; Wang, Geng; Chen, Yuping; Chen, Zhijian; Li, Yi; Lin, Ting; Xie, Xiuying; Liu, Mengzhong; Wang, Huiyun; Yang, Hong; Fu, Jianhua

2016-05-01

To identify miRNA markers useful for esophageal squamous cell carcinoma (ESCC) neoadjuvant chemoradiotherapy (neo-CRT) response prediction. Neo-CRT followed by surgery improves ESCC patients' survival compared with surgery alone. However, CRT outcomes are heterogeneous, and no current methods can predict CRT responses. Differentially expressed miRNAs between ESCC pathological responders and nonresponders after neo-CRT were identified by miRNA profiling and verified by real-time quantitative polymerase chain reaction (qPCR) of 27 ESCCs in the training set. Several class prediction algorithms were used to build the response-classifying models with the qPCR data. Predictive powers of the models were further assessed with a second set of 79 ESCCs. Ten miRNAs with greater than a 1.5-fold change between pathological responders and nonresponders were identified and verified, respectively. A support vector machine (SVM) prediction model, composed of 4 miRNAs (miR-145-5p, miR-152, miR-193b-3p, and miR-376a-3p), were developed. It provided overall accuracies of 100% and 87.3% for discriminating pathological responders and nonresponders in the training and external validation sets, respectively. In multivariate analysis, the subgroup determined by the SVM model was the only independent factor significantly associated with neo-CRT response in the external validation sets. Combined qPCR of the 4 miRNAs provides the possibility of ESCC neo-CRT response prediction, which may facilitate individualized ESCC treatment. Further prospective validation in larger independent cohorts is necessary to fully assess its predictive power.

Cancer-related Concerns of Spouses of Women with Breast Cancer

PubMed Central

Fletcher, Kristin A.; Lewis, Frances Marcus; Haberman, Mel R.

2009-01-01

Objective To describe spouses' reported cancer-related demands attributed to their wife's breast cancer and to test the construct and predictive validity of a brief standardized measure of these demands. Methods Cross-sectional and longitudinal data were obtained from 151 spouses of women newly diagnosed with non-metastatic breast cancer. Descriptive statistics were computed to describe spouses' dominant cancer-related demands and multivariate regression analyses tested the construct and predictive validity of the standardized measure. Results Five categories of spouses' cancer-related demands were identified, such as concerns about: spouses' own functioning; wife's well being and response to treatment; couples' sexual activities; the family's and children's well-being; and the spouses' role in supporting their wives. A 33-item short version of the standardized measure of cancer demands demonstrated construct and predictive validity that was comparable to a 123-item version of the same questionnaire. Greater numbers of illness demands occurred when spouses were more depressed and had less confidence in their ability to manage the impact of the cancer (F=18.08 (3, 103), p<.001). Predictive validity was established by the short form's ability to significantly predict the quality of marital communication and spouses' self-efficacy at a two-month interval. Conclusion The short-version of the standardized measure of cancer-related demands shows promise for future application in clinic settings. Additional testing of the questionnaire is warranted. Spouses' breast cancer-related demands deserve attention by providers. In the absence of assisting them, spouses' illness pressures have deleterious consequences for the quality of marital communication and spouses' self-confidence. PMID:20014184

Different type 2 diabetes risk assessments predict dissimilar numbers at ‘high risk’: a retrospective analysis of diabetes risk-assessment tools

PubMed Central

Gray, Benjamin J; Bracken, Richard M; Turner, Daniel; Morgan, Kerry; Thomas, Michael; Williams, Sally P; Williams, Meurig; Rice, Sam; Stephens, Jeffrey W

2015-01-01

Background Use of a validated risk-assessment tool to identify individuals at high risk of developing type 2 diabetes is currently recommended. It is under-reported, however, whether a different risk tool alters the predicted risk of an individual. Aim This study explored any differences between commonly used validated risk-assessment tools for type 2 diabetes. Design and setting Cross-sectional analysis of individuals who participated in a workplace-based risk assessment in Carmarthenshire, South Wales. Method Retrospective analysis of 676 individuals (389 females and 287 males) who participated in a workplace-based diabetes risk-assessment initiative. Ten-year risk of type 2 diabetes was predicted using the validated QDiabetes®, Leicester Risk Assessment (LRA), FINDRISC, and Cambridge Risk Score (CRS) algorithms. Results Differences between the risk-assessment tools were apparent following retrospective analysis of individuals. CRS categorised the highest proportion (13.6%) of individuals at ‘high risk’ followed by FINDRISC (6.6%), QDiabetes (6.1%), and, finally, the LRA was the most conservative risk tool (3.1%). Following further analysis by sex, over one-quarter of males were categorised at high risk using CRS (25.4%), whereas a greater percentage of females were categorised as high risk using FINDRISC (7.8%). Conclusion The adoption of a different valid risk-assessment tool can alter the predicted risk of an individual and caution should be used to identify those individuals who really are at high risk of type 2 diabetes. PMID:26541180

Different type 2 diabetes risk assessments predict dissimilar numbers at 'high risk': a retrospective analysis of diabetes risk-assessment tools.

PubMed

Gray, Benjamin J; Bracken, Richard M; Turner, Daniel; Morgan, Kerry; Thomas, Michael; Williams, Sally P; Williams, Meurig; Rice, Sam; Stephens, Jeffrey W

2015-12-01

Use of a validated risk-assessment tool to identify individuals at high risk of developing type 2 diabetes is currently recommended. It is under-reported, however, whether a different risk tool alters the predicted risk of an individual. This study explored any differences between commonly used validated risk-assessment tools for type 2 diabetes. Cross-sectional analysis of individuals who participated in a workplace-based risk assessment in Carmarthenshire, South Wales. Retrospective analysis of 676 individuals (389 females and 287 males) who participated in a workplace-based diabetes risk-assessment initiative. Ten-year risk of type 2 diabetes was predicted using the validated QDiabetes(®), Leicester Risk Assessment (LRA), FINDRISC, and Cambridge Risk Score (CRS) algorithms. Differences between the risk-assessment tools were apparent following retrospective analysis of individuals. CRS categorised the highest proportion (13.6%) of individuals at 'high risk' followed by FINDRISC (6.6%), QDiabetes (6.1%), and, finally, the LRA was the most conservative risk tool (3.1%). Following further analysis by sex, over one-quarter of males were categorised at high risk using CRS (25.4%), whereas a greater percentage of females were categorised as high risk using FINDRISC (7.8%). The adoption of a different valid risk-assessment tool can alter the predicted risk of an individual and caution should be used to identify those individuals who really are at high risk of type 2 diabetes. © British Journal of General Practice 2015.

Predictive validity and correlates of self-assessed resilience among U.S. Army soldiers.

PubMed

Campbell-Sills, Laura; Kessler, Ronald C; Ursano, Robert J; Sun, Xiaoying; Taylor, Charles T; Heeringa, Steven G; Nock, Matthew K; Sampson, Nancy A; Jain, Sonia; Stein, Murray B

2018-02-01

Self-assessment of resilience could prove valuable to military and other organizations whose personnel confront foreseen stressors. We evaluated the validity of self-assessed resilience among U.S. Army soldiers, including whether predeployment perceived resilience predicted postdeployment emotional disorder. Resilience was assessed via self-administered questionnaire among new soldiers reporting for basic training (N = 35,807) and experienced soldiers preparing to deploy to Afghanistan (N = 8,558). Concurrent validity of self-assessed resilience was evaluated among recruits by estimating its association with past-month emotional disorder. Predictive validity was examined among 3,526 experienced soldiers with no lifetime emotional disorder predeployment. Predictive models estimated associations of predeployment resilience with incidence of emotional disorder through 9 months postdeployment and with marked improvement in coping at 3 months postdeployment. Weights-adjusted regression models incorporated stringent controls for risk factors. Soldiers characterized themselves as very resilient on average [M = 14.34, SD = 4.20 (recruits); M = 14.75, SD = 4.31 (experienced soldiers); theoretical range = 0-20]. Demographic characteristics exhibited only modest associations with resilience, while severity of childhood maltreatment was negatively associated with resilience in both samples. Among recruits, resilience was inversely associated with past-month emotional disorder [adjusted odds ratio (AOR) = 0.65, 95% CI = 0.62-0.68, P < .0005 (per standard score increase)]. Among deployed soldiers, greater predeployment resilience was associated with decreased incidence of emotional disorder (AOR = 0.91; 95% CI = 0.84-0.98; P = .016) and increased odds of improved coping (AOR = 1.36; 95% CI = 1.24-1.49; P < .0005) postdeployment. Findings supported validity of self-assessed resilience among soldiers, although its predictive effect on incidence of emotional disorder was modest. In conjunction with assessment of known risk factors, measurement of resilience could help predict adaptation to foreseen stressors like deployment. © 2017 Wiley Periodicals, Inc.

Comparison of Bruce treadmill exercise test protocols: is ramped Bruce equal or superior to standard bruce in producing clinically valid studies for patients presenting for evaluation of cardiac ischemia or arrhythmia with body mass index equal to or greater than 30?

PubMed

Bires, Angela Macci; Lawson, Dori; Wasser, Thomas E; Raber-Baer, Donna

2013-12-01

Clinically valid cardiac evaluation via treadmill stress testing requires patients to achieve specific target heart rates and to successfully complete the cardiac examination. A comparison of the standard Bruce protocol and the ramped Bruce protocol was performed using data collected over a 1-y period from a targeted patient population with a body mass index (BMI) equal to or greater than 30 to determine which treadmill protocol provided more successful examination results. The functional capacity, metabolic equivalent units achieved, pressure rate product, and total time on the treadmill as measured for the obese patients were clinically valid and comparable to normal-weight and overweight patients (P < 0.001). Data gathered from each protocol demonstrated that the usage of the ramped Bruce protocol achieved more consistent results in comparison across all BMI groups in achieving 80%-85% of their age-predicted maximum heart rate. This study did not adequately establish that the ramped Bruce protocol was superior to the standard Bruce protocol for the examination of patients with a BMI equal to or greater than 30.

Using a Guided Machine Learning Ensemble Model to Predict Discharge Disposition following Meningioma Resection.

PubMed

Muhlestein, Whitney E; Akagi, Dallin S; Kallos, Justiss A; Morone, Peter J; Weaver, Kyle D; Thompson, Reid C; Chambless, Lola B

2018-04-01

Objective  Machine learning (ML) algorithms are powerful tools for predicting patient outcomes. This study pilots a novel approach to algorithm selection and model creation using prediction of discharge disposition following meningioma resection as a proof of concept. Materials and Methods  A diversity of ML algorithms were trained on a single-institution database of meningioma patients to predict discharge disposition. Algorithms were ranked by predictive power and top performers were combined to create an ensemble model. The final ensemble was internally validated on never-before-seen data to demonstrate generalizability. The predictive power of the ensemble was compared with a logistic regression. Further analyses were performed to identify how important variables impact the ensemble. Results  Our ensemble model predicted disposition significantly better than a logistic regression (area under the curve of 0.78 and 0.71, respectively, p  = 0.01). Tumor size, presentation at the emergency department, body mass index, convexity location, and preoperative motor deficit most strongly influence the model, though the independent impact of individual variables is nuanced. Conclusion  Using a novel ML technique, we built a guided ML ensemble model that predicts discharge destination following meningioma resection with greater predictive power than a logistic regression, and that provides greater clinical insight than a univariate analysis. These techniques can be extended to predict many other patient outcomes of interest.

Validating SPICES as a Screening Tool for Frailty Risks among Hospitalized Older Adults

PubMed Central

Aronow, Harriet Udin; Borenstein, Jeff; Haus, Flora; Braunstein, Glenn D.; Bolton, Linda Burnes

2014-01-01

Older patients are vulnerable to adverse hospital events related to frailty. SPICES, a common screening protocol to identify risk factors in older patients, alerts nurses to initiate care plans to reduce the probability of patient harm. However, there is little published validating the association between SPICES and measures of frailty and adverse outcomes. This paper used data from a prospective cohort study on frailty among 174 older adult inpatients to validate SPICES. Almost all patients met one or more SPICES criteria. The sum of SPICES was significantly correlated with age and other well-validated assessments for vulnerability, comorbid conditions, and depression. Individuals meeting two or more SPICES criteria had a risk of adverse hospital events three times greater than individuals with either no or one criterion. Results suggest that as a screening tool used within 24 hours of admission, SPICES is both valid and predictive of adverse events. PMID:24876954

A Critical Review of Validation, Blind Testing, and Real- World Use of Alchemical Protein-Ligand Binding Free Energy Calculations.

PubMed

Abel, Robert; Wang, Lingle; Mobley, David L; Friesner, Richard A

2017-01-01

Protein-ligand binding is among the most fundamental phenomena underlying all molecular biology, and a greater ability to more accurately and robustly predict the binding free energy of a small molecule ligand for its cognate protein is expected to have vast consequences for improving the efficiency of pharmaceutical drug discovery. We briefly reviewed a number of scientific and technical advances that have enabled alchemical free energy calculations to recently emerge as a preferred approach, and critically considered proper validation and effective use of these techniques. In particular, we characterized a selection bias effect which may be important in prospective free energy calculations, and introduced a strategy to improve the accuracy of the free energy predictions. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

A Systematic Review of Validated Methods for Identifying Cerebrovascular Accident or Transient Ischemic Attack Using Administrative Data

PubMed Central

Andrade, Susan E.; Harrold, Leslie R.; Tjia, Jennifer; Cutrona, Sarah L.; Saczynski, Jane S.; Dodd, Katherine S.; Goldberg, Robert J.; Gurwitz, Jerry H.

2012-01-01

Purpose To perform a systematic review of the validity of algorithms for identifying cerebrovascular accidents (CVAs) or transient ischemic attacks (TIAs) using administrative and claims data. Methods PubMed and Iowa Drug Information Service (IDIS) searches of the English language literature were performed to identify studies published between 1990 and 2010 that evaluated the validity of algorithms for identifying CVAs (ischemic and hemorrhagic strokes, intracranial hemorrhage and subarachnoid hemorrhage) and/or TIAs in administrative data. Two study investigators independently reviewed the abstracts and articles to determine relevant studies according to pre-specified criteria. Results A total of 35 articles met the criteria for evaluation. Of these, 26 articles provided data to evaluate the validity of stroke, 7 reported the validity of TIA, 5 reported the validity of intracranial bleeds (intracerebral hemorrhage and subarachnoid hemorrhage), and 10 studies reported the validity of algorithms to identify the composite endpoints of stroke/TIA or cerebrovascular disease. Positive predictive values (PPVs) varied depending on the specific outcomes and algorithms evaluated. Specific algorithms to evaluate the presence of stroke and intracranial bleeds were found to have high PPVs (80% or greater). Algorithms to evaluate TIAs in adult populations were generally found to have PPVs of 70% or greater. Conclusions The algorithms and definitions to identify CVAs and TIAs using administrative and claims data differ greatly in the published literature. The choice of the algorithm employed should be determined by the stroke subtype of interest. PMID:22262598

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.

Prediction of individual milk proteins including free amino acids in bovine milk using mid-infrared spectroscopy and their correlations with milk processing characteristics.

PubMed

McDermott, A; Visentin, G; De Marchi, M; Berry, D P; Fenelon, M A; O'Connor, P M; Kenny, O A; McParland, S

2016-04-01

The aim of this study was to evaluate the effectiveness of mid-infrared spectroscopy in predicting milk protein and free amino acid (FAA) composition in bovine milk. Milk samples were collected from 7 Irish research herds and represented cows from a range of breeds, parities, and stages of lactation. Mid-infrared spectral data in the range of 900 to 5,000 cm(-1) were available for 730 milk samples; gold standard methods were used to quantify individual protein fractions and FAA of these samples with a view to predicting these gold standard protein fractions and FAA levels with available mid-infrared spectroscopy data. Separate prediction equations were developed for each trait using partial least squares regression; accuracy of prediction was assessed using both cross validation on a calibration data set (n=400 to 591 samples) and external validation on an independent data set (n=143 to 294 samples). The accuracy of prediction in external validation was the same irrespective of whether undertaken on the entire external validation data set or just within the Holstein-Friesian breed. The strongest coefficient of correlation obtained for protein fractions in external validation was 0.74, 0.69, and 0.67 for total casein, total β-lactoglobulin, and β-casein, respectively. Total proteins (i.e., total casein, total whey, and total lactoglobulin) were predicted with greater accuracy then their respective component traits; prediction accuracy using the infrared spectrum was superior to prediction using just milk protein concentration. Weak to moderate prediction accuracies were observed for FAA. The greatest coefficient of correlation in both cross validation and external validation was for Gly (0.75), indicating a moderate accuracy of prediction. Overall, the FAA prediction models overpredicted the gold standard values. Near-unity correlations existed between total casein and β-casein irrespective of whether the traits were based on the gold standard (0.92) or mid-infrared spectroscopy predictions (0.95). Weaker correlations among FAA were observed than the correlations among the protein fractions. Pearson correlations between gold standard protein fractions and the milk processing characteristics of rennet coagulation time, curd firming time, curd firmness, heat coagulating time, pH, and casein micelle size were weak to moderate and ranged from -0.48 (protein and pH) to 0.50 (total casein and a30). Pearson correlations between gold standard FAA and these milk processing characteristics were also weak to moderate and ranged from -0.60 (Val and pH) to 0.49 (Val and K20). Results from this study indicate that mid-infrared spectroscopy has the potential to predict protein fractions and some FAA in milk at a population level. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Pediatric Eating Assessment Tool-10 as an indicator to predict aspiration in children with esophageal atresia.

PubMed

Soyer, Tutku; Yalcin, Sule; Arslan, Selen Serel; Demir, Numan; Tanyel, Feridun Cahit

2017-10-01

Airway aspiration is a common problem in children with esophageal atresia (EA). Pediatric Eating Assessment Tool-10 (pEAT-10) is a self-administered questionnaire to evaluate dysphagia symptoms in children. A prospective study was performed to evaluate the validity of pEAT-10 to predict aspiration in children with EA. Patients with EA were evaluated for age, sex, type of atresia, presence of associated anomalies, type of esophageal repair, time of definitive treatment, and the beginning of oral feeding. Penetration-aspiration score (PAS) was evaluated with videofluoroscopy (VFS) and parents were surveyed for pEAT-10, dysphagia score (DS) and functional oral intake scale (FOIS). PAS scores greater than 7 were considered as risk of aspiration. EAT-10 values greater than 3 were assessed as abnormal. Higher DS scores shows dysphagia whereas higher FOIS shows better feeding abilities. Forty patients were included. Children with PAS greater than 7 were assessed as PAS+ group, and scores less than 7 were constituted as PAS- group. Demographic features and results of surgical treatments showed no difference between groups (p>0.05). The median values of PAS, pEAT-10 and DS scores were significantly higher in PAS+ group when compared to PAS- group (p<0.05). The sensitivity and specificity of pEAT-10 to predict aspiration were 88% and 77%, and the positive and negative predictive values were 22% and 11%, respectively. Type-C cases had better pEAT-10 and FOIS scores with respect to type-A cases, and both scores were statistically more reliable in primary repair than delayed repair (p<0.05). Among the postoperative complications, only leakage had impact on DS, pEAT-10, PAS and FOIS scores (p<0.05). The pEAT-10 is a valid, simple and reliable tool to predict aspiration in children. Patients with higher pEAT-10 scores should undergo detailed evaluation of deglutitive functions and assessment of risks of aspiration to improve safer feeding strategies. Level II (Development of diagnostic criteria in a consecutive series of patients and a universally applied "gold standard"). Copyright © 2017 Elsevier Inc. All rights reserved.

Predicting enteric methane emission of dairy cows with milk Fourier-transform infrared spectra and gas chromatography-based milk fatty acid profiles.

PubMed

van Gastelen, S; Mollenhorst, H; Antunes-Fernandes, E C; Hettinga, K A; van Burgsteden, G G; Dijkstra, J; Rademaker, J L W

2018-06-01

The objective of the present study was to compare the prediction potential of milk Fourier-transform infrared spectroscopy (FTIR) for CH 4 emissions of dairy cows with that of gas chromatography (GC)-based milk fatty acids (MFA). Data from 9 experiments with lactating Holstein-Friesian cows, with a total of 30 dietary treatments and 218 observations, were used. Methane emissions were measured for 3 consecutive days in climate respiration chambers and expressed as production (g/d), yield (g/kg of dry matter intake; DMI), and intensity (g/kg of fat- and protein-corrected milk; FPCM). Dry matter intake was 16.3 ± 2.18 kg/d (mean ± standard deviation), FPCM yield was 25.9 ± 5.06 kg/d, CH 4 production was 366 ± 53.9 g/d, CH 4 yield was 22.5 ± 2.10 g/kg of DMI, and CH 4 intensity was 14.4 ± 2.58 g/kg of FPCM. Milk was sampled during the same days and analyzed by GC and by FTIR. Multivariate GC-determined MFA-based and FTIR-based CH 4 prediction models were developed, and subsequently, the final CH 4 prediction models were evaluated with root mean squared error of prediction and concordance correlation coefficient analysis. Further, we performed a random 10-fold cross validation to calculate the performance parameters of the models (e.g., the coefficient of determination of cross validation). The final GC-determined MFA-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 35.7 g/d, 1.6 g/kg of DMI, and 1.6 g/kg of FPCM and with a concordance correlation coefficient of 0.72, 0.59, and 0.77, respectively. The final FTIR-based CH 4 prediction models estimate CH 4 production, yield, and intensity with a root mean squared error of prediction of 43.2 g/d, 1.9 g/kg of DMI, and 1.7 g/kg of FPCM and with a concordance correlation coefficient of 0.52, 0.40, and 0.72, respectively. The GC-determined MFA-based prediction models described a greater part of the observed variation in CH 4 emission than did the FTIR-based models. The cross validation results indicate that all CH 4 prediction models (both GC-determined MFA-based and FTIR-based models) are robust; the difference between the coefficient of determination and the coefficient of determination of cross validation ranged from 0.01 to 0.07. The results indicate that GC-determined MFA have a greater potential than FTIR spectra to estimate CH 4 production, yield, and intensity. Both techniques hold potential but may not yet be ready to predict CH 4 emission of dairy cows in practice. Additional CH 4 measurements are needed to improve the accuracy and robustness of GC-determined MFA and FTIR spectra for CH 4 prediction. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Prediction of citation counts for clinical articles at two years using data available within three weeks of publication: retrospective cohort study

PubMed Central

2008-01-01

Objective To determine if citation counts at two years could be predicted for clinical articles that pass basic criteria for critical appraisal using data within three weeks of publication from external sources and an online article rating service. Design Retrospective cohort study. Setting Online rating service, Canada. Participants 1274 articles from 105 journals published from January to June 2005, randomly divided into a 60:40 split to provide derivation and validation datasets. Main outcome measures 20 article and journal features, including ratings of clinical relevance and newsworthiness, routinely collected by the McMaster online rating of evidence system, compared with citation counts at two years. Results The derivation analysis showed that the regression equation accounted for 60% of the variation (R2=0.60, 95% confidence interval 0.538 to 0.629). This model applied to the validation dataset gave a similar prediction (R2=0.56, 0.476 to 0.596, shrinkage 0.04; shrinkage measures how well the derived equation matches data from the validation dataset). Cited articles in the top half and top third were predicted with 83% and 61% sensitivity and 72% and 82% specificity. Higher citations were predicted by indexing in numerous databases; number of authors; abstraction in synoptic journals; clinical relevance scores; number of cited references; and original, multicentred, and therapy articles from journals with a greater proportion of articles abstracted. Conclusion Citation counts can be reliably predicted at two years using data within three weeks of publication. PMID:18292132

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

PubMed

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

2015-06-01

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

Memory Binding Test Predicts Incident Amnestic Mild Cognitive Impairment.

PubMed

Mowrey, Wenzhu B; Lipton, Richard B; Katz, Mindy J; Ramratan, Wendy S; Loewenstein, David A; Zimmerman, Molly E; Buschke, Herman

2016-07-14

The Memory Binding Test (MBT), previously known as Memory Capacity Test, has demonstrated discriminative validity for distinguishing persons with amnestic mild cognitive impairment (aMCI) and dementia from cognitively normal elderly. We aimed to assess the predictive validity of the MBT for incident aMCI. In a longitudinal, community-based study of adults aged 70+, we administered the MBT to 246 cognitively normal elderly adults at baseline and followed them annually. Based on previous work, a subtle reduction in memory binding at baseline was defined by a Total Items in the Paired (TIP) condition score of ≤22 on the MBT. Cox proportional hazards models were used to assess the predictive validity of the MBT for incident aMCI accounting for the effects of covariates. The hazard ratio of incident aMCI was also assessed for different prediction time windows ranging from 4 to 7 years of follow-up, separately. Among 246 controls who were cognitively normal at baseline, 48 developed incident aMCI during follow-up. A baseline MBT reduction was associated with an increased risk for developing incident aMCI (hazard ratio (HR) = 2.44, 95% confidence interval: 1.30-4.56, p = 0.005). When varying the prediction window from 4-7 years, the MBT reduction remained significant for predicting incident aMCI (HR range: 2.33-3.12, p: 0.0007-0.04). Persons with poor performance on the MBT are at significantly greater risk for developing incident aMCI. High hazard ratios up to seven years of follow-up suggest that the MBT is sensitive to early disease.

Correcting for Optimistic Prediction in Small Data Sets

PubMed Central

Smith, Gordon C. S.; Seaman, Shaun R.; Wood, Angela M.; Royston, Patrick; White, Ian R.

2014-01-01

The C statistic is a commonly reported measure of screening test performance. Optimistic estimation of the C statistic is a frequent problem because of overfitting of statistical models in small data sets, and methods exist to correct for this issue. However, many studies do not use such methods, and those that do correct for optimism use diverse methods, some of which are known to be biased. We used clinical data sets (United Kingdom Down syndrome screening data from Glasgow (1991–2003), Edinburgh (1999–2003), and Cambridge (1990–2006), as well as Scottish national pregnancy discharge data (2004–2007)) to evaluate different approaches to adjustment for optimism. We found that sample splitting, cross-validation without replication, and leave-1-out cross-validation produced optimism-adjusted estimates of the C statistic that were biased and/or associated with greater absolute error than other available methods. Cross-validation with replication, bootstrapping, and a new method (leave-pair-out cross-validation) all generated unbiased optimism-adjusted estimates of the C statistic and had similar absolute errors in the clinical data set. Larger simulation studies confirmed that all 3 methods performed similarly with 10 or more events per variable, or when the C statistic was 0.9 or greater. However, with lower events per variable or lower C statistics, bootstrapping tended to be optimistic but with lower absolute and mean squared errors than both methods of cross-validation. PMID:24966219

Does self-compassion mitigate the relationship between burnout and barriers to compassion? A cross-sectional quantitative study of 799 nurses.

PubMed

Dev, Vinayak; Fernando, Antonio T; Lim, Anecita Gigi; Consedine, Nathan S

2018-05-01

Burnout has numerous negative consequences for nurses, potentially impairing their ability to deliver compassionate patient care. However, the association between burnout and compassion and, more specifically, barriers to compassion in medicine is unclear. This article evaluates the associations between burnout and barriers to compassion and examines whether dispositional self-compassion might mitigate this association. Consistent with prior work, the authors expected greater burnout to predict greater barriers to compassion. We also expected self-compassion - the ability to be kind to the self during times of distress - to weaken the association between burnout and barriers to compassion among nurses. Registered nurses working in New Zealand medical contexts were recruited using non-random convenience sampling. Following consent, 799 valid participants completed a cross-sectional survey including the Copenhagen Burnout Inventory, the Barriers to Physician Compassion scale, and a measure of dispositional self-compassion. As expected, greater burnout predicted greater barriers to compassion while self-compassion predicted fewer barriers. However, self-compassion mitigated the association between burnout and burnout related barriers to compassion (but not other barriers). The interaction suggested that suggested that the association was stronger (rather than weaker) among those with greater self-compassion. Understanding the lack of compassion and the effects of burnout in patient care are priorities in health. This report extends evidence on the association between burnout and compassion-fatigue to show that burnout also predicts the experience of specific barriers to compassion. While self-compassion predicted lower burnout and barriers, it may not necessarily reduce the extent to which burnout contributes to the experience of barriers to compassion in medicine. Implications for understanding how burnout manifests in barriers to clinical compassion, interventions and professional training, and future directions in nursing are discussed. Copyright © 2018 Elsevier Ltd. All rights reserved.

Validating the BISON fuel performance code to integral LWR experiments

DOE PAGES

Williamson, R. L.; Gamble, K. A.; Perez, D. M.; ...

2016-03-24

BISON is a modern finite element-based nuclear fuel performance code that has been under development at the Idaho National Laboratory (INL) since 2009. The code is applicable to both steady and transient fuel behavior and has been used to analyze a variety of fuel forms in 1D spherical, 2D axisymmetric, or 3D geometries. Code validation is underway and is the subject of this study. A brief overview of BISON’s computational framework, governing equations, and general material and behavioral models is provided. BISON code and solution verification procedures are described, followed by a summary of the experimental data used to datemore » for validation of Light Water Reactor (LWR) fuel. Validation comparisons focus on fuel centerline temperature, fission gas release, and rod diameter both before and following fuel-clad mechanical contact. Comparisons for 35 LWR rods are consolidated to provide an overall view of how the code is predicting physical behavior, with a few select validation cases discussed in greater detail. Our results demonstrate that 1) fuel centerline temperature comparisons through all phases of fuel life are very reasonable with deviations between predictions and experimental data within ±10% for early life through high burnup fuel and only slightly out of these bounds for power ramp experiments, 2) accuracy in predicting fission gas release appears to be consistent with state-of-the-art modeling and with the involved uncertainties and 3) comparison of rod diameter results indicates a tendency to overpredict clad diameter reduction early in life, when clad creepdown dominates, and more significantly overpredict the diameter increase late in life, when fuel expansion controls the mechanical response. In the initial rod diameter comparisons they were unsatisfactory and have lead to consideration of additional separate effects experiments to better understand and predict clad and fuel mechanical behavior. Results from this study are being used to define priorities for ongoing code development and validation activities.« less

Rapid hybridization of nucleic acids using isotachophoresis

PubMed Central

Bercovici, Moran; Han, Crystal M.; Liao, Joseph C.; Santiago, Juan G.

2012-01-01

We use isotachophoresis (ITP) to control and increase the rate of nucleic acid hybridization reactions in free solution. We present a new physical model, validation experiments, and demonstrations of this assay. We studied the coupled physicochemical processes of preconcentration, mixing, and chemical reaction kinetics under ITP. Our experimentally validated model enables a closed form solution for ITP-aided reaction kinetics, and reveals a new characteristic time scale which correctly predicts order 10,000-fold speed-up of chemical reaction rate for order 100 pM reactants, and greater enhancement at lower concentrations. At 500 pM concentration, we measured a reaction time which is 14,000-fold lower than that predicted for standard second-order hybridization. The model and method are generally applicable to acceleration of reactions involving nucleic acids, and may be applicable to a wide range of reactions involving ionic reactants. PMID:22733732

Probability of nitrate contamination of recently recharged groundwaters in the conterminous United States

USGS Publications Warehouse

Nolan, B.T.; Hitt, K.J.; Ruddy, B.C.

2002-01-01

A new logistic regression (LR) model was used to predict the probability of nitrate contamination exceeding 4 mg/L in predominantly shallow, recently recharged ground waters of the United States. The new model contains variables representing (1) N fertilizer loading (p 2 = 0.875), indicating that the LR model fits the data well. The likelihood of nitrate contamination is greater in areas with high N loading and well-drained surficial soils over unconsolidated sand and gravels. The LR model correctly predicted the status of nitrate contamination in 75% of wells in a validation data set. Considering all wells used in both calibration and validation, observed median nitrate concentration increased from 0.24 to 8.30 mg/L as the mapped probability of nitrate exceeding 4 mg/L increased from less than or equal to 0.17 to > 0.83.

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

PubMed

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

2018-07-01

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

Prediction of heterosis using genome-wide SNP-marker data: application to egg production traits in white Leghorn crosses.

PubMed

Amuzu-Aweh, E N; Bijma, P; Kinghorn, B P; Vereijken, A; Visscher, J; van Arendonk, J Am; Bovenhuis, H

2013-12-01

Prediction of heterosis has a long history with mixed success, partly due to low numbers of genetic markers and/or small data sets. We investigated the prediction of heterosis for egg number, egg weight and survival days in domestic white Leghorns, using ∼400 000 individuals from 47 crosses and allele frequencies on ∼53 000 genome-wide single nucleotide polymorphisms (SNPs). When heterosis is due to dominance, and dominance effects are independent of allele frequencies, heterosis is proportional to the squared difference in allele frequency (SDAF) between parental pure lines (not necessarily homozygous). Under these assumptions, a linear model including regression on SDAF partitions crossbred phenotypes into pure-line values and heterosis, even without pure-line phenotypes. We therefore used models where phenotypes of crossbreds were regressed on the SDAF between parental lines. Accuracy of prediction was determined using leave-one-out cross-validation. SDAF predicted heterosis for egg number and weight with an accuracy of ∼0.5, but did not predict heterosis for survival days. Heterosis predictions allowed preselection of pure lines before field-testing, saving ∼50% of field-testing cost with only 4% loss in heterosis. Accuracies from cross-validation were lower than from the model-fit, suggesting that accuracies previously reported in literature are overestimated. Cross-validation also indicated that dominance cannot fully explain heterosis. Nevertheless, the dominance model had considerable accuracy, clearly greater than that of a general/specific combining ability model. This work also showed that heterosis can be modelled even when pure-line phenotypes are unavailable. We concluded that SDAF is a useful predictor of heterosis in commercial layer breeding.

Structurally compliant rocket engine combustion chamber: Experimental and analytical validation

NASA Technical Reports Server (NTRS)

Jankovsky, Robert S.; Arya, Vinod K.; Kazaroff, John M.; Halford, Gary R.

1994-01-01

A new, structurally compliant rocket engine combustion chamber design has been validated through analysis and experiment. Subscale, tubular channel chambers have been cyclically tested and analytically evaluated. Cyclic lives were determined to have a potential for 1000 percent increase over those of rectangular channel designs, the current state of the art. Greater structural compliance in the circumferential direction gave rise to lower thermal strains during hot firing, resulting in lower thermal strain ratcheting and longer predicted fatigue lives. Thermal, structural, and durability analyses of the combustion chamber design, involving cyclic temperatures, strains, and low-cycle fatigue lives, have corroborated the experimental observations.

Habitat islands and the equilibrium theory of island biogeography: testing some predictions

USGS Publications Warehouse

Brown, M.; Dinsmore, J.J.

1988-01-01

Species-area data from a study of marsh birds are used to test five predictions generated by the equilibrium theory of island biogeography. Three predictions are supported: we found a significant species-area relationship, a non-zero level of turnover, and a variance-mean ratio of 0.5. One prediction is rejected: the extinction rates were not greater on small islands. The results of one test are equivocal: the number of species on each island was not always the same. As Gilbert (1980) suggests, a strong species-area relationship alone does not validate the theory. The avian communities we studied were on habitat islands, not true islands, and underwent complete extinction annually. Thus caution must be used before applying the theory to these and other habitat islands.

Mammalian Toxicology Testing: Problem Definition Study, Technology Changes Impact on Testing Requirements.

DTIC Science & Technology

1981-01-01

predicted that "an enlightened attitude towards the use of personal records for research should lead to a far greater proportion of our experience being...damage in animals tested for lifetime exposure. Use of primates will expand for the validation of neurophysiological and psychological tests designed...technicians require further training. Individuals trained in neurophysiological and tissue culture techniques are also in short supply. Behavioral

Towards personalized therapy for multiple sclerosis: prediction of individual treatment response.

PubMed

Kalincik, Tomas; Manouchehrinia, Ali; Sobisek, Lukas; Jokubaitis, Vilija; Spelman, Tim; Horakova, Dana; Havrdova, Eva; Trojano, Maria; Izquierdo, Guillermo; Lugaresi, Alessandra; Girard, Marc; Prat, Alexandre; Duquette, Pierre; Grammond, Pierre; Sola, Patrizia; Hupperts, Raymond; Grand'Maison, Francois; Pucci, Eugenio; Boz, Cavit; Alroughani, Raed; Van Pesch, Vincent; Lechner-Scott, Jeannette; Terzi, Murat; Bergamaschi, Roberto; Iuliano, Gerardo; Granella, Franco; Spitaleri, Daniele; Shaygannejad, Vahid; Oreja-Guevara, Celia; Slee, Mark; Ampapa, Radek; Verheul, Freek; McCombe, Pamela; Olascoaga, Javier; Amato, Maria Pia; Vucic, Steve; Hodgkinson, Suzanne; Ramo-Tello, Cristina; Flechter, Shlomo; Cristiano, Edgardo; Rozsa, Csilla; Moore, Fraser; Luis Sanchez-Menoyo, Jose; Laura Saladino, Maria; Barnett, Michael; Hillert, Jan; Butzkueven, Helmut

2017-09-01

Timely initiation of effective therapy is crucial for preventing disability in multiple sclerosis; however, treatment response varies greatly among patients. Comprehensive predictive models of individual treatment response are lacking. Our aims were: (i) to develop predictive algorithms for individual treatment response using demographic, clinical and paraclinical predictors in patients with multiple sclerosis; and (ii) to evaluate accuracy, and internal and external validity of these algorithms. This study evaluated 27 demographic, clinical and paraclinical predictors of individual response to seven disease-modifying therapies in MSBase, a large global cohort study. Treatment response was analysed separately for disability progression, disability regression, relapse frequency, conversion to secondary progressive disease, change in the cumulative disease burden, and the probability of treatment discontinuation. Multivariable survival and generalized linear models were used, together with the principal component analysis to reduce model dimensionality and prevent overparameterization. Accuracy of the individual prediction was tested and its internal validity was evaluated in a separate, non-overlapping cohort. External validity was evaluated in a geographically distinct cohort, the Swedish Multiple Sclerosis Registry. In the training cohort (n = 8513), the most prominent modifiers of treatment response comprised age, disease duration, disease course, previous relapse activity, disability, predominant relapse phenotype and previous therapy. Importantly, the magnitude and direction of the associations varied among therapies and disease outcomes. Higher probability of disability progression during treatment with injectable therapies was predominantly associated with a greater disability at treatment start and the previous therapy. For fingolimod, natalizumab or mitoxantrone, it was mainly associated with lower pretreatment relapse activity. The probability of disability regression was predominantly associated with pre-baseline disability, therapy and relapse activity. Relapse incidence was associated with pretreatment relapse activity, age and relapsing disease course, with the strength of these associations varying among therapies. Accuracy and internal validity (n = 1196) of the resulting predictive models was high (>80%) for relapse incidence during the first year and for disability outcomes, moderate for relapse incidence in Years 2-4 and for the change in the cumulative disease burden, and low for conversion to secondary progressive disease and treatment discontinuation. External validation showed similar results, demonstrating high external validity for disability and relapse outcomes, moderate external validity for cumulative disease burden and low external validity for conversion to secondary progressive disease and treatment discontinuation. We conclude that demographic, clinical and paraclinical information helps predict individual response to disease-modifying therapies at the time of their commencement. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Evaluation of the rusle and disturbed wepp erosion models for predicting soil loss in the first year after wildfire in NW Spain.

PubMed

Fernández, Cristina; Vega, José A

2018-05-04

Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling. Copyright © 2018 Elsevier Inc. All rights reserved.

Validation of the Predicted Circumferential and Radial Mode Sound Power Levels in the Inlet and Exhaust Ducts of a Fan Ingesting Distorted Inflow

NASA Technical Reports Server (NTRS)

Koch, L. Danielle

2012-01-01

Fan inflow distortion tone noise has been studied computationally and experimentally. Data from two experiments in the NASA Glenn Advanced Noise Control Fan rig have been used to validate acoustic predictions. The inflow to the fan was distorted by cylindrical rods inserted radially into the inlet duct one rotor chord length upstream of the fan. The rods were arranged in both symmetric and asymmetric circumferential patterns. In-duct and farfield sound pressure level measurements were recorded. It was discovered that for positive circumferential modes, measured circumferential mode sound power levels in the exhaust duct were greater than those in the inlet duct and for negative circumferential modes, measured total circumferential mode sound power levels in the exhaust were less than those in the inlet. Predicted trends in overall sound power level were proven to be useful in identifying circumferentially asymmetric distortion patterns that reduce overall inlet distortion tone noise, as compared to symmetric arrangements of rods. Detailed comparisons between the measured and predicted radial mode sound power in the inlet and exhaust duct indicate limitations of the theory.

Are prediction models for Lynch syndrome valid for probands with endometrial cancer?

PubMed

Backes, Floor J; Hampel, Heather; Backes, Katherine A; Vaccarello, Luis; Lewandowski, George; Bell, Jeffrey A; Reid, Gary C; Copeland, Larry J; Fowler, Jeffrey M; Cohn, David E

2009-01-01

Currently, three prediction models are used to predict a patient's risk of having Lynch syndrome (LS). These models have been validated in probands with colorectal cancer (CRC), but not in probands presenting with endometrial cancer (EMC). Thus, the aim was to determine the performance of these prediction models in women with LS presenting with EMC. Probands with EMC and LS were identified. Personal and family history was entered into three prediction models, PREMM(1,2), MMRpro, and MMRpredict. Probabilities of mutations in the mismatch repair genes were recorded. Accurate prediction was defined as a model predicting at least a 5% chance of a proband carrying a mutation. From 562 patients prospectively enrolled in a clinical trial of patients with EMC, 13 (2.2%) were shown to have LS. Nine patients had a mutation in MSH6, three in MSH2, and one in MLH1. MMRpro predicted that 3 of 9 patients with an MSH6, 3 of 3 with an MSH2, and 1 of 1 patient with an MLH1 mutation could have LS. For MMRpredict, EMC coded as "proximal CRC" predicted 5 of 5, and as "distal CRC" three of five. PREMM(1,2) predicted that 4 of 4 with an MLH1 or MSH2 could have LS. Prediction of LS in probands presenting with EMC using current models for probands with CRC works reasonably well. Further studies are needed to develop models that include questions specific to patients with EMC with a greater age range, as well as placing increased emphasis on prediction of LS in probands with MSH6 mutations.

[Risk factor analysis of the patients with solitary pulmonary nodules and establishment of a prediction model for the probability of malignancy].

PubMed

Wang, X; Xu, Y H; Du, Z Y; Qian, Y J; Xu, Z H; Chen, R; Shi, M H

2018-02-23

Objective: This study aims to analyze the relationship among the clinical features, radiologic characteristics and pathological diagnosis in patients with solitary pulmonary nodules, and establish a prediction model for the probability of malignancy. Methods: Clinical data of 372 patients with solitary pulmonary nodules who underwent surgical resection with definite postoperative pathological diagnosis were retrospectively analyzed. In these cases, we collected clinical and radiologic features including gender, age, smoking history, history of tumor, family history of cancer, the location of lesion, ground-glass opacity, maximum diameter, calcification, vessel convergence sign, vacuole sign, pleural indentation, speculation and lobulation. The cases were divided to modeling group (268 cases) and validation group (104 cases). A new prediction model was established by logistic regression analying the data from modeling group. Then the data of validation group was planned to validate the efficiency of the new model, and was compared with three classical models(Mayo model, VA model and LiYun model). With the calculated probability values for each model from validation group, SPSS 22.0 was used to draw the receiver operating characteristic curve, to assess the predictive value of this new model. Results: 112 benign SPNs and 156 malignant SPNs were included in modeling group. Multivariable logistic regression analysis showed that gender, age, history of tumor, ground -glass opacity, maximum diameter, and speculation were independent predictors of malignancy in patients with SPN( P <0.05). We calculated a prediction model for the probability of malignancy as follow: p =e(x)/(1+ e(x)), x=-4.8029-0.743×gender+ 0.057×age+ 1.306×history of tumor+ 1.305×ground-glass opacity+ 0.051×maximum diameter+ 1.043×speculation. When the data of validation group was added to the four-mathematical prediction model, The area under the curve of our mathematical prediction model was 0.742, which is greater than other models (Mayo 0.696, VA 0.634, LiYun 0.681), while the differences between any two of the four models were not significant ( P >0.05). Conclusions: Age of patient, gender, history of tumor, ground-glass opacity, maximum diameter and speculation are independent predictors of malignancy in patients with solitary pulmonary nodule. This logistic regression prediction mathematic model is not inferior to those classical models in estimating the prognosis of SPNs.

Criterion and Construct Validity of an Isometric Midthigh-Pull Dynamometer for Assessing Whole-Body Strength in Professional Rugby League Players.

PubMed

Dobbin, Nick; Hunwicks, Richard; Jones, Ben; Till, Kevin; Highton, Jamie; Twist, Craig

2018-02-01

To examine the criterion and construct validity of an isometric midthigh-pull dynamometer to assess whole-body strength in professional rugby league players. Fifty-six male rugby league players (33 senior and 23 youth players) performed 4 isometric midthigh-pull efforts (ie, 2 on the dynamometer and 2 on the force platform) in a randomized and counterbalanced order. Isometric peak force was underestimated (P < .05) using the dynamometer compared with the force platform (95% LoA: -213.5 ± 342.6 N). Linear regression showed that peak force derived from the dynamometer explained 85% (adjusted R 2  = .85, SEE = 173 N) of the variance in the dependent variable, with the following prediction equation derived: predicted peak force = [1.046 × dynamometer peak force] + 117.594. Cross-validation revealed a nonsignificant bias (P > .05) between the predicted and peak force from the force platform and an adjusted R 2 (79.6%) that represented shrinkage of 0.4% relative to the cross-validation model (80%). Peak force was greater for the senior than the youth professionals using the dynamometer (2261.2 ± 222 cf 1725.1 ± 298.0 N, respectively; P < .05). The isometric midthigh pull assessed using a dynamometer underestimates criterion peak force but is capable of distinguishing muscle-function characteristics between professional rugby league players of different standards.

Operationalisation and validation of the Stopping Elderly Accidents, Deaths, and Injuries (STEADI) fall risk algorithm in a nationally representative sample.

PubMed

Lohman, Matthew C; Crow, Rebecca S; DiMilia, Peter R; Nicklett, Emily J; Bruce, Martha L; Batsis, John A

2017-12-01

Preventing falls and fall-related injuries among older adults is a public health priority. The Stopping Elderly Accidents, Deaths, and Injuries (STEADI) tool was developed to promote fall risk screening and encourage coordination between clinical and community-based fall prevention resources; however, little is known about the tool's predictive validity or adaptability to survey data. Data from five annual rounds (2011-2015) of the National Health and Aging Trends Study (NHATS), a representative cohort of adults age 65 years and older in the USA. Analytic sample respondents (n=7392) were categorised at baseline as having low, moderate or high fall risk according to the STEADI algorithm adapted for use with NHATS data. Logistic mixed-effects regression was used to estimate the association between baseline fall risk and subsequent falls and mortality. Analyses incorporated complex sampling and weighting elements to permit inferences at a national level. Participants classified as having moderate and high fall risk had 2.62 (95% CI 2.29 to 2.99) and 4.76 (95% CI 3.51 to 6.47) times greater odds of falling during follow-up compared with those with low risk, respectively, controlling for sociodemographic and health-related risk factors for falls. High fall risk was also associated with greater likelihood of falling multiple times annually but not with greater risk of mortality. The adapted STEADI clinical fall risk screening tool is a valid measure for predicting future fall risk using survey cohort data. Further efforts to standardise screening for fall risk and to coordinate between clinical and community-based fall prevention initiatives are warranted. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Validation of the GILLS score for tongue-lip adhesion in Robin sequence patients.

PubMed

Abramowicz, Shelly; Bacic, Janine D; Mulliken, John B; Rogers, Gary F

2012-03-01

The GILLS score consists of gastroesophageal reflux disease, preoperative intubation, late surgical intervention, low birth weight, and syndromic diagnosis. The purpose of this study was to test the validity of the GILLS score in predicting success of tongue-lip adhesion (TLA) in managing Robin sequence. Infants with Robin sequence were included in the study if they had a TLA for airway compromise subsequent to formulation of the GILLS scoring system, that is, they were not included in the original GILLS analysis. The patients were prospectively considered based on the presence of the 5 factors that constitute the GILLS score. A score of ≤ 2 predicts success of TLA. Twenty patients met the inclusion criteria. Tongue-lip adhesion managed the compromised airway in 18 (90%) of 20 patients. Overall, the GILLS score had a sensitivity of 83%, specificity of 50%, positive predictive value of 94%, and negative predictive value of 25%. The GILLS score accurately predicts a successful outcome for TLA in infants with Robin sequence. For infants with a score of 2 or less, TLA is the procedure of choice. Infants with a GILLS score of 3 or greater were 5 times more likely to fail TLA than those with a score of 2 or less. In these patients, other methods of managing the airway should be considered.

Field testing of a system for online classification of beef carcasses for longissimus tenderness using visible and near-infrared reflectance spectroscopy.

PubMed

Shackelford, S D; Wheeler, T L; King, D A; Koohmaraie, M

2012-03-01

The present experiments were conducted to field test a system optimized for online prediction of beef LM tenderness based on visible and near-infrared (VISNIR) spectroscopy and to develop and validate a model for prediction of tenderness that would be unbiased by normal variation in bloom time before application of VISNIR. For both Exp. 1 and 2, slice shear force (SSF) was measured on fresh (never frozen) steaks at 14 d postmortem. Carcasses with VISNIR-predicted SSF ≤15 kg were classified as VISNIR predicted tender and carcasses with VISNIR-predicted SSF >15 kg were classified as VISNIR not predicted tender. In Exp. 1, spectroscopy was conducted online, during carcass grading, at 3 large-scale commercial fed-beef processing facilities. Each carcass (n = 1,155) was evaluated immediately after ribbing and again when the carcass was graded. For model development and validation, carcasses were blocked by plant and observed SSF. One-half of the carcasses (n = 579) were assigned to a calibration data set, which was used to develop regression equations, and one-half of the carcasses (n = 576) were assigned to a prediction data set, which was used to validate the regression equations. Carcasses predicted tender by VISNIR spectroscopy had smaller (P < 10(-19)) mean LM SSF values at 14 d postmortem in the calibration (13.9 vs. 16.5 kg) and prediction (13.8 vs. 16.4 kg) data sets than did carcasses not predicted tender by VISNIR spectroscopy. Relative to carcasses not predicted tender by VISNIR, a decreased percentage of carcasses predicted tender by VISNIR had LM SSF >25 kg in the calibration (2.0 vs. 7.8%) and prediction (0.8 vs. 8.0%) data sets. In Exp. 2, carcasses (n = 4,204) were evaluated with VISNIR online at 6 commercial fed-beef processing facilities on 38 production days. The carcasses predicted tender by VISNIR spectroscopy had decreased mean LM SSF values at 14 d postmortem (16.3 vs. 19.9 kg; P < 10(-87)), longer sarcomere lengths (1.77 vs. 1.72 µm; P < 10(-10)), and a greater percentage of desmin degraded (42 vs. 34%; P < 10(-5)) by 14 d postmortem. Relative to carcasses not predicted tender by VISNIR, a decreased percentage of carcasses predicted tender by VISNIR had LM SSF >25 kg (4.9 vs. 21.3%). The present experiments resulted in development and independent validation of a robust method to noninvasively predict LM tenderness of grain-fed beef carcasses. This technology could facilitate tenderness-based beef merchandising systems.

Exploring discrepancies between quantitative validation results and the geomorphic plausibility of statistical landslide susceptibility maps

NASA Astrophysics Data System (ADS)

Steger, Stefan; Brenning, Alexander; Bell, Rainer; Petschko, Helene; Glade, Thomas

2016-06-01

Empirical models are frequently applied to produce landslide susceptibility maps for large areas. Subsequent quantitative validation results are routinely used as the primary criteria to infer the validity and applicability of the final maps or to select one of several models. This study hypothesizes that such direct deductions can be misleading. The main objective was to explore discrepancies between the predictive performance of a landslide susceptibility model and the geomorphic plausibility of subsequent landslide susceptibility maps while a particular emphasis was placed on the influence of incomplete landslide inventories on modelling and validation results. The study was conducted within the Flysch Zone of Lower Austria (1,354 km2) which is known to be highly susceptible to landslides of the slide-type movement. Sixteen susceptibility models were generated by applying two statistical classifiers (logistic regression and generalized additive model) and two machine learning techniques (random forest and support vector machine) separately for two landslide inventories of differing completeness and two predictor sets. The results were validated quantitatively by estimating the area under the receiver operating characteristic curve (AUROC) with single holdout and spatial cross-validation technique. The heuristic evaluation of the geomorphic plausibility of the final results was supported by findings of an exploratory data analysis, an estimation of odds ratios and an evaluation of the spatial structure of the final maps. The results showed that maps generated by different inventories, classifiers and predictors appeared differently while holdout validation revealed similar high predictive performances. Spatial cross-validation proved useful to expose spatially varying inconsistencies of the modelling results while additionally providing evidence for slightly overfitted machine learning-based models. However, the highest predictive performances were obtained for maps that explicitly expressed geomorphically implausible relationships indicating that the predictive performance of a model might be misleading in the case a predictor systematically relates to a spatially consistent bias of the inventory. Furthermore, we observed that random forest-based maps displayed spatial artifacts. The most plausible susceptibility map of the study area showed smooth prediction surfaces while the underlying model revealed a high predictive capability and was generated with an accurate landslide inventory and predictors that did not directly describe a bias. However, none of the presented models was found to be completely unbiased. This study showed that high predictive performances cannot be equated with a high plausibility and applicability of subsequent landslide susceptibility maps. We suggest that greater emphasis should be placed on identifying confounding factors and biases in landslide inventories. A joint discussion between modelers and decision makers of the spatial pattern of the final susceptibility maps in the field might increase their acceptance and applicability.

Developing and Testing a Model to Predict Outcomes of Organizational Change

PubMed Central

Gustafson, David H; Sainfort, François; Eichler, Mary; Adams, Laura; Bisognano, Maureen; Steudel, Harold

2003-01-01

Objective To test the effectiveness of a Bayesian model employing subjective probability estimates for predicting success and failure of health care improvement projects. Data Sources Experts' subjective assessment data for model development and independent retrospective data on 221 healthcare improvement projects in the United States, Canada, and the Netherlands collected between 1996 and 2000 for validation. Methods A panel of theoretical and practical experts and literature in organizational change were used to identify factors predicting the outcome of improvement efforts. A Bayesian model was developed to estimate probability of successful change using subjective estimates of likelihood ratios and prior odds elicited from the panel of experts. A subsequent retrospective empirical analysis of change efforts in 198 health care organizations was performed to validate the model. Logistic regression and ROC analysis were used to evaluate the model's performance using three alternative definitions of success. Data Collection For the model development, experts' subjective assessments were elicited using an integrative group process. For the validation study, a staff person intimately involved in each improvement project responded to a written survey asking questions about model factors and project outcomes. Results Logistic regression chi-square statistics and areas under the ROC curve demonstrated a high level of model performance in predicting success. Chi-square statistics were significant at the 0.001 level and areas under the ROC curve were greater than 0.84. Conclusions A subjective Bayesian model was effective in predicting the outcome of actual improvement projects. Additional prospective evaluations as well as testing the impact of this model as an intervention are warranted. PMID:12785571

Predictors of operating room extubation in adult cardiac surgery.

PubMed

Subramaniam, Kathirvel; DeAndrade, Diana S; Mandell, Daniel R; Althouse, Andrew D; Manmohan, Rajan; Esper, Stephen A; Varga, Jeffrey M; Badhwar, Vinay

2017-11-01

The primary objective of the study was to identify perioperative factors associated with successful immediate extubation in the operating room after adult cardiac surgery. The secondary objective was to derive a simplified predictive scoring system to guide clinicians in operating room extubation. All 1518 patients in this retrospective cohort study underwent standardized fast-track cardiac anesthetic protocol during adult cardiac surgery. Perioperative variables between patients who had successful extubation in the operating room versus in the intensive care unit were retrospectively analyzed using both univariate and multivariable logistic regression analyses. A predictive score of successful operating room extubation was constructed from the multivariable results of 800 patients (derivation set), and the scoring system was further tested using a validation set of 398 patients. Younger age, lower body mass index, higher preoperative serum albumin, absence of chronic lung disease and diabetes, less-invasive surgical approach, isolated coronary bypass surgery, elective surgery, and lower doses of intraoperative intravenous fentanyl were independently associated with higher probability of operating room extubation. The extubation prediction score created in a derivation set of patients performed well in the validation set. Patient scores less than 0 had a minimal probability of successful operating room extubation. Operating room extubation was highly predicted with scores of 5 or greater. Perioperative factors that are independently associated with successful operating room extubation after adult cardiac operations were identified, and an operating room extubation prediction scoring system was validated. This scoring system may be used to guide safe operating room extubation after cardiac operations. Copyright © 2017 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

Understanding mail survey response rates among male reserve component Gulf War era veterans.

PubMed

Schumm, W R; Bollman, S R; Jurich, A P; Castelo, C; Sanders, D; Webb, F J

2000-12-01

In this study of current and former male Reserve and National Guard members from the State of Ohio, it was expected that veterans who were older, had more years of military service, who had participated in the Persian Gulf War, who were Euro-Americans, who were higher in rank, who had higher residential stability in Ohio, who belonged to the Air Force, who had higher formal education, and who belonged to the National Guard would have a greater investment in U.S. society as defined by 11 demographic variables. It was assumed that those with greater investment in society would more often have valid addresses and would be more likely to respond to a survey on military issues, thereby biasing sample outcomes in those directions. Results for male veterans were consistent with the hypothesis that investment in the society system would predict validity of addresses and response rates. In other words, results supported the idea that those veterans who might be expected to have a greater investment in U.S. society were more likely to be located and to respond (once located) to a survey concerning Desert Storm-era military service and its aftermath. Implications for future Desert Storm research are discussed.

Predictors of Entering a Hearing Aid Evaluation Period: A Prospective Study in Older Hearing-Help Seekers

PubMed Central

Deeg, Dorly J.H.; Versfeld, Niek J.; Heymans, Martijn W.; Naylor, Graham; Kramer, Sophia E.

2017-01-01

This study aimed to determine the predictors of entering a hearing aid evaluation period (HAEP) using a prospective design drawing on the health belief model and the transtheoretical model. In total, 377 older persons who presented with hearing problems to an Ear, Nose, and Throat specialist (n = 110) or a hearing aid dispenser (n = 267) filled in a baseline questionnaire. After 4 months, it was determined via a telephone interview whether or not participants had decided to enter a HAEP. Multivariable logistic regression analyses were applied to determine which baseline variables predicted HAEP status. A priori, candidate predictors were divided into ‘likely’ and ‘novel’ predictors based on the literature. The following variables turned out to be significant predictors: more expected hearing aid benefits, greater social pressure, and greater self-reported hearing disability. In addition, greater hearing loss severity and stigma were predictors in women but not in men. Of note, the predictive effect of self-reported hearing disability was modified by readiness such that with higher readiness, the positive predictive effect became stronger. None of the ‘novel’ predictors added significant predictive value. The results support the notion that predictors of hearing aid uptake are also predictive of entering a HAEP. This study shows that some of these predictors appear to be gender specific or are dependent on a person’s readiness for change. After assuring the external validity of the predictors, an important next step would be to develop prediction rules for use in clinical practice, so that older persons’ hearing help-seeking journey can be facilitated. PMID:29237333

Modeling Visual, Vestibular and Oculomotor Interactions in Self-Motion Estimation

NASA Technical Reports Server (NTRS)

Perrone, John

1997-01-01

A computational model of human self-motion perception has been developed in collaboration with Dr. Leland S. Stone at NASA Ames Research Center. The research included in the grant proposal sought to extend the utility of this model so that it could be used for explaining and predicting human performance in a greater variety of aerospace applications. This extension has been achieved along with physiological validation of the basic operation of the model.

Accurate Binding Free Energy Predictions in Fragment Optimization.

PubMed

Steinbrecher, Thomas B; Dahlgren, Markus; Cappel, Daniel; Lin, Teng; Wang, Lingle; Krilov, Goran; Abel, Robert; Friesner, Richard; Sherman, Woody

2015-11-23

Predicting protein-ligand binding free energies is a central aim of computational structure-based drug design (SBDD)--improved accuracy in binding free energy predictions could significantly reduce costs and accelerate project timelines in lead discovery and optimization. The recent development and validation of advanced free energy calculation methods represents a major step toward this goal. Accurately predicting the relative binding free energy changes of modifications to ligands is especially valuable in the field of fragment-based drug design, since fragment screens tend to deliver initial hits of low binding affinity that require multiple rounds of synthesis to gain the requisite potency for a project. In this study, we show that a free energy perturbation protocol, FEP+, which was previously validated on drug-like lead compounds, is suitable for the calculation of relative binding strengths of fragment-sized compounds as well. We study several pharmaceutically relevant targets with a total of more than 90 fragments and find that the FEP+ methodology, which uses explicit solvent molecular dynamics and physics-based scoring with no parameters adjusted, can accurately predict relative fragment binding affinities. The calculations afford R(2)-values on average greater than 0.5 compared to experimental data and RMS errors of ca. 1.1 kcal/mol overall, demonstrating significant improvements over the docking and MM-GBSA methods tested in this work and indicating that FEP+ has the requisite predictive power to impact fragment-based affinity optimization projects.

Negative affect subtypes and craving differentially predict long-term cessation success among smokers achieving initial abstinence.

PubMed

Zuo, Yantao; Rabinovich, Norka E; Gilbert, David G

2017-03-01

This study aimed to examine the associations of individual trajectories of three types of negative affect (NA: anxiety, depression, and anger) and craving during a 44-day period of incentivized smoking abstinence period with cessation outcome at 3 months and at 1 year. Adult smokers (N = 140) completed questionnaire assessments of NA and craving during pre-quit baseline sessions and 15 postquit sessions over the 45 days of biochemically verified abstinence while on nicotine or placebo patch treatment. Growth curve and logistic regression analyses were used to examine the associations of trajectory parameters of the individual NA states and craving with the abstinence outcomes at 3 months and 1 year postquit. Greater declines in anxiety, depression, and anger symptoms over the first 44 days of smoking cessation were predictive of higher odds of abstinence at both 3 months and 1 year. Moreover, the greater declines in anxiety and anger remained as significant predictors of abstinence at both time points, independent of the predictive ability of the trajectory profiles of craving. The findings suggest that slower dissipation of NA, especially anxiety and anger, represents a greater risk for relapse to smoking beyond that predicted by craving during early abstinence. Thus, temporal profiles of the affective symptoms convey unique motivational significance in relapse. Reduction in NA during early abstinence may be a valid target for interventions to increase long-term cessation success rates particularly among individuals with refractory affective symptoms.

Office-Based Screening for Dementia in Parkinson Disease: The Montreal Parkinson Risk of Dementia Scale in 4 Longitudinal Cohorts.

PubMed

Dawson, Benjamin K; Fereshtehnejad, Seyed-Mohammad; Anang, Julius B M; Nomura, Takashi; Rios-Romenets, Silvia; Nakashima, Kenji; Gagnon, Jean-François; Postuma, Ronald B

2018-06-01

Parkinson disease dementia dramatically increases mortality rates, patient expenditures, hospitalization risk, and caregiver burden. Currently, predicting Parkinson disease dementia risk is difficult, particularly in an office-based setting, without extensive biomarker testing. To appraise the predictive validity of the Montreal Parkinson Risk of Dementia Scale, an office-based screening tool consisting of 8 items that are simply assessed. This multicenter study (Montreal, Canada; Tottori, Japan; and Parkinson Progression Markers Initiative sites) used 4 diverse Parkinson disease cohorts with a prospective 4.4-year follow-up. A total of 717 patients with Parkinson disease were recruited between May 2005 and June 2016. Of these, 607 were dementia-free at baseline and followed-up for 1 year or more and so were included. The association of individual baseline scale variables with eventual dementia risk was calculated. Participants were then randomly split into cohorts to investigate weighting and determine the scale's optimal cutoff point. Receiver operating characteristic curves were calculated and correlations with selected biomarkers were investigated. Dementia, as defined by Movement Disorder Society level I criteria. Of the 607 patients (mean [SD] age, 63.4 [10.1]; 376 men [62%]), 70 (11.5%) converted to dementia. All 8 items of the Montreal Parkinson Risk of Dementia Scale independently predicted dementia development at the 5% significance level. The annual conversion rate to dementia in the high-risk group (score, >5) was 14.9% compared with 5.8% in the intermediate group (score, 4-5) and 0.6% in the low-risk group (score, 0-3). The weighting procedure conferred no significant advantage. Overall predictive validity by the area under the receiver operating characteristic curve was 0.877 (95% CI, 0.829-0.924) across all cohorts. A cutoff of 4 or greater yielded a sensitivity of 77.1% (95% CI, 65.6-86.3) and a specificity of 87.2% (95% CI, 84.1-89.9), with a positive predictive value (as of 4.4 years) of 43.90% (95% CI, 37.76-50.24) and a negative predictive value of 96.70% (95% CI, 95.01-97.85). Positive and negative likelihood ratios were 5.94 (95% CI, 4.08-8.65) and 0.26 (95% CI, 0.17-0.40), respectively. Scale results correlated with markers of Alzheimer pathology and neuropsychological test results. Despite its simplicity, the Montreal Parkinson Risk of Dementia Scale demonstrated predictive validity equal or greater to previously described algorithms using biomarker assessments. Future studies using head-to-head comparisons or refinement of weighting would be of interest.

A points-based algorithm for prognosticating clinical outcome of Chiari malformation Type I with syringomyelia: results from a predictive model analysis of 82 surgically managed adult patients.

PubMed

Thakar, Sumit; Sivaraju, Laxminadh; Jacob, Kuruthukulangara S; Arun, Aditya Atal; Aryan, Saritha; Mohan, Dilip; Sai Kiran, Narayanam Anantha; Hegde, Alangar S

2018-01-01

OBJECTIVE Although various predictors of postoperative outcome have been previously identified in patients with Chiari malformation Type I (CMI) with syringomyelia, there is no known algorithm for predicting a multifactorial outcome measure in this widely studied disorder. Using one of the largest preoperative variable arrays used so far in CMI research, the authors attempted to generate a formula for predicting postoperative outcome. METHODS Data from the clinical records of 82 symptomatic adult patients with CMI and altered hindbrain CSF flow who were managed with foramen magnum decompression, C-1 laminectomy, and duraplasty over an 8-year period were collected and analyzed. Various preoperative clinical and radiological variables in the 57 patients who formed the study cohort were assessed in a bivariate analysis to determine their ability to predict clinical outcome (as measured on the Chicago Chiari Outcome Scale [CCOS]) and the resolution of syrinx at the last follow-up. The variables that were significant in the bivariate analysis were further analyzed in a multiple linear regression analysis. Different regression models were tested, and the model with the best prediction of CCOS was identified and internally validated in a subcohort of 25 patients. RESULTS There was no correlation between CCOS score and syrinx resolution (p = 0.24) at a mean ± SD follow-up of 40.29 ± 10.36 months. Multiple linear regression analysis revealed that the presence of gait instability, obex position, and the M-line-fourth ventricle vertex (FVV) distance correlated with CCOS score, while the presence of motor deficits was associated with poor syrinx resolution (p ≤ 0.05). The algorithm generated from the regression model demonstrated good diagnostic accuracy (area under curve 0.81), with a score of more than 128 points demonstrating 100% specificity for clinical improvement (CCOS score of 11 or greater). The model had excellent reliability (κ = 0.85) and was validated with fair accuracy in the validation cohort (area under the curve 0.75). CONCLUSIONS The presence of gait imbalance and motor deficits independently predict worse clinical and radiological outcomes, respectively, after decompressive surgery for CMI with altered hindbrain CSF flow. Caudal displacement of the obex and a shorter M-line-FVV distance correlated with good CCOS scores, indicating that patients with a greater degree of hindbrain pathology respond better to surgery. The proposed points-based algorithm has good predictive value for postoperative multifactorial outcome in these patients.

Estimating the fates of organic contaminants in an aquifer using QSAR.

PubMed

Lim, Seung Joo; Fox, Peter

2013-01-01

The quantitative structure activity relationship (QSAR) model, BIOWIN, was modified to more accurately estimate the fates of organic contaminants in an aquifer. The predictions from BIOWIN were modified to include oxidation and sorption effects. The predictive model therefore included the effects of sorption, biodegradation, and oxidation. A total of 35 organic compounds were used to validate the predictive model. The majority of the ratios of predicted half-life to measured half-life were within a factor of 2 and no ratio values were greater than a factor of 5. In addition, the accuracy of estimating the persistence of organic compounds in the sub-surface was superior when modified by the relative fraction adsorbed to the solid phase, 1/Rf, to that when modified by the remaining fraction of a given compound adsorbed to a solid, 1 - fs.

Vesicoureteral Reflux Index: 2-Institution Analysis and Validation.

PubMed

Arlen, Angela M; Garcia-Roig, Michael; Weiss, Aaron D; Leong, Traci; Cooper, Christopher S; Kirsch, Andrew J

2016-04-01

The vesicoureteral reflux index is a novel tool designed to predict spontaneous reflux resolution in infants younger than 2 years. We performed a multi-institutional validation study to confirm the discriminatory power of the vesicoureteral reflux index to predict the vesicoureteral reflux resolution rate in young children. We identified patients diagnosed with primary vesicoureteral reflux before age 24 months who had 2 or more voiding cystourethrograms available. Demographics, vesicoureteral reflux grade and timing, ureteral anomalies and radiographic outcomes were evaluated. The C-index was estimated for time to event model assessment. A total of 219 girls and 150 boys met study inclusion criteria. Mean ± SD age at diagnosis was 4.7 ± 4.9 months. Of the patients 101 (27.4%) had early to mid filling, 214 (58%) had late filling and 54 (14.6%) had voiding only vesicoureteral reflux. High grade reflux was present in 87 patients (23.6%) and ureteral anomalies were observed in 50 (13.6%). A vesicoureteral reflux index of 1, 2, 3, 4 and 5 or greater showed an improvement/resolution rate of 88.2%, 77.3%, 62.3%, 32.1% and 14.3%, respectively. On time to event analysis children with filling phase vesicoureteral reflux (p <0.001), grade 4-5 reflux (p <0.001) and ureteral anomalies (p = 0.003) had significantly longer median time to resolution. Median time to spontaneous resolution was 12.6, 12.7, 15.1, 25.6 and 31 months or greater for a vesicoureteral reflux index of 1, 2, 3, 4 and 5 or greater, respectively (C-index 0.305, 95% CI 0.252-0.357). During the study period 65 patients (17.6%) underwent surgical intervention. The vesicoureteral reflux index is a simple tool that reliably predicts significant improvement and spontaneous resolution of primary reflux in patients diagnosed at younger than 2 years. The index provides valuable prognostic information, facilitating individualized patient care. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Effects of the truth FinishIt brand on tobacco outcomes.

PubMed

Evans, W Douglas; Rath, Jessica M; Hair, Elizabeth C; Snider, Jeremy Williams; Pitzer, Lindsay; Greenberg, Marisa; Xiao, Haijun; Cantrell, Jennifer; Vallone, Donna

2018-03-01

Since 2000, the truth campaign has grown as a social marketing brand. Back then, truth employed branding to compete directly with the tobacco industry. In 2014, the launch of truth FinishIt reflected changes in the brand's strategy, the tobacco control environment, and youth/young adult behavior. Building on a previous validation study, the current study examined brand equity in truth FinishIt , as measured by validated multi-dimensional scales, and tobacco related attitudes, beliefs, and behavior based on two waves of the Truth Longitudinal Cohort data from 2015 and 2016. A fixed effects logistic regression was used to estimate the change in brand equity between panel survey waves 3 and 4 on past 30-day smoking among ever and current smokers. Additional models determined the effects of brand equity predicting tobacco attitudes/use at follow up among the full sample. All analyses controlled for demographic factors. A one-point increase in the brand equity scale between the two waves was associated with a 66% greater chance of not smoking among ever smokers (OR 1.66, CI 1.11-2.48, p  < 0.05) and an 80% greater chance of not smoking among current smokers (OR 1.80, CI 1.05-3.10, p  < 0.05). Higher overall truth brand equity at wave 3 predicted less smoking at wave 4 and more positive anti-tobacco attitudes. Being male, younger, and non-white predicted some of the tobacco related attitudes. Future research should examine long-term effects of brand equity on tobacco use and how tobacco control can optimize the use of branding in campaigns.

Temporal and geographical external validation study and extension of the Mayo Clinic prediction model to predict eGFR in the younger population of Swiss ADPKD patients.

PubMed

Girardat-Rotar, Laura; Braun, Julia; Puhan, Milo A; Abraham, Alison G; Serra, Andreas L

2017-07-17

Prediction models in autosomal dominant polycystic kidney disease (ADPKD) are useful in clinical settings to identify patients with greater risk of a rapid disease progression in whom a treatment may have more benefits than harms. Mayo Clinic investigators developed a risk prediction tool for ADPKD patients using a single kidney value. Our aim was to perform an independent geographical and temporal external validation as well as evaluate the potential for improving the predictive performance by including additional information on total kidney volume. We used data from the on-going Swiss ADPKD study from 2006 to 2016. The main analysis included a sample size of 214 patients with Typical ADPKD (Class 1). We evaluated the Mayo Clinic model performance calibration and discrimination in our external sample and assessed whether predictive performance could be improved through the addition of subsequent kidney volume measurements beyond the baseline assessment. The calibration of both versions of the Mayo Clinic prediction model using continuous Height adjusted total kidney volume (HtTKV) and using risk subclasses was good, with R 2 of 78% and 70%, respectively. Accuracy was also good with 91.5% and 88.7% of the predicted within 30% of the observed, respectively. Additional information regarding kidney volume did not substantially improve the model performance. The Mayo Clinic prediction models are generalizable to other clinical settings and provide an accurate tool based on available predictors to identify patients at high risk for rapid disease progression.

Characterizing smoking topography of cannabis in heavy users

PubMed Central

Stitzer, Maxine L.; Vandrey, Ryan

2013-01-01

Rationale Little is known about the smoking topography characteristics of heavy cannabis users. Such measures may be able to predict cannabis use-related outcomes and could be used to validate self-reported measures of cannabis use. Objectives The current study was conducted to measure cannabis smoking topography characteristics during periods of ad libitum use and to correlate topography assessments with measures of self-reported cannabis use, withdrawal and craving during abstinence, and cognitive task performance. Methods Participants (N=20) completed an inpatient study in which they alternated between periods of ad libitum cannabis use and abstinence. Measures of self-reported cannabis use, smoking topography, craving, withdrawal, and sleep measures were collected. Results Participants smoked with greater intensity (e.g., greater volume, longer duration) on initial cigarette puffs with a steady decline on subsequent puffs. Smoking characteristics were significantly correlated with severity of withdrawal, notably sleep quality and architecture, and craving during abstinence, suggesting dose-related effects of cannabis use on these outcomes. Smoking characteristics generally were not significantly associated with cognitive performance. Smoking topography measures were significantly correlated with self-reported measures of cannabis use, indicating validity of these assessments, but topography measures were more sensitive than self-report in predicting cannabis-related outcomes. Conclusions A dose–effect relationship between cannabis consumption and outcomes believed to be clinically important was observed. With additional research, smoking topography assessments may become a useful clinical tool. PMID:21922170

Development and validation of a prediction model for measurement variability of lung nodule volumetry in patients with pulmonary metastases.

PubMed

Hwang, Eui Jin; Goo, Jin Mo; Kim, Jihye; Park, Sang Joon; Ahn, Soyeon; Park, Chang Min; Shin, Yeong-Gil

2017-08-01

To develop a prediction model for the variability range of lung nodule volumetry and validate the model in detecting nodule growth. For model development, 50 patients with metastatic nodules were prospectively included. Two consecutive CT scans were performed to assess volumetry for 1,586 nodules. Nodule volume, surface voxel proportion (SVP), attachment proportion (AP) and absolute percentage error (APE) were calculated for each nodule and quantile regression analyses were performed to model the 95% percentile of APE. For validation, 41 patients who underwent metastasectomy were included. After volumetry of resected nodules, sensitivity and specificity for diagnosis of metastatic nodules were compared between two different thresholds of nodule growth determination: uniform 25% volume change threshold and individualized threshold calculated from the model (estimated 95% percentile APE). SVP and AP were included in the final model: Estimated 95% percentile APE = 37.82 · SVP + 48.60 · AP-10.87. In the validation session, the individualized threshold showed significantly higher sensitivity for diagnosis of metastatic nodules than the uniform 25% threshold (75.0% vs. 66.0%, P = 0.004) CONCLUSION: Estimated 95% percentile APE as an individualized threshold of nodule growth showed greater sensitivity in diagnosing metastatic nodules than a global 25% threshold. • The 95 % percentile APE of a particular nodule can be predicted. • Estimated 95 % percentile APE can be utilized as an individualized threshold. • More sensitive diagnosis of metastasis can be made with an individualized threshold. • Tailored nodule management can be provided during nodule growth follow-up.

A Predictive Model of Daily Seismic Activity Induced by Mining, Developed with Data Mining Methods

NASA Astrophysics Data System (ADS)

Jakubowski, Jacek

2014-12-01

The article presents the development and evaluation of a predictive classification model of daily seismic energy emissions induced by longwall mining in sector XVI of the Piast coal mine in Poland. The model uses data on tremor energy, basic characteristics of the longwall face and mined output in this sector over the period from July 1987 to March 2011. The predicted binary variable is the occurrence of a daily sum of tremor seismic energies in a longwall that is greater than or equal to the threshold value of 105 J. Three data mining analytical methods were applied: logistic regression,neural networks, and stochastic gradient boosted trees. The boosted trees model was chosen as the best for the purposes of the prediction. The validation sample results showed its good predictive capability, taking the complex nature of the phenomenon into account. This may indicate the applied model's suitability for a sequential, short-term prediction of mining induced seismic activity.

Microcomputer-based tests for repeated-measures: Metric properties and predictive validities

NASA Technical Reports Server (NTRS)

Kennedy, Robert S.; Baltzley, Dennis R.; Dunlap, William P.; Wilkes, Robert L.; Kuntz, Lois-Ann

1989-01-01

A menu of psychomotor and mental acuity tests were refined. Field applications of such a battery are, for example, a study of the effects of toxic agents or exotic environments on performance readiness, or the determination of fitness for duty. The key requirement of these tasks is that they be suitable for repeated-measures applications, and so questions of stability and reliability are a continuing, central focus of this work. After the initial (practice) session, seven replications of 14 microcomputer-based performance tests (32 measures) were completed by 37 subjects. Each test in the battery had previously been shown to stabilize in less than five 90-second administrations and to possess retest reliabilities greater than r = 0.707 for three minutes of testing. However, all the tests had never been administered together as a battery and they had never been self-administered. In order to provide predictive validity for intelligence measurement, the Wechsler Adult Intelligence Scale-Revised and the Wonderlic Personnel Test were obtained on the same subjects.

Identifying sensitive areas of adaptive observations for prediction of the Kuroshio large meander using a shallow-water model

NASA Astrophysics Data System (ADS)

Zou, Guang'an; Wang, Qiang; Mu, Mu

2016-09-01

Sensitive areas for prediction of the Kuroshio large meander using a 1.5-layer, shallow-water ocean model were investigated using the conditional nonlinear optimal perturbation (CNOP) and first singular vector (FSV) methods. A series of sensitivity experiments were designed to test the sensitivity of sensitive areas within the numerical model. The following results were obtained: (1) the eff ect of initial CNOP and FSV patterns in their sensitive areas is greater than that of the same patterns in randomly selected areas, with the eff ect of the initial CNOP patterns in CNOP sensitive areas being the greatest; (2) both CNOP- and FSV-type initial errors grow more quickly than random errors; (3) the eff ect of random errors superimposed on the sensitive areas is greater than that of random errors introduced into randomly selected areas, and initial errors in the CNOP sensitive areas have greater eff ects on final forecasts. These results reveal that the sensitive areas determined using the CNOP are more sensitive than those of FSV and other randomly selected areas. In addition, ideal hindcasting experiments were conducted to examine the validity of the sensitive areas. The results indicate that reduction (or elimination) of CNOP-type errors in CNOP sensitive areas at the initial time has a greater forecast benefit than the reduction (or elimination) of FSV-type errors in FSV sensitive areas. These results suggest that the CNOP method is suitable for determining sensitive areas in the prediction of the Kuroshio large-meander path.

High fidelity studies of exploding foil initiator bridges, Part 1: Experimental method

NASA Astrophysics Data System (ADS)

Bowden, Mike; Neal, William

2017-01-01

Simulations of high voltage detonators, such as Exploding Bridgewire (EBW) and Exploding Foil Initiators (EFI), have historically been simple, often empirical, one-dimensional models capable of predicting parameters such as current, voltage and in the case of EFIs, flyer velocity. Correspondingly, experimental methods have in general been limited to the same parameters. With the advent of complex, first principles magnetohydrodynamic codes such as ALEGRA and ALE-MHD, it is now possible to simulate these components in three dimensions, predicting a much greater range of parameters than before. A significant improvement in experimental capability was therefore required to ensure these simulations could be adequately validated. In this first paper of a three part study, the experimental method for determining the current, voltage, flyer velocity and multi-dimensional profile of detonator components is presented. This improved capability, along with high fidelity simulations, offer an opportunity to gain a greater understanding of the processes behind the functioning of EBW and EFI detonators.

Energy expenditure in adolescents playing new generation computer games.

PubMed

Graves, Lee; Stratton, Gareth; Ridgers, N D; Cable, N T

2008-07-01

To compare the energy expenditure of adolescents when playing sedentary and new generation active computer games. Cross sectional comparison of four computer games. Setting Research laboratories. Six boys and five girls aged 13-15 years. Participants were fitted with a monitoring device validated to predict energy expenditure. They played four computer games for 15 minutes each. One of the games was sedentary (XBOX 360) and the other three were active (Wii Sports). Predicted energy expenditure, compared using repeated measures analysis of variance. Mean (standard deviation) predicted energy expenditure when playing Wii Sports bowling (190.6 (22.2) kl/kg/min), tennis (202.5 (31.5) kl/kg/min), and boxing (198.1 (33.9) kl/kg/min) was significantly greater than when playing sedentary games (125.5 (13.7) kl/kg/min) (P<0.001). Predicted energy expenditure was at least 65.1 (95% confidence interval 47.3 to 82.9) kl/kg/min greater when playing active rather than sedentary games. Playing new generation active computer games uses significantly more energy than playing sedentary computer games but not as much energy as playing the sport itself. The energy used when playing active Wii Sports games was not of high enough intensity to contribute towards the recommended daily amount of exercise in children.

Development and validation of an eating norms inventory. Americans' lay-beliefs about appropriate eating.

PubMed

Fisher, Robert J; Dubé, Laurette

2011-10-01

What do American adults believe about what, where, when, how much, and how often it is appropriate to eat? Such normative beliefs originate from family and friends through socialization processes, but they are also influenced by governments, educational institutions, and businesses. Norms therefore provide an important link between the social environment and individual attitudes and behaviors. This paper reports on five studies that identify, develop, and validate measures of normative beliefs about eating. In study 1 we use an inductive method to identify what American adults believe are appropriate or desirable eating behaviors. Studies 2 and 3 are used to purify and assess the discriminant and nomological validity of the proposed set of 18 unidimensional eating norms. Study 4 assesses predictive validity and finds that acting in a norm-consistent fashion is associated with lower Body Mass Index (BMI), and greater body satisfaction and subjective health. Study 5 assesses the underlying social desirability and perceived healthiness of the norms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Sliding contact fracture of dental ceramics: Principles and validation

PubMed Central

Ren, Linlin; Zhang, Yu

2014-01-01

Ceramic prostheses are subject to sliding contact under normal and tangential loads. Accurate prediction of the onset of fracture at two contacting surfaces holds the key to greater long-term performance of these prostheses. In this study, building on stress analysis of Hertzian contact and considering fracture criteria for linear elastic materials, a constitutive fracture mechanics relation was developed to incorporate the critical fracture load with the contact geometry, coefficient of friction and material fracture toughness. Critical loads necessary to cause fracture under a sliding indenter were calculated from the constitutive equation, and compared with the loads predicted from elastic stress analysis in conjunction with measured critical load for frictionless normal contact—a semi-empirical approach. The major predictions of the models were calibrated with experimentally determined critical loads of current and future dental ceramics after contact with a rigid spherical slider. Experimental results conform with the trends predicted by the models. PMID:24632538

Claims-based risk model for first severe COPD exacerbation.

PubMed

Stanford, Richard H; Nag, Arpita; Mapel, Douglas W; Lee, Todd A; Rosiello, Richard; Schatz, Michael; Vekeman, Francis; Gauthier-Loiselle, Marjolaine; Merrigan, J F Philip; Duh, Mei Sheng

2018-02-01

To develop and validate a predictive model for first severe chronic obstructive pulmonary disease (COPD) exacerbation using health insurance claims data and to validate the risk measure of controller medication to total COPD treatment (controller and rescue) ratio (CTR). A predictive model was developed and validated in 2 managed care databases: Truven Health MarketScan database and Reliant Medical Group database. This secondary analysis assessed risk factors, including CTR, during the baseline period (Year 1) to predict risk of severe exacerbation in the at-risk period (Year 2). Patients with COPD who were 40 years or older and who had at least 1 COPD medication dispensed during the year following COPD diagnosis were included. Subjects with severe exacerbations in the baseline year were excluded. Risk factors in the baseline period were included as potential predictors in multivariate analysis. Performance was evaluated using C-statistics. The analysis included 223,824 patients. The greatest risk factors for first severe exacerbation were advanced age, chronic oxygen therapy usage, COPD diagnosis type, dispensing of 4 or more canisters of rescue medication, and having 2 or more moderate exacerbations. A CTR of 0.3 or greater was associated with a 14% lower risk of severe exacerbation. The model performed well with C-statistics, ranging from 0.711 to 0.714. This claims-based risk model can predict the likelihood of first severe COPD exacerbation. The CTR could also potentially be used to target populations at greatest risk for severe exacerbations. This could be relevant for providers and payers in approaches to prevent severe exacerbations and reduce costs.

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools.

PubMed

McManus, I C; Dewberry, Chris; Nicholson, Sandra; Dowell, Jonathan S

2013-11-14

Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. A prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010. UKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments. This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general.

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

The UKCAT-12 study: educational attainment, aptitude test performance, demographic and socio-economic contextual factors as predictors of first year outcome in a cross-sectional collaborative study of 12 UK medical schools

PubMed Central

2013-01-01

Background Most UK medical schools use aptitude tests during student selection, but large-scale studies of predictive validity are rare. This study assesses the United Kingdom Clinical Aptitude Test (UKCAT), and its four sub-scales, along with measures of educational attainment, individual and contextual socio-economic background factors, as predictors of performance in the first year of medical school training. Methods A prospective study of 4,811 students in 12 UK medical schools taking the UKCAT from 2006 to 2008 as a part of the medical school application, for whom first year medical school examination results were available in 2008 to 2010. Results UKCAT scores and educational attainment measures (General Certificate of Education (GCE): A-levels, and so on; or Scottish Qualifications Authority (SQA): Scottish Highers, and so on) were significant predictors of outcome. UKCAT predicted outcome better in female students than male students, and better in mature than non-mature students. Incremental validity of UKCAT taking educational attainment into account was significant, but small. Medical school performance was also affected by sex (male students performing less well), ethnicity (non-White students performing less well), and a contextual measure of secondary schooling, students from secondary schools with greater average attainment at A-level (irrespective of public or private sector) performing less well. Multilevel modeling showed no differences between medical schools in predictive ability of the various measures. UKCAT sub-scales predicted similarly, except that Verbal Reasoning correlated positively with performance on Theory examinations, but negatively with Skills assessments. Conclusions This collaborative study in 12 medical schools shows the power of large-scale studies of medical education for answering previously unanswerable but important questions about medical student selection, education and training. UKCAT has predictive validity as a predictor of medical school outcome, particularly in mature applicants to medical school. UKCAT offers small but significant incremental validity which is operationally valuable where medical schools are making selection decisions based on incomplete measures of educational attainment. The study confirms the validity of using all the existing measures of educational attainment in full at the time of selection decision-making. Contextual measures provide little additional predictive value, except that students from high attaining secondary schools perform less well, an effect previously shown for UK universities in general. PMID:24229380

Principal components analysis of the hypomanic attitudes and positive predictions inventory and associations with measures of personality, cognitive style and analogue symptoms in a student sample.

PubMed

Dodd, Alyson L; Mansell, Warren; Sadhnani, Vaneeta; Morrison, Anthony P; Tai, Sara

2010-01-01

An integrative cognitive model proposed that ascribing extreme personal appraisals to changes in internal state is key to the development of the symptoms of bipolar disorder. The Hypomanic Attitudes and Positive Predictions Inventory (HAPPI) was developed to measure these appraisals. The aim of the current study was to validate an expanded 61-item version of the HAPPI. In a largely female student sample (N = 134), principal components analysis (PCA) was performed on the HAPPI. Associations between the HAPPI and analogue bipolar symptoms after 3 months were examined. PCA of the HAPPI revealed six categories of belief: Self Activation, Self-and-Other Critical, Catastrophic, Extreme Appraisals of Social Approval, Appraisals of Extreme Agitation, and Loss of Control. The HAPPI predicted all analogue measures of hypomanic symptoms after 3 months when controlling for baseline symptoms. In a more stringent test incorporating other psychological measures, the HAPPI was independently associated only with activation (e.g. thoughts racing) at 3 months. Dependent dysfunctional attitudes predicted greater conflict (e.g. irritability), depression and reduced well-being, hypomanic personality predicted self-reported diagnostic bipolar symptoms, and behavioural dysregulation predicted depression. Extreme beliefs about internal states show a modest independent association with prospective analogue bipolar symptoms, alongside other psychological factors. Further work will be required to improve the factor structure of the HAPPI and study its validity in clinical samples.

Quantifying Calcium Intake in School Age Children: Development and Validation of the Calcium Counts!© Food Frequency Questionnaire

PubMed Central

ZEMEL, BABETTE S.; CAREY, LISA B.; PAULHAMUS, DONNA R.; STALLINGS, VIRGINIA A.; ITTENBACH, RICHARD F.

2014-01-01

Quantifying dietary behavior is difficult and can be intrusive. Calcium, an essential mineral for skeletal development during childhood, is difficult to assess. Few studies have examined the use of food frequency questionnaires (FFQs) for assessing calcium intake in school-age children. This study evaluated the validity and reliability of the Calcium Counts!© FFQ (CCFFQ) for estimating calcium intake in school children in the US. Healthy children, aged 7–10 years (n = 139) completed the CCFFQ and 7-day weighed food records. A subset of subjects completed a second CCFFQ within 3.6 months. Concurrent validity was determined using Pearson correlations between the CCFFQ and food record estimates of calcium intake, and the relationship between quintiles for the two measures. Predictive validity was determined using generalized linear regression models to explore the effects of age, race, and gender. Inter- and intra-individual variability in calcium intake was high (>300 mg/day). Calcium intake was ~300 mg/day higher by CCFFQ compared to food records. Concurrent validity was moderate (r = 0.61) for the entire cohort and higher for selected subgroups. Predictive validity estimates yielded significant relationships between CCFFQ and food record estimates of calcium intake alone and in the presence of such potential effect modifiers as age group, race, and gender. Test–retest reliability was high (r = 0.74). Although calcium intake estimated by the CCFFQ was greater than that measured by food records, the CCFFQ provides valid and reliable estimates of calcium intake in children. The CCFFQ is especially well-suited as a tool to identify children with low calcium intakes. PMID:19621431

Psychosocial correlates of disordered eating in female collegiate athletes: validation of the ATHLETE questionnaire.

PubMed

Hinton, Pamela S; Kubas, Karen L

2005-01-01

Female athletes may be at greater risk for disordered eating than their nonathletic peers, but the psychological antecedents of this dysfunctional behavior in athletes have yet to be elucidated. The objective of this study was to develop an athletics-oriented measure of psychological predictors of disordered eating and to test its initial reliability and validity. Female athletes from 3 National Collegiate Athletics Association (NCAA) Division I universities completed the ATHLETE, a written questionnaire designed to assess psychosocial factors associated with disordered eating in athletes. Five distinct and internally consistent factors (Drive for Thinness and Performance, Social Pressure on Eating, Performance Perfectionism, Social Pressure on Body Shape, and Team Trust) were positively associated with and predictive of disordered eating behaviors in female athletes. The ATHLETE is a reliable and valid measure of psychological predictors of disordered eating in athletics and will be useful in studying the etiology of disordered eating in female athletes.

Lung cancer in patients with chronic obstructive pulmonary disease. Development and validation of the COPD Lung Cancer Screening Score.

PubMed

de-Torres, Juan P; Wilson, David O; Sanchez-Salcedo, Pablo; Weissfeld, Joel L; Berto, Juan; Campo, Arantzazu; Alcaide, Ana B; García-Granero, Marta; Celli, Bartolome R; Zulueta, Javier J

2015-02-01

Patients with chronic obstructive pulmonary disease (COPD) are at high risk for lung cancer (LC) and represent a potential target to improve the diagnostic yield of screening programs. To develop a predictive score for LC risk for patients with COPD. The Pamplona International Early Lung Cancer Detection Program (P-IELCAP) and the Pittsburgh Lung Screening Study (PLuSS) databases were analyzed. Only patients with COPD on spirometry were included. By logistic regression we determined which factors were independently associated with LC in PLuSS and developed a COPD LC screening score (COPD-LUCSS) to be validated in P-IELCAP. By regression analysis, age greater than 60, body mass index less than 25 kg/m(2), pack-years history greater than 60, and emphysema presence were independently associated with LC diagnosis and integrated into the COPD-LUCSS, which ranges from 0 to 10 points. Two COPD-LUCSS risk categories were proposed: low risk (scores 0-6) and high risk (scores 7-10). In comparison with low-risk patients, in both cohorts LC risk increased 3.5-fold in the high-risk category. The COPD-LUCSS is a good predictor of LC risk in patients with COPD participating in LC screening programs. Validation in two different populations adds strength to the findings.

The Profile of Emotional Competence (PEC): development and validation of a self-reported measure that fits dimensions of emotional competence theory.

PubMed

Brasseur, Sophie; Grégoire, Jacques; Bourdu, Romain; Mikolajczak, Moïra

2013-01-01

Emotional Competence (EC), which refers to individual differences in the identification, understanding, expression, regulation and use of one's own emotions and those of others, has been found to be an important predictor of individuals' adaptation to their environment. Higher EC is associated with greater happiness, better mental and physical health, more satisfying social and marital relationships and greater occupational success. While it is well-known that EC (as a whole) predicts a number of important outcomes, it is unclear so far which specific competency(ies) participate(s) in a given outcome. This is because no measure of EC distinctly measures each of the five core emotional competences, separately for one's own and others' emotions. This lack of information is problematic both theoretically (we do not understand the processes at stake) and practically (we cannot develop customized interventions). This paper aims to address this issue. We developed and validated in four steps a complete (albeit short: 50 items) self-reported measure of EC: the Profile of Emotional Competence. Analyses performed on a representative sample of 5676 subjects revealed promising psychometric properties. The internal consistency of scales and subscales alike was satisfying, factorial structure was as expected, and concurrent/discriminant validity was good.

Embedded measures of performance validity using verbal fluency tests in a clinical sample.

PubMed

Sugarman, Michael A; Axelrod, Bradley N

2015-01-01

The objective of this study was to determine to what extent verbal fluency measures can be used as performance validity indicators during neuropsychological evaluation. Participants were clinically referred for neuropsychological evaluation in an urban-based Veteran's Affairs hospital. Participants were placed into 2 groups based on their objectively evaluated effort on performance validity tests (PVTs). Individuals who exhibited credible performance (n = 431) failed 0 PVTs, and those with poor effort (n = 192) failed 2 or more PVTs. All participants completed the Controlled Oral Word Association Test (COWAT) and Animals verbal fluency measures. We evaluated how well verbal fluency scores could discriminate between the 2 groups. Raw scores and T scores for Animals discriminated between the credible performance and poor-effort groups with 90% specificity and greater than 40% sensitivity. COWAT scores had lower sensitivity for detecting poor effort. A combination of FAS and Animals scores into logistic regression models yielded acceptable group classification, with 90% specificity and greater than 44% sensitivity. Verbal fluency measures can yield adequate detection of poor effort during neuropsychological evaluation. We provide suggested cut points and logistic regression models for predicting the probability of poor effort in our clinical setting and offer suggested cutoff scores to optimize sensitivity and specificity.

A posteriori model validation for the temporal order of directed functional connectivity maps.

PubMed

Beltz, Adriene M; Molenaar, Peter C M

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data).

Validation of Clinical Testing for Warfarin Sensitivity

PubMed Central

Langley, Michael R.; Booker, Jessica K.; Evans, James P.; McLeod, Howard L.; Weck, Karen E.

2009-01-01

Responses to warfarin (Coumadin) anticoagulation therapy are affected by genetic variability in both the CYP2C9 and VKORC1 genes. Validation of pharmacogenetic testing for warfarin responses includes demonstration of analytical validity of testing platforms and of the clinical validity of testing. We compared four platforms for determining the relevant single nucleotide polymorphisms (SNPs) in both CYP2C9 and VKORC1 that are associated with warfarin sensitivity (Third Wave Invader Plus, ParagonDx/Cepheid Smart Cycler, Idaho Technology LightCycler, and AutoGenomics Infiniti). Each method was examined for accuracy, cost, and turnaround time. All genotyping methods demonstrated greater than 95% accuracy for identifying the relevant SNPs (CYP2C9 *2 and *3; VKORC1 −1639 or 1173). The ParagonDx and Idaho Technology assays had the shortest turnaround and hands-on times. The Third Wave assay was readily scalable to higher test volumes but had the longest hands-on time. The AutoGenomics assay interrogated the largest number of SNPs but had the longest turnaround time. Four published warfarin-dosing algorithms (Washington University, UCSF, Louisville, and Newcastle) were compared for accuracy for predicting warfarin dose in a retrospective analysis of a local patient population on long-term, stable warfarin therapy. The predicted doses from both the Washington University and UCSF algorithms demonstrated the best correlation with actual warfarin doses. PMID:19324988

Validation of clinical testing for warfarin sensitivity: comparison of CYP2C9-VKORC1 genotyping assays and warfarin-dosing algorithms.

PubMed

Langley, Michael R; Booker, Jessica K; Evans, James P; McLeod, Howard L; Weck, Karen E

2009-05-01

Responses to warfarin (Coumadin) anticoagulation therapy are affected by genetic variability in both the CYP2C9 and VKORC1 genes. Validation of pharmacogenetic testing for warfarin responses includes demonstration of analytical validity of testing platforms and of the clinical validity of testing. We compared four platforms for determining the relevant single nucleotide polymorphisms (SNPs) in both CYP2C9 and VKORC1 that are associated with warfarin sensitivity (Third Wave Invader Plus, ParagonDx/Cepheid Smart Cycler, Idaho Technology LightCycler, and AutoGenomics Infiniti). Each method was examined for accuracy, cost, and turnaround time. All genotyping methods demonstrated greater than 95% accuracy for identifying the relevant SNPs (CYP2C9 *2 and *3; VKORC1 -1639 or 1173). The ParagonDx and Idaho Technology assays had the shortest turnaround and hands-on times. The Third Wave assay was readily scalable to higher test volumes but had the longest hands-on time. The AutoGenomics assay interrogated the largest number of SNPs but had the longest turnaround time. Four published warfarin-dosing algorithms (Washington University, UCSF, Louisville, and Newcastle) were compared for accuracy for predicting warfarin dose in a retrospective analysis of a local patient population on long-term, stable warfarin therapy. The predicted doses from both the Washington University and UCSF algorithms demonstrated the best correlation with actual warfarin doses.

Language-based Measures of Mindfulness: Initial Validity and Clinical Utility

PubMed Central

Collins, Susan E.; Chawla, Neharika; Hsu, Sharon H.; Grow, Joel; Otto, Jacqueline M.; Marlatt, G. Alan

2009-01-01

This study examined relationships among language use, mindfulness, and substance-use treatment outcomes in the context of an efficacy trial of mindfulness-based relapse prevention (MBRP) for adults with alcohol and other drug use (AOD) disorders (see Bowen, Chawla, Collins et al., in press). An expert panel generated two categories of mindfulness language (ML) describing the mindfulness state and the more encompassing “mindfulness journey,” which included words describing challenges of developing a mindfulness practice. MBRP participants (n=48) completed baseline sociodemographic and AOD measures, and participated in the 8-week MBRP program. AOD data were collected during the 4-month follow-up. A word count program assessed the frequency of ML and other linguistic markers in participants’ responses to open-ended questions about their postintervention impressions of mindfulness practice and MBRP. Findings supported concurrent validity of ML categories: ML words appeared more frequently in the MBRP manual compared to the 12-step Big Book. Further, ML categories correlated with other linguistic variables related to the mindfulness construct. Finally, predictive validity was supported: greater use of ML predicted fewer AOD use days during the 4-month follow-up. This study provided initial support for ML as a valid, clinically useful mindfulness measure. If future studies replicate these findings, ML could be used in conjunction with self-report to provide a more complete picture of the mindfulness experience. PMID:20025383

Reasons for quitting smoking among low-income African American smokers.

PubMed

McBride, C M; Pollak, K I; Bepler, G; Lyna, P; Lipkus, I M; Samsa, G P

2001-09-01

The psychometric characteristics of the Reasons For Quitting scale (RFQ) were assessed among a sample of African American smokers with low income (N=487). The intrinsic and extrinsic scales and their respective subscales were replicated. As hypothesized, higher levels of motivation were associated significantly, in patterns that supported the measure's construct validity, with advanced stage of readiness to quit smoking, greater perceived vulnerability to health effects of smoking, and greater social support for cessation. On the basis of the present study, the RFQ might best predict short-term cessation among older and female smokers. Refinement of the RFQ is needed to assess intrinsic motivators other than health concerns and to identify salient motivators for young and male smokers.

Predicting turns in proteins with a unified model.

PubMed

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications.

Predicting Turns in Proteins with a Unified Model

PubMed Central

Song, Qi; Li, Tonghua; Cong, Peisheng; Sun, Jiangming; Li, Dapeng; Tang, Shengnan

2012-01-01

Motivation Turns are a critical element of the structure of a protein; turns play a crucial role in loops, folds, and interactions. Current prediction methods are well developed for the prediction of individual turn types, including α-turn, β-turn, and γ-turn, etc. However, for further protein structure and function prediction it is necessary to develop a uniform model that can accurately predict all types of turns simultaneously. Results In this study, we present a novel approach, TurnP, which offers the ability to investigate all the turns in a protein based on a unified model. The main characteristics of TurnP are: (i) using newly exploited features of structural evolution information (secondary structure and shape string of protein) based on structure homologies, (ii) considering all types of turns in a unified model, and (iii) practical capability of accurate prediction of all turns simultaneously for a query. TurnP utilizes predicted secondary structures and predicted shape strings, both of which have greater accuracy, based on innovative technologies which were both developed by our group. Then, sequence and structural evolution features, which are profile of sequence, profile of secondary structures and profile of shape strings are generated by sequence and structure alignment. When TurnP was validated on a non-redundant dataset (4,107 entries) by five-fold cross-validation, we achieved an accuracy of 88.8% and a sensitivity of 71.8%, which exceeded the most state-of-the-art predictors of certain type of turn. Newly determined sequences, the EVA and CASP9 datasets were used as independent tests and the results we achieved were outstanding for turn predictions and confirmed the good performance of TurnP for practical applications. PMID:23144872

Use of Fuzzy rainfall-runoff predictions for claypan watersheds with conservation buffers in Northeast Missouri

NASA Astrophysics Data System (ADS)

Anomaa Senaviratne, G. M. M. M.; Udawatta, Ranjith P.; Anderson, Stephen H.; Baffaut, Claire; Thompson, Allen

2014-09-01

Fuzzy rainfall-runoff models are often used to forecast flood or water supply in large catchments and applications at small/field scale agricultural watersheds are limited. The study objectives were to develop, calibrate, and validate a fuzzy rainfall-runoff model using long-term data of three adjacent field scale row crop watersheds (1.65-4.44 ha) with intermittent discharge in the claypan soils of Northeast Missouri. The watersheds were monitored for a six-year calibration period starting 1991 (pre-buffer period). Thereafter, two of them were treated with upland contour grass and agroforestry (tree + grass) buffers (4.5 m wide, 36.5 m apart) to study water quality benefits. The fuzzy system was based on Mamdani method using MATLAB 7.10.0. The model predicted event-based runoff with model performance coefficients of r2 and Nash-Sutcliffe Coefficient (NSC) values greater than 0.65 for calibration and validation. The pre-buffer fuzzy system predicted event-based runoff for 30-50 times larger corn/soybean watersheds with r2 values of 0.82 and 0.68 and NSC values of 0.77 and 0.53, respectively. The runoff predicted by the fuzzy system closely agreed with values predicted by physically-based Agricultural Policy Environmental eXtender model (APEX) for the pre-buffer watersheds. The fuzzy rainfall-runoff model has the potential for runoff predictions at field-scale watersheds with minimum input. It also could up-scale the predictions for large-scale watersheds to evaluate the benefits of conservation practices.

LBSizeCleav: improved support vector machine (SVM)-based prediction of Dicer cleavage sites using loop/bulge length.

PubMed

Bao, Yu; Hayashida, Morihiro; Akutsu, Tatsuya

2016-11-25

Dicer is necessary for the process of mature microRNA (miRNA) formation because the Dicer enzyme cleaves pre-miRNA correctly to generate miRNA with correct seed regions. Nonetheless, the mechanism underlying the selection of a Dicer cleavage site is still not fully understood. To date, several studies have been conducted to solve this problem, for example, a recent discovery indicates that the loop/bulge structure plays a central role in the selection of Dicer cleavage sites. In accordance with this breakthrough, a support vector machine (SVM)-based method called PHDCleav was developed to predict Dicer cleavage sites which outperforms other methods based on random forest and naive Bayes. PHDCleav, however, tests only whether a position in the shift window belongs to a loop/bulge structure. In this paper, we used the length of loop/bulge structures (in addition to their presence or absence) to develop an improved method, LBSizeCleav, for predicting Dicer cleavage sites. To evaluate our method, we used 810 empirically validated sequences of human pre-miRNAs and performed fivefold cross-validation. In both 5p and 3p arms of pre-miRNAs, LBSizeCleav showed greater prediction accuracy than PHDCleav did. This result suggests that the length of loop/bulge structures is useful for prediction of Dicer cleavage sites. We developed a novel algorithm for feature space mapping based on the length of a loop/bulge for predicting Dicer cleavage sites. The better performance of our method indicates the usefulness of the length of loop/bulge structures for such predictions.

Quantifying Vocal Mimicry in the Greater Racket-Tailed Drongo: A Comparison of Automated Methods and Human Assessment

PubMed Central

Agnihotri, Samira; Sundeep, P. V. D. S.; Seelamantula, Chandra Sekhar; Balakrishnan, Rohini

2014-01-01

Objective identification and description of mimicked calls is a primary component of any study on avian vocal mimicry but few studies have adopted a quantitative approach. We used spectral feature representations commonly used in human speech analysis in combination with various distance metrics to distinguish between mimicked and non-mimicked calls of the greater racket-tailed drongo, Dicrurus paradiseus and cross-validated the results with human assessment of spectral similarity. We found that the automated method and human subjects performed similarly in terms of the overall number of correct matches of mimicked calls to putative model calls. However, the two methods also misclassified different subsets of calls and we achieved a maximum accuracy of ninety five per cent only when we combined the results of both the methods. This study is the first to use Mel-frequency Cepstral Coefficients and Relative Spectral Amplitude - filtered Linear Predictive Coding coefficients to quantify vocal mimicry. Our findings also suggest that in spite of several advances in automated methods of song analysis, corresponding cross-validation by humans remains essential. PMID:24603717

Simulating Fatigue Crack Growth in Spiral Bevel Gears

NASA Technical Reports Server (NTRS)

Spievak, Lisa E.; Wawrzynek, Paul A.; Ingraffea, Anthony R.

2000-01-01

The majority of helicopter transmission systems utilize spiral bevel gears to convert the horizontal power from the engine into vertical power for the rotor. Due to the cyclical loading on a gear's tooth, fatigue crack propagation can occur. In rotorcraft applications, a crack's trajectory determines whether the gear failure will be benign or catastrophic for the aircraft. As a result, the capability to predict crack growth in gears is significant. A spiral bevel gear's complex shape requires a three dimensional model of the geometry and cracks. The boundary element method in conjunction with linear elastic fracture mechanics theories is used to predict arbitrarily shaped three dimensional fatigue crack trajectories in a spiral bevel pinion under moving load conditions. The predictions are validated by comparison to experimental results. The sensitivity of the predictions to variations in loading conditions and crack growth rate model parameters is explored. Critical areas that must be understood in greater detail prior to predicting more accurate crack trajectories and crack growth rates in three dimensions are identified.

Evaluation of Model Microphysics Within Precipitation Bands of Extratropical Cyclones

NASA Technical Reports Server (NTRS)

Colle, Brian A.; Yu, Ruyi; Molthan, Andrew L.; Nesbitt, Steven

2014-01-01

It is hypothesized microphysical predictions have greater uncertainties/errors when there are complex interactions that result from mixed phased processes like riming. Use Global Precipitation Measurement (GPM) Mission ground validation studies in Ontario, Canada to verify and improve parameterizations. The WRF realistically simulated the warm frontal snowband at relatively short lead times (1014 h). The snowband structire is sensitive to the microphysical parameterization used in WRF. The Goddard and SBUYLin most realistically predicted the band structure, but overpredicted snow content. The double moment Morrison scheme best produced the slope of the snow distribution, but it underpredicted the intercept. All schemes and the radar derived (which used dry snow ZR) underpredicted the surface precipitation amount, likely because there was more cloud water than expected. The Morrison had the most cloud water and the best precipitation prediction of all schemes.

Validation and refinement of a rule to predict emergency intervention in adult trauma patients.

PubMed

Haukoos, Jason S; Byyny, Richard L; Erickson, Catherine; Paulson, Stephen; Hopkins, Emily; Sasson, Comilla; Bender, Brooke; Gravitz, Craig S; Vogel, Jody A; Colwell, Christopher B; Moore, Ernest E

2011-08-01

Trauma centers use "secondary triage" to determine the necessity of trauma surgeon involvement. A clinical decision rule, which includes penetrating injury, an initial systolic blood pressure less than 100 mm Hg, or an initial pulse rate greater than 100 beats/min, was developed to predict which trauma patients require emergency operative intervention or emergency procedural intervention (cricothyroidotomy or thoracotomy) in the emergency department. Our goal was to validate this rule in an adult trauma population and to compare it with the American College of Surgeons' major resuscitation criteria. We used Level I trauma center registry data from September 1, 1995, through November 30, 2008. Outcomes were confirmed with blinded abstractors. Sensitivity, specificity, and 95% confidence intervals (CIs) were calculated. Our patient sample included 20,872 individuals. The median Injury Severity Score was 9 (interquartile range 4 to 16), 15.3% of patients had penetrating injuries, 13.5% had a systolic blood pressure less than 100 mm Hg, and 32.5% had a pulse rate greater than 100 beats/min. Emergency operative intervention or procedural intervention was required in 1,099 patients (5.3%; 95% CI 5.0% to 5.6%). The sensitivities and specificities of the rule and the major resuscitation criteria for predicting emergency operative intervention or emergency procedural intervention were 95.6% (95% CI 94.3% to 96.8%) and 56.1% (95% CI 55.4% to 56.8%) and 85.5% (95% CI 83.3% to 87.5%) and 80.9% (95% CI 80.3% to 81.4%), respectively. This new rule was more sensitive for predicting the need for emergency operative intervention or emergency procedural intervention directly compared with the American College of Surgeons' major resuscitation criteria, which may improve the effectiveness and efficiency of trauma triage. Copyright © 2011 American College of Emergency Physicians. Published by Mosby, Inc. All rights reserved.

Using the Bayesian Improved Surname Geocoding Method (BISG) to create a working classification of race and ethnicity in a diverse managed care population: a validation study.

PubMed

Adjaye-Gbewonyo, Dzifa; Bednarczyk, Robert A; Davis, Robert L; Omer, Saad B

2014-02-01

To validate classification of race/ethnicity based on the Bayesian Improved Surname Geocoding method (BISG) and assess variations in validity by gender and age. Secondary data on members of Kaiser Permanente Georgia, an integrated managed care organization, through 2010. For 191,494 members with self-reported race/ethnicity, probabilities for belonging to each of six race/ethnicity categories predicted from the BISG algorithm were used to assign individuals to a race/ethnicity category over a range of cutoffs greater than a probability of 0.50. Overall as well as gender- and age-stratified sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Receiver operating characteristic (ROC) curves were generated and used to identify optimal cutoffs for race/ethnicity assignment. The overall cutoffs for assignment that optimized sensitivity and specificity ranged from 0.50 to 0.57 for the four main racial/ethnic categories (White, Black, Asian/Pacific Islander, Hispanic). Corresponding sensitivity, specificity, PPV, and NPV ranged from 64.4 to 81.4 percent, 80.8 to 99.7 percent, 75.0 to 91.6 percent, and 79.4 to 98.0 percent, respectively. Accuracy of assignment was better among males and individuals of 65 years or older. BISG may be useful for classifying race/ethnicity of health plan members when needed for health care studies. © Health Research and Educational Trust.

Biomarker-Based Risk Model to Predict Cardiovascular Mortality in Patients With Stable Coronary Disease.

PubMed

Lindholm, Daniel; Lindbäck, Johan; Armstrong, Paul W; Budaj, Andrzej; Cannon, Christopher P; Granger, Christopher B; Hagström, Emil; Held, Claes; Koenig, Wolfgang; Östlund, Ollie; Stewart, Ralph A H; Soffer, Joseph; White, Harvey D; de Winter, Robbert J; Steg, Philippe Gabriel; Siegbahn, Agneta; Kleber, Marcus E; Dressel, Alexander; Grammer, Tanja B; März, Winfried; Wallentin, Lars

2017-08-15

Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD). This study evaluated and compared the prognostic value of biomarkers and clinical variables to develop a biomarker-based prediction model in patients with stable CHD. In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study. During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This "ABC-CHD" model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts. This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial [STABILITY]; NCT00799903). Copyright © 2017 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Predicting cognitive function from clinical measures of physical function and health status in older adults.

PubMed

Bolandzadeh, Niousha; Kording, Konrad; Salowitz, Nicole; Davis, Jennifer C; Hsu, Liang; Chan, Alison; Sharma, Devika; Blohm, Gunnar; Liu-Ambrose, Teresa

2015-01-01

Current research suggests that the neuropathology of dementia-including brain changes leading to memory impairment and cognitive decline-is evident years before the onset of this disease. Older adults with cognitive decline have reduced functional independence and quality of life, and are at greater risk for developing dementia. Therefore, identifying biomarkers that can be easily assessed within the clinical setting and predict cognitive decline is important. Early recognition of cognitive decline could promote timely implementation of preventive strategies. We included 89 community-dwelling adults aged 70 years and older in our study, and collected 32 measures of physical function, health status and cognitive function at baseline. We utilized an L1-L2 regularized regression model (elastic net) to identify which of the 32 baseline measures were strongly predictive of cognitive function after one year. We built three linear regression models: 1) based on baseline cognitive function, 2) based on variables consistently selected in every cross-validation loop, and 3) a full model based on all the 32 variables. Each of these models was carefully tested with nested cross-validation. Our model with the six variables consistently selected in every cross-validation loop had a mean squared prediction error of 7.47. This number was smaller than that of the full model (115.33) and the model with baseline cognitive function (7.98). Our model explained 47% of the variance in cognitive function after one year. We built a parsimonious model based on a selected set of six physical function and health status measures strongly predictive of cognitive function after one year. In addition to reducing the complexity of the model without changing the model significantly, our model with the top variables improved the mean prediction error and R-squared. These six physical function and health status measures can be easily implemented in a clinical setting.

Development of a Middle-Age and Geriatric Trauma Mortality Risk Score A Tool to Guide Palliative Care Consultations.

PubMed

Konda, Sanjit R; Seymour, Rachel; Manoli, Arthur; Gales, Jordan; Karunakar, Madhav A

2016-11-01

This study aimed to develop a tool to quantify risk of inpatient mortality among geriatric and middleaged trauma patients. This study sought to demonstrate the ability of the novel risk score in the early identification of high risk trauma patients for resource-sparing interventions, including referral to palliative medicine. This retrospective cohort study utilized data from a single level 1 trauma center. Regression analysis was used to create a novel risk of inpatient mortality score. A total of 2,387 low energy and 1,201 high-energy middle-aged (range: 55 to 64 years of age) and geriatric (65 years of age or odler) trauma patients comprised the study cohort. Model validation was performed using 37,474 lowenergy and 97,034 high-energy patients from the National Trauma Databank (NTDB). Potential hospital cost reduction was calculated for early referral of high risk trauma patients to palliative medicine services in comparison to no palliative medicine referral. Factors predictive of inpatient mortality among the study and validation patient cohorts included; age, Glasgow Coma Scale, and Abbreviated Injury Scale for the head and neck and chest. Within the validation cohort, the novel mortality risk score demonstrated greater predictive capacity than existing trauma scores [STTGMALE-AUROC: 0.83 vs. TRISS 0.80, (p < 0.01), STTGMAHE-AUROC: 0.86 vs. TRISS 0.85, (p < 0.01)]. Our model demonstrated early palliative medicine evaluation could produce $1,083,082 in net hospital savings per year. This novel risk score for older trauma patients has shown fidelity in prediction of inpatient mortality; in the study and validation cohorts. This tool may be used for early intervention in the care of patients at high risk of mortality and resource expenditure.

Non-invasive measurement of tibialis anterior muscle temperature during rest, cycling exercise and post-exercise recovery.

PubMed

Flouris, Andreas D; Dinas, Petros C; Tsitoglou, Kiriakos; Patramani, Ioanna; Koutedakis, Yiannis; Kenny, Glen P

2015-07-01

We introduce a non-invasive and accurate method to assess tibialis anterior muscle temperature (Tm) during rest, cycling exercise, and post-exercise recovery using the insulation disk (INDISK) technique. Twenty-six healthy males (23.6  ±  6.2 years; 24.1  ±  3.1 body mass index) were randomly allocated into the 'model' (n = 16) and the 'validation' (n = 10) groups. Participants underwent 20 min supine rest, 20 min cycling exercise at 60% of age-predicted maximum heart rate, and 20 min supine post-exercise recovery. In the model group, Tm (34.55  ±  1.02 °C) was greater than INDISK temperature (Tid; 32.44  ±  1.23 °C; p < 0.001) and skin surface temperature (Tsk; 29.84  ±  1.47 °C; p < 0.001) throughout the experimental protocol. The strongest prediction model (R(2) = 0.646) incorporated Tid and the difference between the current Tid temperature and that recorded four minutes before. No mean difference (p > 0.05) and a strong correlation (r = 0.804; p < 0.001) were observed between Tm and predicted Tm (predTm) in the model group. Cross-validation analyses in the validation group demonstrated no mean difference (p > 0.05), a strong correlation (r = 0.644; p < 0.001), narrow 95% limits of agreement (-0.06  ±  1.51), and low percent coefficient of variation (2.24%) between Tm (34.39  ±  1.00 °C) and predTm (34.45  ±  0.73 °C). We conclude that the novel technique accurately predicts Tm during rest, cycling exercise, and post-exercise recovery, providing a valid and cost-efficient alternative when direct Tm measurement is not feasible.

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy.

PubMed

Bharamgoudar, Reshma; Sonsale, Aniket; Hodson, James; Griffiths, Ewen

2018-07-01

The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45-85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p < 0.001), with the proportions of operations lasting > 90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care.

Age, PaO2/FIO2, and Plateau Pressure Score: A Proposal for a Simple Outcome Score in Patients With the Acute Respiratory Distress Syndrome.

PubMed

Villar, Jesús; Ambrós, Alfonso; Soler, Juan Alfonso; Martínez, Domingo; Ferrando, Carlos; Solano, Rosario; Mosteiro, Fernando; Blanco, Jesús; Martín-Rodríguez, Carmen; Fernández, María Del Mar; López, Julia; Díaz-Domínguez, Francisco J; Andaluz-Ojeda, David; Merayo, Eleuterio; Pérez-Méndez, Lina; Fernández, Rosa Lidia; Kacmarek, Robert M

2016-07-01

Although there is general agreement on the characteristic features of the acute respiratory distress syndrome, we lack a scoring system that predicts acute respiratory distress syndrome outcome with high probability. Our objective was to develop an outcome score that clinicians could easily calculate at the bedside to predict the risk of death of acute respiratory distress syndrome patients 24 hours after diagnosis. A prospective, multicenter, observational, descriptive, and validation study. A network of multidisciplinary ICUs. Six-hundred patients meeting Berlin criteria for moderate and severe acute respiratory distress syndrome enrolled in two independent cohorts treated with lung-protective ventilation. None. Using individual demographic, pulmonary, and systemic data at 24 hours after acute respiratory distress syndrome diagnosis, we derived our prediction score in 300 acute respiratory distress syndrome patients based on stratification of variable values into tertiles, and validated in an independent cohort of 300 acute respiratory distress syndrome patients. Primary outcome was in-hospital mortality. We found that a 9-point score based on patient's age, PaO2/FIO2 ratio, and plateau pressure at 24 hours after acute respiratory distress syndrome diagnosis was associated with death. Patients with a score greater than 7 had a mortality of 83.3% (relative risk, 5.7; 95% CI, 3.0-11.0), whereas patients with scores less than 5 had a mortality of 14.5% (p < 0.0000001). We confirmed the predictive validity of the score in a validation cohort. A simple 9-point score based on the values of age, PaO2/FIO2 ratio, and plateau pressure calculated at 24 hours on protective ventilation after acute respiratory distress syndrome diagnosis could be used in real time for rating prognosis of acute respiratory distress syndrome patients with high probability.

Application of Recursive Partitioning to Derive and Validate a Claims-Based Algorithm for Identifying Keratinocyte Carcinoma (Nonmelanoma Skin Cancer).

PubMed

Chan, An-Wen; Fung, Kinwah; Tran, Jennifer M; Kitchen, Jessica; Austin, Peter C; Weinstock, Martin A; Rochon, Paula A

2016-10-01

Keratinocyte carcinoma (nonmelanoma skin cancer) accounts for substantial burden in terms of high incidence and health care costs but is excluded by most cancer registries in North America. Administrative health insurance claims databases offer an opportunity to identify these cancers using diagnosis and procedural codes submitted for reimbursement purposes. To apply recursive partitioning to derive and validate a claims-based algorithm for identifying keratinocyte carcinoma with high sensitivity and specificity. Retrospective study using population-based administrative databases linked to 602 371 pathology episodes from a community laboratory for adults residing in Ontario, Canada, from January 1, 1992, to December 31, 2009. The final analysis was completed in January 2016. We used recursive partitioning (classification trees) to derive an algorithm based on health insurance claims. The performance of the derived algorithm was compared with 5 prespecified algorithms and validated using an independent academic hospital clinic data set of 2082 patients seen in May and June 2011. Sensitivity, specificity, positive predictive value, and negative predictive value using the histopathological diagnosis as the criterion standard. We aimed to achieve maximal specificity, while maintaining greater than 80% sensitivity. Among 602 371 pathology episodes, 131 562 (21.8%) had a diagnosis of keratinocyte carcinoma. Our final derived algorithm outperformed the 5 simple prespecified algorithms and performed well in both community and hospital data sets in terms of sensitivity (82.6% and 84.9%, respectively), specificity (93.0% and 99.0%, respectively), positive predictive value (76.7% and 69.2%, respectively), and negative predictive value (95.0% and 99.6%, respectively). Algorithm performance did not vary substantially during the 18-year period. This algorithm offers a reliable mechanism for ascertaining keratinocyte carcinoma for epidemiological research in the absence of cancer registry data. Our findings also demonstrate the value of recursive partitioning in deriving valid claims-based algorithms.

Personalized Nutrition-Genes, Diet, and Related Interactive Parameters as Predictors of Cancer in Multiethnic Colorectal Cancer Families.

PubMed

Shiao, S Pamela K; Grayson, James; Lie, Amanda; Yu, Chong Ho

2018-06-20

To personalize nutrition, the purpose of this study was to examine five key genes in the folate metabolism pathway, and dietary parameters and related interactive parameters as predictors of colorectal cancer (CRC) by measuring the healthy eating index (HEI) in multiethnic families. The five genes included methylenetetrahydrofolate reductase ( MTHFR ) 677 and 1298, methionine synthase ( MTR ) 2756, methionine synthase reductase ( MTRR 66), and dihydrofolate reductase ( DHFR ) 19bp , and they were used to compute a total gene mutation score. We included 53 families, 53 CRC patients and 53 paired family friend members of diverse population groups in Southern California. We measured multidimensional data using the ensemble bootstrap forest method to identify variables of importance within domains of genetic, demographic, and dietary parameters to achieve dimension reduction. We then constructed predictive generalized regression (GR) modeling with a supervised machine learning validation procedure with the target variable (cancer status) being specified to validate the results to allow enhanced prediction and reproducibility. The results showed that the CRC group had increased total gene mutation scores compared to the family members ( p < 0.05). Using the Akaike's information criterion and Leave-One-Out cross validation GR methods, the HEI was interactive with thiamine (vitamin B1), which is a new finding for the literature. The natural food sources for thiamine include whole grains, legumes, and some meats and fish which HEI scoring included as part of healthy portions (versus limiting portions on salt, saturated fat and empty calories). Additional predictors included age, as well as gender and the interaction of MTHFR 677 with overweight status (measured by body mass index) in predicting CRC, with the cancer group having more men and overweight cases. The HEI score was significant when split at the median score of 77 into greater or less scores, confirmed through the machine-learning recursive tree method and predictive modeling, although an HEI score of greater than 80 is the US national standard set value for a good diet. The HEI and healthy eating are modifiable factors for healthy living in relation to dietary parameters and cancer prevention, and they can be used for personalized nutrition in the precision-based healthcare era.

Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team.

PubMed

Harrison, David A; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B; Gwinnutt, Carl; Nolan, Jerry P; Rowan, Kathryn M

2014-08-01

The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Risk models for two outcomes-return of spontaneous circulation (ROSC) for greater than 20min and survival to hospital discharge-were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC>20min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC>20min (c index 0.81 versus 0.72). Validated risk models for ROSC>20min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team☆

PubMed Central

Harrison, David A.; Patel, Krishna; Nixon, Edel; Soar, Jasmeet; Smith, Gary B.; Gwinnutt, Carl; Nolan, Jerry P.; Rowan, Kathryn M.

2014-01-01

Aim The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Methods Risk models for two outcomes—return of spontaneous circulation (ROSC) for greater than 20 min and survival to hospital discharge—were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. Results 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC > 20 min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC > 20 min (c index 0.81 versus 0.72). Conclusions Validated risk models for ROSC > 20 min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement. PMID:24830872

Summary of Data from the First AIAA CFD Drag Prediction Workshop

NASA Technical Reports Server (NTRS)

Levy, David W.; Zickuhr, Tom; Vassberg, John; Agrawal, Shreekant; Wahls, Richard A.; Pirzadeh, Shahyar; Hemsch, Michael J.

2002-01-01

The results from the first AIAA CFD Drag Prediction Workshop are summarized. The workshop was designed specifically to assess the state-of-the-art of computational fluid dynamics methods for force and moment prediction. An impartial forum was provided to evaluate the effectiveness of existing computer codes and modeling techniques, and to identify areas needing additional research and development. The subject of the study was the DLR-F4 wing-body configuration, which is representative of transport aircraft designed for transonic flight. Specific test cases were required so that valid comparisons could be made. Optional test cases included constant-C(sub L) drag-rise predictions typically used in airplane design by industry. Results are compared to experimental data from three wind tunnel tests. A total of 18 international participants using 14 different codes submitted data to the workshop. No particular grid type or turbulence model was more accurate, when compared to each other, or to wind tunnel data. Most of the results overpredicted C(sub Lo) and C(sub Do), but induced drag (dC(sub D)/dC(sub L)(exp 2)) agreed fairly well. Drag rise at high Mach number was underpredicted, however, especially at high C(sub L). On average, the drag data were fairly accurate, but the scatter was greater than desired. The results show that well-validated Reynolds-Averaged Navier-Stokes CFD methods are sufficiently accurate to make design decisions based on predicted drag.

Nuclear Energy Knowledge and Validation Center (NEKVaC) Needs Workshop Summary Report

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

Gougar, Hans

2015-02-01

The Department of Energy (DOE) has made significant progress developing simulation tools to predict the behavior of nuclear systems with greater accuracy and of increasing our capability to predict the behavior of these systems outside of the standard range of applications. These analytical tools require a more complex array of validation tests to accurately simulate the physics and multiple length and time scales. Results from modern simulations will allow experiment designers to narrow the range of conditions needed to bound system behavior and to optimize the deployment of instrumentation to limit the breadth and cost of the campaign. Modern validation,more » verification and uncertainty quantification (VVUQ) techniques enable analysts to extract information from experiments in a systematic manner and provide the users with a quantified uncertainty estimate. Unfortunately, the capability to perform experiments that would enable taking full advantage of the formalisms of these modern codes has progressed relatively little (with some notable exceptions in fuels and thermal-hydraulics); the majority of the experimental data available today is the "historic" data accumulated over the last decades of nuclear systems R&D. A validated code-model is a tool for users. An unvalidated code-model is useful for code developers to gain understanding, publish research results, attract funding, etc. As nuclear analysis codes have become more sophisticated, so have the measurement and validation methods and the challenges that confront them. A successful yet cost-effective validation effort requires expertise possessed only by a few, resources possessed only by the well-capitalized (or a willing collective), and a clear, well-defined objective (validating a code that is developed to satisfy the need(s) of an actual user). To that end, the Idaho National Laboratory established the Nuclear Energy Knowledge and Validation Center to address the challenges of modern code validation and to manage the knowledge from past, current, and future experimental campaigns. By pulling together the best minds involved in code development, experiment design, and validation to establish and disseminate best practices and new techniques, the Nuclear Energy Knowledge and Validation Center (NEKVaC or the ‘Center’) will be a resource for industry, DOE Programs, and academia validation efforts.« less

Enhancing Flood Prediction Reliability Using Bayesian Model Averaging

NASA Astrophysics Data System (ADS)

Liu, Z.; Merwade, V.

2017-12-01

Uncertainty analysis is an indispensable part of modeling the hydrology and hydrodynamics of non-idealized environmental systems. Compared to reliance on prediction from one model simulation, using on ensemble of predictions that consider uncertainty from different sources is more reliable. In this study, Bayesian model averaging (BMA) is applied to Black River watershed in Arkansas and Missouri by combining multi-model simulations to get reliable deterministic water stage and probabilistic inundation extent predictions. The simulation ensemble is generated from 81 LISFLOOD-FP subgrid model configurations that include uncertainty from channel shape, channel width, channel roughness and discharge. Model simulation outputs are trained with observed water stage data during one flood event, and BMA prediction ability is validated for another flood event. Results from this study indicate that BMA does not always outperform all members in the ensemble, but it provides relatively robust deterministic flood stage predictions across the basin. Station based BMA (BMA_S) water stage prediction has better performance than global based BMA (BMA_G) prediction which is superior to the ensemble mean prediction. Additionally, high-frequency flood inundation extent (probability greater than 60%) in BMA_G probabilistic map is more accurate than the probabilistic flood inundation extent based on equal weights.

Multi-institutional external validation of seminal vesicle invasion nomograms: head-to-head comparison of Gallina nomogram versus 2007 Partin tables.

PubMed

Zorn, Kevin C; Capitanio, Umberto; Jeldres, Claudio; Arjane, Philippe; Perrotte, Paul; Shariat, Shahrokh F; Lee, David I; Shalhav, Arieh L; Zagaja, Gregory P; Shikanov, Sergey A; Gofrit, Ofer N; Thong, Alan E; Albala, David M; Sun, Leon; Karakiewicz, Pierre I

2009-04-01

The Partin tables represent one of the most widely used prostate cancer staging tools for seminal vesicle invasion (SVI) prediction. Recently, Gallina et al. reported a novel staging tool for the prediction of SVI that further incorporated the use of the percentage of positive biopsy cores. We performed an external validation of the Gallina et al. nomogram and the 2007 Partin tables in a large, multi-institutional North American cohort of men treated with robotic-assisted radical prostatectomy. Clinical and pathologic data were prospectively gathered from 2,606 patients treated with robotic-assisted radical prostatectomy at one of four North American robotic referral centers between 2002 and 2007. Discrimination was quantified with the area under the receiver operating characteristics curve. The calibration compared the predicted and observed SVI rates throughout the entire range of predictions. At robotic-assisted radical prostatectomy, SVI was recorded in 4.2% of patients. The discriminant properties of the Gallina et al. nomogram resulted in 81% accuracy compared with 78% for the 2007 Partin tables. The Gallina et al. nomogram overestimated the true rate of SVI. Conversely, the Partin tables underestimated the true rate of SVI. The Gallina et al. nomogram offers greater accuracy (81%) than the 2007 Partin tables (78%). However, both tools are associated with calibration limitations that need to be acknowledged and considered before their implementation into clinical practice.

Predicting the digestible energy of corn determined with growing swine from nutrient composition and cross-species measurements.

PubMed

Smith, B; Hassen, A; Hinds, M; Rice, D; Jones, D; Sauber, T; Iiams, C; Sevenich, D; Allen, R; Owens, F; McNaughton, J; Parsons, C

2015-03-01

The DE values of corn grain for pigs will differ among corn sources. More accurate prediction of DE may improve diet formulation and reduce diet cost. Corn grain sources ( = 83) were assayed with growing swine (20 kg) in DE experiments with total collection of feces, with 3-wk-old broiler chick in nitrogen-corrected apparent ME (AME) trials and with cecectomized adult roosters in nitrogen-corrected true ME (TME) studies. Additional AME data for the corn grain source set was generated based on an existing near-infrared transmittance prediction model (near-infrared transmittance-predicted AME [NIT-AME]). Corn source nutrient composition was determined by wet chemistry methods. These data were then used to 1) test the accuracy of predicting swine DE of individual corn sources based on available literature equations and nutrient composition and 2) develop models for predicting DE of sources from nutrient composition and the cross-species information gathered above (AME, NIT-AME, and TME). The overall measured DE, AME, NIT-AME, and TME values were 4,105 ± 11, 4,006 ± 10, 4,004 ± 10, and 4,086 ± 12 kcal/kg DM, respectively. Prediction models were developed using 80% of the corn grain sources; the remaining 20% was reserved for validation of the developed prediction equation. Literature equations based on nutrient composition proved imprecise for predicting corn DE; the root mean square error of prediction ranged from 105 to 331 kcal/kg, an equivalent of 2.6 to 8.8% error. Yet among the corn composition traits, 4-variable models developed in the current study provided adequate prediction of DE (model ranging from 0.76 to 0.79 and root mean square error [RMSE] of 50 kcal/kg). When prediction equations were tested using the validation set, these models had a 1 to 1.2% error of prediction. Simple linear equations from AME, NIT-AME, or TME provided an accurate prediction of DE for individual sources ( ranged from 0.65 to 0.73 and RMSE ranged from 50 to 61 kcal/kg). Percentage error of prediction based on the validation data set was greater (1.4%) for the TME model than for the NIT-AME or AME models (1 and 1.2%, respectively), indicating that swine DE values could be accurately predicted by using AME or NIT-AME. In conclusion, regression equations developed from broiler measurements or from analyzed nutrient composition proved adequate to reliably predict the DE of commercially available corn hybrids for growing pigs.

Predicting Likelihood of Having Four or More Positive Nodes in Patient With Sentinel Lymph Node-Positive Breast Cancer: A Nomogram Validation Study

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

Unal, Bulent; Gur, Akif Serhat; Beriwal, Sushil

2009-11-15

Purpose: Katz suggested a nomogram for predicting having four or more positive nodes in sentinel lymph node (SLN)-positive breast cancer patients. The findings from this formula might influence adjuvant radiotherapy decisions. Our goal was to validate the accuracy of the Katz nomogram. Methods and Materials: We reviewed the records of 309 patients with breast cancer who had undergone completion axillary lymph node dissection. The factors associated with the likelihood of having four or more positive axillary nodes were evaluated in patients with one to three positive SLNs. The nomogram developed by Katz was applied to our data set. The areamore » under the curve of the corresponding receiver operating characteristics curve was calculated for the nomogram. Results: Of the 309 patients, 80 (25.9%) had four or more positive axillary lymph nodes. On multivariate analysis, the number of positive SLNs (p < .0001), overall metastasis size (p = .019), primary tumor size (p = .0001), and extracapsular extension (p = .01) were significant factors predicting for four or more positive nodes. For patients with <5% probability, 90.3% had fewer than four positive nodes and 9.7% had four or more positive nodes. The negative predictive value was 91.7%, and sensitivity was 80%. The nomogram was accurate and discriminating (area under the curve, .801). Conclusion: The probability of four or more involved nodes is significantly greater in patients who have an increased number of positive SLNs, increased overall metastasis size, increased tumor size, and extracapsular extension. The Katz nomogram was validated in our patients. This nomogram will be helpful to clinicians making adjuvant treatment recommendations to their patients.« less

Diagnosing malignant melanoma in ambulatory care: a systematic review of clinical prediction rules

PubMed Central

Harrington, Emma; Clyne, Barbara; Wesseling, Nieneke; Sandhu, Harkiran; Armstrong, Laura; Bennett, Holly; Fahey, Tom

2017-01-01

Objectives Malignant melanoma has high morbidity and mortality rates. Early diagnosis improves prognosis. Clinical prediction rules (CPRs) can be used to stratify patients with symptoms of suspected malignant melanoma to improve early diagnosis. We conducted a systematic review of CPRs for melanoma diagnosis in ambulatory care. Design Systematic review. Data sources A comprehensive search of PubMed, EMBASE, PROSPERO, CINAHL, the Cochrane Library and SCOPUS was conducted in May 2015, using combinations of keywords and medical subject headings (MeSH) terms. Study selection and data extraction Studies deriving and validating, validating or assessing the impact of a CPR for predicting melanoma diagnosis in ambulatory care were included. Data extraction and methodological quality assessment were guided by the CHARMS checklist. Results From 16 334 studies reviewed, 51 were included, validating the performance of 24 unique CPRs. Three impact analysis studies were identified. Five studies were set in primary care. The most commonly evaluated CPRs were the ABCD, more than one or uneven distribution of Colour, or a large (greater than 6 mm) Diameter (ABCD) dermoscopy rule (at a cut-point of >4.75; 8 studies; pooled sensitivity 0.85, 95% CI 0.73 to 0.93, specificity 0.72, 95% CI 0.65 to 0.78) and the 7-point dermoscopy checklist (at a cut-point of ≥1 recommending ruling in melanoma; 11 studies; pooled sensitivity 0.77, 95% CI 0.61 to 0.88, specificity 0.80, 95% CI 0.59 to 0.92). The methodological quality of studies varied. Conclusions At their recommended cut-points, the ABCD dermoscopy rule is more useful for ruling out melanoma than the 7-point dermoscopy checklist. A focus on impact analysis will help translate melanoma risk prediction rules into useful tools for clinical practice. PMID:28264830

Validity of administrative database code algorithms to identify vascular access placement, surgical revisions, and secondary patency.

PubMed

Al-Jaishi, Ahmed A; Moist, Louise M; Oliver, Matthew J; Nash, Danielle M; Fleet, Jamie L; Garg, Amit X; Lok, Charmaine E

2018-03-01

We assessed the validity of physician billing codes and hospital admission using International Classification of Diseases 10th revision codes to identify vascular access placement, secondary patency, and surgical revisions in administrative data. We included adults (≥18 years) with a vascular access placed between 1 April 2004 and 31 March 2013 at the University Health Network, Toronto. Our reference standard was a prospective vascular access database (VASPRO) that contains information on vascular access type and dates of placement, dates for failure, and any revisions. We used VASPRO to assess the validity of different administrative coding algorithms by calculating the sensitivity, specificity, and positive predictive values of vascular access events. The sensitivity (95% confidence interval) of the best performing algorithm to identify arteriovenous access placement was 86% (83%, 89%) and specificity was 92% (89%, 93%). The corresponding numbers to identify catheter insertion were 84% (82%, 86%) and 84% (80%, 87%), respectively. The sensitivity of the best performing coding algorithm to identify arteriovenous access surgical revisions was 81% (67%, 90%) and specificity was 89% (87%, 90%). The algorithm capturing arteriovenous access placement and catheter insertion had a positive predictive value greater than 90% and arteriovenous access surgical revisions had a positive predictive value of 20%. The duration of arteriovenous access secondary patency was on average 578 (553, 603) days in VASPRO and 555 (530, 580) days in administrative databases. Administrative data algorithms have fair to good operating characteristics to identify vascular access placement and arteriovenous access secondary patency. Low positive predictive values for surgical revisions algorithm suggest that administrative data should only be used to rule out the occurrence of an event.

[Prognostic estimation in critical patients. Validation of a new and very simple system of prognostic estimation of survival in an intensive care unit].

PubMed

Abizanda, R; Padron, A; Vidal, B; Mas, S; Belenguer, A; Madero, J; Heras, A

2006-04-01

To make the validation of a new system of prognostic estimation of survival in critical patients (EPEC) seen in a multidisciplinar Intensive care unit (ICU). Prospective analysis of a patient cohort seen in the ICU of a multidisciplinar Intensive Medicine Service of a reference teaching hospital with 19 beds. Four hundred eighty four patients admitted consecutively over 6 months in 2003. Data collection of a basic minimum data set that includes patient identification data (gender, age), reason for admission and their origin, prognostic estimation of survival by EPEC, MPM II 0 and SAPS II (the latter two considered as gold standard). Mortality was evaluated on hospital discharge. EPEC validation was done with analysis of its discriminating capacity (ROC curve), calibration of its prognostic capacity (Hosmer Lemeshow C test), resolution of the 2 x 2 Contingency tables around different probability values (20, 50, 70 and mean value of prognostic estimation). The standardized mortality rate (SMR) for each one of the methods was calculated. Linear regression of the EPEC regarding the MPM II 0 and SAPS II was established and concordance analyses were done (Bland-Altman test) of the prediction of mortality by the three systems. In spite of an apparently good linear correlation, similar accuracy of prediction and discrimination capacity, EPEC is not well-calibrated (no likelihood of death greater than 50%) and the concordance analyses show that more than 10% of the pairs were outside the 95% confidence interval. In spite of its ease of application and calculation and of incorporating delay of admission in ICU as a variable, EPEC does not offer any predictive advantage on MPM II 0 or SAPS II, and its predictions adapt to reality worse.

Comparison of energy expenditure in adolescents when playing new generation and sedentary computer games: cross sectional study

PubMed Central

2007-01-01

Objective To compare the energy expenditure of adolescents when playing sedentary and new generation active computer games. Design Cross sectional comparison of four computer games. Setting Research laboratories. Participants Six boys and five girls aged 13-15 years. Procedure Participants were fitted with a monitoring device validated to predict energy expenditure. They played four computer games for 15 minutes each. One of the games was sedentary (XBOX 360) and the other three were active (Wii Sports). Main outcome measure Predicted energy expenditure, compared using repeated measures analysis of variance. Results Mean (standard deviation) predicted energy expenditure when playing Wii Sports bowling (190.6 (22.2) kJ/kg/min), tennis (202.5 (31.5) kJ/kg/min), and boxing (198.1 (33.9) kJ/kg/min) was significantly greater than when playing sedentary games (125.5 (13.7) kJ/kg/min) (P<0.001). Predicted energy expenditure was at least 65.1 (95% confidence interval 47.3 to 82.9) kJ/kg/min greater when playing active rather than sedentary games. Conclusions Playing new generation active computer games uses significantly more energy than playing sedentary computer games but not as much energy as playing the sport itself. The energy used when playing active Wii Sports games was not of high enough intensity to contribute towards the recommended daily amount of exercise in children. PMID:18156227

Comparison of energy expenditure in adolescents when playing new generation and sedentary computer games: cross sectional study.

PubMed

Graves, Lee; Stratton, Gareth; Ridgers, N D; Cable, N T

2007-12-22

To compare the energy expenditure of adolescents when playing sedentary and new generation active computer games. Cross sectional comparison of four computer games. Research laboratories. Six boys and five girls aged 13-15 years. Procedure Participants were fitted with a monitoring device validated to predict energy expenditure. They played four computer games for 15 minutes each. One of the games was sedentary (XBOX 360) and the other three were active (Wii Sports). Predicted energy expenditure, compared using repeated measures analysis of variance. Mean (standard deviation) predicted energy expenditure when playing Wii Sports bowling (190.6 (22.2) kJ/kg/min), tennis (202.5 (31.5) kJ/kg/min), and boxing (198.1 (33.9) kJ/kg/min) was significantly greater than when playing sedentary games (125.5 (13.7) kJ/kg/min) (P<0.001). Predicted energy expenditure was at least 65.1 (95% confidence interval 47.3 to 82.9) kJ/kg/min greater when playing active rather than sedentary games. Playing new generation active computer games uses significantly more energy than playing sedentary computer games but not as much energy as playing the sport itself. The energy used when playing active Wii Sports games was not of high enough intensity to contribute towards the recommended daily amount of exercise in children.

Organs-on-chips at the frontiers of drug discovery

PubMed Central

Esch, Eric W.; Bahinski, Anthony; Huh, Dongeun

2016-01-01

Improving the effectiveness of preclinical predictions of human drug responses is critical to reducing costly failures in clinical trials. Recent advances in cell biology, microfabrication and microfluidics have enabled the development of microengineered models of the functional units of human organs — known as organs-on-chips — that could provide the basis for preclinical assays with greater predictive power. Here, we examine the new opportunities for the application of organ-on-chip technologies in a range of areas in preclinical drug discovery, such as target identification and validation, target-based screening, and phenotypic screening. We also discuss emerging drug discovery opportunities enabled by organs-on-chips, as well as important challenges in realizing the full potential of this technology. PMID:25792263

A novel computer algorithm improves antibody epitope prediction using affinity-selected mimotopes: a case study using monoclonal antibodies against the West Nile virus E protein.

PubMed

Denisova, Galina F; Denisov, Dimitri A; Yeung, Jeffrey; Loeb, Mark B; Diamond, Michael S; Bramson, Jonathan L

2008-11-01

Understanding antibody function is often enhanced by knowledge of the specific binding epitope. Here, we describe a computer algorithm that permits epitope prediction based on a collection of random peptide epitopes (mimotopes) isolated by antibody affinity purification. We applied this methodology to the prediction of epitopes for five monoclonal antibodies against the West Nile virus (WNV) E protein, two of which exhibit therapeutic activity in vivo. This strategy was validated by comparison of our results with existing F(ab)-E protein crystal structures and mutational analysis by yeast surface display. We demonstrate that by combining the results of the mimotope method with our data from mutational analysis, epitopes could be predicted with greater certainty. The two methods displayed great complementarity as the mutational analysis facilitated epitope prediction when the results with the mimotope method were equivocal and the mimotope method revealed a broader number of residues within the epitope than the mutational analysis. Our results demonstrate that the combination of these two prediction strategies provides a robust platform for epitope characterization.

Early prediction of lung cancer recurrence after stereotactic radiotherapy using second order texture statistics

NASA Astrophysics Data System (ADS)

Mattonen, Sarah A.; Palma, David A.; Haasbeek, Cornelis J. A.; Senan, Suresh; Ward, Aaron D.

2014-03-01

Benign radiation-induced lung injury is a common finding following stereotactic ablative radiotherapy (SABR) for lung cancer, and is often difficult to differentiate from a recurring tumour due to the ablative doses and highly conformal treatment with SABR. Current approaches to treatment response assessment have shown limited ability to predict recurrence within 6 months of treatment. The purpose of our study was to evaluate the accuracy of second order texture statistics for prediction of eventual recurrence based on computed tomography (CT) images acquired within 6 months of treatment, and compare with the performance of first order appearance and lesion size measures. Consolidative and ground-glass opacity (GGO) regions were manually delineated on post-SABR CT images. Automatic consolidation expansion was also investigated to act as a surrogate for GGO position. The top features for prediction of recurrence were all texture features within the GGO and included energy, entropy, correlation, inertia, and first order texture (standard deviation of density). These predicted recurrence with 2-fold cross validation (CV) accuracies of 70-77% at 2- 5 months post-SABR, with energy, entropy, and first order texture having leave-one-out CV accuracies greater than 80%. Our results also suggest that automatic expansion of the consolidation region could eliminate the need for manual delineation, and produced reproducible results when compared to manually delineated GGO. If validated on a larger data set, this could lead to a clinically useful computer-aided diagnosis system for prediction of recurrence within 6 months of SABR and allow for early salvage therapy for patients with recurrence.

Factors associated with elevated plateau pressure in patients with acute lung injury receiving lower tidal volume ventilation.

PubMed

Prescott, Hallie C; Brower, Roy G; Cooke, Colin R; Phillips, Gary; O'Brien, James M

2013-03-01

Lung-protective ventilation with lower tidal volume and lower plateau pressure improves mortality in patients with acute lung injury and acute respiratory distress syndrome. We sought to determine the incidence of elevated plateau pressure in acute lung injury /acute respiratory distress syndrome patients receiving lower tidal volume ventilation and to determine the factors that predict elevated plateau pressure in these patients. We used data from 1398 participants in Acute Respiratory Distress Syndrome Network trials, who received lower tidal volume ventilation (≤ 6.5mL/kg predicted body weight). We considered patients with a plateau pressure greater than 30cm H2O and/or a tidal volume less than 5.5mL/kg predicted body weight on study day 1 to have "elevated plateau pressure." We used logistic regression to identify baseline clinical variables associated with elevated plateau pressure and to develop a model to predict elevated plateau pressure using a subset of 1,188 patients. We validated the model in the 210 patients not used for model development. Medical centers participating in Acute Respiratory Distress Syndrome Network clinical trials. None. Of the 1,398 patients in our study, 288 (20.6%) had elevated plateau pressure on day 1. Severity of illness indices and demographic factors (younger age, greater body mass index, and non-white race) were independently associated with elevated plateau pressure. The multivariable logistic regression model for predicting elevated plateau pressure had an area under the receiving operator characteristic curve of 0.71 for both the developmental and the validation subsets. acute lung injury patients receiving lower tidal volume ventilation often have a plateau pressure that exceeds Acute Respiratory Distress Syndrome Network goals. Race, body mass index, and severity of lung injury are each independently associated with elevated plateau pressure. Selecting a smaller initial tidal volume for non-white patients and patients with higher severity of illness may decrease the incidence of elevated plateau pressure. Prospective studies are needed to evaluate this approach.

An investigation of new toxicity test method performance in validation studies: 1. Toxicity test methods that have predictive capacity no greater than chance.

PubMed

Bruner, L H; Carr, G J; Harbell, J W; Curren, R D

2002-06-01

An approach commonly used to measure new toxicity test method (NTM) performance in validation studies is to divide toxicity results into positive and negative classifications, and the identify true positive (TP), true negative (TN), false positive (FP) and false negative (FN) results. After this step is completed, the contingent probability statistics (CPS), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) are calculated. Although these statistics are widely used and often the only statistics used to assess the performance of toxicity test methods, there is little specific guidance in the validation literature on what values for these statistics indicate adequate performance. The purpose of this study was to begin developing data-based answers to this question by characterizing the CPS obtained from an NTM whose data have a completely random association with a reference test method (RTM). Determining the CPS of this worst-case scenario is useful because it provides a lower baseline from which the performance of an NTM can be judged in future validation studies. It also provides an indication of relationships in the CPS that help identify random or near-random relationships in the data. The results from this study of randomly associated tests show that the values obtained for the statistics vary significantly depending on the cut-offs chosen, that high values can be obtained for individual statistics, and that the different measures cannot be considered independently when evaluating the performance of an NTM. When the association between results of an NTM and RTM is random the sum of the complementary pairs of statistics (sensitivity + specificity, NPV + PPV) is approximately 1, and the prevalence (i.e., the proportion of toxic chemicals in the population of chemicals) and PPV are equal. Given that combinations of high sensitivity-low specificity or low specificity-high sensitivity (i.e., the sum of the sensitivity and specificity equal to approximately 1) indicate lack of predictive capacity, an NTM having these performance characteristics should be considered no better for predicting toxicity than by chance alone.

Prediction of severe thunderstorms over Sriharikota Island by using the WRF-ARW operational model

NASA Astrophysics Data System (ADS)

Papa Rao, G.; Rajasekhar, M.; Pushpa Saroja, R.; Sreeshna, T.; Rajeevan, M.; Ramakrishna, S. S. V. S.

2016-05-01

Operational short range prediction of Meso-scale thunderstorms for Sriharikota(13.7°N ,80.18°E) has been performed using two nested domains 27 & 9Km configuration of Weather Research & Forecasting-Advanced Research Weather Model (WRF- ARW V3.4).Thunderstorm is a Mesoscale system with spatial scale of few kilometers to a couple of 100 kilometers and time scale of less than an one hour to several hours, which produces heavy rain, lightning, thunder, surface wind squalls and down-bursts. Numerical study of Thunderstorms at Sriharikota and its neighborhood have been discussed with its antecedent thermodynamic stability indices and Parameters that are usually favorable for the development of convective instability based on WRF ARW model predictions. Instability is a prerequisite for the occurrence of severe weather, the greater the instability, the greater will be the potential of thunderstorm. In the present study, K Index, Total totals Index (TTI), Convective Available Potential Energy (CAPE), Convective Inhibition Energy (CINE), Lifted Index (LI), Precipitable Water (PW), etc. are the instability indices used for the short range prediction of thunderstorms. In this study we have made an attempt to estimate the skill of WRF ARW predictability and diagnosed three thunderstorms that occurred during the late evening to late night of 31st July, 20th September and 2nd October of 2015 over Sriharikota Island which are validated with Local Electric Field Mill (EFM), rainfall observations and Chennai Doppler Weather Radar products. The model predicted thermodynamic indices (CAPE, CINE, K Index, LI, TTI and PW) over Sriharikota which act as good indicators for severe thunderstorm activity.

A posteriori model validation for the temporal order of directed functional connectivity maps

PubMed Central

Beltz, Adriene M.; Molenaar, Peter C. M.

2015-01-01

A posteriori model validation for the temporal order of neural directed functional connectivity maps is rare. This is striking because models that require sequential independence among residuals are regularly implemented. The aim of the current study was (a) to apply to directed functional connectivity maps of functional magnetic resonance imaging data an a posteriori model validation procedure (i.e., white noise tests of one-step-ahead prediction errors combined with decision criteria for revising the maps based upon Lagrange Multiplier tests), and (b) to demonstrate how the procedure applies to single-subject simulated, single-subject task-related, and multi-subject resting state data. Directed functional connectivity was determined by the unified structural equation model family of approaches in order to map contemporaneous and first order lagged connections among brain regions at the group- and individual-levels while incorporating external input, then white noise tests were run. Findings revealed that the validation procedure successfully detected unmodeled sequential dependencies among residuals and recovered higher order (greater than one) simulated connections, and that the procedure can accommodate task-related input. Findings also revealed that lags greater than one were present in resting state data: With a group-level network that contained only contemporaneous and first order connections, 44% of subjects required second order, individual-level connections in order to obtain maps with white noise residuals. Results have broad methodological relevance (e.g., temporal validation is necessary after directed functional connectivity analyses because the presence of unmodeled higher order sequential dependencies may bias parameter estimates) and substantive implications (e.g., higher order lags may be common in resting state data). PMID:26379489

Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

NASA Technical Reports Server (NTRS)

Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell

2011-01-01

Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.

Time to first cigarette in the morning as an index of ability to quit smoking: Implications for nicotine dependence

PubMed Central

Baker, Timothy B.; Piper, Megan E.; McCarthy, Danielle E.; Bolt, Daniel M.; Smith, Stevens S.; Kim, Su-Young; Colby, Suzanne; Conti, David; Giovino, Gary A.; Hatsukami, Dorothy; Hyland, Andrew; Krishnan-Sarin, Suchitra; Niaura, Raymond; Perkins, Kenneth A.; Toll, Benjamin A.

2010-01-01

An inability to maintain abstinence is a key indicator of tobacco dependence. Unfortunately, little evidence exists regarding the ability of the major tobacco dependence measures to predict smoking cessation outcome. This paper used data from four placebo-controlled smoking cessation trials and one international epidemiologic study to determine relations between the Fagerström Test for Nicotine Dependence (FTND; Heatherton et al., 1991), the Heaviness of Smoking Index (HSI; Kozlowski et al., 1994), the Nicotine Dependence Syndrome Scale (NDSS; Shiffman et al., 2004) and the Wisconsin Inventory of Smoking Dependence Motives (WISDM; Piper et al. 2004) with cessation success. Results showed that much of the predictive validity of the FTND could be attributed to its first item, time to first cigarette in the morning, and this item had greater validity than any other single measure. Thus, the time to first cigarette item appears to tap a pattern of heavy, uninterrupted, and automatic smoking and may be a good single-item measure of nicotine dependence. PMID:18067032

The effects of distinctiveness on memory and metamemory for face-name associations.

PubMed

Watier, Nicholas; Collin, Charles

2012-01-01

We examined the influence of face and name distinctiveness on memory and metamemory for face-name associations. Four types of monitoring judgements were solicited during encoding and retrieval of face-name pairs that contained distinct or typical faces (Experiment 1) or names (Experiment 2). The beneficial effects of distinctiveness on associative memory were symmetrical between faces and names, such that relative to their typical counterparts, distinct faces enhanced memory for names, and distinct names enhanced memory for faces. These effects were also apparent in metamemory. Estimates of prospective and retrospective memory performance were greater for face-name associations that contained a distinct face or name compared with a typical face or name, regardless of whether the distinct item was a cue or target. Moreover, the predictive validity of prospective monitoring improved with name distinctiveness, whereas the predictive validity of retrospective monitoring improved with facial distinctiveness. Our results indicate that distinctiveness affects not only the strength of the association between a face and a name, but also the ability to monitor that association.

The use of neuropsychological tests to assess intelligence.

PubMed

Gansler, David A; Varvaris, Mark; Schretlen, David J

We sought to derive a 'neuropsychological intelligence quotient' (NIQ) to replace IQ testing in some routine assessments. We administered neuropsychological testing and a seven-subtest short form of the Wechsler Adult Intelligence Scale to a community sample of 394 adults aged 18-96 years. We regressed Wechsler Full Scale IQs (W-FSIQ) on 23 neuropsychological scores and derived an NIQ from 9 measures that explained significant variance in W-FSIQ. We then compared subgroups of 284 healthy and 108 unhealthy participants in NIQ and W-FSIQ to assess criterion validity, correlated NIQ and W-FSIQ scores with education level and independence for activities of daily living to assess convergent validity, and compared validity coefficients for the NIQ with those of 'hold' and 'no-hold' indices. By design, NIQ and W-FSIQ scores correlated highly (r = .84), and both were higher in healthy participants. The difference was larger for NIQ, which accounted for more variability in activities of daily living. The NIQ and 'no-hold' index were better predicted by health status and less predicted by educational status than the 'hold' index. We constructed an NIQ that correlates highly with Wechsler FSIQ. Tests required to obtain NIQ are commonly used and can be administered in about 45 min. Validity properties of NIQ and W-FSIQ are similar. The NIQ bore greater resemblance to a 'no-hold' than 'hold' index. One can obtain a reasonably accurate estimate of current Full Scale IQ without formal intelligence testing from a brief neuropsychological battery.

Derivation and validation of a composite index of severity in chronic obstructive pulmonary disease: the DOSE Index.

PubMed

Jones, Rupert C; Donaldson, Gavin C; Chavannes, Niels H; Kida, Kozui; Dickson-Spillmann, Maria; Harding, Samantha; Wedzicha, Jadwiga A; Price, David; Hyland, Michael E

2009-12-15

Chronic obstructive pulmonary disease (COPD) is increasingly recognized as a multicomponent disease with systemic consequences and effects on quality of life. Single measures such as lung function provide a limited reflection of how the disease affects patients. Composite measures have the potential to account for many of the facets of COPD. To derive and validate a multicomponent assessment tool of COPD severity that is applicable to all patients and health care settings. The index was derived using data from 375 patients with COPD in primary care. Regression analysis led to a model explaining 48% of the variance in health status as measured by the Clinical COPD Questionnaire with four components: dyspnea (D), airflow obstruction (O), smoking status (S), and exacerbation frequency (E). The DOSE Index was validated in cross-sectional and longitudinal samples in various health care settings in Holland, Japan, and the United Kingdom. The DOSE Index correlated with health status in all data sets. A high DOSE Index score (> or = 4) was associated with a greater risk of hospital admission (odds ratio, 8.3 [4.1-17]) or respiratory failure (odds ratio, 7.8 [3.4-18.3]). The index predicted exacerbations in the subsequent year (P < or = 0.014). The DOSE Index is a simple, valid tool for assessing the severity of COPD. The index is related to a range of clinically important outcomes such as health care consumption and predicts future events.

Blood eosinophil count thresholds and exacerbations in patients with chronic obstructive pulmonary disease.

PubMed

Yun, Jeong H; Lamb, Andrew; Chase, Robert; Singh, Dave; Parker, Margaret M; Saferali, Aabida; Vestbo, Jørgen; Tal-Singer, Ruth; Castaldi, Peter J; Silverman, Edwin K; Hersh, Craig P

2018-06-01

Eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) is associated with exacerbations and responsivity to steroids, suggesting potential shared mechanisms with eosinophilic asthma. However, there is no consistent blood eosinophil count that has been used to define the increased exacerbation risk. We sought to investigate blood eosinophil counts associated with exacerbation risk in patients with COPD. Blood eosinophil counts and exacerbation risk were analyzed in patients with moderate-to-severe COPD by using 2 independent studies of former and current smokers with longitudinal data. The Genetic Epidemiology of COPD (COPDGene) study was analyzed for discovery (n = 1,553), and the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study was analyzed for validation (n = 1,895). A subset of the ECLIPSE study subjects were used to assess the stability of blood eosinophil counts over time. COPD exacerbation risk increased with higher eosinophil counts. An eosinophil count threshold of 300 cells/μL or greater showed adjusted incidence rate ratios for exacerbations of 1.32 in the COPDGene study (95% CI, 1.10-1.63). The cutoff of 300 cells/μL or greater was validated for prospective risk of exacerbation in the ECLIPSE study, with adjusted incidence rate ratios of 1.22 (95% CI, 1.06-1.41) using 3-year follow-up data. Stratified analysis confirmed that the increased exacerbation risk associated with an eosinophil count of 300 cells/μL or greater was driven by subjects with a history of frequent exacerbations in both the COPDGene and ECLIPSE studies. Patients with moderate-to-severe COPD and blood eosinophil counts of 300 cells/μL or greater had an increased risk exacerbations in the COPDGene study, which was prospectively validated in the ECLIPSE study. Copyright © 2018 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

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

Can the prognosis of individual patients with glioblastoma be predicted using an online calculator?

PubMed Central

Parks, Christopher; Heald, James; Hall, Gregory; Kamaly-Asl, Ian

2013-01-01

Background In an exploratory subanalysis of the European Organisation for Research and Treatment of Cancer and National Cancer Institute of Canada (EORTC/NCIC) trial data, Gorlia et al. identified a variety of factors that were predictive of overall survival, including therapy administered, age, extent of surgery, mini-mental score, administration of corticosteroids, World Health Organization (WHO) performance status, and O-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. Gorlia et al. developed 3 nomograms, each intended to predict the survival times of patients with newly diagnosed glioblastoma on the basis of individual-specific combinations of prognostic factors. These are available online as a “GBM Calculator” and are intended for use in patient counseling. This study is an external validation of this calculator. Method One hundred eighty-seven patients from 2 UK neurosurgical units who had histologically confirmed glioblastoma (WHO grade IV) had their information at diagnosis entered into the GBM calculator. A record was made of the actual and predicted median survival time for each patient. Statistical analysis was performed to assess the accuracy, precision, correlation, and discrimination of the calculator. Results The calculator gives both inaccurate and imprecise predictions. Only 23% of predictions were within 25% of the actual survival, and the percentage bias is 140% in our series. The coefficient of variance is 76%, where a smaller percentage would indicate greater precision. There is only a weak positive correlation between the predicted and actual survival among patients (R2 of 0.07). Discrimination is inadequate as measured by a C-index of 0.62. Conclusions The authors would not recommend the use of this tool in patient counseling. If departments were considering its use, we would advise that a similar validating exercise be undertaken. PMID:23543729

Development of clinical decision rules to predict recurrent shock in dengue

PubMed Central

2013-01-01

Introduction Mortality from dengue infection is mostly due to shock. Among dengue patients with shock, approximately 30% have recurrent shock that requires a treatment change. Here, we report development of a clinical rule for use during a patient’s first shock episode to predict a recurrent shock episode. Methods The study was conducted in Center for Preventive Medicine in Vinh Long province and the Children’s Hospital No. 2 in Ho Chi Minh City, Vietnam. We included 444 dengue patients with shock, 126 of whom had recurrent shock (28%). Univariate and multivariate analyses and a preprocessing method were used to evaluate and select 14 clinical and laboratory signs recorded at shock onset. Five variables (admission day, purpura/ecchymosis, ascites/pleural effusion, blood platelet count and pulse pressure) were finally trained and validated by a 10-fold validation strategy with 10 times of repetition, using a logistic regression model. Results The results showed that shorter admission day (fewer days prior to admission), purpura/ecchymosis, ascites/pleural effusion, low platelet count and narrow pulse pressure were independently associated with recurrent shock. Our logistic prediction model was capable of predicting recurrent shock when compared to the null method (P < 0.05) and was not outperformed by other prediction models. Our final scoring rule provided relatively good accuracy (AUC, 0.73; sensitivity and specificity, 68%). Score points derived from the logistic prediction model revealed identical accuracy with AUCs at 0.73. Using a cutoff value greater than −154.5, our simple scoring rule showed a sensitivity of 68.3% and a specificity of 68.2%. Conclusions Our simple clinical rule is not to replace clinical judgment, but to help clinicians predict recurrent shock during a patient’s first dengue shock episode. PMID:24295509

Using High-Resolution Satellite Aerosol Optical Depth To Estimate Daily PM2.5 Geographical Distribution in Mexico City.

PubMed

Just, Allan C; Wright, Robert O; Schwartz, Joel; Coull, Brent A; Baccarelli, Andrea A; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-07-21

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most U.S. and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004-2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross-validation R(2) of 0.724. Cross-validated root-mean-squared prediction error (RMSPE) of the model was 5.55 μg/m(3). This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City.

Using high-resolution satellite aerosol optical depth to estimate daily PM2.5 geographical distribution in Mexico City

PubMed Central

Just, Allan C.; Wright, Robert O.; Schwartz, Joel; Coull, Brent A.; Baccarelli, Andrea A.; Tellez-Rojo, Martha María; Moody, Emily; Wang, Yujie; Lyapustin, Alexei; Kloog, Itai

2015-01-01

Recent advances in estimating fine particle (PM2.5) ambient concentrations use daily satellite measurements of aerosol optical depth (AOD) for spatially and temporally resolved exposure estimates. Mexico City is a dense megacity that differs from other previously modeled regions in several ways: it has bright land surfaces, a distinctive climatological cycle, and an elevated semi-enclosed air basin with a unique planetary boundary layer dynamic. We extend our previous satellite methodology to the Mexico City area, a region with higher PM2.5 than most US and European urban areas. Using a novel 1 km resolution AOD product from the MODIS instrument, we constructed daily predictions across the greater Mexico City area for 2004–2014. We calibrated the association of AOD to PM2.5 daily using municipal ground monitors, land use, and meteorological features. Predictions used spatial and temporal smoothing to estimate AOD when satellite data were missing. Our model performed well, resulting in an out-of-sample cross validation R2 of 0.724. Cross-validated root mean squared prediction error (RMSPE) of the model was 5.55 μg/m3. This novel model reconstructs long- and short-term spatially resolved exposure to PM2.5 for epidemiological studies in Mexico City. PMID:26061488

Propagation of a laser beam in a plasma

NASA Technical Reports Server (NTRS)

Chapman, J. M.; Kevorkian, J.; Steinhauer, L. C.; Vagners, J.

1975-01-01

This paper shows that for a nonabsorbing medium with a prescribed index of refraction, the effects of beam stability, line focusing, and beam distortion can be predicted from simple ray optics. When the paraxial approximation is used, diffraction effects are examined for Gaussian, Lorentzian, and square beams. Most importantly, it is shown that for a Gaussian beam, diffraction effects can be included simply by adding imaginary solutions to the paraxial ray equations. Also presented are several procedures to extend the paraxial approximation so that the solution will have a domain of validity of greater extent.

Predicting workplace aggression and violence.

PubMed

Barling, Julian; Dupré, Kathryne E; Kelloway, E Kevin

2009-01-01

Consistent with the relative recency of research on workplace aggression and the considerable media attention given to high-profile incidents, numerous myths about the nature of workplace aggression have emerged. In this review, we examine these myths from an evidence-based perspective, bringing greater clarity to our understanding of the predictors of workplace aggression. We conclude by pointing to the need for more research focusing on construct validity and prevention issues as well as for methodologies that minimize the likelihood of mono-method bias and that strengthen the ability to make causal inferences.

Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study

PubMed Central

Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda

2016-01-01

Background Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules’ performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Methods Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. Results A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2–4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Conclusion Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved. PMID:26730980

Design Characteristics Influence Performance of Clinical Prediction Rules in Validation: A Meta-Epidemiological Study.

PubMed

Ban, Jong-Wook; Emparanza, José Ignacio; Urreta, Iratxe; Burls, Amanda

2016-01-01

Many new clinical prediction rules are derived and validated. But the design and reporting quality of clinical prediction research has been less than optimal. We aimed to assess whether design characteristics of validation studies were associated with the overestimation of clinical prediction rules' performance. We also aimed to evaluate whether validation studies clearly reported important methodological characteristics. Electronic databases were searched for systematic reviews of clinical prediction rule studies published between 2006 and 2010. Data were extracted from the eligible validation studies included in the systematic reviews. A meta-analytic meta-epidemiological approach was used to assess the influence of design characteristics on predictive performance. From each validation study, it was assessed whether 7 design and 7 reporting characteristics were properly described. A total of 287 validation studies of clinical prediction rule were collected from 15 systematic reviews (31 meta-analyses). Validation studies using case-control design produced a summary diagnostic odds ratio (DOR) 2.2 times (95% CI: 1.2-4.3) larger than validation studies using cohort design and unclear design. When differential verification was used, the summary DOR was overestimated by twofold (95% CI: 1.2 -3.1) compared to complete, partial and unclear verification. The summary RDOR of validation studies with inadequate sample size was 1.9 (95% CI: 1.2 -3.1) compared to studies with adequate sample size. Study site, reliability, and clinical prediction rule was adequately described in 10.1%, 9.4%, and 7.0% of validation studies respectively. Validation studies with design shortcomings may overestimate the performance of clinical prediction rules. The quality of reporting among studies validating clinical prediction rules needs to be improved.

Temperament and impulsivity predictors of smoking cessation outcomes.

PubMed

López-Torrecillas, Francisca; Perales, José C; Nieto-Ruiz, Ana; Verdejo-García, Antonio

2014-01-01

Temperament and impulsivity are powerful predictors of addiction treatment outcomes. However, a comprehensive assessment of these features has not been examined in relation to smoking cessation outcomes. Naturalistic prospective study. Treatment-seeking smokers (n = 140) were recruited as they engaged in an occupational health clinic providing smoking cessation treatment between 2009 and 2013. Participants were assessed at baseline with measures of temperament (Temperament and Character Inventory), trait impulsivity (Barratt Impulsivity Scale), and cognitive impulsivity (Go/No Go, Delay Discounting and Iowa Gambling Task). The outcome measure was treatment status, coded as "dropout" versus "relapse" versus "abstinence" at 3, 6, and 12 months endpoints. Participants were telephonically contacted and reminded of follow-up face to face assessments at each endpoint. The participants that failed to answer the phone calls or self-reported discontinuation of treatment and failed to attend the upcoming follow-up session were coded as dropouts. The participants that self-reported continuing treatment, and successfully attended the upcoming follow-up session were coded as either "relapse" or "abstinence", based on the results of smoking behavior self-reports cross-validated with co-oximetry hemoglobin levels. Multinomial regression models were conducted to test whether temperament and impulsivity measures predicted dropout and relapse relative to abstinence outcomes. Higher scores on temperament dimensions of novelty seeking and reward dependence predicted poorer retention across endpoints, whereas only higher scores on persistence predicted greater relapse. Higher scores on the trait dimension of non-planning impulsivity but not performance on cognitive impulsivity predicted poorer retention. Higher non-planning impulsivity and poorer performance in the Iowa Gambling Task predicted greater relapse at 3 and 6 months and 6 months respectively. Temperament measures, and specifically novelty seeking and reward dependence, predict smoking cessation treatment retention, whereas persistence, non-planning impulsivity and poor decision-making predict smoking relapse.

Development of an in Silico Model of DPPH• Free Radical Scavenging Capacity: Prediction of Antioxidant Activity of Coumarin Type Compounds.

PubMed

Goya Jorge, Elizabeth; Rayar, Anita Maria; Barigye, Stephen J; Jorge Rodríguez, María Elisa; Sylla-Iyarreta Veitía, Maité

2016-06-07

A quantitative structure-activity relationship (QSAR) study of the 2,2-diphenyl-l-picrylhydrazyl (DPPH•) radical scavenging ability of 1373 chemical compounds, using DRAGON molecular descriptors (MD) and the neural network technique, a technique based on the multilayer multilayer perceptron (MLP), was developed. The built model demonstrated a satisfactory performance for the training ( R 2 = 0.713 ) and test set ( Q ext 2 = 0.654 ) , respectively. To gain greater insight on the relevance of the MD contained in the MLP model, sensitivity and principal component analyses were performed. Moreover, structural and mechanistic interpretation was carried out to comprehend the relationship of the variables in the model with the modeled property. The constructed MLP model was employed to predict the radical scavenging ability for a group of coumarin-type compounds. Finally, in order to validate the model's predictions, an in vitro assay for one of the compounds (4-hydroxycoumarin) was performed, showing a satisfactory proximity between the experimental and predicted pIC50 values.

Strategies to predict rheumatoid arthritis development in at-risk populations

PubMed Central

van der Helm-van Mil, Annette H.

2016-01-01

The development of RA is conceived as a multiple hit process and the more hits that are acquired, the greater the risk of developing clinically apparent RA. Several at-risk phases have been described, including the presence of genetic and environmental factors, RA-related autoantibodies and biomarkers and symptoms. Intervention in these preclinical phases may be more effective compared with intervention in the clinical phase. One prerequisite for preventive strategies is the ability to estimate an individual’s risk adequately. This review evaluates the ability to predict the risk of RA in the various preclinical stages. Present data suggest that a combination of genetic and environmental factors is helpful to identify persons at high risk of RA among first-degree relatives. Furthermore, a combination of symptoms, antibody characteristics and environmental factors has been shown to be relevant for risk prediction in seropositive arthralgia patients. Large prospective studies are needed to validate and improve risk prediction in preclinical disease stages. PMID:25096602

Prediction of Erectile Function Following Treatment for Prostate Cancer

PubMed Central

Alemozaffar, Mehrdad; Regan, Meredith M.; Cooperberg, Matthew R.; Wei, John T.; Michalski, Jeff M.; Sandler, Howard M.; Hembroff, Larry; Sadetsky, Natalia; Saigal, Christopher S.; Litwin, Mark S.; Klein, Eric; Kibel, Adam S.; Hamstra, Daniel A.; Pisters, Louis L.; Kuban, Deborah A.; Kaplan, Irving D.; Wood, David P.; Ciezki, Jay; Dunn, Rodney L.; Carroll, Peter R.; Sanda, Martin G.

2013-01-01

Context Sexual function is the health-related quality of life (HRQOL) domain most commonly impaired after prostate cancer treatment; however, validated tools to enable personalized prediction of erectile dysfunction after prostate cancer treatment are lacking. Objective To predict long-term erectile function following prostate cancer treatment based on individual patient and treatment characteristics. Design Pretreatment patient characteristics, sexual HRQOL, and treatment details measured in a longitudinal academic multicenter cohort (Prostate Cancer Outcomes and Satisfaction With Treatment Quality Assessment; enrolled from 2003 through 2006), were used to develop models predicting erectile function 2 years after treatment. A community-based cohort (community-based Cancer of the Prostate Strategic Urologic Research Endeavor [CaPSURE]; enrolled 1995 through 2007) externally validated model performance. Patients in US academic and community-based practices whose HRQOL was measured pretreatment (N = 1201) underwent follow-up after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. Sexual outcomes among men completing 2 years’ follow-up (n = 1027) were used to develop models predicting erectile function that were externally validated among 1913 patients in a community-based cohort. Main Outcome Measures Patient-reported functional erections suitable for intercourse 2 years following prostate cancer treatment. Results Two years after prostate cancer treatment, 368 (37% [95% CI, 34%–40%]) of all patients and 335 (48% [95% CI, 45%–52%]) of those with functional erections prior to treatment reported functional erections; 531 (53% [95% CI, 50%–56%]) of patients without penile prostheses reported use of medications or other devices for erectile dysfunction. Pretreatment sexual HRQOL score, age, serum prostate-specific antigen level, race/ethnicity, body mass index, and intended treatment details were associated with functional erections 2 years after treatment. Multivariable logistic regression models predicting erectile function estimated 2-year function probabilities from as low as 10% or less to as high as 70% or greater depending on the individual’s pretreatment patient characteristics and treatment details. The models performed well in predicting erections in external validation among CaPSURE cohort patients (areas under the receiver operating characteristic curve, 0.77 [95% CI, 0.74–0.80] for prostatectomy; 0.87 [95% CI, 0.80–0.94] for external radiotherapy; and 0.90 [95% CI, 0.85–0.95] for brachytherapy). Conclusion Stratification by pretreatment patient characteristics and treatment details enables prediction of erectile function 2 years after prostatectomy, external radiotherapy, or brachytherapy for prostate cancer. PMID:21934053

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation.

PubMed

Saatchi, Mahdi; McClure, Mathew C; McKay, Stephanie D; Rolf, Megan M; Kim, JaeWoo; Decker, Jared E; Taxis, Tasia M; Chapple, Richard H; Ramey, Holly R; Northcutt, Sally L; Bauck, Stewart; Woodward, Brent; Dekkers, Jack C M; Fernando, Rohan L; Schnabel, Robert D; Garrick, Dorian J; Taylor, Jeremy F

2011-11-28

Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy.

Accuracies of genomic breeding values in American Angus beef cattle using K-means clustering for cross-validation

PubMed Central

2011-01-01

Background Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but the recurrent inclusion of genotyped sires in retraining analyses will be necessary to routinely produce for the industry the direct genomic values with the highest accuracy. PMID:22122853

Clinical Implications of a Dimensional Approach: The Normal:Abnormal Spectrum of Early Irritability.

PubMed

Wakschlag, Lauren S; Estabrook, Ryne; Petitclerc, Amelie; Henry, David; Burns, James L; Perlman, Susan B; Voss, Joel L; Pine, Daniel S; Leibenluft, Ellen; Briggs-Gowan, Margaret L

2015-08-01

The importance of dimensional approaches is widely recognized, but an empirical base for clinical application is lacking. This is particularly true for irritability, a dimensional phenotype that cuts across many areas of psychopathology and manifests early in life. We examine longitudinal, dimensional patterns of irritability and their clinical import in early childhood. Irritability was assessed longitudinally over an average of 16 months in a clinically enriched, diverse community sample of preschoolers (N = 497; mean = 4.2 years; SD = 0.8). Using the Temper Loss scale of the Multidimensional Assessment Profile of Disruptive Behavior (MAP-DB) as a developmentally sensitive indicator of early childhood irritability, we examined its convergent/divergent, clinical, and incremental predictive validity, and modeled its linear and nonlinear associations with clinical risk. The Temper Loss scale demonstrated convergent and divergent validity to child and maternal factors. In multivariate analyses, Temper Loss predicted mood (separation anxiety disorder [SAD], generalized anxiety disorder [GAD], and depression/dysthymia), disruptive (oppositional defiant disorder [ODD], attention-deficit/hyperactivity disorder [ADHD], and conduct disorder [CD]) symptoms. Preschoolers with even mildly elevated Temper Loss scale scores showed substantially increased risk of symptoms and disorders. For ODD, GAD, SAD, and depression, increases in Temper Loss scale scores at the higher end of the dimension had a greater impact on symptoms relative to increases at the lower end. Temper Loss scale scores also showed incremental validity over DSM-IV disorders in predicting subsequent impairment. Finally, accounting for the substantial heterogeneity in longitudinal patterns of Temper Loss significantly improved prediction of mood and disruptive symptoms. Dimensional, longitudinal characterization of irritability informs clinical prediction. A vital next step will be empirically generating parameters for the incorporation of dimensional information into clinical decision-making with reasonable certainty. Copyright © 2015 American Academy of Child and Adolescent Psychiatry. All rights reserved.

Prediction of psychosis across protocols and risk cohorts using automated language analysis

PubMed Central

Corcoran, Cheryl M.; Carrillo, Facundo; Fernández‐Slezak, Diego; Bedi, Gillinder; Klim, Casimir; Javitt, Daniel C.; Bearden, Carrie E.; Cecchi, Guillermo A.

2018-01-01

Language and speech are the primary source of data for psychiatrists to diagnose and treat mental disorders. In psychosis, the very structure of language can be disturbed, including semantic coherence (e.g., derailment and tangentiality) and syntactic complexity (e.g., concreteness). Subtle disturbances in language are evident in schizophrenia even prior to first psychosis onset, during prodromal stages. Using computer‐based natural language processing analyses, we previously showed that, among English‐speaking clinical (e.g., ultra) high‐risk youths, baseline reduction in semantic coherence (the flow of meaning in speech) and in syntactic complexity could predict subsequent psychosis onset with high accuracy. Herein, we aimed to cross‐validate these automated linguistic analytic methods in a second larger risk cohort, also English‐speaking, and to discriminate speech in psychosis from normal speech. We identified an automated machine‐learning speech classifier – comprising decreased semantic coherence, greater variance in that coherence, and reduced usage of possessive pronouns – that had an 83% accuracy in predicting psychosis onset (intra‐protocol), a cross‐validated accuracy of 79% of psychosis onset prediction in the original risk cohort (cross‐protocol), and a 72% accuracy in discriminating the speech of recent‐onset psychosis patients from that of healthy individuals. The classifier was highly correlated with previously identified manual linguistic predictors. Our findings support the utility and validity of automated natural language processing methods to characterize disturbances in semantics and syntax across stages of psychotic disorder. The next steps will be to apply these methods in larger risk cohorts to further test reproducibility, also in languages other than English, and identify sources of variability. This technology has the potential to improve prediction of psychosis outcome among at‐risk youths and identify linguistic targets for remediation and preventive intervention. More broadly, automated linguistic analysis can be a powerful tool for diagnosis and treatment across neuropsychiatry. PMID:29352548

Prediction of psychosis across protocols and risk cohorts using automated language analysis.

PubMed

Corcoran, Cheryl M; Carrillo, Facundo; Fernández-Slezak, Diego; Bedi, Gillinder; Klim, Casimir; Javitt, Daniel C; Bearden, Carrie E; Cecchi, Guillermo A

2018-02-01

Language and speech are the primary source of data for psychiatrists to diagnose and treat mental disorders. In psychosis, the very structure of language can be disturbed, including semantic coherence (e.g., derailment and tangentiality) and syntactic complexity (e.g., concreteness). Subtle disturbances in language are evident in schizophrenia even prior to first psychosis onset, during prodromal stages. Using computer-based natural language processing analyses, we previously showed that, among English-speaking clinical (e.g., ultra) high-risk youths, baseline reduction in semantic coherence (the flow of meaning in speech) and in syntactic complexity could predict subsequent psychosis onset with high accuracy. Herein, we aimed to cross-validate these automated linguistic analytic methods in a second larger risk cohort, also English-speaking, and to discriminate speech in psychosis from normal speech. We identified an automated machine-learning speech classifier - comprising decreased semantic coherence, greater variance in that coherence, and reduced usage of possessive pronouns - that had an 83% accuracy in predicting psychosis onset (intra-protocol), a cross-validated accuracy of 79% of psychosis onset prediction in the original risk cohort (cross-protocol), and a 72% accuracy in discriminating the speech of recent-onset psychosis patients from that of healthy individuals. The classifier was highly correlated with previously identified manual linguistic predictors. Our findings support the utility and validity of automated natural language processing methods to characterize disturbances in semantics and syntax across stages of psychotic disorder. The next steps will be to apply these methods in larger risk cohorts to further test reproducibility, also in languages other than English, and identify sources of variability. This technology has the potential to improve prediction of psychosis outcome among at-risk youths and identify linguistic targets for remediation and preventive intervention. More broadly, automated linguistic analysis can be a powerful tool for diagnosis and treatment across neuropsychiatry. © 2018 World Psychiatric Association.

Young and restless: validation of the Mind-Wandering Questionnaire (MWQ) reveals disruptive impact of mind-wandering for youth

PubMed Central

Mrazek, Michael D.; Phillips, Dawa T.; Franklin, Michael S.; Broadway, James M.; Schooler, Jonathan W.

2013-01-01

Mind-wandering is the focus of extensive investigation, yet until recently there has been no validated scale to directly measure trait levels of task-unrelated thought. Scales commonly used to assess mind-wandering lack face validity, measuring related constructs such as daydreaming or behavioral errors. Here we report four studies validating a Mind-Wandering Questionnaire (MWQ) across college, high school, and middle school samples. The 5-item scale showed high internal consistency, as well as convergent validity with existing measures of mind-wandering and related constructs. Trait levels of mind-wandering, as measured by the MWQ, were correlated with task-unrelated thought measured by thought sampling during a test of reading comprehension. In both middle school and high school samples, mind-wandering during testing was associated with worse reading comprehension. By contrast, elevated trait levels of mind-wandering predicted worse mood, less life-satisfaction, greater stress, and lower self-esteem. By extending the use of thought sampling to measure mind-wandering among adolescents, our findings also validate the use of this methodology with younger populations. Both the MWQ and thought sampling indicate that mind-wandering is a pervasive—and problematic—influence on the performance and well-being of adolescents. PMID:23986739

Rating long-term care facilities on pressure ulcer development: importance of case-mix adjustment.

PubMed

Berlowitz, D R; Ash, A S; Brandeis, G H; Brand, H K; Halpern, J L; Moskowitz, M A

1996-03-15

To determine the importance of case-mix adjustment in interpreting differences in rates of pressure ulcer development in Department of Veterans Affairs long- term care facilities. A sample assembled from the Patient Assessment File, a Veterans Affairs administrative database, was used to derive predictors of pressure ulcer development; the resulting model was validated in a separate sample. Facility-level rates of pressure ulcer development, both unadjusted and adjusted for case mix using the predictive model, were compared. Department of Veterans Affairs long-term care facilities. The derivation sample consisted of 31 150 intermediate medicine and nursing home residents who were initially free of pressure ulcers and were institutionalized between October 1991 and April 1993. The validation sample consisted of 17 946 residents institutionalized from April 1993 to October 1993. Development of a stage 2 or greater pressure ulcer. 11 factors predicted pressure ulcer development. Validated performance properties of the resulting model were good. Model-predicted rates of pressure ulcer development at individual long-term care facilities varied from 1.9% to 6.3%, and observed rates ranged from 0% to 10.9%. Case-mix-adjusted rates and ranks of facilities differed considerably from unadjusted ratings. For example, among five facilities that were identified as high outliers on the basis of unadjusted rates, two remained as outliers after adjustment for case mix. Long-term care facilities differ in case mix. Adjustments for case mix result in different judgments about facility performance and should be used when facility incidence rates are compared.

Validity of two methods for estimation of vertical jump height.

PubMed

Dias, Jonathan Ache; Dal Pupo, Juliano; Reis, Diogo C; Borges, Lucas; Santos, Saray G; Moro, Antônio R P; Borges, Noé G

2011-07-01

The objectives of this study were (a) to determine the concurrent validity of the flight time (FT) and double integration of vertical reaction force (DIF) methods in the estimation of vertical jump height with the video method (VID) as reference; (b) to verify the degree of agreement among the 3 methods; (c) to propose regression equations to predict the jump height using the FT and DIF. Twenty healthy male and female nonathlete college students participated in this study. The experiment involved positioning a contact mat (CTM) on the force platform (FP), with a video camera 3 m from the FP and perpendicular to the sagittal plane of the subject being assessed. Each participant performed 15 countermovement jumps with 60-second intervals between the trials. Significant differences were found between the jump height obtained by VID and the results with FT (p ≤ 0.01) and DIF (p ≤ 0.01), showing that the methods are not valid. Additionally, the DIF showed a greater degree of agreement with the reference method than the FT did, and both presented a systematic error. From the linear regression test was determined the prediction equations with a high degree of linearity between the methods VID vs. DIF (R = 0.988) and VID vs. FT (R = 0.979). Therefore, the prediction equations suggested may allow coaches to measure the vertical jump performance of athletes by the FT and DIF, using a CTM or an FP, which represents more practical and viable approaches in the sports field; comparisons can then be made with the results of other athletes evaluated by VID.

The Development of a Machine Learning Inpatient Acute Kidney Injury Prediction Model.

PubMed

Koyner, Jay L; Carey, Kyle A; Edelson, Dana P; Churpek, Matthew M

2018-07-01

To develop an acute kidney injury risk prediction model using electronic health record data for longitudinal use in hospitalized patients. Observational cohort study. Tertiary, urban, academic medical center from November 2008 to January 2016. All adult inpatients without pre-existing renal failure at admission, defined as first serum creatinine greater than or equal to 3.0 mg/dL, International Classification of Diseases, 9th Edition, code for chronic kidney disease stage 4 or higher or having received renal replacement therapy within 48 hours of first serum creatinine measurement. None. Demographics, vital signs, diagnostics, and interventions were used in a Gradient Boosting Machine algorithm to predict serum creatinine-based Kidney Disease Improving Global Outcomes stage 2 acute kidney injury, with 60% of the data used for derivation and 40% for validation. Area under the receiver operator characteristic curve (AUC) was calculated in the validation cohort, and subgroup analyses were conducted across admission serum creatinine, acute kidney injury severity, and hospital location. Among the 121,158 included patients, 17,482 (14.4%) developed any Kidney Disease Improving Global Outcomes acute kidney injury, with 4,251 (3.5%) developing stage 2. The AUC (95% CI) was 0.90 (0.90-0.90) for predicting stage 2 acute kidney injury within 24 hours and 0.87 (0.87-0.87) within 48 hours. The AUC was 0.96 (0.96-0.96) for receipt of renal replacement therapy (n = 821) in the next 48 hours. Accuracy was similar across hospital settings (ICU, wards, and emergency department) and admitting serum creatinine groupings. At a probability threshold of greater than or equal to 0.022, the algorithm had a sensitivity of 84% and a specificity of 85% for stage 2 acute kidney injury and predicted the development of stage 2 a median of 41 hours (interquartile range, 12-141 hr) prior to the development of stage 2 acute kidney injury. Readily available electronic health record data can be used to predict impending acute kidney injury prior to changes in serum creatinine with excellent accuracy across different patient locations and admission serum creatinine. Real-time use of this model would allow early interventions for those at high risk of acute kidney injury.

Risk prediction and aversion by anterior cingulate cortex.

PubMed

Brown, Joshua W; Braver, Todd S

2007-12-01

The recently proposed error-likelihood hypothesis suggests that anterior cingulate cortex (ACC) and surrounding areas will become active in proportion to the perceived likelihood of an error. The hypothesis was originally derived from a computational model prediction. The same computational model now makes a further prediction that ACC will be sensitive not only to predicted error likelihood, but also to the predicted magnitude of the consequences, should an error occur. The product of error likelihood and predicted error consequence magnitude collectively defines the general "expected risk" of a given behavior in a manner analogous but orthogonal to subjective expected utility theory. New fMRI results from an incentivechange signal task now replicate the error-likelihood effect, validate the further predictions of the computational model, and suggest why some segments of the population may fail to show an error-likelihood effect. In particular, error-likelihood effects and expected risk effects in general indicate greater sensitivity to earlier predictors of errors and are seen in risk-averse but not risk-tolerant individuals. Taken together, the results are consistent with an expected risk model of ACC and suggest that ACC may generally contribute to cognitive control by recruiting brain activity to avoid risk.

Continued warming could transform Greater Yellowstone fire regimes by mid-21st century

PubMed Central

Westerling, Anthony L.; Turner, Monica G.; Smithwick, Erica A. H.; Romme, William H.; Ryan, Michael G.

2011-01-01

Climate change is likely to alter wildfire regimes, but the magnitude and timing of potential climate-driven changes in regional fire regimes are not well understood. We considered how the occurrence, size, and spatial location of large fires might respond to climate projections in the Greater Yellowstone ecosystem (GYE) (Wyoming), a large wildland ecosystem dominated by conifer forests and characterized by infrequent, high-severity fire. We developed a suite of statistical models that related monthly climate data (1972–1999) to the occurrence and size of fires >200 ha in the northern Rocky Mountains; these models were cross-validated and then used with downscaled (∼12 km × 12 km) climate projections from three global climate models to predict fire occurrence and area burned in the GYE through 2099. All models predicted substantial increases in fire by midcentury, with fire rotation (the time to burn an area equal to the landscape area) reduced to <30 y from the historical 100–300 y for most of the GYE. Years without large fires were common historically but are expected to become rare as annual area burned and the frequency of regionally synchronous fires increase. Our findings suggest a shift to novel fire–climate–vegetation relationships in Greater Yellowstone by midcentury because fire frequency and extent would be inconsistent with persistence of the current suite of conifer species. The predicted new fire regime would transform the flora, fauna, and ecosystem processes in this landscape and may indicate similar changes for other subalpine forests. PMID:21788495

Disentangling the Predictive Validity of High School Grades for Academic Success in University

ERIC Educational Resources Information Center

Vulperhorst, Jonne; Lutz, Christel; de Kleijn, Renske; van Tartwijk, Jan

2018-01-01

To refine selective admission models, we investigate which measure of prior achievement has the best predictive validity for academic success in university. We compare the predictive validity of three core high school subjects to the predictive validity of high school grade point average (GPA) for academic achievement in a liberal arts university…

Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury

PubMed Central

Pannu, Neesh; Hemmelgarn, Brenda R.; Austin, Peter C.; Tan, Zhi; McArthur, Eric; Manns, Braden J.; Tonelli, Marcello; Wald, Ron; Quinn, Robert R.; Ravani, Pietro; Garg, Amit X.

2017-01-01

Importance Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. Objective To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Design, Setting, and Participants Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Exposures Demographic, laboratory, and comorbidity variables measured prior to discharge. Main Outcomes and Measures Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. Results The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). Conclusions and Relevance A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research. PMID:29136443

Derivation and External Validation of Prediction Models for Advanced Chronic Kidney Disease Following Acute Kidney Injury.

PubMed

James, Matthew T; Pannu, Neesh; Hemmelgarn, Brenda R; Austin, Peter C; Tan, Zhi; McArthur, Eric; Manns, Braden J; Tonelli, Marcello; Wald, Ron; Quinn, Robert R; Ravani, Pietro; Garg, Amit X

2017-11-14

Some patients will develop chronic kidney disease after a hospitalization with acute kidney injury; however, no risk-prediction tools have been developed to identify high-risk patients requiring follow-up. To derive and validate predictive models for progression of acute kidney injury to advanced chronic kidney disease. Data from 2 population-based cohorts of patients with a prehospitalization estimated glomerular filtration rate (eGFR) of more than 45 mL/min/1.73 m2 and who had survived hospitalization with acute kidney injury (defined by a serum creatinine increase during hospitalization > 0.3 mg/dL or > 50% of their prehospitalization baseline), were used to derive and validate multivariable prediction models. The risk models were derived from 9973 patients hospitalized in Alberta, Canada (April 2004-March 2014, with follow-up to March 2015). The risk models were externally validated with data from a cohort of 2761 patients hospitalized in Ontario, Canada (June 2004-March 2012, with follow-up to March 2013). Demographic, laboratory, and comorbidity variables measured prior to discharge. Advanced chronic kidney disease was defined by a sustained reduction in eGFR less than 30 mL/min/1.73 m2 for at least 3 months during the year after discharge. All participants were followed up for up to 1 year. The participants (mean [SD] age, 66 [15] years in the derivation and internal validation cohorts and 69 [11] years in the external validation cohort; 40%-43% women per cohort) had a mean (SD) baseline serum creatinine level of 1.0 (0.2) mg/dL and more than 20% had stage 2 or 3 acute kidney injury. Advanced chronic kidney disease developed in 408 (2.7%) of 9973 patients in the derivation cohort and 62 (2.2%) of 2761 patients in the external validation cohort. In the derivation cohort, 6 variables were independently associated with the outcome: older age, female sex, higher baseline serum creatinine value, albuminuria, greater severity of acute kidney injury, and higher serum creatinine value at discharge. In the external validation cohort, a multivariable model including these 6 variables had a C statistic of 0.81 (95% CI, 0.75-0.86) and improved discrimination and reclassification compared with reduced models that included age, sex, and discharge serum creatinine value alone (integrated discrimination improvement, 2.6%; 95% CI, 1.1%-4.0%; categorical net reclassification index, 13.5%; 95% CI, 1.9%-25.1%) or included age, sex, and acute kidney injury stage alone (integrated discrimination improvement, 8.0%; 95% CI, 5.1%-11.0%; categorical net reclassification index, 79.9%; 95% CI, 60.9%-98.9%). A multivariable model using routine laboratory data was able to predict advanced chronic kidney disease following hospitalization with acute kidney injury. The utility of this model in clinical care requires further research.

Advancing the Multi-Informant Assessment of Sluggish Cognitive Tempo: Child Self-Report in Relation to Parent and Teacher Ratings of SCT and Impairment.

PubMed

Sáez, Belén; Servera, Mateu; Burns, G Leonard; Becker, Stephen P

2018-04-27

Despite increasing interest in sluggish cognitive tempo (SCT) in children and advancements in its measurement, little research has examined child self-reported SCT. Child self-report of SCT is important for the multi-informant assessment of SCT. The current study used a large, school-based sample of children and a multi-informant design to examine child self-reported SCT using the Child Concentration Inventory - Version 2 (CCI-2) which was recently revised based on meta-analytic findings and parallels the item content of validated parent and teacher rating scales. The study involved 2142 unique children (ages 8-13 years, 50.51% males). Children (n = 1980) completed measures of SCT, loneliness, and preference for solitude. Mothers (n = 1648), fathers (n = 1358), and teachers (n = 1773) completed measures of SCT, attention-deficit/hyperactivity disorder-IN (ADHD-IN), academic impairment, social impairment, and conflicted shyness. Children's self-reported SCT demonstrated good reliability with the 15 SCT symptoms showing moderate to strong loadings on the SCT factor. The child self-report SCT factor also showed moderate convergent validity with mother, father, and teacher ratings of children's SCT. In addition, higher child-reported SCT predicted greater mother, father, and teacher ratings of children's academic impairment even after controlling for mother, father, and teacher ratings of children's SCT and ADHD-IN. Higher child-rated SCT also predicted greater mother ratings of children's social impairment after controlling for mother ratings of children's SCT and ADHD-IN. The present study provides initial empirical support for the reliability and validity of child-reported SCT as part of the multi-informant assessment of SCT. A key direction for future research includes evaluating the unique contributions of different informants and their utility within specific contexts to guide evidence-based recommendations for assessing SCT.

Distorted Beliefs about Luck and Skill and Their Relation to Gambling Problems and Gambling Behavior in Dutch Gamblers.

PubMed

Cowie, Megan E; Stewart, Sherry H; Salmon, Joshua; Collins, Pam; Al-Hamdani, Mohammed; Boffo, Marilisa; Salemink, Elske; de Jong, David; Smits, Ruby; Wiers, Reinout W

2017-01-01

Gamblers' cognitive distortions are thought to be an important mechanism involved in the development and maintenance of problem gambling. The Gambling Cognitions Inventory (GCI) evaluates two categories of distortions: beliefs that one is lucky (i.e., "Luck/Chance") and beliefs that one has special gambling-related skills (i.e., "Skill/Attitude"). Prior psychometric evaluations of the GCI demonstrated the utility of both subscales as measures of distortions and their concurrent relations to gambling problems among Canadian gamblers. However, these associations have not yet been studied in gamblers from other cultures nor have relationships between the GCI and indices of gambling behavior been investigated. In addition, the predictive validity of the GCI scales have not been evaluated in studies to date. The present study investigated the validity of the GCI as a measure of cognitive distortions in a sample of 49 Dutch gamblers by examining its concurrent and prospective relationships to both gambling problems (as measured through a standardized nine-item questionnaire assessing gambling-related problems) and behaviors (as measured through two variables: days spent gambling and time spent gambling in minutes) at baseline and over 1-month and 6-month intervals. The GCI subscales were internally consistent at all timepoints, and moderately to strongly inter-correlated at all timepoints. Each subscale correlated with an independent dimension of gambling both concurrently and prospectively: Luck/Chance was related to greater gambling problems and Skill/Attitude was related to greater gambling behavior . Thus, the two GCI subscales, while inter-correlated, appear to be related to different gambling outcomes, at least among Dutch gamblers. Moreover, the first evidence of the predictive validity of the GCI scales was demonstrated over a 1-month and 6-month interval. It is recommended that both types of cognitive distortions be considered in research and clinical practice to fully understand and address individual risk for excessive and problematic gambling.

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.

Distorted Beliefs about Luck and Skill and Their Relation to Gambling Problems and Gambling Behavior in Dutch Gamblers

PubMed Central

Cowie, Megan E.; Stewart, Sherry H.; Salmon, Joshua; Collins, Pam; Al-Hamdani, Mohammed; Boffo, Marilisa; Salemink, Elske; de Jong, David; Smits, Ruby; Wiers, Reinout W.

2017-01-01

Gamblers’ cognitive distortions are thought to be an important mechanism involved in the development and maintenance of problem gambling. The Gambling Cognitions Inventory (GCI) evaluates two categories of distortions: beliefs that one is lucky (i.e., “Luck/Chance”) and beliefs that one has special gambling-related skills (i.e., “Skill/Attitude”). Prior psychometric evaluations of the GCI demonstrated the utility of both subscales as measures of distortions and their concurrent relations to gambling problems among Canadian gamblers. However, these associations have not yet been studied in gamblers from other cultures nor have relationships between the GCI and indices of gambling behavior been investigated. In addition, the predictive validity of the GCI scales have not been evaluated in studies to date. The present study investigated the validity of the GCI as a measure of cognitive distortions in a sample of 49 Dutch gamblers by examining its concurrent and prospective relationships to both gambling problems (as measured through a standardized nine-item questionnaire assessing gambling-related problems) and behaviors (as measured through two variables: days spent gambling and time spent gambling in minutes) at baseline and over 1-month and 6-month intervals. The GCI subscales were internally consistent at all timepoints, and moderately to strongly inter-correlated at all timepoints. Each subscale correlated with an independent dimension of gambling both concurrently and prospectively: Luck/Chance was related to greater gambling problems and Skill/Attitude was related to greater gambling behavior. Thus, the two GCI subscales, while inter-correlated, appear to be related to different gambling outcomes, at least among Dutch gamblers. Moreover, the first evidence of the predictive validity of the GCI scales was demonstrated over a 1-month and 6-month interval. It is recommended that both types of cognitive distortions be considered in research and clinical practice to fully understand and address individual risk for excessive and problematic gambling. PMID:29312086

[The Alvarado score validation in diagnosing acute appendicitis in children at Braga Hospital].

PubMed

Gonçalves, Jean Pierre; Cerqueira, Arnaldo; Martins, Sofia

2011-12-01

Acute appendicitis (AA) is the leading cause of emergency abdominal surgery in children. The diagnosis is essentially clinical, but some methodologies, such as Alvarado score (AS), have been developed in order to avoid non-therapeutic laparotomy (15-30%). AS ≥ 5 or 6 is compatible with AA and is an indication for the patient to remain on observations, if AS ≥ 7 a laparotomy procedure may be indicated. To validate the AS for the AA diagnosis of children admitted at Braga Hospital. A validation study of diagnostic method (AS) using the histological examination as a gold standard. The study population consisted of 192 children (4-17 years) with abdominal pain that underwent appendectomy in the last 20 months (December 2008 to July 2010). It was determined the values of sensitivity (S), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), likelihood ratio (LR) and the ROC curve for three different cut-off points (SA =5, 6 and 7). We found that as the cut-off point of AS decreases progressively the sensitivity and specificity increases and reduces the VPN and VPP. Assuming a cut-off value of 5, only 18 children would be false negatives, instead of the 67 children if the cut-off point was 7 points. The analysis of ROC curves demonstrated a greater area under the curve for a cut-off equal to or greater than 5 (AUC = 70%). We recommend using a cut-off value of 5 points, since only 18 children with AA were initially classified as appendicitis unlikely, this value would increase to 67 patients for the SA value of ≥ 7. The AS is a valuable tool in screening children with abdominal pain for the diagnosis of AA. Nonetheless the diagnosis and final decision must be based on clinical and systematic reassessment of patients.

Effects of breed, sex, and age on the variation and ability of fecal near-infrared reflectance spectra to predict the composition of goat diets.

PubMed

Walker, J W; Campbell, E S; Lupton, C J; Taylor, C A; Waldron, D F; Landau, S Y

2007-02-01

The effects of breed, sex, and age of goats on fecal near-infrared reflectance spectroscopy-predicted percentage juniper in the diet were investigated, as were spectral differences in feces from goats differing in estimated genetic merit for juniper consumption. Eleven goats from each breed, sex, and age combination, representing 2 breeds (Angora and meat-type), 3 sex classifications (female, intact male, and castrated male), and 2 age categories [adult and kid (less than 12 mo of age)] were fed complete, pelleted rations containing 0 or 14% juniper. After 7 d on the same diet, fecal samples were collected for 3 d, and the spectra from the 3 replicate samples were averaged. Fecal samples were assigned to calibration or validation data sets. In a second experiment, Angora and meat goats with high or low estimated genetic merit for juniper consumption were fed the same diet to determine the effect of consumer group on fecal spectra. Feces were scanned in the 1,100- to 2,500-nm range with a scanning reflectance monochromator. Fecal spectra were analyzed for the difference in spectral characteristics and for differences in predicted juniper in the diet using internal and independent calibration equations. Internal calibration had a high precision (R(2) = 0.94), but the precision of independent validations (r(2) = 0.56) was low. Spectral differences were affected by diet, sex, breed, and age (P < 0.04). However, diet was the largest source of variation in spectral differences. Predicted percentage of juniper in the diet also showed that diet was the largest source of variation, accounting for 95% of the variation in predictions from internal calibrations and 51% of the variation in independent validations. Predictions from independent calibrations readily detected differences (P < 0.001) in the percentage of juniper in the 2 diets, and the predicted differences were similar to the actual differences. Predicted juniper in the diet was also affected by sex. Feces from goats from different juniper consumer groups fed a common diet were spectrally different, and the difference may have resulted from a greater intake by high- compared with low-juniper-consuming goats. Fecal near-infrared reflectance spectroscopy predictions of botanical composition of diets should be considered an interval scale of measurement.

Space shuttle nonmetallic materials age life prediction

NASA Technical Reports Server (NTRS)

Mendenhall, G. D.; Hassell, J. A.; Nathan, R. A.

1975-01-01

The chemiluminescence from samples of polybutadiene, Viton, Teflon, Silicone, PL 731 Adhesive, and SP 296 Boron-Epoxy composite was measured at temperatures from 25 to 150 C. Excellent correlations were obtained between chemiluminescence and temperature. These correlations serve to validate accelerated aging tests (at elevated temperatures) designed to predict service life at lower temperatures. In most cases, smooth or linear correlations were obtained between chemiluminescence and physical properties of purified polymer gums, including the tensile strength, viscosity, and loss tangent. The latter is a complex function of certain polymer properties. Data were obtained with far greater ease by the chemiluminescence technique than by the conventional methods of study. The chemiluminescence from the Teflon (Halon) samples was discovered to arise from trace amounts of impurities, which were undetectable by conventional, destructive analysis of the sample.

Reaction path of energetic materials using THOR code

NASA Astrophysics Data System (ADS)

Durães, L.; Campos, J.; Portugal, A.

1998-07-01

The method of predicting reaction path, using THOR code, allows for isobar and isochor adiabatic combustion and CJ detonation regimes, the calculation of the composition and thermodynamic properties of reaction products of energetic materials. THOR code assumes the thermodynamic equilibria of all possible products, for the minimum Gibbs free energy, using HL EoS. The code allows the possibility of estimating various sets of reaction products, obtained successively by the decomposition of the original reacting compound, as a function of the released energy. Two case studies of thermal decomposition procedure were selected, calculated and discussed—pure Ammonium Nitrate and its based explosive ANFO, and Nitromethane—because their equivalence ratio is respectively lower, near and greater than the stoicheiometry. Predictions of reaction path are in good correlation with experimental values, proving the validity of proposed method.

Application of a Model for Simulating the Vacuum Arc Remelting Process in Titanium Alloys

NASA Astrophysics Data System (ADS)

Patel, Ashish; Tripp, David W.; Fiore, Daniel

Mathematical modeling is routinely used in the process development and production of advanced aerospace alloys to gain greater insight into system dynamics and to predict the effect of process modifications or upsets on final properties. This article describes the application of a 2-D mathematical VAR model presented in previous LMPC meetings. The impact of process parameters on melt pool geometry, solidification behavior, fluid-flow and chemistry in Ti-6Al-4V ingots will be discussed. Model predictions were first validated against the measured characteristics of industrially produced ingots, and process inputs and model formulation were adjusted to match macro-etched pool shapes. The results are compared to published data in the literature. Finally, the model is used to examine ingot chemistry during successive VAR melts.

Assessing Infant Feeding Attitudes of Expectant Women in a Provincial Population in Canada: Validation of the Iowa Infant Feeding Attitude Scale.

PubMed

Twells, Laurie K; Midodzi, William K; Ludlow, Valerie; Murphy-Goodridge, Janet; Burrage, Lorraine; Gill, Nicole; Halfyard, Beth; Schiff, Rebecca; Newhook, Leigh Anne

2016-08-01

Maternal attitudes to infant feeding are predictive of intent and initiation of breastfeeding. The Iowa Infant Feeding Attitude Scale (IIFAS) has not been validated in the Canadian population. This study was conducted in Newfoundland and Labrador, a Canadian province with low breastfeeding rates. Objectives were to assess the reliability and validity of the IIFAS in expectant mothers; to compare attitudes to infant feeding in urban and rural areas; and to examine whether attitudes are associated with intent to breastfeed. The IIFAS assessment tool was administered to 793 pregnant women. Differences in the total IIFAS scores were compared between urban and rural areas. Reliability and validity analysis was conducted on the IIFAS. The receiver operating characteristic (ROC) of the IIFAS was assessed against mother's intent to breastfeed. The mean ± SD of the total IIFAS score of the overall sample was 64.0 ± 10.4. There were no significant differences in attitudes between urban (63.9 ± 10.5) and rural (64.4 ± 9.9) populations. There were significant differences in total IIFAS scores between women who intend to breastfeed (67.3 ± 8.3) and those who do not (51.6 ± 7.7), regardless of population region. The high value of the area under the curve (AUC) of the ROC (AUC = 0.92) demonstrates excellent ability of the IIFAS to predict intent to breastfeed. The internal consistency of the IIFAS was strong, with a Cronbach's alpha greater than .80 in the overall sample. The IIFAS examined in this provincial population provides a valid and reliable assessment of maternal attitudes toward infant feeding. This tool could be used to identify mothers less likely to breastfeed and to inform health promotion programs. © The Author(s) 2014.

Predicting forest height using the GOST, Landsat 7 ETM+, and airborne LiDAR for sloping terrains in the Greater Khingan Mountains of China

NASA Astrophysics Data System (ADS)

Gu, Chengyan; Clevers, Jan G. P. W.; Liu, Xiao; Tian, Xin; Li, Zhouyuan; Li, Zengyuan

2018-03-01

Sloping terrain of forests is an overlooked factor in many models simulating the canopy bidirectional reflectance distribution function, which limits the estimation accuracy of forest vertical structure parameters (e.g., forest height). The primary objective of this study was to predict forest height on sloping terrain over large areas with the Geometric-Optical Model for Sloping Terrains (GOST) using airborne Light Detection and Ranging (LiDAR) data and Landsat 7 imagery in the western Greater Khingan Mountains of China. The Sequential Maximum Angle Convex Cone (SMACC) algorithm was used to generate image endmembers and corresponding abundances in Landsat imagery. Then, LiDAR-derived forest metrics, topographical factors and SMACC abundances were used to calibrate and validate the GOST, which aimed to accurately decompose the SMACC mixed forest pixels into sunlit crown, sunlit background and shade components. Finally, the forest height of the study area was retrieved based on a back-propagation neural network and a look-up table. Results showed good performance for coniferous forests on all slopes and at all aspects, with significant coefficients of determination above 0.70 and root mean square errors (RMSEs) between 0.50 m and 1.00 m based on ground observed validation data. Higher RMSEs were found in areas with forest heights below 5 m and above 17 m. For 90% of the forested area, the average RMSE was 3.58 m. Our study demonstrates the tremendous potential of the GOST for quantitative mapping of forest height on sloping terrains with multispectral and LiDAR inputs.

Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure.

PubMed

Correa, John B; Apolzan, John W; Shepard, Desti N; Heil, Daniel P; Rood, Jennifer C; Martin, Corby K

2016-07-01

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland-Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity.

Prediction of acute kidney injury within 30 days of cardiac surgery.

PubMed

Ng, Shu Yi; Sanagou, Masoumeh; Wolfe, Rory; Cochrane, Andrew; Smith, Julian A; Reid, Christopher Michael

2014-06-01

To predict acute kidney injury after cardiac surgery. The study included 28,422 cardiac surgery patients who had had no preoperative renal dialysis from June 2001 to June 2009 in 18 hospitals. Logistic regression analyses were undertaken to identify the best combination of risk factors for predicting acute kidney injury. Two models were developed, one including the preoperative risk factors and another including the pre-, peri-, and early postoperative risk factors. The area under the receiver operating characteristic curve was calculated, using split-sample internal validation, to assess model discrimination. The incidence of acute kidney injury was 5.8% (1642 patients). The mortality for patients who experienced acute kidney injury was 17.4% versus 1.6% for patients who did not. On validation, the area under the curve for the preoperative model was 0.77, and the Hosmer-Lemeshow goodness-of-fit P value was .06. For the postoperative model area under the curve was 0.81 and the Hosmer-Lemeshow P value was .6. Both models had good discrimination and acceptable calibration. Acute kidney injury after cardiac surgery can be predicted using preoperative risk factors alone or, with greater accuracy, using pre-, peri-, and early postoperative risk factors. The ability to identify high-risk individuals can be useful in preoperative patient management and for recruitment of appropriate patients to clinical trials. Prediction in the early stages of postoperative care can guide subsequent intensive care of patients and could also be the basis of a retrospective performance audit tool. Copyright © 2014 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

Regional climates in the GISS general circulation model: Surface air temperature

NASA Technical Reports Server (NTRS)

Hewitson, Bruce

1994-01-01

One of the more viable research techniques into global climate change for the purpose of understanding the consequent environmental impacts is based on the use of general circulation models (GCMs). However, GCMs are currently unable to reliably predict the regional climate change resulting from global warming, and it is at the regional scale that predictions are required for understanding human and environmental responses. Regional climates in the extratropics are in large part governed by the synoptic-scale circulation and the feasibility of using this interscale relationship is explored to provide a way of moving to grid cell and sub-grid cell scales in the model. The relationships between the daily circulation systems and surface air temperature for points across the continental United States are first developed in a quantitative form using a multivariate index based on principal components analysis (PCA) of the surface circulation. These relationships are then validated by predicting daily temperature using observed circulation and comparing the predicted values with the observed temperatures. The relationships predict surface temperature accurately over the major portion of the country in winter, and for half the country in summer. These relationships are then applied to the surface synoptic circulation of the Goddard Institute for Space Studies (GISS) GCM control run, and a set of surface grid cell temperatures are generated. These temperatures, based on the larger-scale validated circulation, may now be used with greater confidence at the regional scale. The generated temperatures are compared to those of the model and show that the model has regional errors of up to 10 C in individual grid cells.

Canopy Temperature and Vegetation Indices from High-Throughput Phenotyping Improve Accuracy of Pedigree and Genomic Selection for Grain Yield in Wheat

PubMed Central

Rutkoski, Jessica; Poland, Jesse; Mondal, Suchismita; Autrique, Enrique; Pérez, Lorena González; Crossa, José; Reynolds, Matthew; Singh, Ravi

2016-01-01

Genomic selection can be applied prior to phenotyping, enabling shorter breeding cycles and greater rates of genetic gain relative to phenotypic selection. Traits measured using high-throughput phenotyping based on proximal or remote sensing could be useful for improving pedigree and genomic prediction model accuracies for traits not yet possible to phenotype directly. We tested if using aerial measurements of canopy temperature, and green and red normalized difference vegetation index as secondary traits in pedigree and genomic best linear unbiased prediction models could increase accuracy for grain yield in wheat, Triticum aestivum L., using 557 lines in five environments. Secondary traits on training and test sets, and grain yield on the training set were modeled as multivariate, and compared to univariate models with grain yield on the training set only. Cross validation accuracies were estimated within and across-environment, with and without replication, and with and without correcting for days to heading. We observed that, within environment, with unreplicated secondary trait data, and without correcting for days to heading, secondary traits increased accuracies for grain yield by 56% in pedigree, and 70% in genomic prediction models, on average. Secondary traits increased accuracy slightly more when replicated, and considerably less when models corrected for days to heading. In across-environment prediction, trends were similar but less consistent. These results show that secondary traits measured in high-throughput could be used in pedigree and genomic prediction to improve accuracy. This approach could improve selection in wheat during early stages if validated in early-generation breeding plots. PMID:27402362

Mobility stress test approach to predicting frailty, disability, and mortality in high-functioning older adults.

PubMed

Verghese, Joe; Holtzer, Roee; Lipton, Richard B; Wang, Cuiling

2012-10-01

To examine the validity of the Walking While Talking Test (WWT), a mobility stress test, to predict frailty, disability, and death in high-functioning older adults. Prospective cohort study. Community sample. Six hundred thirty-one community-residing adults aged 70 and older participating in the Einstein Aging Study (mean follow-up 32 months). High-functioning status at baseline was defined as absence of disability and dementia and normal walking speeds. Hazard ratios (HRs) for frailty, disability, and all-cause mortality. Frailty was defined as presence of three out of the following five attributes: weight loss, weakness, exhaustion, low physical activity, and slow gait. The predictive validity of the WWT was also compared with that of the Short Physical Performance Battery (SPPB) for study outcomes. Two hundred eighteen participants developed frailty, 88 developed disability, and 49 died. Each 10-cm/s decrease in WWT speed was associated with greater risk of frailty (HR = 1.12, 95% confidence interval (CI) = 1.06-1.18), disability (HR = 1.13, 95% CI = 1.03-1.23), and mortality (HR = 1.13, 95% CI = 1.01-1.27). Most associations remained robust even after accounting for potential confounders and gait speed. Comparisons of HRs and model fit suggest that the WWT may better predict frailty whereas SPPB may better predict disability. Mobility stress tests such as the WWT are robust predictors of risk of frailty, disability, and mortality in high-functioning older adults. © 2012, Copyright the Authors Journal compilation © 2012, The American Geriatrics Society.

Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure

PubMed Central

Correa, John B.; Apolzan, John W.; Shepard, Desti N.; Heil, Daniel P.; Rood, Jennifer C.; Martin, Corby K.

2016-01-01

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland–Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity. PMID:27270210

Bridging the gap: using microsociological theory to understand how expressed emotion predicts clinical outcomes.

PubMed

Stanhope, Victoria; Solomon, Phyllis

2007-06-01

Research has shown that expressed emotion (EE) among families is a strong predictor of relapse for people with severe mental illness. Recent studies have also found the presence of EE in consumer-provider relationships. Despite high consistency in the findings related to EE and relapse, the concept has weak validity as little is known about how exactly it triggers relapse. Microsociological theory provides a framework with which to analyze social interaction and, more specifically, understand how interactions relate to the emotions of pride and shame. By identifying the components of interaction rituals, the theory provides insight into the key processes underlying EE and demonstrates how methodologies based on direct observation have the potential to measure EE with greater validity. This article describes how microsociological theory can be applied to the concept of EE.

Treatment agreement, adherence, and outcome in cognitive behavioral treatments for insomnia.

PubMed

Dong, Lu; Soehner, Adriane M; Bélanger, Lynda; Morin, Charles M; Harvey, Allison G

2018-03-01

Patient adherence has been identified as an important barrier to the implementation of evidence-based psychological treatments. In cognitive behavioral treatments (CBT) for insomnia, the current study examined (a) the validity of therapist ratings of patient agreement and adherence against an established behavioral measure of adherence, and (b) the relationship between treatment agreement, adherence, and outcome. Participants were 188 adults meeting DSM-IV-TR criteria for chronic insomnia who were randomized to receive behavior therapy, cognitive therapy, or CBT for insomnia. Treatment agreement/adherence was measured by (a) weekly therapist ratings of patient agreement and homework completion, and (b) adherence to behavioral strategies (ABS) derived from patient-reported sleep diary. Outcome measures were Insomnia Severity Index and insomnia remission (Insomnia Severity Index <8). Therapist ratings of patient agreement as well as homework completion were significantly associated with sleep diary-derived global ABS. Therapist-rated patient agreement and homework completion as well as global ABS predicted greater insomnia symptoms reduction from pretreatment to posttreatment. Patient agreement also predicted insomnia symptoms reduction from pretreatment to 6-month follow-up. Patient agreement, adherence, and ABS measures during treatment significantly predicted insomnia remission at posttreatment, and all but therapist rating of homework completion predicted remission at 6-month follow-up. Greater patient agreement and adherence (therapist ratings and ABS) during treatment predicted better treatment outcome. Therapist-rated treatment agreement and adherence correspond well with patient-reported sleep diary-derived adherence measure. These simple, deployable therapist-rated patient agreement and adherence can potentially be useful for treatments for other disorders. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Measuring subjective sleepiness at work in hospital nurses: validation of a modified delivery format of the Karolinska Sleepiness Scale.

PubMed

Geiger Brown, Jeanne; Wieroney, Margaret; Blair, Lori; Zhu, Shijun; Warren, Joan; Scharf, Steven M; Hinds, Pamela S

2014-12-01

Sleepiness during the work shift is common and can be hazardous to workers and, in the case of nurses, to patients under their care. Thus, measuring sleepiness in occupational studies is an important component of workplace health and safety. The Karolinska Sleepiness Scale (KSS) is usually used as a momentary assessment of a respondent's state of sleepiness; however, end-of-shift measurement is sometimes preferred based on the study setting. We assessed the predictive validity of the KSS as an end-of-shift recall measurement, asking for "average" sleepiness over the shift and "highest" level of sleepiness during the shift. Hospital registered nurses (N=40) working 12-h shifts completed an end-of-shift diary over 4 weeks that included the National Aeronautical and Space Administration Task Load Index (NASA-TLX) work intensity items and the KSS (498 shifts over 4 weeks). Vigilant attention was assessed by measuring reaction time, lapses, and anticipations using a 10-min performance vigilance task (PVT) at the end of the shift. The Horne-Ostberg Questionnaire, Epworth Sleepiness Scale, General Sleep Disturbance Scale, and Cleveland Sleep Habits Questionnaire were also collected at baseline to assess factors that could be associated with higher sleepiness. We hypothesized that higher KSS scores would correlate with vigilant attention parameters reflective of sleepiness (slower reaction times and more lapses and anticipations on a performance vigilance task) and also with those factors known to produce higher sleepiness. These factors included the following: (1) working night shifts, especially for those with "morningness" trait; (2) working sequential night shifts; (3) having low physical and mental work demands and low time pressure; (4) having concomitant organic sleep disorders; and (5) having greater "trait" sleepiness (Epworth Sleepiness Scale). Linear mixed models and generalized linear mixed models were used to test associations that could assess the predictive validity of this format of administering the KSS. Greater sleepiness, as measured by higher KSS scores, was found on shifts with nurses working night shift, the third sequential night compared to the first, those with sleep disorder symptoms (especially insomnia), and in nurses with trait sleepiness on the Epworth scale. Less sleepiness (lower KSS scores) was seen in shifts with a high level of time pressure and in nurses with a biologic predisposition to be more alert in the morning (morningness trait) who worked the day shift. We found partial support for using the Karolinska Sleepiness Scale in the recalled format based on our multiple tests of predictive validity.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data.

PubMed

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C; Schwartz, Joel; Broday, David M

2015-12-01

Estimates of exposure to PM 2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM 2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM 2.5 and PM 10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM 2.5 and PM 10 over Israel. We later constructed daily predictions across Israel for 2003-2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R 2 values of 0.79 and 0.72 for PM 10 and PM 2.5 , respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM 2.5 and PM 10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM 2.5 and PM 10 in Israel, which could be used in the future for epidemiological studies.

Estimating daily PM2.5 and PM10 across the complex geo-climate region of Israel using MAIAC satellite-based AOD data

PubMed Central

Kloog, Itai; Sorek-Hamer, Meytar; Lyapustin, Alexei; Coull, Brent; Wang, Yujie; Just, Allan C.; Schwartz, Joel; Broday, David M.

2017-01-01

Estimates of exposure to PM2.5 are often derived from geographic characteristics based on land-use regression or from a limited number of fixed ground monitors. Remote sensing advances have integrated these approaches with satellite-based measures of aerosol optical depth (AOD), which is spatially and temporally resolved, allowing greater coverage for PM2.5 estimations. Israel is situated in a complex geo-climatic region with contrasting geographic and weather patterns, including both dark and bright surfaces within a relatively small area. Our goal was to examine the use of MODIS-based MAIAC data in Israel, and to explore the reliability of predicted PM2.5 and PM10 at a high spatiotemporal resolution. We applied a three stage process, including a daily calibration method based on a mixed effects model, to predict ground PM2.5 and PM10 over Israel. We later constructed daily predictions across Israel for 2003–2013 using spatial and temporal smoothing, to estimate AOD when satellite data were missing. Good model performance was achieved, with out-of-sample cross validation R2 values of 0.79 and 0.72 for PM10 and PM2.5, respectively. Model predictions had little bias, with cross-validated slopes (predicted vs. observed) of 0.99 for both the PM2.5 and PM10 models. To our knowledge, this is the first study that utilizes high resolution 1km MAIAC AOD retrievals for PM prediction while accounting for geo-climate complexities, such as experienced in Israel. This novel model allowed the reconstruction of long- and short-term spatially resolved exposure to PM2.5 and PM10 in Israel, which could be used in the future for epidemiological studies. PMID:28966551

Effects of sample survey design on the accuracy of classification tree models in species distribution models

USGS Publications Warehouse

Edwards, T.C.; Cutler, D.R.; Zimmermann, N.E.; Geiser, L.; Moisen, Gretchen G.

2006-01-01

We evaluated the effects of probabilistic (hereafter DESIGN) and non-probabilistic (PURPOSIVE) sample surveys on resultant classification tree models for predicting the presence of four lichen species in the Pacific Northwest, USA. Models derived from both survey forms were assessed using an independent data set (EVALUATION). Measures of accuracy as gauged by resubstitution rates were similar for each lichen species irrespective of the underlying sample survey form. Cross-validation estimates of prediction accuracies were lower than resubstitution accuracies for all species and both design types, and in all cases were closer to the true prediction accuracies based on the EVALUATION data set. We argue that greater emphasis should be placed on calculating and reporting cross-validation accuracy rates rather than simple resubstitution accuracy rates. Evaluation of the DESIGN and PURPOSIVE tree models on the EVALUATION data set shows significantly lower prediction accuracy for the PURPOSIVE tree models relative to the DESIGN models, indicating that non-probabilistic sample surveys may generate models with limited predictive capability. These differences were consistent across all four lichen species, with 11 of the 12 possible species and sample survey type comparisons having significantly lower accuracy rates. Some differences in accuracy were as large as 50%. The classification tree structures also differed considerably both among and within the modelled species, depending on the sample survey form. Overlap in the predictor variables selected by the DESIGN and PURPOSIVE tree models ranged from only 20% to 38%, indicating the classification trees fit the two evaluated survey forms on different sets of predictor variables. The magnitude of these differences in predictor variables throws doubt on ecological interpretation derived from prediction models based on non-probabilistic sample surveys. ?? 2006 Elsevier B.V. All rights reserved.

Is the Noradrenergic Symptom Cluster a Valid Construct in Adjunctive Treatment of Major Depressive Disorder?

PubMed

Stauffer, Virginia L; Liu, Peng; Goldberger, Celine; Marangell, Lauren B; Nelson, Craig; Gorwood, Philip; Fava, Maurizio

2017-03-01

To identify symptoms potentially representative of a noradrenergic symptom cluster as possible predictors of response to the selective norepinephrine reuptake inhibitor (NRI) edivoxetine when used as monotherapy or adjunctive treatment in patients with DSM-IV-TR major depressive disorder (MDD). Pooled data from 4 adjunctive treatment trials (selective serotonin reuptake inhibitor [SSRI] + edivoxetine 6-18 mg/d vs SSRI + placebo; N = 2,066) and data from 1 monotherapy trial (edivoxetine 6-18 mg/d versus placebo; N = 495) were used to identify predictors of response related to noradrenergic symptoms using a resampling-based ensemble tree method. The trials were conducted from 2008 to 2013. In the pooled adjunctive trials, no subgroup was identified that demonstrated a greater edivoxetine-placebo treatment difference than the overall patient cohort. In the edivoxetine monotherapy trial, no subgroup showing greater mean edivoxetine-placebo differences on the Montgomery-Asberg Depression Rating Scale versus the overall patient cohort was identified; a subgroup (67%) with high b​aseline Massachusetts General Hospital Cognitive and Physical Functioning Questionnaire (CPFQ) total score (≥ 28) showed statistically significantly (P = .02) greater mean edivoxetine-placebo differences on the Sheehan Disability Scale versus the overall patient cohort, and subgroups with baseline CPFQ total score ≥ 28 (65%), CPFQ cognition dimension score ≥ 16 (63%), or CPFQ physical dimension score ≥ 13 (59%) showed statistically significantly (P ≤ .025) greater mean edivoxetine-placebo differences on the CPFQ total score versus the overall patient cohort. While we could not identify symptoms predictive of response to the selective NRI edivoxetine used as adjunctive treatment, impaired cognition and physical symptoms may predict greater improvement during monotherapy. ClinicalTrials.gov identifiers: NCT00840034, NCT01173601, NCT01187407, NCT01185340, NCT00795821. © Copyright 2017 Physicians Postgraduate Press, Inc.

The development and validation of a multivariable model to predict whether patients referred for total knee replacement are suitable surgical candidates at the time of initial consultation.

PubMed

Churchill, Laura; Malian, Samuel J; Chesworth, Bert M; Bryant, Dianne; MacDonald, Steven J; Marsh, Jacquelyn D; Giffin, J Robert

2016-12-01

In previous studies, 50%-70% of patients referred to orthopedic surgeons for total knee replacement (TKR) were not surgical candidates at the time of initial assessment. The purpose of our study was to identify and cross-validate patient self-reported predictors of suitability for TKR and to determine the clinical utility of a predictive model to guide the timing and appropriateness of referral to a surgeon. We assessed pre-consultation patient data as well as the surgeon's findings and post-consultation recommendations. We used multivariate logistic regression to detect self-reported items that could identify suitable surgical candidates. Patients' willingness to undergo surgery, higher rating of pain, greater physical function, previous intra-articular injections and patient age were the factors predictive of patients being offered and electing to undergo TKR. The application of the model developed in our study would effectively reduce the proportion of nonsurgical referrals by 25%, while identifying the vast majority of surgical candidates (> 90%). Using patient-reported information, we can correctly predict the outcome of specialist consultation for TKR in 70% of cases. To reduce long waits for first consultation with a surgeon, it may be possible to use these items to educate and guide referring clinicians and patients to understand when specialist consultation is the next step in managing the patient with severe osteoarthritis of the knee.

The development and validation of a multivariable model to predict whether patients referred for total knee replacement are suitable surgical candidates at the time of initial consultation

PubMed Central

Churchill, Laura; Malian, Samuel J.; Chesworth, Bert M.; Bryant, Dianne; MacDonald, Steven J.; Marsh, Jacquelyn D.; Giffin, J. Robert

2016-01-01

Background In previous studies, 50%–70% of patients referred to orthopedic surgeons for total knee replacement (TKR) were not surgical candidates at the time of initial assessment. The purpose of our study was to identify and cross-validate patient self-reported predictors of suitability for TKR and to determine the clinical utility of a predictive model to guide the timing and appropriateness of referral to a surgeon. Methods We assessed pre-consultation patient data as well as the surgeon’s findings and post-consultation recommendations. We used multivariate logistic regression to detect self-reported items that could identify suitable surgical candidates. Results Patients’ willingness to undergo surgery, higher rating of pain, greater physical function, previous intra-articular injections and patient age were the factors predictive of patients being offered and electing to undergo TKR. Conclusion The application of the model developed in our study would effectively reduce the proportion of nonsurgical referrals by 25%, while identifying the vast majority of surgical candidates (> 90%). Using patient-reported information, we can correctly predict the outcome of specialist consultation for TKR in 70% of cases. To reduce long waits for first consultation with a surgeon, it may be possible to use these items to educate and guide referring clinicians and patients to understand when specialist consultation is the next step in managing the patient with severe osteoarthritis of the knee. PMID:28234616

Multi-Institutional External Validation of Seminal Vesicle Invasion Nomograms: Head-to-Head Comparison of Gallina Nomogram Versus 2007 Partin Tables

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

Zorn, Kevin C.; Capitanio, Umberto; Jeldres, Claudio

2009-04-01

Purpose: The Partin tables represent one of the most widely used prostate cancer staging tools for seminal vesicle invasion (SVI) prediction. Recently, Gallina et al. reported a novel staging tool for the prediction of SVI that further incorporated the use of the percentage of positive biopsy cores. We performed an external validation of the Gallina et al. nomogram and the 2007 Partin tables in a large, multi-institutional North American cohort of men treated with robotic-assisted radical prostatectomy. Methods and Materials: Clinical and pathologic data were prospectively gathered from 2,606 patients treated with robotic-assisted radical prostatectomy at one of four Northmore » American robotic referral centers between 2002 and 2007. Discrimination was quantified with the area under the receiver operating characteristics curve. The calibration compared the predicted and observed SVI rates throughout the entire range of predictions. Results: At robotic-assisted radical prostatectomy, SVI was recorded in 4.2% of patients. The discriminant properties of the Gallina et al. nomogram resulted in 81% accuracy compared with 78% for the 2007 Partin tables. The Gallina et al. nomogram overestimated the true rate of SVI. Conversely, the Partin tables underestimated the true rate of SVI. Conclusion: The Gallina et al. nomogram offers greater accuracy (81%) than the 2007 Partin tables (78%). However, both tools are associated with calibration limitations that need to be acknowledged and considered before their implementation into clinical practice.« less

Can the Pediatric Logistic Organ Dysfunction-2 Score on Day 1 Be Used in Clinical Criteria for Sepsis in Children?

PubMed

Leclerc, Francis; Duhamel, Alain; Deken, Valérie; Grandbastien, Bruno; Leteurtre, Stéphane

2017-08-01

A recent task force has proposed the use of Sequential Organ Failure Assessment in clinical criteria for sepsis in adults. We sought to evaluate the predictive validity for PICU mortality of the Pediatric Logistic Organ Dysfunction-2 and of the "quick" Pediatric Logistic Organ Dysfunction-2 scores on day 1 in children with suspected infection. Secondary analysis of the database used for the development and validation of the Pediatric Logistic Organ Dysfunction-2. Nine university-affiliated PICUs in Europe. Only children with hypotension-low systolic blood pressure or low mean blood pressure using age-adapted cutoffs-and lactatemia greater than 2 mmol/L were considered in shock. We developed the quick Pediatric Logistic Organ Dysfunction-2 score on day 1 including tachycardia, hypotension, and altered mentation (Glasgow < 11): one point for each variable (range, 0-3). Outcome was mortality at PICU discharge. Discrimination (Area under receiver operating characteristic curve-95% CI) and calibration (goodness of fit test) of the scores were studied. This study included 862 children with suspected infection (median age: 12.3 mo; mortality: n = 60 [7.0%]). Area under the curve of the Pediatric Logistic Organ Dysfunction-2 score on day 1 was 0.91 (0.86-0.96) in children with suspected infection, 0.88 (0.79-0.96) in those with low systolic blood pressure and hyperlactatemia, and 0.91 (0.85-0.97) in those with low mean blood pressure and hyperlactatemia; calibration p value was 0.03, 0.36, and 0.49, respectively. A Pediatric Logistic Organ Dysfunction-2 score on day 1 greater than or equal to 8 reflected an overall risk of mortality greater than or equal to 9.3% in children with suspected infection. Area under the curve of the quick Pediatric Logistic Organ Dysfunction-2 score on day 1 was 0.82 (0.76-0.87) with systolic blood pressure or mean blood pressure; calibration p value was 0.89 and 0.72, respectively. A score greater than or equal to 2 reflected a mortality risk greater than or equal to 19.8% with systolic blood pressure and greater than or equal to 15.9% with mean blood pressure. Among children admitted to PICU with suspected infection, Pediatric Logistic Organ Dysfunction-2 score on day 1 was highly predictive of PICU mortality suggesting its use to standardize definitions and diagnostic criteria of pediatric sepsis. Further studies are needed to determine the usefulness of the quick Pediatric Logistic Organ Dysfunction-2 score on day 1 outside of the PICU.

Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study

PubMed Central

Greenberg, Tsafrir; Chase, Henry W.; Almeida, Jorge R.; Stiffler, Richelle; Zevallos, Carlos R.; Aslam, Haris A.; Deckersbach, Thilo; Weyandt, Sarah; Cooper, Crystal; Toups, Marisa; Carmody, Thomas; Kurian, Benji; Peltier, Scott; Adams, Phillip; McInnis, Melvin G.; Oquendo, Maria A.; McGrath, Patrick J.; Fava, Maurizio; Weissman, Myrna; Parsey, Ramin; Trivedi, Madhukar H.; Phillips, Mary L.

2016-01-01

Objective Anhedonia, disrupted reward processing, is a core symptom of major depressive disorder. Recent findings demonstrate altered reward-related ventral striatal reactivity in depressed individuals, but the extent to which this is specific to anhedonia remains poorly understood. The authors examined the effect of anhedonia on reward expectancy (expected outcome value) and prediction error-(discrepancy between expected and actual outcome) related ventral striatal reactivity, as well as the relationship between these measures. Method A total of 148 unmedicated individuals with major depressive disorder and 31 healthy comparison individuals recruited for the multisite EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study underwent functional MRI during a well-validated reward task. Region of interest and whole-brain data were examined in the first- (N=78) and second- (N=70) recruited cohorts, as well as the total sample, of depressed individuals, and in healthy individuals. Results Healthy, but not depressed, individuals showed a significant inverse relationship between reward expectancy and prediction error-related right ventral striatal reactivity. Across all participants, and in depressed individuals only, greater anhedonia severity was associated with a reduced reward expectancy-prediction error inverse relationship, even after controlling for other symptoms. Conclusions The normal reward expectancy and prediction error-related ventral striatal reactivity inverse relationship concords with conditioning models, predicting a shift in ventral striatal responding from reward outcomes to reward cues. This study shows, for the first time, an absence of this relationship in two cohorts of unmedicated depressed individuals and a moderation of this relationship by anhedonia, suggesting reduced reward-contingency learning with greater anhedonia. These findings help elucidate neural mechanisms of anhedonia, as a step toward identifying potential biosignatures of treatment response. PMID:26183698

Moderation of the Relationship Between Reward Expectancy and Prediction Error-Related Ventral Striatal Reactivity by Anhedonia in Unmedicated Major Depressive Disorder: Findings From the EMBARC Study.

PubMed

Greenberg, Tsafrir; Chase, Henry W; Almeida, Jorge R; Stiffler, Richelle; Zevallos, Carlos R; Aslam, Haris A; Deckersbach, Thilo; Weyandt, Sarah; Cooper, Crystal; Toups, Marisa; Carmody, Thomas; Kurian, Benji; Peltier, Scott; Adams, Phillip; McInnis, Melvin G; Oquendo, Maria A; McGrath, Patrick J; Fava, Maurizio; Weissman, Myrna; Parsey, Ramin; Trivedi, Madhukar H; Phillips, Mary L

2015-09-01

Anhedonia, disrupted reward processing, is a core symptom of major depressive disorder. Recent findings demonstrate altered reward-related ventral striatal reactivity in depressed individuals, but the extent to which this is specific to anhedonia remains poorly understood. The authors examined the effect of anhedonia on reward expectancy (expected outcome value) and prediction error- (discrepancy between expected and actual outcome) related ventral striatal reactivity, as well as the relationship between these measures. A total of 148 unmedicated individuals with major depressive disorder and 31 healthy comparison individuals recruited for the multisite EMBARC (Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care) study underwent functional MRI during a well-validated reward task. Region of interest and whole-brain data were examined in the first- (N=78) and second- (N=70) recruited cohorts, as well as the total sample, of depressed individuals, and in healthy individuals. Healthy, but not depressed, individuals showed a significant inverse relationship between reward expectancy and prediction error-related right ventral striatal reactivity. Across all participants, and in depressed individuals only, greater anhedonia severity was associated with a reduced reward expectancy-prediction error inverse relationship, even after controlling for other symptoms. The normal reward expectancy and prediction error-related ventral striatal reactivity inverse relationship concords with conditioning models, predicting a shift in ventral striatal responding from reward outcomes to reward cues. This study shows, for the first time, an absence of this relationship in two cohorts of unmedicated depressed individuals and a moderation of this relationship by anhedonia, suggesting reduced reward-contingency learning with greater anhedonia. These findings help elucidate neural mechanisms of anhedonia, as a step toward identifying potential biosignatures of treatment response.

Predicting the Occurrence of Hypotension in Stable Patients With Nonvariceal Upper Gastrointestinal Bleeding: Point-of-Care Lactate Testing.

PubMed

Ko, Byuk Sung; Kim, Won Young; Ryoo, Seung Mok; Ahn, Shin; Sohn, Chang Hwan; Seo, Dong Woo; Lee, Yoon-Seon; Lim, Kyoung Soo; Jung, Hwoon-Yong

2015-11-01

It is difficult to assess risk in normotensive patients with upper gastrointestinal bleeding. The aim of this study was to evaluate whether the initial lactate value can predict the in-hospital occurrence of hypotension in stable patients with acute nonvariceal upper gastrointestinal bleeding. Retrospective, observational, single-center study. Emergency department of a tertiary-care, university-affiliated hospital during a 5-year period. Medical records of 3,489 patients with acute upper gastrointestinal bleeding who were normotensive at presentation to the emergency department. We analyzed the ability of point-of-care testing of lactate at emergency department admission to predict hypotension development (defined as systolic blood pressure <90 mm Hg) within 24 hours after emergency department admission. None. Of the 1,003 patients with acute nonvariceal upper gastrointestinal bleeding, 157 patients experienced hypotension within 24 hours. Lactate was independently associated with hypotension development (odds ratio, 1.6; 95% CI, 1.4-1.7), and the risk of hypotension significantly increased as the lactate increased from 2.5-4.9 mmol/L (odds ratio, 2.2) to 5.0-7.4 mmol/L (odds ratio, 4.0) and to greater than or equal to 7.5 mmol/L (odds ratio, 39.2) (p<0.001). Lactate elevation (≥2.5 mmol/L) was associated with 90% specificity and an 84% negative predictive value for hypotension development. When the lactate levels were greater than 5.0 mmol/L, the specificity and negative predictive value increased to 98% and 87%, respectively. Point-of-care testing of lactate can predict in-hospital occurrence of hypotension in stable patients with acute nonvariceal upper gastrointestinal bleeding. However, subsequently, prospective validate research will be required to clarify this.

Validation of a prediction model for predicting the probability of morbidity related to a trial of labour in Quebec.

PubMed

Chaillet, Nils; Bujold, Emmanuel; Dubé, Eric; Grobman, William A

2012-09-01

Pregnant women with a history of previous Caesarean section face the decision either to undergo an elective repeat Caesarean section (ERCS) or to attempt a trial of labour with the goal of achieving a vaginal birth after Caesarean (VBAC). Both choices are associated with their own risks of maternal and neonatal morbidity. We aimed to determine the external validity of a prediction model for the success of trial of labour after Caesarean section (TOLAC) that could help these women in their decision-making. We used a perinatal database including 185,437 deliveries from 32 obstetrical centres in Quebec between 2007 and 2011 and selected women with one previous Caesarean section who were eligible for a TOLAC. We compared the frequency of maternal and neonatal morbidity between women who underwent TOLAC and those who underwent an ERCS according to the probability of success of TOLAC calculated from a published model of prediction. Of 8508 eligible women, including 3113 who underwent TOLAC, both maternal and neonatal morbidities became less frequent as the predicted chance of VBAC increased (P < 0.05). Women undergoing a TOLAC were more likely to have maternal morbidity than those who underwent an ERCS when the predicted probability of VBAC was less than 60% (relative risk [RR] 2.3; 95% CI 1.4 to 4.0); conversely, maternal morbidity was not different between the two groups when the predicted probability of VBAC was at least 60% (RR 0.8; 95% CI 0.6 to 1.1). Neonatal morbidity was similar between groups when the probability of VBAC success was 70% or greater (RR 1.2; 95% CI 0.9 to 1.5). The use of a prediction model for TOLAC success could be useful in the prediction of TOLAC success and perinatal morbidity in a Canadian population. Neither maternal nor neonatal morbidity are increased with a TOLAC when the probability of VBAC success is at least 70%.

Human amygdala engagement moderated by early life stress exposure is a biobehavioral target for predicting recovery on antidepressants.

PubMed

Goldstein-Piekarski, Andrea N; Korgaonkar, Mayuresh S; Green, Erin; Suppes, Trisha; Schatzberg, Alan F; Hastie, Trevor; Nemeroff, Charles B; Williams, Leanne M

2016-10-18

Amygdala circuitry and early life stress (ELS) are both strongly and independently implicated in the neurobiology of depression. Importantly, animal models have revealed that the contribution of ELS to the development and maintenance of depression is likely a consequence of structural and physiological changes in amygdala circuitry in response to stress hormones. Despite these mechanistic foundations, amygdala engagement and ELS have not been investigated as biobehavioral targets for predicting functional remission in translational human studies of depression. Addressing this question, we integrated human neuroimaging and measurement of ELS within a controlled trial of antidepressant outcomes. Here we demonstrate that the interaction between amygdala activation engaged by emotional stimuli and ELS predicts functional remission on antidepressants with a greater than 80% cross-validated accuracy. Our model suggests that in depressed people with high ELS, the likelihood of remission is highest with greater amygdala reactivity to socially rewarding stimuli, whereas for those with low-ELS exposure, remission is associated with lower amygdala reactivity to both rewarding and threat-related stimuli. This full model predicted functional remission over and above the contribution of demographics, symptom severity, ELS, and amygdala reactivity alone. These findings identify a human target for elucidating the mechanisms of antidepressant functional remission and offer a target for developing novel therapeutics. The results also offer a proof-of-concept for using neuroimaging as a target for guiding neuroscience-informed intervention decisions at the level of the individual person.

Development and validation of the alcohol Expectancy Questionnaire Short Form (EQ-SF).

PubMed

Mezquita, Laura; Camacho, Laura; Suso-Ribera, Carlos; Ortet, Generós; Ibáñez, Manuel I

2018-01-15

Alcohol expectancies are proximal variables to alcohol use and misuse. In recent decades, different measures have been developed to assess this construct. One of the most frequently used and recommended instruments is the Expectancy Questionnaire (EQ; Leigh y Stacy, 1993). Our aim is to develop a short version of the EQ (EQ-SF) for suitable use in time-limited administrations. Two samples, adolescents (N = 514, 57.20% females) and adults (N = 548, 61.50% females), completed the EQ together with alcohol-use measures. Different item selection strategies were applied to select the 24 items. The EQ-SF structure was explored using confirmatory factor analysis, and measurement invariance was tested running a multi-group analysis comparing groups by sex and age. Reliability was tested using Cronbach's alpha and omega coefficients. Concurrent validity was investigated with regression analyses. The EQ-SF showed acceptable between-groups measurement invariance. Alphas and omegas ranged from .77 to .93. Positive expectancies predicted both alcohol use and alcohol-related problems. Negative expectancies predicted alcohol-related problems. Sex and age moderated these associations. Males with high positive alcohol expectancies showed higher alcohol consumption than females, while adults with high negative alcohol expectancies showed greater alcohol-related problems than adolescents. Different evidence on the validity and reliability of the EQ-SF suggest that it is a suitable instrument to assess alcohol expectancies in the Spanish population.

Assessing the stability of human locomotion: a review of current measures

PubMed Central

Bruijn, S. M.; Meijer, O. G.; Beek, P. J.; van Dieën, J. H.

2013-01-01

Falling poses a major threat to the steadily growing population of the elderly in modern-day society. A major challenge in the prevention of falls is the identification of individuals who are at risk of falling owing to an unstable gait. At present, several methods are available for estimating gait stability, each with its own advantages and disadvantages. In this paper, we review the currently available measures: the maximum Lyapunov exponent (λS and λL), the maximum Floquet multiplier, variability measures, long-range correlations, extrapolated centre of mass, stabilizing and destabilizing forces, foot placement estimator, gait sensitivity norm and maximum allowable perturbation. We explain what these measures represent and how they are calculated, and we assess their validity, divided up into construct validity, predictive validity in simple models, convergent validity in experimental studies, and predictive validity in observational studies. We conclude that (i) the validity of variability measures and λS is best supported across all levels, (ii) the maximum Floquet multiplier and λL have good construct validity, but negative predictive validity in models, negative convergent validity and (for λL) negative predictive validity in observational studies, (iii) long-range correlations lack construct validity and predictive validity in models and have negative convergent validity, and (iv) measures derived from perturbation experiments have good construct validity, but data are lacking on convergent validity in experimental studies and predictive validity in observational studies. In closing, directions for future research on dynamic gait stability are discussed. PMID:23516062

Ventral striatal response during decision making involving risk and reward is associated with future binge drinking in adolescents.

PubMed

Morales, Angelica M; Jones, Scott A; Ehlers, Alissa; Lavine, Jessye B; Nagel, Bonnie J

2018-05-07

Beginning to engage in heavy alcohol use during adolescence, as opposed to later in life, is associated with elevated risk for a variety of negative consequences, including the development of an alcohol use disorder. Behavioral studies suggest that poor decision making predicts alcohol use during adolescence; however, more research is needed to determine the neurobiological risk factors that underlie this association. Using functional magnetic resonance imaging, brain activation during decision making involving risk and reward was assessed in 47 adolescents (14-15 years old) with no significant history or alcohol or drug use. After baseline assessment, participants completed follow-up interviews every 3 months to assess the duration to onset of binge drinking. Adolescents who made a greater number of risky selections and had greater activation in the nucleus accumbens, precuneus, and occipital cortex during decision making involving greater potential for risk and reward began binge drinking sooner. Findings suggest that heightened activation of reward circuitry during decision making under risk is a neurobiological risk factor for earlier onset of binge drinking. Furthermore, brain activation was a significant predictor of onset to binge drinking, even after controlling for decision-making behavior, suggesting that neurobiological markers may provide additional predictive validity over behavioral assessments. Interventions designed to modify these behavioral and neurobiological risk factors may be useful for curbing heavy alcohol use during adolescence.

Independent external validation of predictive models for urinary dysfunction following external beam radiotherapy of the prostate: Issues in model development and reporting.

PubMed

Yahya, Noorazrul; Ebert, Martin A; Bulsara, Max; Kennedy, Angel; Joseph, David J; Denham, James W

2016-08-01

Most predictive models are not sufficiently validated for prospective use. We performed independent external validation of published predictive models for urinary dysfunctions following radiotherapy of the prostate. Multivariable models developed to predict atomised and generalised urinary symptoms, both acute and late, were considered for validation using a dataset representing 754 participants from the TROG 03.04-RADAR trial. Endpoints and features were harmonised to match the predictive models. The overall performance, calibration and discrimination were assessed. 14 models from four publications were validated. The discrimination of the predictive models in an independent external validation cohort, measured using the area under the receiver operating characteristic (ROC) curve, ranged from 0.473 to 0.695, generally lower than in internal validation. 4 models had ROC >0.6. Shrinkage was required for all predictive models' coefficients ranging from -0.309 (prediction probability was inverse to observed proportion) to 0.823. Predictive models which include baseline symptoms as a feature produced the highest discrimination. Two models produced a predicted probability of 0 and 1 for all patients. Predictive models vary in performance and transferability illustrating the need for improvements in model development and reporting. Several models showed reasonable potential but efforts should be increased to improve performance. Baseline symptoms should always be considered as potential features for predictive models. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Direct Validation of Differential Prediction.

ERIC Educational Resources Information Center

Lunneborg, Clifford E.

Using academic achievement data for 655 University students, direct validation of differential predictions based on a battery of aptitude/achievement measures selected for their differential prediction efficiency was attempted. In the cross-validation of the prediction of actual differences among five academic area GPA's, this set of differential…

How well should probabilistic seismic hazard maps work?

NASA Astrophysics Data System (ADS)

Vanneste, K.; Stein, S.; Camelbeeck, T.; Vleminckx, B.

2016-12-01

Recent large earthquakes that gave rise to shaking much stronger than shown in earthquake hazard maps have stimulated discussion about how well these maps forecast future shaking. These discussions have brought home the fact that although the maps are designed to achieve certain goals, we know little about how well they actually perform. As for any other forecast, this question involves verification and validation. Verification involves assessing how well the algorithm used to produce hazard maps implements the conceptual PSHA model ("have we built the model right?"). Validation asks how well the model forecasts the shaking that actually occurs ("have we built the right model?"). We explore the verification issue by simulating the shaking history of an area with assumed distribution of earthquakes, frequency-magnitude relation, temporal occurrence model, and ground-motion prediction equation. We compare the "observed" shaking at many sites over time to that predicted by a hazard map generated for the same set of parameters. PSHA predicts that the fraction of sites at which shaking will exceed that mapped is p = 1 - exp(t/T), where t is the duration of observations and T is the map's return period. This implies that shaking in large earthquakes is typically greater than shown on hazard maps, as has occurred in a number of cases. A large number of simulated earthquake histories yield distributions of shaking consistent with this forecast, with a scatter about this value that decreases as t/T increases. The median results are somewhat lower than predicted for small values of t/T and approach the predicted value for larger values of t/T. Hence, the algorithm appears to be internally consistent and can be regarded as verified for this set of simulations. Validation is more complicated because a real observed earthquake history can yield a fractional exceedance significantly higher or lower than that predicted while still being consistent with the hazard map in question. As a result, given that in the real world we have only a single sample, it is hard to assess whether a misfit between a map and observations arises by chance or reflects a biased map.

On the Modeling of Vacuum Arc Remelting Process in Titanium Alloys

NASA Astrophysics Data System (ADS)

Patel, Ashish; Fiore, Daniel

2016-07-01

Mathematical modeling is routinely used in the process development and production of advanced aerospace alloys to gain greater insight into the effect of process parameters on final properties. This article describes the application of a 2-D mathematical VAR model presented at previous LMPC meetings. The impact of process parameters on melt pool geometry, solidification behavior, fluid-flow and chemistry in a Ti-6Al-4V ingot is discussed. Model predictions are validated against published data from a industrial size ingot, and results of a parametric study on particle dissolution are also discussed.

Internalized Homophobia and Perceived Stigma: A Validation Study of Stigma Measures in a Sample of Young Men who Have Sex with Men.

PubMed

Puckett, Jae A; Newcomb, Michael E; Ryan, Daniel T; Swann, Greg; Garofalo, Robert; Mustanski, Brian

2017-03-01

Young men who have sex with men (YMSM) experience minority stressors that impact their mental health, substance use, and sexual risk behaviors. Internalized homophobia (IH) and perceived stigma represent two of these minority stressors, and there has been limited research empirically validating measures of these constructs. We validated measures of IH and perceived stigma with a sample of 450 YMSM (mean age=18.9) and a sample of 370 YMSM (mean age=22.9). Results from exploratory and confirmatory factor analyses supported modifications to the IH and perceived stigma scales, ultimately revealing a three factor and one factor structure, respectively. Convergent and discriminant validity were examined utilizing correlations between IH, perceived stigma, and other variables related to minority stress (e.g., victimization). We evaluated predictive validity by examining relations with mental health, substance use, and risky sexual behaviors measured 12-months from baseline. There were mixed findings for IH, with subscales varying in their relations to mental health, drinking, and sexual risk variables. Perceived stigma was not related to mental health or substance use, but was associated with greater prevalence of STIs. Findings supported the use of these modified scales with YMSM and highlight the need for further measurement studies.

Internalized Homophobia and Perceived Stigma: A Validation Study of Stigma Measures in a Sample of Young Men who Have Sex with Men

PubMed Central

Puckett, Jae A.; Newcomb, Michael E.; Ryan, Daniel T.; Swann, Greg; Garofalo, Robert; Mustanski, Brian

2017-01-01

Young men who have sex with men (YMSM) experience minority stressors that impact their mental health, substance use, and sexual risk behaviors. Internalized homophobia (IH) and perceived stigma represent two of these minority stressors, and there has been limited research empirically validating measures of these constructs. We validated measures of IH and perceived stigma with a sample of 450 YMSM (mean age=18.9) and a sample of 370 YMSM (mean age=22.9). Results from exploratory and confirmatory factor analyses supported modifications to the IH and perceived stigma scales, ultimately revealing a three factor and one factor structure, respectively. Convergent and discriminant validity were examined utilizing correlations between IH, perceived stigma, and other variables related to minority stress (e.g., victimization). We evaluated predictive validity by examining relations with mental health, substance use, and risky sexual behaviors measured 12-months from baseline. There were mixed findings for IH, with subscales varying in their relations to mental health, drinking, and sexual risk variables. Perceived stigma was not related to mental health or substance use, but was associated with greater prevalence of STIs. Findings supported the use of these modified scales with YMSM and highlight the need for further measurement studies. PMID:28824733

Defining when to initiate massive transfusion: a validation study of individual massive transfusion triggers in PROMMTT patients.

PubMed

Callcut, Rachael A; Cotton, Bryan A; Muskat, Peter; Fox, Erin E; Wade, Charles E; Holcomb, John B; Schreiber, Martin A; Rahbar, Mohammad H; Cohen, Mitchell J; Knudson, M Margaret; Brasel, Karen J; Bulger, Eileen M; Del Junco, Deborah J; Myers, John G; Alarcon, Louis H; Robinson, Bryce R H

2013-01-01

Early predictors of massive transfusion (MT) would prevent undertriage of patients likely to require MT. This study validates triggers using the Prospective Observational Multicenter Major Trauma Transfusion (PROMMTT) study. All enrolled patients in PROMMTT were analyzed. The initial emergency department value for each trigger (international normalized ratio [INR], systolic blood pressure, hemoglobin, base deficit, positive result for Focused Assessment for the Sonography of Trauma examination, heart rate, temperature, and penetrating injury mechanism) was compared for patients receiving MT (≥ 10 U of packed red blood cells in 24 hours) versus no MT. Adjusted odds ratios (ORs) for MT are reported using multiple logistic regression. If all triggers were known, a Massive Transfusion Score (MTS) was created, with 1 point assigned for each met trigger. A total of 1,245 patients were prospectively enrolled with 297 receiving an MT. Data were available for all triggers in 66% of the patients including 67% of the MTs (199 of 297). INR was known in 87% (1,081 of 1,245). All triggers except penetrating injury mechanism and heart rate were valid individual predictors of MT, with INR as the most predictive (adjusted OR, 2.5; 95% confidence interval, 1.7-3.7). For those with all triggers known, a positive INR trigger was seen in 49% receiving MT. Patients with an MTS of less than 2 were unlikely to receive MT (negative predictive value, 89%). If any two triggers were present (MTS ≥ 2), sensitivity for predicting MT was 85%. MT was present in 33% with an MTS of 2 greater compared with 11% of those with MTS of less than 2 (OR, 3.9; 95% confidence interval, 2.6-5.8; p < 0.0005). Parameters that can be obtained early in the initial emergency department evaluation are valid predictors for determining the likelihood of MT. Diagnostic, level II.

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

The Utility of the Mayo-Portland Adaptability Inventory Participation Index (M2PI) in US Military Veterans With a History of Mild Traumatic Brain Injury.

PubMed

OʼRourke, Justin; Critchfield, Edan; Soble, Jason; Bain, Kathleen; Fullen, Chrystal; Eapen, Blessen

2018-05-31

To examine the utility of the Mayo-Portland Adaptability Inventory-4th Edition Participation Index (M2PI) as a self-report measure of functional outcome following mild traumatic brain injury (mTBI) in US Military veterans. Department of Veterans Affairs Polytrauma Rehabilitation Center specialty hospital. On hundred thirty-nine veterans with a history of self-reported mTBI. Retrospective cross-sectional examination of data collected from regular clinical visits. M2PI, Neurobehavioral Symptoms Inventory with embedded validity measures, Posttraumatic Stress Disorder Checklist-Military Version. Forty-one percent of the sample provided symptom reports that exceeded established cut scores on embedded symptom validity tests. Invalid responders had higher levels of unemployment and endorsed significantly greater functional impairment, posttraumatic stress symptoms, and postconcussive complaints. For valid responders, regression analyses revealed that self-reported functioning was primarily related to posttraumatic stress complaints, followed by postconcussive cognitive complaints. For invalid responders, posttraumatic stress complaints also predicted self-reported functioning. Caution is recommended when utilizing the M2PI to measure functional outcome following mTBI in military veterans, particularly in the absence of symptom validity tests.

Simply criminal: predicting burglars' occupancy decisions with a simple heuristic.

PubMed

Snook, Brent; Dhami, Mandeep K; Kavanagh, Jennifer M

2011-08-01

Rational choice theories of criminal decision making assume that offenders weight and integrate multiple cues when making decisions (i.e., are compensatory). We tested this assumption by comparing how well a compensatory strategy called Franklin's Rule captured burglars' decision policies regarding residence occupancy compared to a non-compensatory strategy (i.e., Matching Heuristic). Forty burglars each decided on the occupancy of 20 randomly selected photographs of residences (for which actual occupancy was known when the photo was taken). Participants also provided open-ended reports on the cues that influenced their decisions in each case, and then rated the importance of eight cues (e.g., deadbolt visible) over all decisions. Burglars predicted occupancy beyond chance levels. The Matching Heuristic was a significantly better predictor of burglars' decisions than Franklin's Rule, and cue use in the Matching Heuristic better corresponded to the cue ecological validities in the environment than cue use in Franklin's Rule. The most important cue in burglars' models was also the most ecologically valid or predictive of actual occupancy (i.e., vehicle present). The majority of burglars correctly identified the most important cue in their models, and the open-ended technique showed greater correspondence between self-reported and captured cue use than the rating over decision technique. Our findings support a limited rationality perspective to understanding criminal decision making, and have implications for crime prevention.

[Kriging analysis of vegetation index depression in peak cluster karst area].

PubMed

Yang, Qi-Yong; Jiang, Zhong-Cheng; Ma, Zu-Lu; Cao, Jian-Hua; Luo, Wei-Qun; Li, Wen-Jun; Duan, Xiao-Fang

2012-04-01

In order to master the spatial variability of the normal different vegetation index (NDVI) of the peak cluster karst area, taking into account the problem of the mountain shadow "missing" information of remote sensing images existing in the karst area, NDVI of the non-shaded area were extracted in Guohua Ecological Experimental Area, in Pingguo County, Guangxi applying image processing software, ENVI. The spatial variability of NDVI was analyzed applying geostatistical method, and the NDVI of the mountain shadow areas was predicted and validated. The results indicated that the NDVI of the study area showed strong spatial variability and spatial autocorrelation resulting from the impact of intrinsic factors, and the range was 300 m. The spatial distribution maps of the NDVI interpolated by Kriging interpolation method showed that the mean of NDVI was 0.196, apparently strip and block. The higher NDVI values distributed in the area where the slope was greater than 25 degrees of the peak cluster area, while the lower values distributed in the area such as foot of the peak cluster and depression, where slope was less than 25 degrees. Kriging method validation results show that interpolation has a very high prediction accuracy and could predict the NDVI of the shadow area, which provides a new idea and method for monitoring and evaluation of the karst rocky desertification.

Tolerance of sexual harassment: a laboratory paradigm.

PubMed

Angelone, David J; Mitchell, Damon; Carola, Kara

2009-12-01

The present study attempted to develop a laboratory analogue for the study of tolerance for sexual harassment by using an online speed-dating paradigm. In that context, the relation between participants' sexual harassment attitudes, perpetrator attractiveness, perpetrator status, and perceived dating potential of the perpetrator were examined as factors influencing participants' tolerance of sexually harassing behavior. Participants were 128 female college students from a small northeastern public university. Results indicated that attractiveness, high social status, and attitudinal beliefs about sexual harassment were all predictive of tolerance for sexual harassment, providing preliminary support for the validity of this paradigm. In addition, participants' self reported likelihood to date a bogus male dating candidate was also predictive of tolerance for sexual harassment, over and above the aforementioned variables, suggesting that dating potential can play a role in perceptions of sexual harassment. Further, this experiment demonstrated that perceptions of sexual harassment can be assessed using the in vivo measurement of behavior. In addition, using an online environment not only provides a contemporary spin and adds a greater degree of external validity compared to other sexual harassment analogues, it also reduces any risk of potential physical sexual contact for participants.

Cueing an unresolved personal goal causes persistent ruminative self-focus: an experimental evaluation of control theories of rumination.

PubMed

Roberts, Henrietta; Watkins, Edward R; Wills, Andy J

2013-12-01

Control theory predicts that the detection of goal discrepancies initiates ruminative self-focus (Martin & Tesser, 1996). Despite the breadth of applications and interest in control theory, there is a lack of experimental evidence evaluating this prediction. The present study provided the first experimental test of this prediction. We examined uninstructed state rumination in response to the cueing of resolved and unresolved goals in a non-clinical population using a novel measure of online rumination. Consistent with control theory, cueing an unresolved goal resulted in significantly greater recurrent intrusive ruminative thoughts than cueing a resolved goal. Individual differences in trait rumination moderated the impact of the goal cueing task on the extent of state rumination: individuals who had a stronger tendency to habitually ruminate were more susceptible to the effects of cueing goal discrepancies. The findings await replication in a clinically depressed sample where there is greater variability and higher levels of trait rumination. These results indicate that control theories of goal pursuit provide a valuable framework for understanding the circumstances that trigger state rumination. Additionally, our measure of uninstructed online state rumination was found to be a valid and sensitive index of the extent and temporal course of state rumination, indicating its value for further investigating the proximal causes of state rumination. Copyright © 2013 Elsevier Ltd. All rights reserved.

Lexical analysis in schizophrenia: how emotion and social word use informs our understanding of clinical presentation.

PubMed

Minor, Kyle S; Bonfils, Kelsey A; Luther, Lauren; Firmin, Ruth L; Kukla, Marina; MacLain, Victoria R; Buck, Benjamin; Lysaker, Paul H; Salyers, Michelle P

2015-05-01

The words people use convey important information about internal states, feelings, and views of the world around them. Lexical analysis is a fast, reliable method of assessing word use that has shown promise for linking speech content, particularly in emotion and social categories, with psychopathological symptoms. However, few studies have utilized lexical analysis instruments to assess speech in schizophrenia. In this exploratory study, we investigated whether positive emotion, negative emotion, and social word use was associated with schizophrenia symptoms, metacognition, and general functioning in a schizophrenia cohort. Forty-six participants generated speech during a semi-structured interview, and word use categories were assessed using a validated lexical analysis measure. Trained research staff completed symptom, metacognition, and functioning ratings using semi-structured interviews. Word use categories significantly predicted all variables of interest, accounting for 28% of the variance in symptoms and 16% of the variance in metacognition and general functioning. Anger words, a subcategory of negative emotion, significantly predicted greater symptoms and lower functioning. Social words significantly predicted greater metacognition. These findings indicate that lexical analysis instruments have the potential to play a vital role in psychosocial assessments of schizophrenia. Future research should replicate these findings and examine the relationship between word use and additional clinical variables across the schizophrenia-spectrum. Copyright © 2015 Elsevier Ltd. All rights reserved.

An ecologically based model of alcohol-consumption decision making: evidence for the discriminative and predictive role of contextual reward and punishment information.

PubMed

Bogg, Tim; Finn, Peter R

2009-05-01

Using insights from Ecological Systems Theory and Reinforcement Sensitivity Theory, the current study assessed the utility of a series of hypothetical role-based alcohol-consumption scenarios that varied in their presentation of rewarding and punishing information. The scenarios, along with measures of impulsive sensation seeking and a self-report of weekly alcohol consumption, were administered to a sample of alcohol-dependent and non-alcohol-dependent college-age individuals (N = 170). The results showed scenario attendance decisions were largely unaffected by alcohol-dependence status and variations in contextual reward and punishment information. In contrast to the attendance findings, the results for the alcohol-consumption decisions showed alcohol-dependent individuals reported a greater frequency of deciding to drink, as well as indicating greater alcohol consumption in the contexts of complementary rewarding or nonpunishing information. Regression results provided evidence for the criterion-related validity of scenario outcomes in an account of diagnostic alcohol problems. The results are discussed in terms of the conceptual and predictive gains associated with an assessment approach to alcohol-consumption decision making that combines situational information organized and balanced through the frameworks of Ecological Systems Theory and Reinforcement Sensitivity Theory.

Development of Decision Support Formulas for the Prediction of Bladder Outlet Obstruction and Prostatic Surgery in Patients With Lower Urinary Tract Symptom/Benign Prostatic Hyperplasia: Part II, External Validation and Usability Testing of a Smartphone App.

PubMed

Choo, Min Soo; Jeong, Seong Jin; Cho, Sung Yong; Yoo, Changwon; Jeong, Chang Wook; Ku, Ja Hyeon; Oh, Seung-June

2017-04-01

We aimed to externally validate the prediction model we developed for having bladder outlet obstruction (BOO) and requiring prostatic surgery using 2 independent data sets from tertiary referral centers, and also aimed to validate a mobile app for using this model through usability testing. Formulas and nomograms predicting whether a subject has BOO and needs prostatic surgery were validated with an external validation cohort from Seoul National University Bundang Hospital and Seoul Metropolitan Government-Seoul National University Boramae Medical Center between January 2004 and April 2015. A smartphone-based app was developed, and 8 young urologists were enrolled for usability testing to identify any human factor issues of the app. A total of 642 patients were included in the external validation cohort. No significant differences were found in the baseline characteristics of major parameters between the original (n=1,179) and the external validation cohort, except for the maximal flow rate. Predictions of requiring prostatic surgery in the validation cohort showed a sensitivity of 80.6%, a specificity of 73.2%, a positive predictive value of 49.7%, and a negative predictive value of 92.0%, and area under receiver operating curve of 0.84. The calibration plot indicated that the predictions have good correspondence. The decision curve showed also a high net benefit. Similar evaluation results using the external validation cohort were seen in the predictions of having BOO. Overall results of the usability test demonstrated that the app was user-friendly with no major human factor issues. External validation of these newly developed a prediction model demonstrated a moderate level of discrimination, adequate calibration, and high net benefit gains for predicting both having BOO and requiring prostatic surgery. Also a smartphone app implementing the prediction model was user-friendly with no major human factor issue.

Development and external multicenter validation of Chinese Prostate Cancer Consortium prostate cancer risk calculator for initial prostate biopsy.

PubMed

Chen, Rui; Xie, Liping; Xue, Wei; Ye, Zhangqun; Ma, Lulin; Gao, Xu; Ren, Shancheng; Wang, Fubo; Zhao, Lin; Xu, Chuanliang; Sun, Yinghao

2016-09-01

Substantial differences exist in the relationship of prostate cancer (PCa) detection rate and prostate-specific antigen (PSA) level between Western and Asian populations. Classic Western risk calculators, European Randomized Study for Screening of Prostate Cancer Risk Calculator, and Prostate Cancer Prevention Trial Risk Calculator, were shown to be not applicable in Asian populations. We aimed to develop and validate a risk calculator for predicting the probability of PCa and high-grade PCa (defined as Gleason Score sum 7 or higher) at initial prostate biopsy in Chinese men. Urology outpatients who underwent initial prostate biopsy according to the inclusion criteria were included. The multivariate logistic regression-based Chinese Prostate Cancer Consortium Risk Calculator (CPCC-RC) was constructed with cases from 2 hospitals in Shanghai. Discriminative ability, calibration and decision curve analysis were externally validated in 3 CPCC member hospitals. Of the 1,835 patients involved, PCa was identified in 338/924 (36.6%) and 294/911 (32.3%) men in the development and validation cohort, respectively. Multivariate logistic regression analyses showed that 5 predictors (age, logPSA, logPV, free PSA ratio, and digital rectal examination) were associated with PCa (Model 1) or high-grade PCa (Model 2), respectively. The area under the curve of Model 1 and Model 2 was 0.801 (95% CI: 0.771-0.831) and 0.826 (95% CI: 0.796-0.857), respectively. Both models illustrated good calibration and substantial improvement in decision curve analyses than any single predictors at all threshold probabilities. Higher predicting accuracy, better calibration, and greater clinical benefit were achieved by CPCC-RC, compared with European Randomized Study for Screening of Prostate Cancer Risk Calculator and Prostate Cancer Prevention Trial Risk Calculator in predicting PCa. CPCC-RC performed well in discrimination and calibration and decision curve analysis in external validation compared with Western risk calculators. CPCC-RC may aid in decision-making of prostate biopsy in Chinese or in other Asian populations with similar genetic and environmental backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Problem behaviours and symptom dimensions of psychiatric disorders in adults with intellectual disabilities: An exploratory and confirmatory factor analysis.

PubMed

Melville, Craig A; Johnson, Paul C D; Smiley, Elita; Simpson, Neill; Purves, David; McConnachie, Alex; Cooper, Sally-Ann

2016-08-01

The limited evidence on the relationship between problem behaviours and symptoms of psychiatric disorders experienced by adults with intellectual disabilities leads to conflict about diagnostic criteria and confused treatment. This study examined the relationship between problem behaviours and other psychopathology, and compared the predictive validity of dimensional and categorical models experienced by adults with intellectual disabilities. Exploratory and confirmatory factor analyses appropriate for non-continuous data were used to derive, and validate, symptom dimensions using two clinical datasets (n=457; n=274). Categorical diagnoses were derived using DC-LD. Severity and 5-year longitudinal outcome was measured using a battery of instruments. Five factors/dimensions were identified and confirmed. Problem behaviours were included in an emotion dysregulation-problem behaviour dimension that was distinct from the depressive, anxiety, organic and psychosis dimensions. The dimensional model had better predictive validity than categorical diagnosis. International classification systems should not include problem behaviours as behavioural equivalents in diagnostic criteria for depression or other psychiatric disorders. Investigating the relevance of emotional regulation to psychopathology may provide an important pathway for development of improved interventions. There is uncertainty whether new onset problem behaviours or a change in longstanding problem behaviours should be considered as symptoms of depression or other types of psychiatric disorders in adults with intellectual disabilities. The validity of previous studies was limited by the use of pre-defined, categorical diagnoses or unreliable statistical methods. This study used robust statistical modelling to examine problem behaviours within a dimensional model of symptoms. We found that problem behaviours were included in an emotional dysregulation dimension and not in the dimension that included symptoms that are typical of depression. The dimensional model of symptoms had greater predictive validity than categorical diagnoses of psychiatric disorders. Our findings suggest that problem behaviours are a final common pathway for emotional distress in adults with intellectual disabilities so clinicians should not use a change in problem behaviours as a diagnostic criterion for depression, or other psychiatric disorders. Copyright © 2016 Elsevier Ltd. All rights reserved.

A clinical score to predict the need for intraaortic balloon pump in patients undergoing coronary artery bypass grafting.

PubMed

Miceli, Antonio; Duggan, Simon M J; Capoun, Radek; Romeo, Francesco; Caputo, Massimo; Angelini, Gianni D

2010-08-01

There is no accepted consensus on the definition of high-risk patients who may benefit from the use of intraaortic balloon pump (IABP) in coronary artery bypass grafting (CABG). The aim of this study was to develop a risk model to identify high-risk patients and predict the need for IABP insertion during CABG. From April 1996 to December 2006, 8,872 consecutive patients underwent isolated CABG; of these 182 patients (2.1%) received intraoperative or postoperative IABP. The scoring risk model was developed in 4,575 patients (derivation dataset) and validated on the remaining patients (validation dataset). Predictive accuracy was evaluated by the area under the receiver operating characteristic curve. Mortality was 1% in the entire cohort and 18.7% (22 patients) in the group which received IABP. Multivariable analysis showed that age greater than 70 years, moderate and poor left ventricular dysfunction, previous cardiac surgery, emergency operation, left main disease, Canadian Cardiovascular Society 3-4 class, and recent myocardial infarction were independent risk factors for the need of IABP insertion. Three risk groups were identified. The observed probability of receiving IABP and mortality in the validation dataset was 36.4% and 10% in the high-risk group (score >14), 10.9% and 2.8% in the medium-risk group (score 7 to 13), and 1.7% and 0.7% in the low-risk group (score 0 to 6). This simple clinical risk model based on preoperative clinical data can be used to identify high-risk patients who may benefit from elective insertion of IABP during CABG. Copyright 2010 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

A Two-Center Validation of "Patient Does Not Follow Commands" and Three Other Simplified Measures to Replace the Glasgow Coma Scale for Field Trauma Triage.

PubMed

Hopkins, Emily; Green, Steven M; Kiemeney, Michael; Haukoos, Jason S

2018-05-02

Out-of-hospital personnel worldwide calculate the 13-point Glasgow Coma Scale (GCS) score as a routine part of field trauma triage. We wish to independently validate a simpler binary assessment to replace the GCS for this task. We analyzed trauma center registries from Loma Linda University Health (2003 to 2015) and Denver Health Medical Center (2009 to 2015) to compare the binary assessment "patient does not follow commands" (ie, GCS motor score <6) with GCS score less than or equal to 13 for the prediction of 5 trauma outcomes: emergency intubation, clinically significant brain injury, need for neurosurgical intervention, Injury Severity Score greater than 15, and mortality. As a secondary analysis, we similarly evaluated 3 other measures simpler than the GCS: GCS motor score less than 5, Simplified Motor Score, and the "alert, voice, pain, unresponsive" scale. In this analysis of 47,973 trauma patients, we found that the binary assessment "patient does not follow commands" was essentially identical to GCS score less than or equal to 13 for the prediction of all 5 trauma outcomes, with slightly superior positive likelihood ratios (eg, those for mortality 2.37 versus 2.13) offsetting slightly inferior negative ones (eg, those for mortality 0.25 versus 0.24) and its graphic depiction of sensitivity versus specificity superimposing the GCS prediction curve. We found similar results for the 3 other simplified measures. In this 2-center external validation, we confirmed that a simple binary assessment-"patient does not follow commands"-could effectively replace the more complicated GCS for field trauma triage. Copyright © 2018 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Development and Validation of a Clinic-Based Prediction Tool to Identify Female Athletes at High Risk for Anterior Cruciate Ligament Injury

PubMed Central

Myer, Gregory D.; Ford, Kevin R.; Khoury, Jane; Succop, Paul; Hewett, Timothy E.

2012-01-01

Background Prospective measures of high knee abduction moment (KAM) during landing identify female athletes at high risk for anterior cruciate ligament injury. Laboratory-based measurements demonstrate 90% accuracy in prediction of high KAM. Clinic-based prediction algorithms that employ correlates derived from laboratory-based measurements also demonstrate high accuracy for prediction of high KAM mechanics during landing. Hypotheses Clinic-based measures derived from highly predictive laboratory-based models are valid for the accurate prediction of high KAM status, and simultaneous measurements using laboratory-based and clinic-based techniques highly correlate. Study Design Cohort study (diagnosis); Level of evidence, 2. Methods One hundred female athletes (basketball, soccer, volleyball players) were tested using laboratory-based measures to confirm the validity of identified laboratory-based correlate variables to clinic-based measures included in a prediction algorithm to determine high KAM status. To analyze selected clinic-based surrogate predictors, another cohort of 20 female athletes was simultaneously tested with both clinic-based and laboratory-based measures. Results The prediction model (odds ratio: 95% confidence interval), derived from laboratory-based surrogates including (1) knee valgus motion (1.59: 1.17-2.16 cm), (2) knee flexion range of motion (0.94: 0.89°-1.00°), (3) body mass (0.98: 0.94-1.03 kg), (4) tibia length (1.55: 1.20-2.07 cm), and (5) quadriceps-to-hamstrings ratio (1.70: 0.48%-6.0%), predicted high KAM status with 84% sensitivity and 67% specificity (P < .001). Clinic-based techniques that used a calibrated physician’s scale, a standard measuring tape, standard camcorder, ImageJ software, and an isokinetic dynamometer showed high correlation (knee valgus motion, r = .87; knee flexion range of motion, r = .95; and tibia length, r = .98) to simultaneous laboratory-based measurements. Body mass and quadriceps-to-hamstrings ratio were included in both methodologies and therefore had r values of 1.0. Conclusion Clinically obtainable measures of increased knee valgus, knee flexion range of motion, body mass, tibia length, and quadriceps-to-hamstrings ratio predict high KAM status in female athletes with high sensitivity and specificity. Female athletes who demonstrate high KAM landing mechanics are at increased risk for anterior cruciate ligament injury and are more likely to benefit from neuromuscular training targeted to this risk factor. Use of the developed clinic-based assessment tool may facilitate high-risk athletes’ entry into appropriate interventions that will have greater potential to reduce their injury risk. PMID:20595554

Validation of the Greek version of the Neurological Disorders Depression Inventory for Epilepsy (NDDI-E).

PubMed

Zis, Panagiotis; Yfanti, Paraskevi; Siatouni, Anna; Tavernarakis, Antonios; Gatzonis, Stylianos

2013-12-01

The Neurological Disorders Depression Inventory for Epilepsy (NDDI-E) was developed as a screening tool for symptoms of major depressive episodes in people with epilepsy. Our study describes the development, validation, and psychometric properties of the Greek version of the NDDI-E. A consecutive sample of 101 patients with epilepsy, eligible to participate in the study, has been assessed using the Mini International Neuropsychiatric Interview version 5.0.0 and the NDDI-E. All patients had no major difficulties in understanding or answering the questions of the Greek version. Cronbach's alpha coefficient was 0.74. Receiver operating characteristic analysis showed an area under the curve of 91% (95% CI=83%-99%; SE: 0.040, p<0.001). At a cutoff score of greater than 15, the NDDI-E showed a sensitivity of 91%, a specificity of 81%, and a negative predictive value of 97%. © 2013 Elsevier Inc. All rights reserved.

Validation of bioelectrical-impedance analysis as a measurement of change in body composition in obesity

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

Kushner, R.F.; Kunigk, A.; Alspaugh, M.

1990-08-01

The bioelectrical-impedance-analysis (BIA) method accurately measures body composition in weight-stable subjects. This study validates the use of BIA to measure change in body composition. Twelve obese females underwent weight loss at a mean rate of 1.16 kg/wk. Body composition was measured by deuterium oxide dilution (D2O), BIA, and skinfold anthropometry (SFA) at baseline and at 5% decrements in weight. Highly significant correlations were obtained between D2O and BIA (r = 0.971) and between D2O and SFA (r = 0.932). Overall, BIA predicted change in fat-free mass with greater accuracy (to 0.4 kg) and precision (+/- 1.28 kg) than did anthropometrymore » (to 0.8 kg and +/- 2.58 kg, respectively). We conclude that BIA is a useful clinical method for measuring change in body composition.« less

Validity of the MCAT in Predicting Performance in the First Two Years of Medical School.

ERIC Educational Resources Information Center

Jones, Robert F.; Thomae-Forgues, Maria

1984-01-01

The first systematic summary of predictive validity research on the new Medical College Admission Test (MCAT) is presented. The results show that MCAT scores have significant predictive validity with respect to first- and second-year medical school course grades. Further directions for MCAT validity research are described. (Author/MLW)

Noninvasive scoring algorithm to identify significant liver fibrosis among treatment-naive chronic hepatitis C patients.

PubMed

Koller, Tomas; Kollerova, Jana; Huorka, Martin; Meciarova, Iveta; Payer, Juraj

2014-10-01

Staging for liver fibrosis is recommended in the management of hepatitis C as an argument for treatment priority. Our aim was to construct a noninvasive algorithm to predict the significant liver fibrosis (SLF) using common biochemical markers and compare it with some existing models. The study group included 104 consecutive cases; SLF was defined as Ishak fibrosis stage greater than 2. The patient population was assigned randomly to the training and the validation groups of 52 cases each. The training group was used to construct the algorithm from parameters with the best predictive value. Each parameter was assigned a score that was added to the noninvasive fibrosis score (NFS). The accuracy of NFS in predicting SLF was tested in the validation group and compared with APRI, FIB4, and Forns models. Our algorithm used age, alkaline phosphatase, ferritin, APRI, α2 macroglobulin, and insulin and the NFS ranged from -4 to 5. The probability of SLF was 2.6 versus 77.1% in NFS<0 and NFS>0, leaving NFS=0 in a gray zone (29.8% of cases). The area under the receiver operating curve was 0.895 and 0.886, with a specificity, sensitivity, and diagnostic accuracy of 85.1, 92.3, and 87.5% versus 77.8, 100, and 87.9% for the training and the validation group. In comparison, the area under the receiver operating curve for APRI=0.810, FIB4=0.781, and Forns=0.703 with a diagnostic accuracy of 83.9, 72.3, and 62% and gray zone cases in 46.15, 37.5, and 44.2%. We devised an algorithm to calculate the NFS to predict SLF with good accuracy, fewer cases in the gray zone, and a straightforward clinical interpretation. NFS could be used for the initial evaluation of the treatment priority.

Diagnosing malignant melanoma in ambulatory care: a systematic review of clinical prediction rules.

PubMed

Harrington, Emma; Clyne, Barbara; Wesseling, Nieneke; Sandhu, Harkiran; Armstrong, Laura; Bennett, Holly; Fahey, Tom

2017-03-06

Malignant melanoma has high morbidity and mortality rates. Early diagnosis improves prognosis. Clinical prediction rules (CPRs) can be used to stratify patients with symptoms of suspected malignant melanoma to improve early diagnosis. We conducted a systematic review of CPRs for melanoma diagnosis in ambulatory care. Systematic review. A comprehensive search of PubMed, EMBASE, PROSPERO, CINAHL, the Cochrane Library and SCOPUS was conducted in May 2015, using combinations of keywords and medical subject headings (MeSH) terms. Studies deriving and validating, validating or assessing the impact of a CPR for predicting melanoma diagnosis in ambulatory care were included. Data extraction and methodological quality assessment were guided by the CHARMS checklist. From 16 334 studies reviewed, 51 were included, validating the performance of 24 unique CPRs. Three impact analysis studies were identified. Five studies were set in primary care. The most commonly evaluated CPRs were the ABCD, more than one or uneven distribution of Colour, or a large (greater than 6 mm) Diameter (ABCD) dermoscopy rule (at a cut-point of >4.75; 8 studies; pooled sensitivity 0.85, 95% CI 0.73 to 0.93, specificity 0.72, 95% CI 0.65 to 0.78) and the 7-point dermoscopy checklist (at a cut-point of ≥1 recommending ruling in melanoma; 11 studies; pooled sensitivity 0.77, 95% CI 0.61 to 0.88, specificity 0.80, 95% CI 0.59 to 0.92). The methodological quality of studies varied. At their recommended cut-points, the ABCD dermoscopy rule is more useful for ruling out melanoma than the 7-point dermoscopy checklist. A focus on impact analysis will help translate melanoma risk prediction rules into useful tools for clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Predicting survival in patients receiving continuous flow left ventricular assist devices: the HeartMate II risk score.

PubMed

Cowger, Jennifer; Sundareswaran, Kartik; Rogers, Joseph G; Park, Soon J; Pagani, Francis D; Bhat, Geetha; Jaski, Brian; Farrar, David J; Slaughter, Mark S

2013-01-22

The aim of this study was to derive and validate a model to predict survival in candidates for HeartMate II (HMII) (Thoratec, Pleasanton, California) left ventricular assist device (LVAD) support. LVAD mortality risk prediction is important for candidate selection and communicating expectations to patients and clinicians. With the evolution of LVAD support, prior risk prediction models have become less valid. Patients enrolled into the HMII bridge to transplantation and destination therapy trials (N = 1,122) were randomly divided into derivation (DC) (n = 583) and validation cohorts (VC) (n = 539). Pre-operative candidate predictors of 90-day mortality were examined in the DC with logistic regression, from which the HMII Risk Score (HMRS) was derived. The HMRS was then applied to the VC. There were 149 (13%) deaths within 90 days. In the DC, mortality (n = 80) was higher in older patients (odds ratio [OR]: 1.3, 95% confidence interval [CI]: 1.1 to 1.7 per 10 years), those with greater hypoalbuminemia (OR: 0.49, 95% CI: 0.31 to 0.76 per mg/dl of albumin), renal dysfunction (OR: 2.1, 95% CI: 1.4 to 3.2 per mg/dl creatinine), coagulopathy (OR: 3.1, 95% CI: 1.7 to 5.8 per international normalized ratio unit), and in those receiving LVAD support at less experienced centers (OR: 2.2, 95% CI: 1.2 to 4.4 for <15 trial patients). Mortality in the DC low, medium, and high HMRS groups was 4%, 16%, and 29%, respectively (p < 0.001). In the VC, corresponding mortality was 8%, 11%, and 25%, respectively (p < 0.001). HMRS discrimination was good (area under the receiver-operating characteristic curve: 0.71, 95% CI: 0.66 to 0.75). The HMRS might be useful for mortality risk stratification in HMII candidates and may serve as an additional tool in the patient selection process. Copyright © 2013 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

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).

Fine-Scale Variation and Genetic Determinants of Alternative Splicing across Individuals

PubMed Central

Coulombe-Huntington, Jasmin; Lam, Kevin C. L.; Dias, Christel; Majewski, Jacek

2009-01-01

Recently, thanks to the increasing throughput of new technologies, we have begun to explore the full extent of alternative pre–mRNA splicing (AS) in the human transcriptome. This is unveiling a vast layer of complexity in isoform-level expression differences between individuals. We used previously published splicing sensitive microarray data from lymphoblastoid cell lines to conduct an in-depth analysis on splicing efficiency of known and predicted exons. By combining publicly available AS annotation with a novel algorithm designed to search for AS, we show that many real AS events can be detected within the usually unexploited, speculative majority of the array and at significance levels much below standard multiple-testing thresholds, demonstrating that the extent of cis-regulated differential splicing between individuals is potentially far greater than previously reported. Specifically, many genes show subtle but significant genetically controlled differences in splice-site usage. PCR validation shows that 42 out of 58 (72%) candidate gene regions undergo detectable AS, amounting to the largest scale validation of isoform eQTLs to date. Targeted sequencing revealed a likely causative SNP in most validated cases. In all 17 incidences where a SNP affected a splice-site region, in silico splice-site strength modeling correctly predicted the direction of the micro-array and PCR results. In 13 other cases, we identified likely causative SNPs disrupting predicted splicing enhancers. Using Fst and REHH analysis, we uncovered significant evidence that 2 putative causative SNPs have undergone recent positive selection. We verified the effect of five SNPs using in vivo minigene assays. This study shows that splicing differences between individuals, including quantitative differences in isoform ratios, are frequent in human populations and that causative SNPs can be identified using in silico predictions. Several cases affected disease-relevant genes and it is likely some of these differences are involved in phenotypic diversity and susceptibility to complex diseases. PMID:20011102

Predicting Alcohol-Impaired Driving among Spanish Youth with the Theory of Reasoned Action.

PubMed

Espada, José P; Griffin, Kenneth W; Gonzálvez, María T; Orgilés, Mireia

2015-06-19

Alcohol consumption is a risk factor for motor vehicle accidents in young drivers. Crashes associated with alcohol consumption typically have greater severity. This study examines the prevalence of driving under the influence among Spanish youth and tests the theory of reasoned action as a model for predicting driving under the influence. Participants included 478 Spanish university students aged 17-26 years. Findings indicated that alcohol was the substance most associated with impaired driving, and was involved in more traffic crashes. Men engage in higher levels of alcohol and other drug use, and perceived less risk in drunk driving (p < .01). The study confirms that alcohol use and driving under the influence of alcohol are highly prevalent in Spanish young people, and some gender differences exist in these behaviors (p < .01). Furthermore, the study confirms the validity of theory of reasoned action as a predictive model of driving under the influence of alcohol among youth in Spain (p < .001) and can help in the design of prevention programs.

Prediction and Cross-Situational Consistency of Daily Behavior across Cultures: Testing Trait and Cultural Psychology Perspectives

PubMed Central

Church, A. Timothy; Katigbak, Marcia S.; Reyes, Jose Alberto S.; Salanga, Maria Guadalupe C.; Miramontes, Lilia A.; Adams, Nerissa B.

2008-01-01

Trait and cultural psychology perspectives on the cross-situational consistency of behavior, and the predictive validity of traits, were tested in a daily process study in the United States (N = 68), an individualistic culture, and the Philippines (N = 80), a collectivistic culture. Participants completed the Revised NEO Personality Inventory (Costa & McCrae, 1992) and a measure of self-monitoring, then reported their daily behaviors and associated situational contexts for approximately 30 days. Consistent with trait perspectives, the Big Five traits predicted daily behaviors in both cultures, and relative (interindividual) consistency was observed across many, although not all, situational contexts. The frequency of various Big Five behaviors varied across relevant situational contexts in both cultures and, consistent with cultural psychology perspectives, there was a tendency for Filipinos to exhibit greater situational variability than Americans. Self-monitoring showed some ability to account for individual differences in situational variability in the American sample, but not the Filipino sample. PMID:22146866

Proposal of a Method to Determine the Correlation between Total Suspended Solids and Dissolved Organic Matter in Water Bodies from Spectral Imaging and Artificial Neural Networks

PubMed Central

Kupssinskü, Lucas S.; T. Guimarães, Tainá; Koste, Emilie C.; da Silva, Juarez M.; de Souza, Laís V.; Oliverio, William F. M.; Jardim, Rogélio S.; Koch, Ismael É.; de Souza, Jonas G.; Mauad, Frederico F.

2018-01-01

Water quality monitoring through remote sensing with UAVs is best conducted using multispectral sensors; however, these sensors are expensive. We aimed to predict multispectral bands from a low-cost sensor (R, G, B bands) using artificial neural networks (ANN). We studied a lake located on the campus of Unisinos University, Brazil, using a low-cost sensor mounted on a UAV. Simultaneously, we collected water samples during the UAV flight to determine total suspended solids (TSS) and dissolved organic matter (DOM). We correlated the three bands predicted with TSS and DOM. The results show that the ANN validation process predicted the three bands of the multispectral sensor using the three bands of the low-cost sensor with a low average error of 19%. The correlations with TSS and DOM resulted in R2 values of greater than 0.60, consistent with literature values. PMID:29315219

Using tipping points of emotional intelligence and cognitive competencies to predict financial performance of leaders.

PubMed

Boyatzis, Richard E

2006-01-01

Competencies have been shown to differentiate outstanding managers and leaders from their less effective counterparts. Some of the competencies related to effectiveness reflect cognitive intelligence, but many of them are behavioral manifestations of emotional intelligence. Meanwhile, the performance measures used have often been an approximation of effectiveness. A study of leaders in a multi-national, consulting company shows that the frequency with which they demonstrate a variety of competencies, as seen by others, predicts financial performance in the seven quarters following the competency assessment. This, like other studies only clarify which competencies are necessary for outstanding performance. Borrowing from complexity theory, a tipping point analysis allows examination of how much of the competency is sufficient for outstanding performance. Using the tipping point analysis shows an even greater impact of competencies on the financial performance measures of the leaders in the study. The emotional intelligence competencies constituted most (i.e., 13/14) of the validated competencies predicting financial performance.

Fluid resuscitation following a burn injury: implications of a mathematical model of microvascular exchange.

PubMed

Bert, J; Gyenge, C; Bowen, B; Reed, R; Lund, T

1997-03-01

A validated mathematical model of microvascular exchange in thermally injured humans has been used to predict the consequences of different forms of resuscitation and potential modes of action of pharmaceuticals on the distribution and transport of fluid and macromolecules in the body. Specially, for 10 and/or 50 per cent burn surface area injuries, predictions are presented for no resuscitation, resuscitation with the Parkland formula (a high fluid and low protein formulation) and resuscitation with the Evans formula (a low fluid and high protein formulation). As expected, Parkland formula resuscitation leads to interstitial accumulation of excess fluid, while use of the Evans formula leads to interstitial accumulation of excessive amounts of proteins. The hypothetical effects of pharmaceuticals on the transport barrier properties of the microvascular barrier and on the highly negative tissue pressure generated postburn in the injured tissue were also investigated. Simulations predict a relatively greater amelioration of the acute postburn edema through modulation of the postburn tissue pressure effects.

Quantifying the Pathway and Predicting Spontaneous Emulsification during Material Exchange in a Two Phase Liquid System.

PubMed

Spooner, Stephen; Rahnama, Alireza; Warnett, Jason M; Williams, Mark A; Li, Zushu; Sridhar, Seetharaman

2017-10-30

Kinetic restriction of a thermodynamically favourable equilibrium is a common theme in materials processing. The interfacial instability in systems where rate of material exchange is far greater than the mass transfer through respective bulk phases is of specific interest when tracking the transient interfacial area, a parameter integral to short processing times for productivity streamlining in all manufacturing where interfacial reaction occurs. This is even more pertinent in high-temperature systems for energy and cost savings. Here the quantified physical pathway of interfacial area change due to material exchange in liquid metal-molten oxide systems is presented. In addition the predicted growth regime and emulsification behaviour in relation to interfacial tension as modelled using phase-field methodology is shown. The observed in-situ emulsification behaviour links quantitatively the geometry of perturbations as a validation method for the development of simulating the phenomena. Thus a method is presented to both predict and engineer the formation of micro emulsions to a desired specification.

Testing continuum descriptions of low-Mach-number shock structures

NASA Technical Reports Server (NTRS)

Pham-Van-diep, Gerald C.; Erwin, Daniel A.; Muntz, E. P.

1991-01-01

Numerical experiments have been performed on normal shock waves with Monte Carlo Direct Simulations (MCDS's) to investigate the validity of continuum theories at very low Mach numbers. Results from the Navier-Stokes and the Burnett equations are compared to MCDS's for both hard-sphere and Maxwell gases. It is found that the maximum-slope shock thicknesses are described equally well (within the MCDS computational scatter) by either of the continuum formulations for Mach numbers smaller than about 1.2. For Mach numbers greater that 1.2, the Burnett predictions are more accurate than the Navier-Stokes results. Temperature-density profile separations are best described by the Burnett equations for Mach numbers greater than about 1.3. At lower Mach numbers the MCDS scatter is too great to differentiate between the two continuum theories. For all Mach numbers above one, the shock shapes are more accurately described by the Burnett equations.

Physically based approaches incorporating evaporation for early warning predictions of rainfall-induced landslides

NASA Astrophysics Data System (ADS)

Reder, Alfredo; Rianna, Guido; Pagano, Luca

2018-02-01

In the field of rainfall-induced landslides on sloping covers, models for early warning predictions require an adequate trade-off between two aspects: prediction accuracy and timeliness. When a cover's initial hydrological state is a determining factor in triggering landslides, taking evaporative losses into account (or not) could significantly affect both aspects. This study evaluates the performance of three physically based predictive models, converting precipitation and evaporative fluxes into hydrological variables useful in assessing slope safety conditions. Two of the models incorporate evaporation, with one representing evaporation as both a boundary and internal phenomenon, and the other only a boundary phenomenon. The third model totally disregards evaporation. Model performances are assessed by analysing a well-documented case study involving a 2 m thick sloping volcanic cover. The large amount of monitoring data collected for the soil involved in the case study, reconstituted in a suitably equipped lysimeter, makes it possible to propose procedures for calibrating and validating the parameters of the models. All predictions indicate a hydrological singularity at the landslide time (alarm). A comparison of the models' predictions also indicates that the greater the complexity and completeness of the model, the lower the number of predicted hydrological singularities when no landslides occur (false alarms).

Evaluation of SAMe-TT2R2 Score on Predicting Success With Extended-Interval Warfarin Monitoring.

PubMed

Hwang, Andrew Y; Carris, Nicholas W; Dietrich, Eric A; Gums, John G; Smith, Steven M

2018-06-01

In patients with stable international normalized ratios, 12-week extended-interval warfarin monitoring can be considered; however, predictors of success with this strategy are unknown. The previously validated SAMe-TT 2 R 2 score (considering sex, age, medical history, treatment, tobacco, and race) predicts anticoagulation control during standard follow-up (every 4 weeks), with lower scores associated with greater time in therapeutic range. To evaluate the ability of the SAMe-TT 2 R 2 score in predicting success with extended-interval warfarin follow-up in patients with previously stable warfarin doses. In this post hoc analysis of a single-arm feasibility study, baseline SAMe-TT 2 R 2 scores were calculated for patients with ≥1 extended-interval follow-up visit. The primary analysis assessed achieved weeks of extended-interval follow-up according to baseline SAMe-TT 2 R 2 scores. A total of 47 patients receiving chronic anticoagulation completed a median of 36 weeks of extended-interval follow-up. The median baseline SAMe-TT 2 R 2 score was 1 (range 0-5). Lower SAMe-TT 2 R 2 scores appeared to be associated with greater duration of extended-interval follow-up achieved, though the differences between scores were not statistically significant. No individual variable of the SAMe-TT 2 R 2 score was associated with achieved weeks of extended-interval follow-up. Analysis of additional patient factors found that longer duration (≥24 weeks) of prior stable treatment was significantly associated with greater weeks of extended-interval follow-up completed ( P = 0.04). Conclusion and Relevance: This pilot study provides limited evidence that the SAMe-TT 2 R 2 score predicts success with extended-interval warfarin follow-up but requires confirmation in a larger study. Further research is also necessary to establish additional predictors of successful extended-interval warfarin follow-up.

Do cravings predict smoking cessation in smokers calling a national quit line: secondary analyses from a randomised trial for the utility of 'urges to smoke' measures.

PubMed

Taggar, Jaspal S; Lewis, Sarah; Docherty, Graeme; Bauld, Linda; McEwen, Andy; Coleman, Tim

2015-04-14

Single-item urges to smoke measures have been contemplated as important measures of nicotine dependence This study aimed to prospectively determine the relationships between measures of craving to smoke and smoking cessation, and compare their ability to predict cessation with the Heaviness of Smoking Index, an established measure of nicotine dependence. We conducted a secondary analysis of data from the randomised controlled PORTSSS trial. Measures of nicotine dependence, ascertained before making a quit attempt, were the HSI, frequency of urges to smoke (FUTS) and strength of urges to smoke (SUTS). Self-reported abstinence at six months after quitting was the primary outcome measure. Multivariate logistic regression and Receiver Operating Characteristic (ROC) analysis were used to assess associations and abilities of the nicotine dependence measures to predict smoking cessation. Of 2,535 participants, 53.5% were female; the median (Interquartile range) age was 38 (28-50) years. Both FUTS and HSI were inversely associated with abstinence six months after quitting; for each point increase in HSI score, participants were 16% less likely to have stopped smoking (OR 0.84, 95% C.I 0.78-0.89, p < 0.0001). Compared to participants with the lowest possible FUTS scores, those with greater scores had generally lower odds of cessation (p across frequency of urges categories=0.0026). SUTS was not associated with smoking cessation. ROC analysis suggested the HSI and FUTS had similar predictive validity for cessation. Higher FUTS and HSI scores were inversely associated with successful smoking cessation six months after quit attempts began and both had similar validity for predicting cessation.

Evaluation of recently validated non-invasive formula using basic lung functions as new screening tool for pulmonary hypertension in idiopathic pulmonary fibrosis patients

PubMed Central

Ghanem, Maha K.; Makhlouf, Hoda A.; Agmy, Gamal R.; Imam, Hisham M. K.; Fouad, Doaa A.

2009-01-01

BACKGROUND: A prediction formula for mean pulmonary artery pressure (MPAP) using standard lung function measurement has been recently validated to screen for pulmonary hypertension (PH) in idiopathic pulmonary fibrosis (IPF) patients. OBJECTIVE: To test the usefulness of this formula as a new non invasive screening tool for PH in IPF patients. Also, to study its correlation with patients' clinical data, pulmonary function tests, arterial blood gases (ABGs) and other commonly used screening methods for PH including electrocardiogram (ECG), chest X ray (CXR), trans-thoracic echocardiography (TTE) and computerized tomography pulmonary angiography (CTPA). MATERIALS AND METHODS: Cross-sectional study of 37 IPF patients from tertiary hospital. The accuracy of MPAP estimation was assessed by examining the correlation between the predicted MPAP using the formula and PH diagnosed by other screening tools and patients' clinical signs of PH. RESULTS: There was no statistically significant difference in the prediction of PH using cut off point of 21 or 25 mm Hg (P = 0.24). The formula-predicted MPAP greater than 25 mm Hg strongly correlated in the expected direction with O2 saturation (r = −0.95, P < 0.000), partial arterial O2 tension (r = −0.71, P < 0.000), right ventricular systolic pressure measured by TTE (r = 0.6, P < 0.000) and hilar width on CXR (r = 0.31, P = 0.03). Chest symptoms, ECG and CTPA signs of PH poorly correlated with the same formula (P > 0.05). CONCLUSIONS: The prediction formula for MPAP using standard lung function measurements is a simple non invasive tool that can be used as TTE to screen for PH in IPF patients and select those who need right heart catheterization. PMID:19881164

Generalised equations for the prediction of percentage body fat by anthropometry in adult men and women aged 18-81 years.

PubMed

Leahy, Siobhan; O'Neill, Cian; Sohun, Rhoda; Toomey, Clodagh; Jakeman, Philip

2013-02-28

Anthropometric data indicate that the human phenotype is changing. Today's adult is greater in stature, body mass and fat mass. Accurate measurement of body composition is necessary to maintain surveillance of obesity within the population and to evaluate associated interventions. The aim of the present study was to construct and validate generalised equations for percentage body fat (%BF) prediction from anthropometry in 1136 adult men and women. Reference values for %BF were obtained using dual-energy X-ray absorptiometry. Skinfold thickness (SF) at ten sites and girth (G) at seven sites were measured on 736 men and women aged 18-81 years (%BF 5·1-56·8%). Quantile regression was employed to construct prediction equations from age and log-transformed SF and G measures. These equations were then cross-validated on a cohort of 400 subjects of similar age and fatness. The following generalised equations were found to most accurately predict %BF: Men: (age x 0·1) + (logtricepsSF x 7·6) + (logmidaxillaSF x 8·8) + (logsuprspinaleSF x 11·9) - 11·3 (standard error of the estimate: 2·5%, 95% limits of agreement: - 4·8, + 4·9) Women: (age x 0·1) + (logabdominalG x 39·4) + (logmidaxillaSF x 4·9) + (logbicepsSF x 11·0) + (logmedialcalfSF x 9·1) - 73·5 (standard error of the estimate: 3·0%, 95% limits of agreement: - 5·7, + 5·9) These generalised anthropometric equations accurately predict %BF and are suitable for the measurement of %BF in adult men and women of varying levels of fatness across the lifespan.

A simple prediction score for developing a hospital-acquired infection after acute ischemic stroke.

PubMed

Friedant, Adam J; Gouse, Brittany M; Boehme, Amelia K; Siegler, James E; Albright, Karen C; Monlezun, Dominique J; George, Alexander J; Beasley, Timothy Mark; Martin-Schild, Sheryl

2015-03-01

Hospital-acquired infections (HAIs) are a major cause of morbidity and mortality in acute ischemic stroke patients. Although prior scoring systems have been developed to predict pneumonia in ischemic stroke patients, these scores were not designed to predict other infections. We sought to develop a simple scoring system for any HAI. Patients admitted to our stroke center (July 2008-June 2012) were retrospectively assessed. Patients were excluded if they had an in-hospital stroke, unknown time from symptom onset, or delay from symptom onset to hospital arrival greater than 48 hours. Infections were diagnosed via clinical, laboratory, and imaging modalities using standard definitions. A scoring system was created to predict infections based on baseline patient characteristics. Of 568 patients, 84 (14.8%) developed an infection during their stays. Patients who developed infection were older (73 versus 64, P < .0001), more frequently diabetic (43.9% versus 29.1%, P = .0077), and had more severe strokes on admission (National Institutes of Health Stroke Scale [NIHSS] score 12 versus 5, P < .0001). Ranging from 0 to 7, the overall infection score consists of age 70 years or more (1 point), history of diabetes (1 point), and NIHSS score (0-4 conferred 0 points, 5-15 conferred 3 points, >15 conferred 5 points). Patients with an infection score of 4 or more were at 5 times greater odds of developing an infection (odds ratio, 5.67; 95% confidence interval, 3.28-9.81; P < .0001). In our sample, clinical, laboratory, and imaging information available at admission identified patients at risk for infections during their acute hospitalizations. If validated in other populations, this score could assist providers in predicting infections after ischemic stroke. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Intolerance for smoking abstinence among nicotine-deprived, treatment-seeking smokers.

PubMed

Germeroth, Lisa J; Baker, Nathaniel L; Saladin, Michael E

2018-09-01

The Intolerance for Smoking Abstinence Discomfort Questionnaire (IDQ-S) assesses distress tolerance specific to nicotine withdrawal. Though developed to assess withdrawal-related distress, the IDQ-S has not been validated among nicotine-deprived, treatment-seeking smokers. The present study extended previous research by examining the predictive utility of the IDQ-S among abstinent, motivated-to-quit smokers. Abstinent, treatment-seeking smokers completed the IDQ-S Withdrawal Intolerance and Lack of Cognitive Coping scales, assessments of nicotine dependence and reinforcement, and smoking history at baseline. At baseline and at 24-h, 2-week, and 1-month follow-up, participants completed a smoking cue-reactivity task (collection of cue-elicited craving and negative affect), and assessments of cigarettes per day (CPD; daily diaries at follow-up), carbon monoxide (CO), and cotinine. Greater IDQ-S Withdrawal Intolerance was associated with younger age, higher nicotine dependence and reinforcement, and less smoking years (ps < .03). Greater IDQ-S Lack of Cognitive Coping was associated with less education, lower nicotine dependence and reinforcement, higher baseline CPD, and no prior quit attempts (ps < .04). IDQ-S scales did not significantly predict cue-elicited craving or negative affect, CPD, CO, or cotinine levels at follow-up (ps > .10). Withdrawal intolerance and lack of cognitive coping did not predict smoking outcomes among nicotine-deprived, treatment-seeking smokers, but were associated with smoking characteristics, including nicotine dependence and reinforcement. Withdrawal intolerance and lack of cognitive coping may not be especially useful in predicting craving and smoking behavior, but future studies should replicate the present study's findings and assess the stability of the IDQ-S before forming firm conclusions about its predictive utility. Copyright © 2018 Elsevier Ltd. All rights reserved.

Wind Prediction Accuracy for Air Traffic Management Decision Support Tools

NASA Technical Reports Server (NTRS)

Cole, Rod; Green, Steve; Jardin, Matt; Schwartz, Barry; Benjamin, Stan

2000-01-01

The performance of Air Traffic Management and flight deck decision support tools depends in large part on the accuracy of the supporting 4D trajectory predictions. This is particularly relevant to conflict prediction and active advisories for the resolution of conflicts and the conformance with of traffic-flow management flow-rate constraints (e.g., arrival metering / required time of arrival). Flight test results have indicated that wind prediction errors may represent the largest source of trajectory prediction error. The tests also discovered relatively large errors (e.g., greater than 20 knots), existing in pockets of space and time critical to ATM DST performance (one or more sectors, greater than 20 minutes), are inadequately represented by the classic RMS aggregate prediction-accuracy studies of the past. To facilitate the identification and reduction of DST-critical wind-prediction errors, NASA has lead a collaborative research and development activity with MIT Lincoln Laboratories and the Forecast Systems Lab of the National Oceanographic and Atmospheric Administration (NOAA). This activity, begun in 1996, has focussed on the development of key metrics for ATM DST performance, assessment of wind-prediction skill for state of the art systems, and development/validation of system enhancements to improve skill. A 13 month study was conducted for the Denver Center airspace in 1997. Two complementary wind-prediction systems were analyzed and compared to the forecast performance of the then standard 60 km Rapid Update Cycle - version 1 (RUC-1). One system, developed by NOAA, was the prototype 40-km RUC-2 that became operational at NCEP in 1999. RUC-2 introduced a faster cycle (1 hr vs. 3 hr) and improved mesoscale physics. The second system, Augmented Winds (AW), is a prototype en route wind application developed by MITLL based on the Integrated Terminal Wind System (ITWS). AW is run at a local facility (Center) level, and updates RUC predictions based on an optimal interpolation of the latest ACARS reports since the RUC run. This paper presents an overview of the study's results including the identification and use of new large mor wind-prediction accuracy metrics that are key to ATM DST performance.

Development and validation of a dementia screening tool for primary care in Taiwan: Brain Health Test

PubMed Central

Tsai, Ping-Huang; Liu, Jian-Liang; Lin, Ker-Neng; Chang, Chiung-Chih; Pai, Ming-Chyi; Wang, Wen-Fu; Huang, Jen-Ping; Hwang, Tzung-Jeng; Wang, Pei-Ning

2018-01-01

Objectives To develop a simple dementia screening tool to assist primary care physicians in identifying patients with cognitive impairment among subjects with memory complaints or at a high risk for dementia. Design The Brain Health Test (BHT) was developed by several experienced neurologists, psychiatrists, and clinical psychologists in the Taiwan Dementia Society. Validation of the BHT was conducted in the memory clinics of various levels of hospitals in Taiwan. Participants All dementia patients at the memory clinics who met the inclusion criteria of age greater or equal to 50 years were enrolled. Besides the BHT, the Mini-Mental State Examination and Clinical Dementia Rating were used to evaluate the cognition state of the patients and the severity of dementia. Results The BHT includes two parts: a risk evaluation and a cognitive test (BHT-cog). Self or informants reports of memory decline or needing help from others to manage money or medications were significantly associated with cognitive impairment. Among the risk factors evaluated in the BHT, a total risk score greater or equal to 8 was defined as a high risk for dementia. The total score for the finalized BHT-cog was 16. When the cutoff value for the BHT-cog was set to 10 for differentiating dementia and a normal mental state, the sensitivity was 91.5%, the specificity was 87.3%, the positive predictive value was 94.8%, and the negative predictive value was 80.1% The area under the receiver operating characteristic curve between dementia and healthy subjects was 0.958 (95% CI = 0.941–0.975). Conclusions The BHT is a simple tool that may be useful in primary care settings to identify high-risk patients to target for cognitive screening. PMID:29694392

A pediatric FOUR score coma scale: interrater reliability and predictive validity.

PubMed

Czaikowski, Brianna L; Liang, Hong; Stewart, C Todd

2014-04-01

The Full Outline of UnResponsiveness (FOUR) Score is a coma scale that consists of four components (eye and motor response, brainstem reflexes, and respiration). It was originally validated among the adult population and recently in a pediatric population. To enhance clinical assessment of pediatric intensive care unit patients, including those intubated and/or sedated, at our children's hospital, we modified the FOUR Score Scale for this population. This modified scale would provide many of the same advantages as the original, such as interrater reliability, simplicity, and elimination of the verbal component that is not compatible with the Glasgow Coma Scale (GCS), creating a more valuable neurological assessment tool for the nursing community. Our goal was to potentially provide greater information than the formally used GCS when assessing critically ill, neurologically impaired patients, including those sedated and/or intubated. Experienced pediatric intensive care unit nurses were trained as "expert raters." Two different nurses assessed each subject using the Pediatric FOUR Score Scale (PFSS), GCS, and Richmond Agitation Sedation Scale at three different time points. Data were compared with the Pediatric Cerebral Performance Category (PCPC) assessed by another nurse. Our hypothesis was that the PFSS and PCPC should highly correlate and the GCS and PCPC should correlate lower. Study results show that the PFSS is excellent for interrater reliability for trained nurse-rater pairs and prediction of poor outcome and in-hospital mortality, under various situations, but there were no statistically significant differences between the PFSS and the GCS. However, the PFSS does have the potential to provide greater neurological assessment in the intubated and/or sedated patient based on the outcomes of our study.

Adaptive scapula bone remodeling computational simulation: Relevance to regenerative medicine

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

Sharma, Gulshan B., E-mail: gbsharma@ucalgary.ca; University of Pittsburgh, Swanson School of Engineering, Department of Bioengineering, Pittsburgh, Pennsylvania 15213; University of Calgary, Schulich School of Engineering, Department of Mechanical and Manufacturing Engineering, Calgary, Alberta T2N 1N4

Shoulder arthroplasty success has been attributed to many factors including, bone quality, soft tissue balancing, surgeon experience, and implant design. Improved long-term success is primarily limited by glenoid implant loosening. Prosthesis design examines materials and shape and determines whether the design should withstand a lifetime of use. Finite element (FE) analyses have been extensively used to study stresses and strains produced in implants and bone. However, these static analyses only measure a moment in time and not the adaptive response to the altered environment produced by the therapeutic intervention. Computational analyses that integrate remodeling rules predict how bone will respondmore » over time. Recent work has shown that subject-specific two- and three dimensional adaptive bone remodeling models are feasible and valid. Feasibility and validation were achieved computationally, simulating bone remodeling using an intact human scapula, initially resetting the scapular bone material properties to be uniform, numerically simulating sequential loading, and comparing the bone remodeling simulation results to the actual scapula’s material properties. Three-dimensional scapula FE bone model was created using volumetric computed tomography images. Muscle and joint load and boundary conditions were applied based on values reported in the literature. Internal bone remodeling was based on element strain-energy density. Initially, all bone elements were assigned a homogeneous density. All loads were applied for 10 iterations. After every iteration, each bone element’s remodeling stimulus was compared to its corresponding reference stimulus and its material properties modified. The simulation achieved convergence. At the end of the simulation the predicted and actual specimen bone apparent density were plotted and compared. Location of high and low predicted bone density was comparable to the actual specimen. High predicted bone density was greater than actual specimen. Low predicted bone density was lower than actual specimen. Differences were probably due to applied muscle and joint reaction loads, boundary conditions, and values of constants used. Work is underway to study this. Nonetheless, the results demonstrate three dimensional bone remodeling simulation validity and potential. Such adaptive predictions take physiological bone remodeling simulations one step closer to reality. Computational analyses are needed that integrate biological remodeling rules and predict how bone will respond over time. We expect the combination of computational static stress analyses together with adaptive bone remodeling simulations to become effective tools for regenerative medicine research.« less

Adaptive scapula bone remodeling computational simulation: Relevance to regenerative medicine

NASA Astrophysics Data System (ADS)

Sharma, Gulshan B.; Robertson, Douglas D.

2013-07-01

Shoulder arthroplasty success has been attributed to many factors including, bone quality, soft tissue balancing, surgeon experience, and implant design. Improved long-term success is primarily limited by glenoid implant loosening. Prosthesis design examines materials and shape and determines whether the design should withstand a lifetime of use. Finite element (FE) analyses have been extensively used to study stresses and strains produced in implants and bone. However, these static analyses only measure a moment in time and not the adaptive response to the altered environment produced by the therapeutic intervention. Computational analyses that integrate remodeling rules predict how bone will respond over time. Recent work has shown that subject-specific two- and three dimensional adaptive bone remodeling models are feasible and valid. Feasibility and validation were achieved computationally, simulating bone remodeling using an intact human scapula, initially resetting the scapular bone material properties to be uniform, numerically simulating sequential loading, and comparing the bone remodeling simulation results to the actual scapula's material properties. Three-dimensional scapula FE bone model was created using volumetric computed tomography images. Muscle and joint load and boundary conditions were applied based on values reported in the literature. Internal bone remodeling was based on element strain-energy density. Initially, all bone elements were assigned a homogeneous density. All loads were applied for 10 iterations. After every iteration, each bone element's remodeling stimulus was compared to its corresponding reference stimulus and its material properties modified. The simulation achieved convergence. At the end of the simulation the predicted and actual specimen bone apparent density were plotted and compared. Location of high and low predicted bone density was comparable to the actual specimen. High predicted bone density was greater than actual specimen. Low predicted bone density was lower than actual specimen. Differences were probably due to applied muscle and joint reaction loads, boundary conditions, and values of constants used. Work is underway to study this. Nonetheless, the results demonstrate three dimensional bone remodeling simulation validity and potential. Such adaptive predictions take physiological bone remodeling simulations one step closer to reality. Computational analyses are needed that integrate biological remodeling rules and predict how bone will respond over time. We expect the combination of computational static stress analyses together with adaptive bone remodeling simulations to become effective tools for regenerative medicine research.

How to test validity in orthodontic research: a mixed dentition analysis example.

PubMed

Donatelli, Richard E; Lee, Shin-Jae

2015-02-01

The data used to test the validity of a prediction method should be different from the data used to generate the prediction model. In this study, we explored whether an independent data set is mandatory for testing the validity of a new prediction method and how validity can be tested without independent new data. Several validation methods were compared in an example using the data from a mixed dentition analysis with a regression model. The validation errors of real mixed dentition analysis data and simulation data were analyzed for increasingly large data sets. The validation results of both the real and the simulation studies demonstrated that the leave-1-out cross-validation method had the smallest errors. The largest errors occurred in the traditional simple validation method. The differences between the validation methods diminished as the sample size increased. The leave-1-out cross-validation method seems to be an optimal validation method for improving the prediction accuracy in a data set with limited sample sizes. Copyright © 2015 American Association of Orthodontists. Published by Elsevier Inc. All rights reserved.

The utility of the functional independence measure (FIM) in discharge planning for burn patients.

PubMed

Choo, Benji; Umraw, Nisha; Gomez, Manuel; Cartotto, Robert; Fish, Joel S

2006-02-01

Determining burn patients' need for inpatient rehabilitation at discharge is difficult and an objective clinical indicator might aid in this decision. The functional independence measure (FIM) is a validated outcome measure that predicts the need for rehabilitation services. This study evaluated the utility of the FIM score for discharge planning in burn patients. A retrospective chart review and FIM score determination was performed on all major burn patients discharged from a regional adult burn centre between July 1, 1999 and June 30, 2000. From 164 adult burn patients discharged, 37 met the American Burn Association criteria for major burns. One patient had insufficient data. Therefore, 36 patients were studied (mean age 47.3 +/- 17.4 years, and mean body area burned 27.4 +/- 12.9%). All 17 patients with FIM scores greater than 110 were discharged home, and patients with FIM score of 110 or lower were discharged to another institution (rehabilitation hospital n = 14, other acute care hospital n = 4, or a nursing home n = 1) p < 0.0001. A discharge FIM score of 110 or lower was strongly associated with the need for inpatient rehabilitation, while a FIM score greater than 110 indicates the patient is independent enough to manage at home. Further prospective studies will be necessary to validate these findings.

Behavioral observations of positive and negative valence systems in early childhood predict physiological measures of emotional processing three years later.

PubMed

Kessel, Ellen M; Kujawa, Autumn; Goldstein, Brandon; Hajcak, Greg; Bufferd, Sara J; Dyson, Margaret; Klein, Daniel N

2017-07-01

The Research Domain Criteria (RDoC) constructs of Positive Valence Systems (PVS) and Negative Valence Systems (NVS) are presumed to manifest behaviorally through early-emerging temperamental negative affectivity (NA) and positive affectivity (PA). The late positive potential (LPP) is a physiological measure of attention towards both negative and positive emotional stimuli; however, its associations with behavioral aspects of PVS and NVS have yet to be examined. In a community sample of children (N = 340), we examined longitudinal relationships between observational measures of temperamental PA and NA assessed at age 6, and the LPP to both pleasant and unpleasant images assessed at age 9. Lower PA at age 6 predicted reduced LPP amplitudes to pleasant, but not unpleasant, images. NA as a composite measure was not related to the LPP, but specific associations were observed with facets of NA: greater fear predicted an enhanced LPP to unpleasant images, whereas greater sadness predicted a reduced LPP to unpleasant images. We were unable to evaluate concurrent associations between behavioral observations of temperament and the LPP, and effect sizes were modest. Results support correspondence between behavioral and physiological measures of emotional processing across development, and provide evidence of discriminant validity in that PA was specifically related to the LPP to pleasant images, while facets of NA were specifically linked to the LPP to unpleasant images. Distinct associations of temperamental sadness and fear with the LPP highlight the importance of further evaluating subconstructs of NVS. Copyright © 2016 Elsevier B.V. All rights reserved.

Validation of the firefighter WFI treadmill protocol for predicting VO2 max.

PubMed

Dolezal, B A; Barr, D; Boland, D M; Smith, D L; Cooper, C B

2015-03-01

The Wellness-Fitness Initiative submaximal treadmill exercise test (WFI-TM) is recommended by the US National Fire Protection Agency to assess aerobic capacity (VO2 max) in firefighters. However, predicting VO2 max from submaximal tests can result in errors leading to erroneous conclusions about fitness. To investigate the level of agreement between VO2 max predicted from the WFI-TM against its direct measurement using exhaled gas analysis. The WFI-TM was performed to volitional fatigue. Differences between estimated VO2 max (derived from the WFI-TM equation) and direct measurement (exhaled gas analysis) were compared by paired t-test and agreement was determined using Pearson Product-Moment correlation and Bland-Altman analysis. Statistical significance was set at P < 0.05. Fifty-nine men performed the WFI-TM. Mean (standard deviation) values for estimated and measured VO2 max were 44.6 (3.4) and 43.6 (7.9) ml/kg/min, respectively (P < 0.01). The mean bias by which WFI-TM overestimated VO2 max was 0.9ml/kg/min with a 95% prediction interval of ±13.1. Prediction errors for 22% of subjects were within ±5%; 36% had errors greater than or equal to ±15% and 7% had greater than ±30% errors. The correlation between predicted and measured VO2 max was r = 0.55 (standard error of the estimate = 2.8ml/kg/min). WFI-TM predicts VO2 max with 11% error. There is a tendency to overestimate aerobic capacity in less fit individuals and to underestimate it in more fit individuals leading to a clustering of values around 42ml/kg/min, a criterion used by some fire departments to assess fitness for duty. © The Author 2015. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A new framework to enhance the interpretation of external validation studies of clinical prediction models.

PubMed

Debray, Thomas P A; Vergouwe, Yvonne; Koffijberg, Hendrik; Nieboer, Daan; Steyerberg, Ewout W; Moons, Karel G M

2015-03-01

It is widely acknowledged that the performance of diagnostic and prognostic prediction models should be assessed in external validation studies with independent data from "different but related" samples as compared with that of the development sample. We developed a framework of methodological steps and statistical methods for analyzing and enhancing the interpretation of results from external validation studies of prediction models. We propose to quantify the degree of relatedness between development and validation samples on a scale ranging from reproducibility to transportability by evaluating their corresponding case-mix differences. We subsequently assess the models' performance in the validation sample and interpret the performance in view of the case-mix differences. Finally, we may adjust the model to the validation setting. We illustrate this three-step framework with a prediction model for diagnosing deep venous thrombosis using three validation samples with varying case mix. While one external validation sample merely assessed the model's reproducibility, two other samples rather assessed model transportability. The performance in all validation samples was adequate, and the model did not require extensive updating to correct for miscalibration or poor fit to the validation settings. The proposed framework enhances the interpretation of findings at external validation of prediction models. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Absolute fracture risk assessment using lumbar spine and femoral neck bone density measurements: derivation and validation of a hybrid system.

PubMed

Leslie, William D; Lix, Lisa M

2011-03-01

The World Health Organization (WHO) Fracture Risk Assessment Tool (FRAX) computes 10-year probability of major osteoporotic fracture from multiple risk factors, including femoral neck (FN) T-scores. Lumbar spine (LS) measurements are not currently part of the FRAX formulation but are used widely in clinical practice, and this creates confusion when there is spine-hip discordance. Our objective was to develop a hybrid 10-year absolute fracture risk assessment system in which nonvertebral (NV) fracture risk was assessed from the FN and clinical vertebral (V) fracture risk was assessed from the LS. We identified 37,032 women age 45 years and older undergoing baseline FN and LS dual-energy X-ray absorptiometry (DXA; 1990-2005) from a population database that contains all clinical DXA results for the Province of Manitoba, Canada. Results were linked to longitudinal health service records for physician billings and hospitalizations to identify nontrauma vertebral and nonvertebral fracture codes after bone mineral density (BMD) testing. The population was randomly divided into equal-sized derivation and validation cohorts. Using the derivation cohort, three fracture risk prediction systems were created from Cox proportional hazards models (adjusted for age and multiple FRAX risk factors): FN to predict combined all fractures, FN to predict nonvertebral fractures, and LS to predict vertebral (without nonvertebral) fractures. The hybrid system was the sum of nonvertebral risk from the FN model and vertebral risk from the LS model. The FN and hybrid systems were both strongly predictive of overall fracture risk (p < .001). In the validation cohort, ROC analysis showed marginally better performance of the hybrid system versus the FN system for overall fracture prediction (p = .24) and significantly better performance for vertebral fracture prediction (p < .001). In a discordance subgroup with FN and LS T-score differences greater than 1 SD, there was a significant improvement in overall fracture prediction with the hybrid method (p = .025). Risk reclassification under the hybrid system showed better alignment with observed fracture risk, with 6.4% of the women reclassified to a different risk category. In conclusion, a hybrid 10-year absolute fracture risk assessment system based on combining FN and LS information is feasible. The improvement in fracture risk prediction is small but supports clinical interest in a system that integrates LS in fracture risk assessment. Copyright © 2011 American Society for Bone and Mineral Research.

Cumulative impact of common genetic variants and other risk factors on colorectal cancer risk in 42,103 individuals

PubMed Central

Dunlop, Malcolm G.; Tenesa, Albert; Farrington, Susan M.; Ballereau, Stephane; Brewster, David H.; Pharoah, Paul DP.; Schafmayer, Clemens; Hampe, Jochen; Völzke, Henry; Chang-Claude, Jenny; Hoffmeister, Michael; Brenner, Hermann; von Holst, Susanna; Picelli, Simone; Lindblom, Annika; Jenkins, Mark A.; Hopper, John L.; Casey, Graham; Duggan, David; Newcomb, Polly; Abulí, Anna; Bessa, Xavier; Ruiz-Ponte, Clara; Castellví-Bel, Sergi; Niittymäki, Iina; Tuupanen, Sari; Karhu, Auli; Aaltonen, Lauri; Zanke, Brent W.; Hudson, Thomas J.; Gallinger, Steven; Barclay, Ella; Martin, Lynn; Gorman, Maggie; Carvajal-Carmona, Luis; Walther, Axel; Kerr, David; Lubbe, Steven; Broderick, Peter; Chandler, Ian; Pittman, Alan; Penegar, Steven; Campbell, Harry; Tomlinson, Ian; Houlston, Richard S.

2016-01-01

Objective Colorectal cancer (CRC) has a substantial heritable component. Common genetic variation has been shown to contribute to CRC risk. In a large, multi-population study, we set out to assess the feasibility of CRC risk prediction using common genetic variant data, combined with other risk factors. We built a risk prediction model and applied it to the Scottish population using available data. Design Nine populations of European descent were studied to develop and validate colorectal cancer risk prediction models. Binary logistic regression was used to assess the combined effect of age, gender, family history (FH) and genotypes at 10 susceptibility loci that individually only modestly influence colorectal cancer risk. Risk models were generated from case-control data incorporating genotypes alone (n=39,266), and in combination with gender, age and family history (n=11,324). Model discriminatory performance was assessed using 10-fold internal cross-validation and externally using 4,187 independent samples. 10-year absolute risk was estimated by modelling genotype and FH with age- and gender-specific population risks. Results Median number of risk alleles was greater in cases than controls (10 vs 9, p<2.2×10−16), confirmed in external validation sets (Sweden p=1.2×10−6, Finland p=2×10−5). Mean per-allele increase in risk was 9% (OR 1.09; 95% CI 1.05–1.13). Discriminative performance was poor across the risk spectrum (area under curve (AUC) for genotypes alone - 0.57; AUC for genotype/age/gender/FH - 0.59). However, modelling genotype data, FH, age and gender with Scottish population data shows the practicalities of identifying a subgroup with >5% predicted 10-year absolute risk. Conclusion We show that genotype data provides additional information that complements age, gender and FH as risk factors. However, individualized genetic risk prediction is not currently feasible. Nonetheless, the modelling exercise suggests public health potential, since it is possible to stratify the population into CRC risk categories, thereby informing targeted prevention and surveillance. PMID:22490517

Validity and validation of expert (Q)SAR systems.

PubMed

Hulzebos, E; Sijm, D; Traas, T; Posthumus, R; Maslankiewicz, L

2005-08-01

At a recent workshop in Setubal (Portugal) principles were drafted to assess the suitability of (quantitative) structure-activity relationships ((Q)SARs) for assessing the hazards and risks of chemicals. In the present study we applied some of the Setubal principles to test the validity of three (Q)SAR expert systems and validate the results. These principles include a mechanistic basis, the availability of a training set and validation. ECOSAR, BIOWIN and DEREK for Windows have a mechanistic or empirical basis. ECOSAR has a training set for each QSAR. For half of the structural fragments the number of chemicals in the training set is >4. Based on structural fragments and log Kow, ECOSAR uses linear regression to predict ecotoxicity. Validating ECOSAR for three 'valid' classes results in predictivity of > or = 64%. BIOWIN uses (non-)linear regressions to predict the probability of biodegradability based on fragments and molecular weight. It has a large training set and predicts non-ready biodegradability well. DEREK for Windows predictions are supported by a mechanistic rationale and literature references. The structural alerts in this program have been developed with a training set of positive and negative toxicity data. However, to support the prediction only a limited number of chemicals in the training set is presented to the user. DEREK for Windows predicts effects by 'if-then' reasoning. The program predicts best for mutagenicity and carcinogenicity. Each structural fragment in ECOSAR and DEREK for Windows needs to be evaluated and validated separately.

Prospective validation of pathologic complete response models in rectal cancer: Transferability and reproducibility.

PubMed

van Soest, Johan; Meldolesi, Elisa; van Stiphout, Ruud; Gatta, Roberto; Damiani, Andrea; Valentini, Vincenzo; Lambin, Philippe; Dekker, Andre

2017-09-01

Multiple models have been developed to predict pathologic complete response (pCR) in locally advanced rectal cancer patients. Unfortunately, validation of these models normally omit the implications of cohort differences on prediction model performance. In this work, we will perform a prospective validation of three pCR models, including information whether this validation will target transferability or reproducibility (cohort differences) of the given models. We applied a novel methodology, the cohort differences model, to predict whether a patient belongs to the training or to the validation cohort. If the cohort differences model performs well, it would suggest a large difference in cohort characteristics meaning we would validate the transferability of the model rather than reproducibility. We tested our method in a prospective validation of three existing models for pCR prediction in 154 patients. Our results showed a large difference between training and validation cohort for one of the three tested models [Area under the Receiver Operating Curve (AUC) cohort differences model: 0.85], signaling the validation leans towards transferability. Two out of three models had a lower AUC for validation (0.66 and 0.58), one model showed a higher AUC in the validation cohort (0.70). We have successfully applied a new methodology in the validation of three prediction models, which allows us to indicate if a validation targeted transferability (large differences between training/validation cohort) or reproducibility (small cohort differences). © 2017 American Association of Physicists in Medicine.

An early-biomarker algorithm predicts lethal graft-versus-host disease and survival

PubMed Central

Hartwell, Matthew J.; Özbek, Umut; Holler, Ernst; Major-Monfried, Hannah; Reddy, Pavan; Aziz, Mina; Hogan, William J.; Ayuk, Francis; Efebera, Yvonne A.; Hexner, Elizabeth O.; Bunworasate, Udomsak; Qayed, Muna; Ordemann, Rainer; Wölfl, Matthias; Mielke, Stephan; Chen, Yi-Bin; Devine, Steven; Jagasia, Madan; Kitko, Carrie L.; Litzow, Mark R.; Kröger, Nicolaus; Locatelli, Franco; Morales, George; Nakamura, Ryotaro; Reshef, Ran; Rösler, Wolf; Weber, Daniela; Yanik, Gregory A.; Levine, John E.; Ferrara, James L.M.

2017-01-01

BACKGROUND. No laboratory test can predict the risk of nonrelapse mortality (NRM) or severe graft-versus-host disease (GVHD) after hematopoietic cellular transplantation (HCT) prior to the onset of GVHD symptoms. METHODS. Patient blood samples on day 7 after HCT were obtained from a multicenter set of 1,287 patients, and 620 samples were assigned to a training set. We measured the concentrations of 4 GVHD biomarkers (ST2, REG3α, TNFR1, and IL-2Rα) and used them to model 6-month NRM using rigorous cross-validation strategies to identify the best algorithm that defined 2 distinct risk groups. We then applied the final algorithm in an independent test set (n = 309) and validation set (n = 358). RESULTS. A 2-biomarker model using ST2 and REG3α concentrations identified patients with a cumulative incidence of 6-month NRM of 28% in the high-risk group and 7% in the low-risk group (P < 0.001). The algorithm performed equally well in the test set (33% vs. 7%, P < 0.001) and the multicenter validation set (26% vs. 10%, P < 0.001). Sixteen percent, 17%, and 20% of patients were at high risk in the training, test, and validation sets, respectively. GVHD-related mortality was greater in high-risk patients (18% vs. 4%, P < 0.001), as was severe gastrointestinal GVHD (17% vs. 8%, P < 0.001). The same algorithm can be successfully adapted to define 3 distinct risk groups at GVHD onset. CONCLUSION. A biomarker algorithm based on a blood sample taken 7 days after HCT can consistently identify a group of patients at high risk for lethal GVHD and NRM. FUNDING. The National Cancer Institute, American Cancer Society, and the Doris Duke Charitable Foundation. PMID:28194439

Derivation and validation of a multivariate model to predict mortality from pulmonary embolism with cancer: the POMPE-C tool

PubMed Central

Roy, Pierre-Marie; Than, Martin P.; Hernandez, Jackeline; Courtney, D. Mark; Jones, Alan E.; Penazola, Andrea; Pollack, Charles V.

2012-01-01

Background Clinical guidelines recommend risk stratification of patients with acute pulmonary embolism (PE). Active cancer increases risk of PE and worsens prognosis, but also causes incidental PE that may be discovered during cancer staging. No quantitative decision instrument has been derived specifically for patients with active cancer and PE. Methods Classification and regression technique was used to reduce 25 variables prospectively collected from 408 patients with AC and PE. Selected variables were transformed into a logistic regression model, termed POMPE-C, and compared with the pulmonary embolism severity index (PESI) score to predict the outcome variable of death within 30 days. Validation was performed in an independent sample of 182 patients with active cancer and PE. Results POMPE-C included eight predictors: body mass, heart rate >100, respiratory rate, SaO2%, respiratory distress, altered mental status, do not resuscitate status, and unilateral limb swelling. In the derivation set, the area under the ROC curve for POMPE-C was 0.84 (95% CI: 0.82-0.87), significantly greater than PESI (0.68, 0.60-0.76). In the validation sample, POMPE-C had an AUC of 0.86 (0.78-0.93). No patient with POMPE-C estimate ≤5% died within 30 days (0/50, 0-7%), whereas 10/13 (77%, 46-95%) with POMPE-C estimate >50% died within 30 days. Conclusion In patients with active cancer and PE, POMPE-C demonstrated good prognostic accuracy for 30 day mortality and better performance than PESI. If validated in a large sample, POMPE-C may provide a quantitative basis to decide treatment options for PE discovered during cancer staging and with advanced cancer. PMID:22475313

The healthy Nordic diet predicts muscle strength 10 years later in old women, but not old men.

PubMed

Perälä, Mia-Maria; von Bonsdorff, Mikaela B; Männistö, Satu; Salonen, Minna K; Simonen, Mika; Kanerva, Noora; Rantanen, Taina; Pohjolainen, Pertti; Eriksson, Johan G

2017-07-01

a number of nutrients have been found to be associated with better muscle strength and mass; however, the role of the whole diet on muscle strength and mass remains still unknown. to examine whether the healthy Nordic diet predicts muscle strength, and mass 10 years later among men and women. about 1,072 participants belong to the Helsinki Birth Cohort Study, born 1934-44. Diet was assessed with a validated food-frequency questionnaire during 2001-04. The Nordic diet score (NDS) was calculated. The score included Nordic fruits, vegetables, cereals, ratio of polyunsaturated to saturated fatty acids, low-fat milk, fish, red meat, total fat and alcohol. Higher scores indicated better adherence to the healthy Nordic diet. Hand grip strength, leg strength (knee extension) and muscle mass were measured during the follow-up, between 2011 and 2013. in women, each 1-unit increase in the NDS was related to 1.83 N greater leg strength (95% confidence interval [CI] 0.14-3.51; P = 0.034), and 1.44 N greater hand grip strength (95% CI: 0.04-2.84; P = 0.044). Women in the highest quartile of the NDS had on average 20.0 N greater knee extension results, and 14.2 N greater hand grip results than those in the lowest quartile. No such associations were observed among men. The NDS was not significantly related to muscle mass either in men or women. adherence to the healthy Nordic diet seems to protect from weaker muscle strength in old women. Therefore, the healthy Nordic diet may help to prevent disability. © The Author 2017. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For permissions, please email: journals.permissions@oup.com

Early Prediction of Intensive Care Unit-Acquired Weakness: A Multicenter External Validation Study.

PubMed

Witteveen, Esther; Wieske, Luuk; Sommers, Juultje; Spijkstra, Jan-Jaap; de Waard, Monique C; Endeman, Henrik; Rijkenberg, Saskia; de Ruijter, Wouter; Sleeswijk, Mengalvio; Verhamme, Camiel; Schultz, Marcus J; van Schaik, Ivo N; Horn, Janneke

2018-01-01

An early diagnosis of intensive care unit-acquired weakness (ICU-AW) is often not possible due to impaired consciousness. To avoid a diagnostic delay, we previously developed a prediction model, based on single-center data from 212 patients (development cohort), to predict ICU-AW at 2 days after ICU admission. The objective of this study was to investigate the external validity of the original prediction model in a new, multicenter cohort and, if necessary, to update the model. Newly admitted ICU patients who were mechanically ventilated at 48 hours after ICU admission were included. Predictors were prospectively recorded, and the outcome ICU-AW was defined by an average Medical Research Council score <4. In the validation cohort, consisting of 349 patients, we analyzed performance of the original prediction model by assessment of calibration and discrimination. Additionally, we updated the model in this validation cohort. Finally, we evaluated a new prediction model based on all patients of the development and validation cohort. Of 349 analyzed patients in the validation cohort, 190 (54%) developed ICU-AW. Both model calibration and discrimination of the original model were poor in the validation cohort. The area under the receiver operating characteristics curve (AUC-ROC) was 0.60 (95% confidence interval [CI]: 0.54-0.66). Model updating methods improved calibration but not discrimination. The new prediction model, based on all patients of the development and validation cohort (total of 536 patients) had a fair discrimination, AUC-ROC: 0.70 (95% CI: 0.66-0.75). The previously developed prediction model for ICU-AW showed poor performance in a new independent multicenter validation cohort. Model updating methods improved calibration but not discrimination. The newly derived prediction model showed fair discrimination. This indicates that early prediction of ICU-AW is still challenging and needs further attention.

The Predictive Validity of the Minnesota Reading Assessment for Students in Postsecondary Vocational Education Programs.

ERIC Educational Resources Information Center

Brown, James M.; Chang, Gerald

1982-01-01

The predictive validity of the Minnesota Reading Assessment (MRA) when used to project potential performance of postsecondary vocational-technical education students was examined. Findings confirmed the MRA to be a valid predictor, although the error in prediction varied between the criterion variables. (Author/GK)

Comparative Predictive Validity of the New MCAT Using Different Admissions Criteria.

ERIC Educational Resources Information Center

Golmon, Melton E.; Berry, Charles A.

1981-01-01

New Medical College Admission Test (MCAT) scores and undergraduate academic achievement were examined for their validity in predicting the performance of two select student populations at Northwestern University Medical School. The data support the hypothesis that New MCAT scores possess substantial predictive validity. (Author/MLW)

Prediction of adult height in girls: the Beunen-Malina-Freitas method.

PubMed

Beunen, Gaston P; Malina, Robert M; Freitas, Duarte L; Thomis, Martine A; Maia, José A; Claessens, Albrecht L; Gouveia, Elvio R; Maes, Hermine H; Lefevre, Johan

2011-12-01

The purpose of this study was to validate and cross-validate the Beunen-Malina-Freitas method for non-invasive prediction of adult height in girls. A sample of 420 girls aged 10-15 years from the Madeira Growth Study were measured at yearly intervals and then 8 years later. Anthropometric dimensions (lengths, breadths, circumferences, and skinfolds) were measured; skeletal age was assessed using the Tanner-Whitehouse 3 method and menarcheal status (present or absent) was recorded. Adult height was measured and predicted using stepwise, forward, and maximum R (2) regression techniques. Multiple correlations, mean differences, standard errors of prediction, and error boundaries were calculated. A sample of the Leuven Longitudinal Twin Study was used to cross-validate the regressions. Age-specific coefficients of determination (R (2)) between predicted and measured adult height varied between 0.57 and 0.96, while standard errors of prediction varied between 1.1 and 3.9 cm. The cross-validation confirmed the validity of the Beunen-Malina-Freitas method in girls aged 12-15 years, but at lower ages the cross-validation was less consistent. We conclude that the Beunen-Malina-Freitas method is valid for the prediction of adult height in girls aged 12-15 years. It is applicable to European populations or populations of European ancestry.

Neutrophil-to-lymphocyte ratio and mural nodule height as predictive factors for malignant intraductal papillary mucinous neoplasms.

PubMed

Watanabe, Yusuke; Niina, Yusuke; Nishihara, Kazuyoshi; Okayama, Takafumi; Tamiya, Sadafumi; Nakano, Toru

2018-01-15

Accurate preoperative prediction for malignant IPMN is still challenging. The aim of this study was to investigate the validity of neutrophil-to-lymphocyte ratio (NLR) and mural nodule height (MNH) for predicting malignant intraductal papillary mucinous neoplasm (IPMN). The medical records of 60 patients who underwent pancreatectomy for IPMN were retrospectively reviewed. NLR tended to be higher in malignant IPMN (median: 2.23) than in benign IPMN (median: 2.04; p = .14). MNH was significantly greater in malignant IPMN (median: 16 mm) than in benign IPMN (median: 8 mm; p < .01). The optimal cutoff values for the NLR and MNH were 3.60 and 11 mm, respectively. The sensitivity and specificity of NLR ≥3.60 for predicting malignant IPMN were 40% and 93%, and those of MNH ≥11 mm were 73% and 77%, respectively. Univariate analysis revealed that NLR ≥3.60 (p < .01) and MNH ≥11 mm (p < .01) were significant predictive factors. On multivariate analysis, enhanced solid component was identified as an independent factor, but NLR ≥3.60 and MNH ≥11 mm were not. NLR and MNH are suboptimal tests in predicting malignant IPMN; however, they can be useful to assist in clinical decision-making.

RF model of the distribution system as a communication channel, phase 2. Volume 1: Summary Report

NASA Technical Reports Server (NTRS)

Rustay, R. C.; Gajjar, J. T.; Rankin, R. W.; Wentz, R. C.; Wooding, R.

1982-01-01

The design, implementation, and verification of a computerized model for predicting the steady-state sinusoidal response of radial (tree) configured distribution feeders was undertaken. That work demonstrated the feasibility and validity based on verification measurements made on a limited size portion of an actual live feeder. On that basis a follow-on effort concerned with (1) extending the verification based on a greater variety of situations and network size, (2) extending the model capabilities for reverse direction propagation, (3) investigating parameter sensitivities, (4) improving transformer models, and (5) investigating procedures/fixes for ameliorating propagation trouble spots was conducted. Results are summarized.

Application of a Framework to Assess the Usefulness of Alternative Sepsis Criteria.

PubMed

Seymour, Christopher W; Coopersmith, Craig M; Deutschman, Clifford S; Gesten, Foster; Klompas, Michael; Levy, Mitchell; Martin, Gregory S; Osborn, Tiffany M; Rhee, Chanu; Warren, David K; Watson, R Scott; Angus, Derek C

2016-03-01

The current definition of sepsis is life-threatening, acute organ dysfunction secondary to a dysregulated host response to infection. Criteria to operationalize this definition can be judged by six domains of usefulness (reliability, content, construct and criterion validity, measurement burden, and timeliness). The relative importance of these six domains depends on the intended purpose for the criteria (clinical care, basic and clinical research, surveillance, or quality improvement [QI] and audit). For example, criteria for clinical care should have high content and construct validity, timeliness, and low measurement burden to facilitate prompt care. Criteria for surveillance or QI/audit place greater emphasis on reliability across individuals and sites and lower emphasis on timeliness. Criteria for clinical trials require timeliness to ensure prompt enrollment and reasonable reliability but can tolerate high measurement burden. Basic research also tolerates high measurement burden and may not need stability over time. In an illustrative case study, we compared examples of criteria designed for clinical care, surveillance and QI/audit among 396,241 patients admitted to 12 academic and community hospitals in an integrated health system. Case rates differed four-fold and mortality three-fold. Predictably, clinical care criteria, which emphasized timeliness and low burden and therefore used vital signs and routine laboratory tests, had the greater case identification with lowest mortality. QI/audit criteria, which emphasized reliability and criterion validity, used discharge information and had the lowest case identification with highest mortality. Using this framework to identify the purpose and apply domains of usefulness can help with the evaluation of existing sepsis diagnostic criteria and provide a roadmap for future work.

Longitudinal predictors of school-age academic achievement: unique contributions of toddler-age aggression, oppositionality, inattention, and hyperactivity.

PubMed

Brennan, Lauretta M; Shaw, Daniel S; Dishion, Thomas J; Wilson, Melvin

2012-11-01

This project examined the unique predictive validity of parent ratings of toddler-age aggression, oppositionality, inattention, and hyperactivity-impulsivity to academic achievement at school-age in a sample of 566 high-risk children and families. The study also investigated potential indirect effects of the Family Check-Up on school-age academic achievement through changes in child behavior problems. The results demonstrated that toddler-age aggression was most consistently associated with school-age academic achievement, albeit modestly. Moreover, findings showed that the intervention predicted greater decreases in aggression from ages 2-3 to 4-5 compared to controls. The results suggest that in high-risk toddler-aged children, aggression may be a more consistent predictor of school-age academic achievement than other externalizing dimensions, which has implications for early identification and efforts to promote children's adaptation.

The Trivers–Willard hypothesis: sex ratio or investment?

PubMed Central

Veller, Carl; Haig, David; Nowak, Martin A.

2016-01-01

The Trivers–Willard hypothesis has commonly been considered to predict two things. First, that a mother in good condition should bias the sex ratio of her offspring towards males (if males exhibit greater variation in reproductive value). Second, that a mother in good condition should invest more per son than per daughter. These two predictions differ empirically, mechanistically and, as we demonstrate here, theoretically too. We construct a simple model of sex allocation that allows simultaneous analysis of both versions of the Trivers–Willard hypothesis. We show that the sex ratio version holds under very general conditions, being valid for a large class of male and female fitness functions. The investment version, on the other hand, is shown to hold only for a small subset of male and female fitness functions. Our results help to make sense of the observation that the sex ratio version is empirically more successful than the investment version. PMID:27170721

Artificial neural network study on organ-targeting peptides

NASA Astrophysics Data System (ADS)

Jung, Eunkyoung; Kim, Junhyoung; Choi, Seung-Hoon; Kim, Minkyoung; Rhee, Hokyoung; Shin, Jae-Min; Choi, Kihang; Kang, Sang-Kee; Lee, Nam Kyung; Choi, Yun-Jaie; Jung, Dong Hyun

2010-01-01

We report a new approach to studying organ targeting of peptides on the basis of peptide sequence information. The positive control data sets consist of organ-targeting peptide sequences identified by the peroral phage-display technique for four organs, and the negative control data are prepared from random sequences. The capacity of our models to make appropriate predictions is validated by statistical indicators including sensitivity, specificity, enrichment curve, and the area under the receiver operating characteristic (ROC) curve (the ROC score). VHSE descriptor produces statistically significant training models and the models with simple neural network architectures show slightly greater predictive power than those with complex ones. The training and test set statistics indicate that our models could discriminate between organ-targeting and random sequences. We anticipate that our models will be applicable to the selection of organ-targeting peptides for generating peptide drugs or peptidomimetics.

Emotional Reactivity and Regulation in Head Start Children: Links to Ecologically-Valid Behaviors and Internalizing Problems

PubMed Central

Morgan, Judith K.; Izard, Carroll E.; Hyde, Christopher

2013-01-01

Children’s emotional reactivity may interact with their regulatory behaviors to contribute to internalizing problems and social functioning even early in development. Ninety-one preschool children participated in a longitudinal project examining children’s reactivity and regulatory behaviors as predictors of internalizing problems and positive and negative social behavior in the classroom. Children who paired negative emotion expression with disengagement during a laboratory task showed higher levels of internalizing problems and more negative social behavior in the classroom six months later. Positive emotion expression paired with engagement during a laboratory task predicted more positive social behavior in the classroom six months later. Physiological reactivity and regulation also predicted children’s social behavior in the classroom. Findings suggest that preschool children with maladaptive reactivity and regulatory patterns may be at greater risk for internalizing problems even in early childhood. PMID:25067866

Predictors of delay in heart failure patients and consequences for outcomes.

PubMed

Sethares, Kristen A; Chin, Elizabeth; Jurgens, Corrine Y

2015-02-01

Persons with heart failure (HF) symptoms delay up to 7 days before seeking treatment. Delay can result in worse symptoms and potentially impact outcomes. The purpose of this review was to describe predictors and outcomes of delay in HF patients. Demographic factors, increased symptom number, social factors, greater HF knowledge, lower anxiety, and depression predicted increased delay. HF patients had difficulty recognizing and interpreting symptoms of HF. Results are conflicting related to symptom pattern, time of care seeking, and history of HF as predictors of delay. The only outcome predicted by delay was length of stay with those delaying longer reporting longer lengths of stay. Future research related to delay should include theoretical frameworks and larger, more ethnically diverse samples from multiple sites and link delay to outcomes. Valid and reliable instruments are needed to measure delay and related factors. HF education should include supportive others.

Assessing fitness-for-duty and predicting performance with cognitive neurophysiological measures

NASA Astrophysics Data System (ADS)

Smith, Michael E.; Gevins, Alan

2005-05-01

Progress is described in developing a novel test of neurocognitive status for fitness-for-duty testing. The Sustained Attention & Memory (SAM) test combines neurophysiologic (EEG) measures of brain activation with performance measures during a psychometric test of sustained attention and working memory, and then gauges changes in neurocognitive status relative to an individual"s normative baseline. In studies of the effects of common psychoactive substances that can affect job performance, including sedating antihistamines, caffeine, alcohol, marijuana, and prescription medications, test sensitivity was greater for the combined neurophysiological and performance measures than for task performance measures by themselves. The neurocognitive effects of overnight sleep deprivation were quite evident, and such effects predicted subsequent performance impairment on a flight simulator task. Sensitivity to diurnal circadian variations was also demonstrated. With further refinement and independent validation, the SAM Test may prove useful for assessing readiness-to-perform in high-asset personnel working in demanding, high risk situations.

Measurement of pH in whole blood by near-infrared spectroscopy

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

Alam, M. Kathleen; Maynard, John D.; Robinson, M. Ries

1999-03-01

Whole blood pH has been determined {ital in vitro} by using near-infrared spectroscopy over the wavelength range of 1500 to 1785 nm with multivariate calibration modeling of the spectral data obtained from two different sample sets. In the first sample set, the pH of whole blood was varied without controlling cell size and oxygen saturation (O{sub 2} Sat) variation. The result was that the red blood cell (RBC) size and O{sub 2} Sat correlated with pH. Although the partial least-squares (PLS) multivariate calibration of these data produced a good pH prediction cross-validation standard error of prediction (CVSEP)=0.046, R{sup 2}=0.982, themore » spectral data were dominated by scattering changes due to changing RBC size that correlated with the pH changes. A second experiment was carried out where the RBC size and O{sub 2} Sat were varied orthogonally to the pH variation. A PLS calibration of the spectral data obtained from these samples produced a pH prediction with an R{sup 2} of 0.954 and a cross-validated standard error of prediction of 0.064 pH units. The robustness of the PLS calibration models was tested by predicting the data obtained from the other sets. The predicted pH values obtained from both data sets yielded R{sup 2} values greater than 0.9 once the data were corrected for differences in hemoglobin concentration. For example, with the use of the calibration produced from the second sample set, the pH values from the first sample set were predicted with an R{sup 2} of 0.92 after the predictions were corrected for bias and slope. It is shown that spectral information specific to pH-induced chemical changes in the hemoglobin molecule is contained within the PLS loading vectors developed for both the first and second data sets. It is this pH specific information that allows the spectra dominated by pH-correlated scattering changes to provide robust pH predictive ability in the uncorrelated data, and visa versa. {copyright} {ital 1999} {ital Society for Applied Spectroscopy}« less

Construct Validity of the Emotional Eating Scale Adapted for Children and Adolescents

PubMed Central

Vannucci, Anna; Tanofsky-Kraff, Marian; Shomaker, Lauren B.; Ranzenhofer, Lisa M.; Matheson, Brittany E.; Cassidy, Omni L.; Zocca, Jaclyn M.; Kozlosky, Merel; Yanovski, Susan Z.; Yanovski, Jack A.

2012-01-01

Background Emotional eating, defined as eating in response to a range of negative emotions, is common in youth. Yet, there are few easily administered and well-validated methods to assess emotional eating in pediatric populations. Objective The current study tested the construct validity of the Emotional Eating Scale Adapted for Children and Adolescents (EES-C) by examining its relationship to observed emotional eating at laboratory test meals. Method One hundred fifty-one youth (8-18 years) participated in two multi-item lunch buffet meals on separate days. They ate ad libitum after being instructed to “eat as much as you would at a normal meal” or to “let yourself go and eat as much as you want.” State negative affect was assessed immediately prior to each meal. The EES-C was completed three months, on average, prior to the first test meal. Results Among youth with high EES-C total scores, but not low EES-C scores, higher pre-meal state negative affect was related to greater total energy intake at both meals, with and without the inclusion of age, race, sex, and BMI-z as covariates (ps < 0.03). Discussion The EES-C demonstrates good construct validity for children and adolescents’ observed energy intake across laboratory test meals designed to capture both normal and disinhibited eating. Future research is required to evaluate the construct validity of the EES-C in the natural environment and the predictive validity of the EES-C longitudinally. PMID:22124451

Conceptual and measurement issues in early parenting practices research: an epidemiologic perspective.

PubMed

Walker, Lorraine O; Kirby, Russell S

2010-11-01

Early parenting practices are significant to public health because of their linkages to child health outcomes. This paper focuses on the current state of the science regarding conceptual frameworks that incorporate early parenting practices in epidemiologic research and evidence supporting reliability and validity of self-report measures of such practices. Guided by a provisional definition of early parenting practices, literature searches were conducted using PubMed and Sociological Abstracts. Twenty-five published studies that included parent-report measures of early parenting practices met inclusion criteria. Findings on conceptual frameworks were analyzed qualitatively, whereas evidence of reliability and validity were organized into four domains (safety, feeding and oral health, development promotion, and discipline) and summarized in tabular form. Quantitative estimates of measures of reliability and validity were extracted, where available. We found two frameworks incorporating early parenting: one a program theory and the other a predictive model. We found no reported evidence of the reliability or validity of parent-report measures of safety or feeding and oral health practices. Evidence for reliability and validity were reported with greater frequency for development promotion and discipline practices, but report of the most pertinent type of reliability estimation, test-retest reliability, was rare. Failure to examine associations of early parenting practices with any child outcomes within most studies resulted in missed opportunities to indirectly estimate validity of parenting practice measures. Stronger evidence concerning specific measurement properties of early parenting practices is important to advancing maternal-child research, surveillance, and practice.

Methacholine challenge testing: improved patient comfort with a 2-tiered protocol.

PubMed

Segel, Michael J; Rabinovich, Einat; Schwarz, Yehuda; Ben-Dov, Issahar

2013-06-01

The methacholine challenge test (MCT) is a test of bronchial hyperreactivity used as an aid in the diagnosis of asthma. MCT results are reported as the provocation concentration at which the forced expiratory volume in 1 second (FEV1) decreases 20% (PC20). The requirement for a 20% or greater decrease in FEV1 results in precipitous decreases in FEV1 in some patients. To improve MCT safety without compromising accuracy. We performed a retrospective analysis of 879 consecutive MCTs (derivation cohort). A novel protocol for MCT was developed and validated in a cohort of 564 MCTs performed in a second institution. In comparison with a PC20 cutoff of less than 8 mg/mL, a provocation concentration at which the FEV1 decreases 10% (PC10) cutoff of 1 mg/mL or less has a sensitivity of 86%, a specificity of 98%, a positive predictive value (PPV) of 97%, and a negative predictive value (NPV) of 91%. We propose a novel 2-tiered protocol for MCT. If the PC10 is 1 mg/mL or less, bronchial hyperreactivity is present; if the PC10 is greater than 1 mg/mL, the test is continued until the provocative concentration is 8 mg/mL or a 20% decrease in FEV1 is achieved. Compared with the standard protocol, the proposed protocol has a sensitivity, specificity, PPV, NPV, and overall accuracy of 100%, 98%, 97.6%, 100%, and 99%, respectively. The modified protocol would have enabled us to avoid 26 of 42 cases (62%) in which a 40% or greater decrease in FEV1 occurred and would save 0.65 dose for every MCT performed. The 2-tiered protocol performed well in the validation cohort; sensitivity, specificity, PPV, NPV, and overall accuracy were 100%, 98%, 87%, 100%, and 98%, respectively. The proposed 2-tiered protocol is accurate, saves time, and avoids precipitous decreases in FEV1. Copyright © 2013 American College of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.

Teachers' Grade Assignment and the Predictive Validity of Criterion-Referenced Grades

ERIC Educational Resources Information Center

Thorsen, Cecilia; Cliffordson, Christina

2012-01-01

Research has found that grades are the most valid instruments for predicting educational success. Why grades have better predictive validity than, for example, standardized tests is not yet fully understood. One possible explanation is that grades reflect not only subject-specific knowledge and skills but also individual differences in other…

Attenuation of Frontostriatal Connectivity During Reward Processing Predicts Response to Psychotherapy in Major Depressive Disorder.

PubMed

Walsh, Erin; Carl, Hannah; Eisenlohr-Moul, Tory; Minkel, Jared; Crowther, Andrew; Moore, Tyler; Gibbs, Devin; Petty, Chris; Bizzell, Josh; Smoski, Moria J; Dichter, Gabriel S

2017-03-01

There are few reliable predictors of response to antidepressant treatments. In the present investigation, we examined pretreatment functional brain connectivity during reward processing as a potential predictor of response to Behavioral Activation Treatment for Depression (BATD), a validated psychotherapy that promotes engagement with rewarding stimuli and reduces avoidance behaviors. Thirty-three outpatients with major depressive disorder (MDD) and 20 matched controls completed two runs of the monetary incentive delay task during functional magnetic resonance imaging after which participants with MDD received up to 15 sessions of BATD. Seed-based generalized psychophysiological interaction analyses focused on task-based connectivity across task runs, as well as the attenuation of connectivity from the first to the second run of the task. The average change in Beck Depression Inventory-II scores due to treatment was 10.54 points, a clinically meaningful response. Groups differed in seed-based functional connectivity among multiple frontostriatal regions. Hierarchical linear modeling revealed that improved treatment response to BATD was predicted by greater connectivity between the left putamen and paracingulate gyrus during reward anticipation. In addition, MDD participants with greater attenuation of connectivity between several frontostriatal seeds, and midline subcallosal cortex and left paracingulate gyrus demonstrated improved response to BATD. These findings indicate that pretreatment frontostriatal functional connectivity during reward processing is predictive of response to a psychotherapy modality that promotes improving approach-related behaviors in MDD. Furthermore, connectivity attenuation among reward-processing regions may be a particularly powerful endophenotypic predictor of response to BATD in MDD.

Repeatable Battery for the Assessment of Neuropsychological Status: Effort Index Cutoff Scores for Psychometrically Defined Malingering Groups in a Military Sample.

PubMed

Jones, Alvin

2016-05-01

This research examined cutoff scores for the Effort Index (EI), an embedded measure of performance validity, for the Repeatable Battery for the Assessment of Neuropsychological Status. EI cutoffs were explored for an active-duty military sample composed mostly of patients with traumatic brain injury. Four psychometrically defined malingering groups including a definite malingering, probable to definite malingering, probable malingering, and a combined group were formed based on the number of validity tests failed. Excellent specificities (0.97 or greater) were found for all cutoffs examined (EI ≥ 1 to EI ≥ 3). Excellent sensitivities (0.80 to 0.89) were also found for the definite malingering group. Sensitivities were 0.49 or below for the other groups. Positive and negative predictive values and likelihood ratios indicated that the cutoffs for EI were much stronger for ruling-in than ruling-out malingering. Analyses indicated the validity tests used to form the malingering groups were uncorrelated, which serves to enhance the validity of the formation of the malingering groups. Cutoffs were similar to other research using samples composed predominantly of head-injured individuals. Published by Oxford University Press 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

The dominance of introspective measures and what this implies: The example of environmental attitude.

PubMed

Otto, Siegmar; Kröhne, Ulf; Richter, David

2018-01-01

The behavioral sciences, including most of psychology, seek to explain and predict behavior with the help of theories and models that involve concepts (e.g., attitudes) that are subsequently translated into measures. Currently, some subdisciplines such as social psychology focus almost exclusively on measures that demand reflection or even introspection when administered to persons. We argue that such a focus hinders progress in explaining behavior. One major reason is that such an exclusive focus on reflections results in common method bias, which then produces spurious relations, or in other words, low discriminant validity. Without the valid measurement of theoretical concepts, theoretical assumptions cannot be tested, and hence, theory development will be hampered. We argue that the use of a greater variety of methods would reduce these problems and would in turn foster theory building. Using a representative sample of N = 472 participants (age: M = 51.0, SD = 17.7; 54% female), we compared the validity of a classical introspective attitude measure (i.e., the New Ecological Paradigm) with that of an alternative attitude measure (i.e., the General Ecological Behavior scale). The latter measure, which was based on self-reported behavior, showed substantially better validity that we argue could aid theory development.

The dominance of introspective measures and what this implies: The example of environmental attitude

PubMed Central

Kröhne, Ulf; Richter, David

2018-01-01

The behavioral sciences, including most of psychology, seek to explain and predict behavior with the help of theories and models that involve concepts (e.g., attitudes) that are subsequently translated into measures. Currently, some subdisciplines such as social psychology focus almost exclusively on measures that demand reflection or even introspection when administered to persons. We argue that such a focus hinders progress in explaining behavior. One major reason is that such an exclusive focus on reflections results in common method bias, which then produces spurious relations, or in other words, low discriminant validity. Without the valid measurement of theoretical concepts, theoretical assumptions cannot be tested, and hence, theory development will be hampered. We argue that the use of a greater variety of methods would reduce these problems and would in turn foster theory building. Using a representative sample of N = 472 participants (age: M = 51.0, SD = 17.7; 54% female), we compared the validity of a classical introspective attitude measure (i.e., the New Ecological Paradigm) with that of an alternative attitude measure (i.e., the General Ecological Behavior scale). The latter measure, which was based on self-reported behavior, showed substantially better validity that we argue could aid theory development. PMID:29447235

Comparison and validation of injury risk classifiers for advanced automated crash notification systems.

PubMed

Kusano, Kristofer; Gabler, Hampton C

2014-01-01

The odds of death for a seriously injured crash victim are drastically reduced if he or she received care at a trauma center. Advanced automated crash notification (AACN) algorithms are postcrash safety systems that use data measured by the vehicles during the crash to predict the likelihood of occupants being seriously injured. The accuracy of these models are crucial to the success of an AACN. The objective of this study was to compare the predictive performance of competing injury risk models and algorithms: logistic regression, random forest, AdaBoost, naïve Bayes, support vector machine, and classification k-nearest neighbors. This study compared machine learning algorithms to the widely adopted logistic regression modeling approach. Machine learning algorithms have not been commonly studied in the motor vehicle injury literature. Machine learning algorithms may have higher predictive power than logistic regression, despite the drawback of lacking the ability to perform statistical inference. To evaluate the performance of these algorithms, data on 16,398 vehicles involved in non-rollover collisions were extracted from the NASS-CDS. Vehicles with any occupants having an Injury Severity Score (ISS) of 15 or greater were defined as those requiring victims to be treated at a trauma center. The performance of each model was evaluated using cross-validation. Cross-validation assesses how a model will perform in the future given new data not used for model training. The crash ΔV (change in velocity during the crash), damage side (struck side of the vehicle), seat belt use, vehicle body type, number of events, occupant age, and occupant sex were used as predictors in each model. Logistic regression slightly outperformed the machine learning algorithms based on sensitivity and specificity of the models. Previous studies on AACN risk curves used the same data to train and test the power of the models and as a result had higher sensitivity compared to the cross-validated results from this study. Future studies should account for future data; for example, by using cross-validation or risk presenting optimistic predictions of field performance. Past algorithms have been criticized for relying on age and sex, being difficult to measure by vehicle sensors, and inaccuracies in classifying damage side. The models with accurate damage side and including age/sex did outperform models with less accurate damage side and without age/sex, but the differences were small, suggesting that the success of AACN is not reliant on these predictors.

Predictive validity of the HCR-20 for inpatient aggression: the effect of intellectual disability on accuracy.

PubMed

O'Shea, L E; Picchioni, M M; McCarthy, J; Mason, F L; Dickens, G L

2015-11-01

People with intellectual disability (ID) account for a large proportion of aggressive incidents in secure and forensic psychiatric services. Although the Historical, Clinical, Risk Management 20 (HCR-20) has good predictive validity in inpatient settings, it does not perform equally in all groups and there is little evidence for its efficacy in those with ID. A pseudo-prospective cohort study of the predictive efficacy of the HCR-20 for those with ID (n = 109) was conducted in a UK secure mental health setting using routinely collected risk data. Performance of the HCR-20 in the ID group was compared with a comparison group of adult inpatients without an ID (n = 504). Analysis controlled for potential covariates including security level, length of stay, gender and diagnosis. The HCR-20 total score was a significant predictor of any aggression and of physical aggression for both groups, although the area under the curve values did not reach the threshold for a large effect size. The clinical subscale performed significantly better in those without an ID compared with those with. The ID group had a greater number of relevant historical and risk management items. The clinicians' summary judgment significantly predicted both types of aggressive outcomes in the ID group, but did not predict either in those without an ID. This study demonstrates that, after controlling for a range of potential covariates, the HCR-20 is a significant predictor of inpatient aggression in people with an ID and performs as well as for a comparison group of mentally disordered individuals without ID. The potency of HCR-20 subscales and items varied between the ID and comparison groups suggesting important target areas for improved prediction and risk management interventions in those with ID. © 2015 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

The stroke impairment assessment set: its internal consistency and predictive validity.

PubMed

Tsuji, T; Liu, M; Sonoda, S; Domen, K; Chino, N

2000-07-01

To study the scale quality and predictive validity of the Stroke Impairment Assessment Set (SIAS) developed for stroke outcome research. Rasch analysis of the SIAS; stepwise multiple regression analysis to predict discharge functional independence measure (FIM) raw scores from demographic data, the SIAS scores, and the admission FIM scores; cross-validation of the prediction rule. Tertiary rehabilitation center in Japan. One hundred ninety stroke inpatients for the study of the scale quality and the predictive validity; a second sample of 116 stroke inpatients for the cross-validation study. Mean square fit statistics to study the degree of fit to the unidimensional model; logits to express item difficulties; discharge FIM scores for the study of predictive validity. The degree of misfit was acceptable except for the shoulder range of motion (ROM), pain, visuospatial function, and speech items; and the SIAS items could be arranged on a common unidimensional scale. The difficulty patterns were identical at admission and at discharge except for the deep tendon reflexes, ROM, and pain items. They were also similar for the right- and left-sided brain lesion groups except for the speech and visuospatial items. For the prediction of the discharge FIM scores, the independent variables selected were age, the SIAS total scores, and the admission FIM scores; and the adjusted R2 was .64 (p < .0001). Stability of the predictive equation was confirmed in the cross-validation sample (R2 = .68, p < .001). The unidimensionality of the SIAS was confirmed, and the SIAS total scores proved useful for stroke outcome prediction.

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.

Attentional effects on orientation judgements are dependent on memory consolidation processes.

PubMed

Haskell, Christie; Anderson, Britt

2016-11-01

Are the effects of memory and attention on perception synergistic, antagonistic, or independent? Tested separately, memory and attention have been shown to affect the accuracy of orientation judgements. When multiple stimuli are presented sequentially versus simultaneously, error variance is reduced. When a target is validly cued, precision is increased. What if they are manipulated together? We combined memory and attention manipulations in an orientation judgement task to answer this question. Two circular gratings were presented sequentially or simultaneously. On some trials a brief luminance cue preceded the stimuli. Participants were cued to report the orientation of one of the two gratings by rotating a response grating. We replicated the finding that error variance is reduced on sequential trials. Critically, we found interacting effects of memory and attention. Valid cueing reduced the median, absolute error only when two stimuli appeared together and improved it to the level of performance on uncued sequential trials, whereas invalid cueing always increased error. This effect was not mediated by cue predictiveness; however, predictive cues reduced the standard deviation of the error distribution, whereas nonpredictive cues reduced "guessing". Our results suggest that, when the demand on memory is greater than a single stimulus, attention is a bottom-up process that prioritizes stimuli for consolidation. Thus attention and memory are synergistic.

Simulation of Three-Dimensional Symmetric and Asymmetric Instabilities in Attachment-Line Boundary Layers

NASA Technical Reports Server (NTRS)

Joslin, Ronald D.

1996-01-01

On a swept wing, contamination along the leading edge, Tollmien-Schlichting waves, stationary or traveling crossflow vortices, and/or Taylor-Gortler vortices can cause the catastrophic breakdown of laminar to turbulent flow, which leads to increased skin-friction drag for the aircraft. The discussion in this Note will be limited to disturbances which evolve along the attachment line (leading edge of swept wing). If the Reynolds number of the attachment-line boundary layer is greater than some critical value, then the complete wing is inevitably engulfed in turbulent flow. Essentially, there are two critical Reynolds number points that must be considered. The first is for small-amplitude disturbances, and the second is for bypass transition. The present study will use direct numerical simulations to validate a linear 2D-eigenvalue prediction method based on parabolized stability equations by Lin and Malik. This method is considered because it suggests that a number of symmetric and asymmetric modes exist and are stable or unstable on the attachment line depending on the Reynolds number. If validated, the approach would predict a number of modes which are linearly damped in the Reynolds number regime 100 to 245; however, these modes may grow nonlinearly and provide an explanation to this region.

New Measures Assessing Predictors of Academic Persistence for Historically Underrepresented Racial/Ethnic Undergraduates in Science

PubMed Central

Byars-Winston, Angela; Rogers, Jenna; Branchaw, Janet; Pribbenow, Christine; Hanke, Ryan; Pfund, Christine

2016-01-01

An important step in broadening participation of historically underrepresented (HU) racial/ethnic groups in the sciences is the creation of measures validated with these groups that will allow for greater confidence in the results of investigations into factors that predict their persistence. This study introduces new measures of theoretically derived factors emanating from social cognitive and social identity theories associated with persistence for HU racial/ethnic groups in science disciplines. The purpose of this study was to investigate: 1) the internal reliability and factor analyses for measures of research-related self-efficacy beliefs, sources of self-efficacy, outcome expectations, and science identity; and 2) potential group differences in responses to the measures, examining the main and interaction effects of gender and race/ethnicity. Survey data came from a national sample of 688 undergraduate students in science majors who were primarily black/African American and Hispanic/Latino/a with a 2:1 ratio of females to males. Analyses yielded acceptable validity statistics and race × gender group differences were observed in mean responses to several measures. Implications for broadening participation of HU groups in the sciences are discussed regarding future tests of predictive models of student persistence and training programs to consider cultural diversity factors in their design. PMID:27521235

Modeling thermal infrared (2-14 micrometer) reflectance spectra of frost and snow

NASA Technical Reports Server (NTRS)

Wald, Andrew E.

1994-01-01

Existing theories of radiative transfer in close-packed media assume that each particle scatters independently of its neighbors. For opaque particles, such as are common in the thermal infrared, this assumption is not valid, and these radiative transfer theories will not be accurate. A new method is proposed, called 'diffraction subtraction', which modifies the scattering cross section of close-packed large, opaque spheres to account for the effect of close packing on the diffraction cross section of a scattering particle. This method predicts the thermal infrared reflectance of coarse (greater than 50 micrometers radius), disaggregated granular snow. However, such coarse snow is typically old and metamorphosed, with adjacent grains welded together. The reflectance of such a welded block can be described as partly Fresnel in nature and cannot be predicted using Mie inputs to radiative transfer theory. Owing to the high absorption coefficient of ice in the thermal infrared, a rough surface reflectance model can be used to calculate reflectance from such a block. For very small (less than 50 micrometers), disaggregated particles, it is incorrect in principle to treat diffraction independently of reflection and refraction, and the theory fails. However, for particles larger than 50 micrometers, independent scattering is a valid assumption, and standard radiative transfer theory works.

The dimensional salience solution to the expectancy-value muddle: an extension.

PubMed

Newton, Joshua D; Newton, Fiona J; Ewing, Michael T

2014-01-01

The theory of reasoned action (TRA) specifies a set of expectancy-value, belief-based frameworks that underpin attitude (behavioural beliefs × outcome evaluations) and subjective norm (normative beliefs × motivation to comply). Unfortunately, the most common method for analysing these frameworks generates statistically uninterpretable findings, resulting in what has been termed the 'expectancy-value muddle'. Recently, however, a dimensional salience approach was found to resolve this muddle for the belief-based framework underpinning attitude. An online survey of 262 participants was therefore conducted to determine whether the dimensional salience approach could also be applied to the belief-based framework underpinning subjective norm. Results revealed that motivations to comply were greater for salient, as opposed to non-salient, social referents. The belief-based framework underpinning subjective norm was therefore represented by evaluating normative belief ratings for salient social referents. This modified framework was found to predict subjective norm, although predictions were greater when participants were forced to select five salient social referents rather than being free to select any number of social referents. These findings validate the use of the dimensional salience approach for examining the belief-based frameworks underpinning subjective norm. As such, this approach provides a complete solution to addressing the expectancy-value muddle in the TRA.

An Ecologically Based Model of Alcohol-Consumption Decision Making: Evidence for the Discriminative and Predictive Role of Contextual Reward and Punishment Information*

PubMed Central

Bogg, Tim; Finn, Peter R.

2009-01-01

Objective: Using insights from Ecological Systems Theory and Reinforcement Sensitivity Theory, the current study assessed the utility of a series of hypothetical role-based alcohol-consumption scenarios that varied in their presentation of rewarding and punishing information. Method: The scenarios, along with measures of impulsive sensation seeking and a self-report of weekly alcohol consumption, were administered to a sample of alcohol-dependent and non-alcohol-dependent college-age individuals (N = 170). Results: The results showed scenario attendance decisions were largely unaffected by alcohol-dependence status and variations in contextual reward and punishment information. In contrast to the attendance findings, the results for the alcohol-consumption decisions showed alcohol-dependent individuals reported a greater frequency of deciding to drink, as well as indicating greater alcohol consumption in the contexts of complementary rewarding or nonpunishing information. Regression results provided evidence for the criterion-related validity of scenario outcomes in an account of diagnostic alcohol problems. Conclusions: The results are discussed in terms of the conceptual and predictive gains associated with an assessment approach to alcohol-consumption decision making that combines situational information organized and balanced through the frameworks of Ecological Systems Theory and Reinforcement Sensitivity Theory. PMID:19371496

Prediction and visualization of redox conditions in the groundwater of Central Valley, California

NASA Astrophysics Data System (ADS)

Rosecrans, Celia Z.; Nolan, Bernard T.; Gronberg, JoAnn M.

2017-03-01

Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions. Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of models of varying complexity, as a basis for selecting final models. Trained models were applied to cross-validation testing data and a separate hold-out dataset to evaluate model predictive performance by emphasizing three model metrics of fit: Kappa; accuracy; and the area under the receiver operator characteristic curve (ROC). The final trained models were used for mapping predictions at discrete depths to a depth of 304.8 m. Trained DO and Mn models had accuracies of 86-100%, Kappa values of 0.69-0.99, and ROC values of 0.92-1.0. Model accuracies for cross-validation testing datasets were 82-95% and ROC values were 0.87-0.91, indicating good predictive performance. Kappas for the cross-validation testing dataset were 0.30-0.69, indicating fair to substantial agreement between testing observations and model predictions. Hold-out data were available for the manganese model only and indicated accuracies of 89-97%, ROC values of 0.73-0.75, and Kappa values of 0.06-0.30. The predictive performance of both the DO and Mn models was reasonable, considering all three of these fit metrics and the low percentages of low-DO and high-Mn events in the data.

Predicting Blunt Cerebrovascular Injury in Pediatric Trauma: Validation of the “Utah Score”

PubMed Central

Ravindra, Vijay M.; Bollo, Robert J.; Sivakumar, Walavan; Akbari, Hassan; Naftel, Robert P.; Limbrick, David D.; Jea, Andrew; Gannon, Stephen; Shannon, Chevis; Birkas, Yekaterina; Yang, George L.; Prather, Colin T.; Kestle, John R.

2017-01-01

Abstract Risk factors for blunt cerebrovascular injury (BCVI) may differ between children and adults, suggesting that children at low risk for BCVI after trauma receive unnecessary computed tomography angiography (CTA) and high-dose radiation. We previously developed a score for predicting pediatric BCVI based on retrospective cohort analysis. Our objective is to externally validate this prediction score with a retrospective multi-institutional cohort. We included patients who underwent CTA for traumatic cranial injury at four pediatric Level I trauma centers. Each patient in the validation cohort was scored using the “Utah Score” and classified as high or low risk. Before analysis, we defined a misclassification rate <25% as validating the Utah Score. Six hundred forty-five patients (mean age 8.6 ± 5.4 years; 63.4% males) underwent screening for BCVI via CTA. The validation cohort was 411 patients from three sites compared with the training cohort of 234 patients. Twenty-two BCVIs (5.4%) were identified in the validation cohort. The Utah Score was significantly associated with BCVIs in the validation cohort (odds ratio 8.1 [3.3, 19.8], p < 0.001) and discriminated well in the validation cohort (area under the curve 72%). When the Utah Score was applied to the validation cohort, the sensitivity was 59%, specificity was 85%, positive predictive value was 18%, and negative predictive value was 97%. The Utah Score misclassified 16.6% of patients in the validation cohort. The Utah Score for predicting BCVI in pediatric trauma patients was validated with a low misclassification rate using a large, independent, multicenter cohort. Its implementation in the clinical setting may reduce the use of CTA in low-risk patients. PMID:27297774

Self-Esteem, Social Support, Internalized Homophobia, and Coping Strategies of HIV+ Gay Men.

ERIC Educational Resources Information Center

Nicholson, William Dean; Long, Bonita C.

1990-01-01

Findings from 89 human immunodeficiency virus positive (HIV+) homosexual men revealed that greater homophobia and less self-esteem predicted avoidant coping, whereas less homophobia and less time since diagnosis predicted proactive coping. Greater time since diagnosis, less avoidant coping, less homophobia, and greater self-esteem predicted better…

The Predictive Validity of Teacher Candidate Letters of Reference

ERIC Educational Resources Information Center

Mason, Richard W.; Schroeder, Mark P.

2014-01-01

Letters of reference are widely used as an essential part of the hiring process of newly licensed teachers. While the predictive validity of these letters of reference has been called into question it has never been empirically studied. The current study examined the predictive validity of the quality of letters of reference for forty-one student…

Predictive Validity of a Student Self-Report Screener of Behavioral and Emotional Risk in an Urban High School

ERIC Educational Resources Information Center

Dowdy, Erin; Harrell-Williams, Leigh; Dever, Bridget V.; Furlong, Michael J.; Moore, Stephanie; Raines, Tara; Kamphaus, Randy W.

2016-01-01

Increasingly, schools are implementing school-based screening for risk of behavioral and emotional problems; hence, foundational evidence supporting the predictive validity of screening instruments is important to assess. This study examined the predictive validity of the Behavior Assessment System for Children-2 Behavioral and Emotional Screening…

Predictive Validity of Curriculum-Based Measures for English Learners at Varying English Proficiency Levels

ERIC Educational Resources Information Center

Kim, Jennifer Sun; Vanderwood, Michael L.; Lee, Catherine Y.

2016-01-01

This study examined the predictive validity of curriculum-based measures in reading for Spanish-speaking English learners (ELs) at various levels of English proficiency. Third-grade Spanish-speaking EL students were screened during the fall using DIBELS Oral Reading Fluency (DORF) and Daze. Predictive validity was examined in relation to spring…

Propeller aircraft interior noise model utilization study and validation

NASA Technical Reports Server (NTRS)

Pope, L. D.

1984-01-01

Utilization and validation of a computer program designed for aircraft interior noise prediction is considered. The program, entitled PAIN (an acronym for Propeller Aircraft Interior Noise), permits (in theory) predictions of sound levels inside propeller driven aircraft arising from sidewall transmission. The objective of the work reported was to determine the practicality of making predictions for various airplanes and the extent of the program's capabilities. The ultimate purpose was to discern the quality of predictions for tonal levels inside an aircraft occurring at the propeller blade passage frequency and its harmonics. The effort involved three tasks: (1) program validation through comparisons of predictions with scale-model test results; (2) development of utilization schemes for large (full scale) fuselages; and (3) validation through comparisons of predictions with measurements taken in flight tests on a turboprop aircraft. Findings should enable future users of the program to efficiently undertake and correctly interpret predictions.

Empirical comparison between different methods for genomic prediction of number of piglets born alive in moderate sized breeding populations.

PubMed

Fangmann, A; Sharifi, R A; Heinkel, J; Danowski, K; Schrade, H; Erbe, M; Simianer, H

2017-04-01

Currently used multi-step methods to incorporate genomic information in the prediction of breeding values (BV) implicitly involve many assumptions which, if violated, may result in loss of information, inaccuracies and bias. To overcome this, single-step genomic best linear unbiased prediction (ssGBLUP) was proposed combining pedigree, phenotype and genotype of all individuals for genetic evaluation. Our objective was to implement ssGBLUP for genomic predictions in pigs and to compare the accuracy of ssGBLUP with that of multi-step methods with empirical data of moderately sized pig breeding populations. Different predictions were performed: conventional parent average (PA), direct genomic value (DGV) calculated with genomic BLUP (GBLUP), a GEBV obtained by blending the DGV with PA, and ssGBLUP. Data comprised individuals from a German Landrace (LR) and Large White (LW) population. The trait 'number of piglets born alive' (NBA) was available for 182,054 litters of 41,090 LR sows and 15,750 litters from 4534 LW sows. The pedigree contained 174,021 animals, of which 147,461 (26,560) animals were LR (LW) animals. In total, 526 LR and 455 LW animals were genotyped with the Illumina PorcineSNP60 BeadChip. After quality control and imputation, 495 LR (424 LW) animals with 44,368 (43,678) SNP on 18 autosomes remained for the analysis. Predictive abilities, i.e., correlations between de-regressed proofs and genomic BV, were calculated with a five-fold cross validation and with a forward prediction for young genotyped validation animals born after 2011. Generally, predictive abilities for LR were rather small (0.08 for GBLUP, 0.19 for GEBV and 0.18 for ssGBLUP). For LW, ssGBLUP had the greatest predictive ability (0.45). For both breeds, assessment of reliabilities for young genotyped animals indicated that genomic prediction outperforms PA with ssGBLUP providing greater reliabilities (0.40 for LR and 0.32 for LW) than GEBV (0.35 for LR and 0.29 for LW). Grouping of animals according to information sources revealed that genomic prediction had the highest potential benefit for genotyped animals without their own phenotype. Although, ssGBLUP did not generally outperform GBLUP or GEBV, the results suggest that ssGBLUP can be a useful and conceptually convincing approach for practical genomic prediction of NBA in moderately sized LR and LW populations.

A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies

PubMed Central

Dimitrov, Borislav D; Motterlini, Nicola; Fahey, Tom

2015-01-01

Objective Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. Study design and methods: Methodological study of systematic reviews of validation studies of CPRs: a) ABCD2 rule for prediction of 7 day stroke; and b) CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”). As confirmation, a logistic regression model (with derivation study coefficients) was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs), 95% confidence intervals (CIs), and indexes of heterogeneity (I2) on forest plots (fixed and random effects models), with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. Results Our simplified method, applied to ABCD2 rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points), indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82), however, calibration in some studies was low. In such cases with miscalibration, the under-prediction (RRs =0.73–0.91, 95% CIs 0.41–1.48) could be further corrected by intercept adjustment to account for incidence differences. An improvement of both heterogeneities and P-values (Hosmer-Lemeshow goodness-of-fit test) was observed. Better calibration and improved pooled RRs (0.90–1.06), with narrower 95% CIs (0.57–1.41) were achieved. Conclusion Our results have an immediate clinical implication in situations when predicted outcomes in CPR validation studies are lacking or deficient by describing how such predictions can be obtained by everyone using the derivation study alone, without any need for highly specialized knowledge or sophisticated statistics. PMID:25931829

Development of a predictive limited sampling strategy for estimation of mycophenolic acid area under the concentration time curve in patients receiving concomitant sirolimus or cyclosporine.

PubMed

Figurski, Michal J; Nawrocki, Artur; Pescovitz, Mark D; Bouw, Rene; Shaw, Leslie M

2008-08-01

Limited sampling strategies for estimation of the area under the concentration time curve (AUC) for mycophenolic acid (MPA) co-administered with sirolimus (SRL) have not been previously evaluated. The authors developed and validated 68 regression models for estimation of MPA AUC for two groups of patients, one with concomitant SRL (n = 24) and the second with concomitant cyclosporine (n=14), using various combinations of time points between 0 and 4 hours after drug administration. To provide as robust a model as possible, a dataset-splitting method similar to a bootstrap was used. In this method, the dataset was randomly split in half 100 times. Each time, one half of the data was used to estimate the equation coefficients, and the other half was used to test and validate the models. Final models were obtained by calculating the median values of the coefficients. Substantial differences were found in the pharmacokinetics of MPA between these groups. The mean MPA AUC as well as the standard deviation was much greater in the SRL group, 56.4 +/- 23.5 mg.h/L, compared with 30.4 +/- 11.0 mg.h/L in the cyclosporine group (P < 0.001). Mean maximum concentration was also greater in the SRL group: 16.4 +/- 7.7 mg/L versus 11.7 +/- 7.1mg/L (P < 0.005). The second absorption peak in the pharmacokinetic profile, presumed to result from enterohepatic recycling of glucuronide MPA, was observed in 70% of the profiles in the SRL group and in 35% of profiles from the cyclosporine group. Substantial differences in the predictive performance of the regression models, based on the same time points, were observed between the two groups. The best model for the SRL group was based on 0 (trough) and 40 minutes and 4 hour time points with R2, root mean squared error, and predictive performance values of 0.82, 10.0, and 78%, respectively. In the cyclosporine group, the best model was 0 and 40 minutes and 2 hours, with R2, RMSE, and predictive performance values of 0.86, 4.1, and 83%, respectively. The model with 2 hours as the last time point is also recommended for the SRL group for practical reasons, with the above parameters of 0.77, 11.3, and 69%, respectively.

Benefit and harm of intensive blood pressure treatment: Derivation and validation of risk models using data from the SPRINT and ACCORD trials

PubMed Central

Denton, Brian T.; Hayward, Rodney A.

2017-01-01

Background Intensive blood pressure (BP) treatment can avert cardiovascular disease (CVD) events but can cause some serious adverse events. We sought to develop and validate risk models for predicting absolute risk difference (increased risk or decreased risk) for CVD events and serious adverse events from intensive BP therapy. A secondary aim was to test if the statistical method of elastic net regularization would improve the estimation of risk models for predicting absolute risk difference, as compared to a traditional backwards variable selection approach. Methods and findings Cox models were derived from SPRINT trial data and validated on ACCORD-BP trial data to estimate risk of CVD events and serious adverse events; the models included terms for intensive BP treatment and heterogeneous response to intensive treatment. The Cox models were then used to estimate the absolute reduction in probability of CVD events (benefit) and absolute increase in probability of serious adverse events (harm) for each individual from intensive treatment. We compared the method of elastic net regularization, which uses repeated internal cross-validation to select variables and estimate coefficients in the presence of collinearity, to a traditional backwards variable selection approach. Data from 9,069 SPRINT participants with complete data on covariates were utilized for model development, and data from 4,498 ACCORD-BP participants with complete data were utilized for model validation. Participants were exposed to intensive (goal systolic pressure < 120 mm Hg) versus standard (<140 mm Hg) treatment. Two composite primary outcome measures were evaluated: (i) CVD events/deaths (myocardial infarction, acute coronary syndrome, stroke, congestive heart failure, or CVD death), and (ii) serious adverse events (hypotension, syncope, electrolyte abnormalities, bradycardia, or acute kidney injury/failure). The model for CVD chosen through elastic net regularization included interaction terms suggesting that older age, black race, higher diastolic BP, and higher lipids were associated with greater CVD risk reduction benefits from intensive treatment, while current smoking was associated with fewer benefits. The model for serious adverse events chosen through elastic net regularization suggested that male sex, current smoking, statin use, elevated creatinine, and higher lipids were associated with greater risk of serious adverse events from intensive treatment. SPRINT participants in the highest predicted benefit subgroup had a number needed to treat (NNT) of 24 to prevent 1 CVD event/death over 5 years (absolute risk reduction [ARR] = 0.042, 95% CI: 0.018, 0.066; P = 0.001), those in the middle predicted benefit subgroup had a NNT of 76 (ARR = 0.013, 95% CI: −0.0001, 0.026; P = 0.053), and those in the lowest subgroup had no significant risk reduction (ARR = 0.006, 95% CI: −0.007, 0.018; P = 0.71). Those in the highest predicted harm subgroup had a number needed to harm (NNH) of 27 to induce 1 serious adverse event (absolute risk increase [ARI] = 0.038, 95% CI: 0.014, 0.061; P = 0.002), those in the middle predicted harm subgroup had a NNH of 41 (ARI = 0.025, 95% CI: 0.012, 0.038; P < 0.001), and those in the lowest subgroup had no significant risk increase (ARI = −0.007, 95% CI: −0.043, 0.030; P = 0.72). In ACCORD-BP, participants in the highest subgroup of predicted benefit had significant absolute CVD risk reduction, but the overall ACCORD-BP participant sample was skewed towards participants with less predicted benefit and more predicted risk than in SPRINT. The models chosen through traditional backwards selection had similar ability to identify absolute risk difference for CVD as the elastic net models, but poorer ability to correctly identify absolute risk difference for serious adverse events. A key limitation of the analysis is the limited sample size of the ACCORD-BP trial, which expanded confidence intervals for ARI among persons with type 2 diabetes. Additionally, it is not possible to mechanistically explain the physiological relationships explaining the heterogeneous treatment effects captured by the models, since the study was an observational secondary data analysis. Conclusions We found that predictive models could help identify subgroups of participants in both SPRINT and ACCORD-BP who had lower versus higher ARRs in CVD events/deaths with intensive BP treatment, and participants who had lower versus higher ARIs in serious adverse events. PMID:29040268

The predictive validity of three versions of the MCAT in relation to performance in medical school, residency, and licensing examinations: a longitudinal study of 36 classes of Jefferson Medical College.

PubMed

Callahan, Clara A; Hojat, Mohammadreza; Veloski, Jon; Erdmann, James B; Gonnella, Joseph S

2010-06-01

The Medical College Admission Test (MCAT) has undergone several revisions for content and validity since its inception. With another comprehensive review pending, this study examines changes in the predictive validity of the MCAT's three recent versions. Study participants were 7,859 matriculants in 36 classes entering Jefferson Medical College between 1970 and 2005; 1,728 took the pre-1978 version of the MCAT; 3,032 took the 1978-1991 version, and 3,099 took the post-1991 version. MCAT subtest scores were the predictors, and performance in medical school, attrition, scores on the medical licensing examinations, and ratings of clinical competence in the first year of residency were the criterion measures. No significant improvement in validity coefficients was observed for performance in medical school or residency. Validity coefficients for all three versions of the MCAT in predicting Part I/Step 1 remained stable (in the mid-0.40s, P < .01). A systematic decline was observed in the validity coefficients of the MCAT versions in predicting Part II/Step 2. It started at 0.47 for the pre-1978 version, decreased to between 0.42 and 0.40 for the 1978-1991 versions, and to 0.37 for the post-1991 version. Validity coefficients for the MCAT versions in predicting Part III/Step 3 remained near 0.30. These were generally larger for women than men. Although the findings support the short- and long-term predictive validity of the MCAT, opportunities to strengthen it remain. Subsequent revisions should increase the test's ability to predict performance on United States Medical Licensing Examination Step 2 and must minimize the differential validity for gender.

NASA's Evolutionary Xenon Thruster (NEXT) Project Qualification Propellant Throughput Milestone: Performance, Erosion, and Thruster Service Life Prediction After 450 kg

NASA Technical Reports Server (NTRS)

Herman, Daniel A.

2010-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is tasked with significantly improving and extending the capabilities of current state-of-the-art NSTAR thruster. The service life capability of the NEXT ion thruster is being assessed by thruster wear test and life-modeling of critical thruster components, such as the ion optics and cathodes. The NEXT Long-Duration Test (LDT) was initiated to validate and qualify the NEXT thruster propellant throughput capability. The NEXT thruster completed the primary goal of the LDT; namely to demonstrate the project qualification throughput of 450 kg by the end of calendar year 2009. The NEXT LDT has demonstrated 28,500 hr of operation and processed 466 kg of xenon throughput--more than double the throughput demonstrated by the NSTAR flight-spare. Thruster performance changes have been consistent with a priori predictions. Thruster erosion has been minimal and consistent with the thruster service life assessment, which predicts the first failure mode at greater than 750 kg throughput. The life-limiting failure mode for NEXT is predicted to be loss of structural integrity of the accelerator grid due to erosion by charge-exchange ions.

Predicting personality traits related to consumer behavior using SNS analysis

NASA Astrophysics Data System (ADS)

Baik, Jongbum; Lee, Kangbok; Lee, Soowon; Kim, Yongbum; Choi, Jayoung

2016-07-01

Modeling a user profile is one of the important factors for devising a personalized recommendation. The traditional approach for modeling a user profile in computer science is to collect and generalize the user's buying behavior or preference history, generated from the user's interactions with recommender systems. According to consumer behavior research, however, internal factors such as personality traits influence a consumer's buying behavior. Existing studies have tried to adapt the Big 5 personality traits to personalized recommendations. However, although studies have shown that these traits can be useful to some extent for personalized recommendation, the causal relationship between the Big 5 personality traits and the buying behaviors of actual consumers has not been validated. In this paper, we propose a novel method for predicting the four personality traits-Extroversion, Public Self-consciousness, Desire for Uniqueness, and Self-esteem-that correlate with buying behaviors. The proposed method automatically constructs a user-personality-traits prediction model for each user by analyzing the user behavior on a social networking service. The experimental results from an analysis of the collected Facebook data show that the proposed method can predict user-personality traits with greater precision than methods that use the variables proposed in previous studies.

Symmetric airfoil geometry effects on leading edge noise.

PubMed

Gill, James; Zhang, X; Joseph, P

2013-10-01

Computational aeroacoustic methods are applied to the modeling of noise due to interactions between gusts and the leading edge of real symmetric airfoils. Single frequency harmonic gusts are interacted with various airfoil geometries at zero angle of attack. The effects of airfoil thickness and leading edge radius on noise are investigated systematically and independently for the first time, at higher frequencies than previously used in computational methods. Increases in both leading edge radius and thickness are found to reduce the predicted noise. This noise reduction effect becomes greater with increasing frequency and Mach number. The dominant noise reduction mechanism for airfoils with real geometry is found to be related to the leading edge stagnation region. It is shown that accurate leading edge noise predictions can be made when assuming an inviscid meanflow, but that it is not valid to assume a uniform meanflow. Analytic flat plate predictions are found to over-predict the noise due to a NACA 0002 airfoil by up to 3 dB at high frequencies. The accuracy of analytic flat plate solutions can be expected to decrease with increasing airfoil thickness, leading edge radius, gust frequency, and Mach number.

Can the Absence of Prejudice be More Threatening than its Presence? It Depends on one's Worldview

PubMed Central

Townsend, Sarah S. M.; Major, Brenda; Sawyer, Pamela J.; Mendes, Wendy Berry

2010-01-01

The current research used validated cardiovascular measures to examine threat reactions among members of stigmatized groups when interacting with members of nonstigmatized groups who were, or were not, prejudiced against their group. We hypothesized that people's beliefs about the fairness of the status system would moderate their experience of threat during intergroup interactions. We predicted that for members of stigmatized groups who believe the status system is fair, interacting with a prejudiced relative to an unprejudiced partner would disconfirm their worldview and result in greater threat. In contrast, we predicted that for members of stigmatized groups who believe the system is unfair, interacting with a prejudiced relative to an unprejudiced partner would confirm their worldview and result in less threat. We examined these predictions among Latinas interacting with a White female confederate (Study 1) and White females interacting with a White male confederate (Study 2). As predicted, people's beliefs about the fairness of the status system moderated their experiences of threat during intergroup interactions, indicated both by cardiovascular responses and nonverbal behavior. The specific pattern of the moderation differed across the two studies. PMID:21114352

Effects of temporal and spatial resolution of calibration data on integrated hydrologic water quality model identification

NASA Astrophysics Data System (ADS)

Jiang, Sanyuan; Jomaa, Seifeddine; Büttner, Olaf; Rode, Michael

2014-05-01

Hydrological water quality modeling is increasingly used for investigating runoff and nutrient transport processes as well as watershed management but it is mostly unclear how data availablity determins model identification. In this study, the HYPE (HYdrological Predictions for the Environment) model, which is a process-based, semi-distributed hydrological water quality model, was applied in two different mesoscale catchments (Selke (463 km2) and Weida (99 km2)) located in central Germany to simulate discharge and inorganic nitrogen (IN) transport. PEST and DREAM(ZS) were combined with the HYPE model to conduct parameter calibration and uncertainty analysis. Split-sample test was used for model calibration (1994-1999) and validation (1999-2004). IN concentration and daily IN load were found to be highly correlated with discharge, indicating that IN leaching is mainly controlled by runoff. Both dynamics and balances of water and IN load were well captured with NSE greater than 0.83 during validation period. Multi-objective calibration (calibrating hydrological and water quality parameters simultaneously) was found to outperform step-wise calibration in terms of model robustness. Multi-site calibration was able to improve model performance at internal sites, decrease parameter posterior uncertainty and prediction uncertainty. Nitrogen-process parameters calibrated using continuous daily averages of nitrate-N concentration observations produced better and more robust simulations of IN concentration and load, lower posterior parameter uncertainty and IN concentration prediction uncertainty compared to the calibration against uncontinuous biweekly nitrate-N concentration measurements. Both PEST and DREAM(ZS) are efficient in parameter calibration. However, DREAM(ZS) is more sound in terms of parameter identification and uncertainty analysis than PEST because of its capability to evolve parameter posterior distributions and estimate prediction uncertainty based on global search and Bayesian inference schemes.

Modelling size-dependent cannibalism in barramundi Lates calcarifer: cannibalistic polyphenism and its implication to aquaculture.

PubMed

Ribeiro, Flavio F; Qin, Jian G

2013-01-01

This study quantified size-dependent cannibalism in barramundi Lates calcarifer through coupling a range of prey-predator pairs in a different range of fish sizes. Predictive models were developed using morphological traits with the alterative assumption of cannibalistic polyphenism. Predictive models were validated with the data from trials where cannibals were challenged with progressing increments of prey sizes. The experimental observations showed that cannibals of 25-131 mm total length could ingest the conspecific prey of 78-72% cannibal length. In the validation test, all predictive models underestimate the maximum ingestible prey size for cannibals of a similar size range. However, the model based on the maximal mouth width at opening closely matched the empirical observations, suggesting a certain degree of phenotypic plasticity of mouth size among cannibalistic individuals. Mouth size showed allometric growth comparing with body depth, resulting in a decreasing trend on the maximum size of ingestible prey as cannibals grow larger, which in parts explains why cannibalism in barramundi is frequently observed in the early developmental stage. Any barramundi has the potential to become a cannibal when the initial prey size was <50% of the cannibal body length, but fish could never become a cannibal when prey were >58% of their size, suggesting that 50% of size difference can be the threshold to initiate intracohort cannibalism in a barramundi population. Cannibalistic polyphenism was likely to occur in barramundi that had a cannibalistic history. An experienced cannibal would have a greater ability to stretch its mouth size to capture a much larger prey than the models predict. The awareness of cannibalistic polyphenism has important application in fish farming management to reduce cannibalism.

Modelling Size-Dependent Cannibalism in Barramundi Lates calcarifer: Cannibalistic Polyphenism and Its Implication to Aquaculture

PubMed Central

Ribeiro, Flavio F.; Qin, Jian G.

2013-01-01

This study quantified size-dependent cannibalism in barramundi Lates calcarifer through coupling a range of prey-predator pairs in a different range of fish sizes. Predictive models were developed using morphological traits with the alterative assumption of cannibalistic polyphenism. Predictive models were validated with the data from trials where cannibals were challenged with progressing increments of prey sizes. The experimental observations showed that cannibals of 25–131 mm total length could ingest the conspecific prey of 78–72% cannibal length. In the validation test, all predictive models underestimate the maximum ingestible prey size for cannibals of a similar size range. However, the model based on the maximal mouth width at opening closely matched the empirical observations, suggesting a certain degree of phenotypic plasticity of mouth size among cannibalistic individuals. Mouth size showed allometric growth comparing with body depth, resulting in a decreasing trend on the maximum size of ingestible prey as cannibals grow larger, which in parts explains why cannibalism in barramundi is frequently observed in the early developmental stage. Any barramundi has the potential to become a cannibal when the initial prey size was <50% of the cannibal body length, but fish could never become a cannibal when prey were >58% of their size, suggesting that 50% of size difference can be the threshold to initiate intracohort cannibalism in a barramundi population. Cannibalistic polyphenism was likely to occur in barramundi that had a cannibalistic history. An experienced cannibal would have a greater ability to stretch its mouth size to capture a much larger prey than the models predict. The awareness of cannibalistic polyphenism has important application in fish farming management to reduce cannibalism. PMID:24349295

Modeling Exposures to the Oxidative Potential of PM10

PubMed Central

2012-01-01

Differences in the toxicity of ambient particulate matter (PM) due to varying particle composition across locations may contribute to variability in results from air pollution epidemiologic studies. Though most studies have used PM mass concentration as the exposure metric, an alternative which accounts for particle toxicity due to varying particle composition may better elucidate whether PM from specific sources is responsible for observed health effects. The oxidative potential (OP) of PM < 10 μm (PM10) was measured as the rate of depletion of the antioxidant reduced glutathione (GSH) in a model of human respiratory tract lining fluid. Using a database of GSH OP measures collected in greater London, U.K. from 2002 to 2006, we developed and validated a predictive spatiotemporal model of the weekly GSH OP of PM10 that included geographic predictors. Predicted levels of OP were then used in combination with those of weekly PM10 mass to estimate exposure to PM10 weighted by its OP. Using cross-validation (CV), brake and tire wear emissions of PM10 from traffic within 50 m and tailpipe emissions of nitrogen oxides from heavy-goods vehicles within 100 m were important predictors of GSH OP levels. Predictive accuracy of the models was high for PM10 (CV R2=0.83) but only moderate for GSH OP (CV R2 = 0.44) when comparing weekly levels; however, the GSH OP model predicted spatial trends well (spatial CV R2 = 0.73). Results suggest that PM10 emitted from traffic sources, specifically brake and tire wear, has a higher OP than that from other sources, and that this effect is very local, occurring within 50–100 m of roadways. PMID:22731499

SU-G-JeP4-02: An Investigation of Respiratory Surrogate Motion Data Requirements for Multiple-Step Ahead Prediction

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

Zawisza, I; Ren, L; Yin, F

Purpose: Respiratory-gated radiotherapy and dynamic tracking employ real-time imaging and surrogate motion-monitoring methods with tumor motion prediction in advance of real-time. This study investigated respiratory motion data length on prediction accuracy of tumor motion. Methods: Predictions generated from the algorithm are validated against a one-dimensional surrogate signal of amplitude versus time. Prediction consists of three major components: extracting top-ranked subcomponents from training data matching the last respiratory cycle; calculating weighting factors from best-matched subcomponents; fusing data proceeding best-matched subcomponents with respective weighting factors to form predictions. Predictions for one respiratory cycle (∼3-6seconds) were assessed using 351 patient data from themore » respiratory management device. Performance was evaluated for correlation coefficient and root mean square error (RMSE) between prediction and final respiratory cycle. Results: Respiratory prediction results fell into two classes, where best predictions for 70 cycles or less performed using relative prediction and greater than 70 cycles are predicted similarly using relative and derivative relative. For 70 respiratory cycles or less, the average correlation between prediction and final respiratory cycle was 0.9999±0.0001, 0.9999±0.0001, 0.9988±0.0003, 0.9985±0.0023, and 0.9981±0.0023 with RMSE values of 0.0091±0.0030, 0.0091±0.0030, 0.0305±0.0051, 0.0299±0.0259, and 0.0299±0.0259 for equal, relative, pattern, derivative equal and derivative relative weighting methods, respectively. Respectively, the total best prediction for each method was 37, 65, 20, 22, and 22. For data with greater than 70 cycles average correlation was 0.9999±0.0001, 0.9999±0.0001, 0.9988±0.0004, 0.9988±0.0020, and 0.9988±0.0020 with RMSE values of 0.0081±0.0031, 0.0082±0.0033, 0.0306±0.0056, 0.0218±0.0222, and 0.0218±0.0222 for equal, relative, pattern, derivative equal and derivative relative weighting methods, respectively. Respectively, the total best prediction for each method was 24, 44, 42, 30, and 45. Conclusion: The prediction algorithms are effective in estimating surrogate motion in advance. These results indicate an advantage in using relative prediction for shorter data and either relative or derivative relative prediction for longer data.« less

Performance of genomic prediction within and across generations in maritime pine.

PubMed

Bartholomé, Jérôme; Van Heerwaarden, Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-08-11

Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.

Prosocial Personality Traits Differentially Predict Egalitarianism, Generosity, and Reciprocity in Economic Games

PubMed Central

Zhao, Kun; Ferguson, Eamonn; Smillie, Luke D.

2016-01-01

Recent research has highlighted the role of prosocial personality traits—agreeableness and honesty-humility—in egalitarian distributions of wealth in the dictator game. Expanding on these findings, we ran two studies to examine individual differences in two other forms of prosociality—generosity and reciprocity—with respect to two major models of personality, the Big Five and the HEXACO. Participants (combined N = 560) completed a series of economic games in which allocations in the dictator game were compared with those in the generosity game, a non-constant-sum wealth distribution task where proposers with fixed payoffs selected the size of their partner’s payoff (“generosity”). We further examined positive and negative reciprocity by manipulating a partner’s previous move (“reciprocity”). Results showed clear evidence of both generosity and positive reciprocity in social preferences, with allocations to a partner greater in the generosity game than in the dictator game, and greater still when a player had been previously assisted by their partner. There was also a consistent interaction with gender, whereby men were more generous when this was costless and women were more egalitarian overall. Furthermore, these distinct forms of prosociality were differentially predicted by personality traits, in line with the core features of these traits and the theoretical distinctions between them. HEXACO honesty-humility predicted dictator, but not generosity allocations, while traits capturing tendencies toward irritability and anger predicted lower generosity, but not dictator allocations. In contrast, the politeness—but not compassion—aspect of Big Five agreeableness was uniquely and broadly associated with prosociality across all games. These findings support the discriminant validity between related prosocial constructs, and have important implications for understanding the motives and mechanisms taking place within economic games. PMID:27555824

Prosocial Personality Traits Differentially Predict Egalitarianism, Generosity, and Reciprocity in Economic Games.

PubMed

Zhao, Kun; Ferguson, Eamonn; Smillie, Luke D

2016-01-01

Recent research has highlighted the role of prosocial personality traits-agreeableness and honesty-humility-in egalitarian distributions of wealth in the dictator game. Expanding on these findings, we ran two studies to examine individual differences in two other forms of prosociality-generosity and reciprocity-with respect to two major models of personality, the Big Five and the HEXACO. Participants (combined N = 560) completed a series of economic games in which allocations in the dictator game were compared with those in the generosity game, a non-constant-sum wealth distribution task where proposers with fixed payoffs selected the size of their partner's payoff ("generosity"). We further examined positive and negative reciprocity by manipulating a partner's previous move ("reciprocity"). Results showed clear evidence of both generosity and positive reciprocity in social preferences, with allocations to a partner greater in the generosity game than in the dictator game, and greater still when a player had been previously assisted by their partner. There was also a consistent interaction with gender, whereby men were more generous when this was costless and women were more egalitarian overall. Furthermore, these distinct forms of prosociality were differentially predicted by personality traits, in line with the core features of these traits and the theoretical distinctions between them. HEXACO honesty-humility predicted dictator, but not generosity allocations, while traits capturing tendencies toward irritability and anger predicted lower generosity, but not dictator allocations. In contrast, the politeness-but not compassion-aspect of Big Five agreeableness was uniquely and broadly associated with prosociality across all games. These findings support the discriminant validity between related prosocial constructs, and have important implications for understanding the motives and mechanisms taking place within economic games.

Risk Factors for Death and Major Morbidity in Guatemalan Children with Acute Bacterial Meningitis.

PubMed

Olson, Daniel; Lamb, Molly M; Gaensbauer, James T; Todd, James K; Halsey, Neal A; Asturias, Edwin J

2015-07-01

Acute bacterial meningitis (ABM) remains a significant cause of pediatric illness and death in low and middle income countries. Identifying severity risk factors and predictive scores may guide interventions to reduce poor outcomes. Data from a prospective surveillance study for ABM in children aged 0-59 months admitted to 3 referral hospitals in Guatemala City from 2000 to 2007 were analyzed. ABM was defined as positive cerebrospinal fluid (CSF) culture, positive latex agglutination or CSF white blood cell greater than 100 cells/mL. Univariate and multivariate analyses of risk factors at hospital admission that predicted major morbidity or death during hospitalization were performed, along with validation of the predictive Herson-Todd score (HTS). Of 809 children with ABM episodes, 221 (27.3%) survived with major morbidity and 192 (23.7%) died. Among 383 children with nonmissing data, the most significant multivariate predictors for death or major morbidity were seizure [odds ratio (OR), 101.5; P < 0.001], CSF glucose less than 20 mg/dL (OR, 5.3; P = 0.0004), symptom duration more than 3 days (OR, 3.7; P = 0.003) and coma (OR, 6.3; P = 0.004). Of 221 children with a HTS greater than 5, 204 (92%) died or suffered major morbidity (OR, 10.3; P < 0.0001). ABM is a cause of considerable morbidity and mortality in Guatemala. Several clinical risk factors and the composite HTS predicted death or major morbidity. These predictors could help clinicians in low and middle income country guide medical care for ABM and could contribute to the public health impact assessment in preventing meningitis with vaccines.

Using presurgical psychological testing to predict 1-year appointment adherence and weight loss in bariatric surgery patients: predictive validity and methodological considerations.

PubMed

Marek, Ryan J; Tarescavage, Anthony M; Ben-Porath, Yossef S; Ashton, Kathleen; Merrell Rish, Julie; Heinberg, Leslie J

2015-01-01

Previous studies suggest that presurgical psychopathology accounts for some of the variance in suboptimal weight loss outcomes among Roux-en-Y gastric bypass (RYGB) patients, but research has been equivocal. The present study seeks to extend the past literature by examining associations between presurgical scale scores on the broadband Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) and suboptimal weight loss and poor adherence to follow-up 1 year postoperatively after accounting for several methodologic considerations. Cleveland Clinic Bariatric and Metabolic Institute, Cleveland, Ohio, USA. The sample consisted of 498 RYGB patients, who produced a valid presurgical MMPI-2-RF protocol at program intake. The sample was primarily female (72.9%), Caucasian (64.9%), and middle-aged (mean = 46.4 years old; standard deviation [SD] = 11.6). The mean presurgical body mass index (BMI) was 47.4 kg/m(2) (SD = 8.2) and mean percent weight loss (%WL) at 1 year postoperatively was 31.18 %WL (SD = 8.44). As expected, scales from the Behavioral/Externalizing Dysfunction (BXD) domain of the MMPI-2-RF were associated with worse weight loss outcomes and poor adherence to follow-up, particularly after accounting for range restriction due to underreporting. Individuals producing elevated scores on these scales were at greater risk for achieving suboptimal weight loss (<50% excess weight loss) and not following up with their appointment compared with those who scored below cut-offs. Patients who are more likely to engage in undercontrolled behavior (e.g., poor impulse control), as indicated by presurgical MMPI-2-RF findings, are at greater risk for suboptimal weight loss and poor adherence to follow-up following RYGB. Objective psychological assessments should also be conducted postoperatively to ensure that intervention is administered in a timely manner. Future research in the area of presurgical psychological screening should consider the impact of underreporting and other discussed methodologic issues in predictive analyses. Copyright © 2015 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

A simple risk scoring system for prediction of relapse after inpatient alcohol treatment.

PubMed

Pedersen, Mads Uffe; Hesse, Morten

2009-01-01

Predicting relapse after alcoholism treatment can be useful in targeting patients for aftercare services. However, a valid and practical instrument for predicting relapse risk does not exist. Based on a prospective study of alcoholism treatment, we developed the Risk of Alcoholic Relapse Scale (RARS) using items taken from the Addiction Severity Index and some basic demographic information. The RARS was cross-validated using two non-overlapping samples, and tested for its ability to predict relapse across different models of treatment. The RARS predicted relapse to drinking within 6 months after alcoholism treatment in both the original and the validation sample, and in a second validation sample it predicted admission to new treatment 3 years after treatment. The RARS can identify patients at high risk of relapse who need extra aftercare and support after treatment.

Implementing statistical equating for MRCP(UK) Parts 1 and 2.

PubMed

McManus, I C; Chis, Liliana; Fox, Ray; Waller, Derek; Tang, Peter

2014-09-26

The MRCP(UK) exam, in 2008 and 2010, changed the standard-setting of its Part 1 and Part 2 examinations from a hybrid Angoff/Hofstee method to statistical equating using Item Response Theory, the reference group being UK graduates. The present paper considers the implementation of the change, the question of whether the pass rate increased amongst non-UK candidates, any possible role of Differential Item Functioning (DIF), and changes in examination predictive validity after the change. Analysis of data of MRCP(UK) Part 1 exam from 2003 to 2013 and Part 2 exam from 2005 to 2013. Inspection suggested that Part 1 pass rates were stable after the introduction of statistical equating, but showed greater annual variation probably due to stronger candidates taking the examination earlier. Pass rates seemed to have increased in non-UK graduates after equating was introduced, but was not associated with any changes in DIF after statistical equating. Statistical modelling of the pass rates for non-UK graduates found that pass rates, in both Part 1 and Part 2, were increasing year on year, with the changes probably beginning before the introduction of equating. The predictive validity of Part 1 for Part 2 was higher with statistical equating than with the previous hybrid Angoff/Hofstee method, confirming the utility of IRT-based statistical equating. Statistical equating was successfully introduced into the MRCP(UK) Part 1 and Part 2 written examinations, resulting in higher predictive validity than the previous Angoff/Hofstee standard setting. Concerns about an artefactual increase in pass rates for non-UK candidates after equating were shown not to be well-founded. Most likely the changes resulted from a genuine increase in candidate ability, albeit for reasons which remain unclear, coupled with a cognitive illusion giving the impression of a step-change immediately after equating began. Statistical equating provides a robust standard-setting method, with a better theoretical foundation than judgemental techniques such as Angoff, and is more straightforward and requires far less examiner time to provide a more valid result. The present study provides a detailed case study of introducing statistical equating, and issues which may need to be considered with its introduction.

Resilience or hope? Incremental and convergent validity of the resilience scale for adults (RSA) and the Herth hope scale (HHS) in the prediction of anxiety and depression.

PubMed

Morote, Roxanna; Hjemdal, Odin; Krysinska, Karolina; Martinez Uribe, Patricia; Corveleyn, Jozef

2017-10-27

Hope and resilience protect against inner vulnerabilities or harsh life circumstances; they explain individual differences in physical or mental health outcomes under high stress. They have been studied in complementary or competing theoretical frameworks; therefore, the study of measures of hope and resilience should be undertaken prior to explore if they are truly value-added for research. This study investigates the convergent and incremental validity of the Resilience Scale for Adults (RSA) and the Herth Hope Scale (HHS), in the prediction of anxiety and depression (HSCL-25). Participants in this community-based sample are 762 adults from 18 to 74 years old. They answered the RSA, HHS, Spanish Language Stressful Life-Events Checklist (SL-SLE), and the Hopkins Symptom Checklist-25 (HSCL-25). Incremental validity analyses combined hierarchical regression and structural equation models (SEM). First, hierarchical regression models were compared based on three criteria (R 2 Diff., ΔF, and semi-partial r), then the direct effect of resilience on affective symptoms was compared with the mediated effect of resilience on affective symptoms through hope. The hierarchical models showed that (1) hope and resilience account significantly for the variance of affective symptoms above age, sex, and life-stress; (2) Resilience Total score has greater incremental validity than positive scales of HHS Hope; and (3) RSA Total score, HHS Optimism/Spiritual support, Stressful life-events and sex are unique predictors of affective symptoms. The SEM analyses verified a stronger direct effect of resilience in the prediction of affective symptoms above the significant partial mediated effect of resilience through hope. Additionally, results show that age and better educational opportunities were associated with protection (i.e. resilience and hope) and emotional well-being (i.e. affective symptoms and hopelessness). Women showed higher scores in social competences and resources (RSA), interconnectedness and initiative to take action (HHS). However, they have poorer evaluations of own abilities and efficacy (RSA), and higher scores in all the affective symptoms assessed. The RSA has incremental validity above the HHS, however, both the RSA and the HHS are effective, differentiated and complementary measures of protection that are of high relevance for research on psychosocial and emotional well-being.

Criterion for evaluating the predictive ability of nonlinear regression models without cross-validation.

PubMed

Kaneko, Hiromasa; Funatsu, Kimito

2013-09-23

We propose predictive performance criteria for nonlinear regression models without cross-validation. The proposed criteria are the determination coefficient and the root-mean-square error for the midpoints between k-nearest-neighbor data points. These criteria can be used to evaluate predictive ability after the regression models are updated, whereas cross-validation cannot be performed in such a situation. The proposed method is effective and helpful in handling big data when cross-validation cannot be applied. By analyzing data from numerical simulations and quantitative structural relationships, we confirm that the proposed criteria enable the predictive ability of the nonlinear regression models to be appropriately quantified.

A Public-Private Partnership Develops and Externally Validates a 30-Day Hospital Readmission Risk Prediction Model

PubMed Central

Choudhry, Shahid A.; Li, Jing; Davis, Darcy; Erdmann, Cole; Sikka, Rishi; Sutariya, Bharat

2013-01-01

Introduction: Preventing the occurrence of hospital readmissions is needed to improve quality of care and foster population health across the care continuum. Hospitals are being held accountable for improving transitions of care to avert unnecessary readmissions. Advocate Health Care in Chicago and Cerner (ACC) collaborated to develop all-cause, 30-day hospital readmission risk prediction models to identify patients that need interventional resources. Ideally, prediction models should encompass several qualities: they should have high predictive ability; use reliable and clinically relevant data; use vigorous performance metrics to assess the models; be validated in populations where they are applied; and be scalable in heterogeneous populations. However, a systematic review of prediction models for hospital readmission risk determined that most performed poorly (average C-statistic of 0.66) and efforts to improve their performance are needed for widespread usage. Methods: The ACC team incorporated electronic health record data, utilized a mixed-method approach to evaluate risk factors, and externally validated their prediction models for generalizability. Inclusion and exclusion criteria were applied on the patient cohort and then split for derivation and internal validation. Stepwise logistic regression was performed to develop two predictive models: one for admission and one for discharge. The prediction models were assessed for discrimination ability, calibration, overall performance, and then externally validated. Results: The ACC Admission and Discharge Models demonstrated modest discrimination ability during derivation, internal and external validation post-recalibration (C-statistic of 0.76 and 0.78, respectively), and reasonable model fit during external validation for utility in heterogeneous populations. Conclusions: The ACC Admission and Discharge Models embody the design qualities of ideal prediction models. The ACC plans to continue its partnership to further improve and develop valuable clinical models. PMID:24224068

Assessment of MELCOR condensation models with the presence of noncondensable gas in natural convection flow regime

DOE PAGES

Yoon, Dhongik S; Jo, HangJin; Corradini, Michael L

2017-04-01

Condensation of steam vapor is an important mode of energy removal from the reactor containment. The presence of noncondensable gas complicates the process and makes it difficult to model. MELCOR, one of the more widely used system codes for containment analyses, uses the heat and mass transfer analogy to model condensation heat transfer. To investigate previously reported nodalization-dependence in natural convection flow regime, MELCOR condensation model as well as other models are studied. The nodalization-dependence issue is resolved by using physical length from the actual geometry rather than node size of each control volume as the characteristic length scale formore » MELCOR containment analyses. At the transition to turbulent natural convection regime, the McAdams correlation for convective heat transfer produces a better prediction compared to the original MELCOR model. The McAdams correlation is implemented in MELCOR and the prediction is validated against a set of experiments on a scaled AP600 containment. The MELCOR with our implemented model produces improved predictions. For steam molar fractions in the gas mixture greater than about 0.58, the predictions are within the uncertainty margin of the measurements. The simulation results still underestimate the heat transfer from the gas-steam mixture, implying that conservative predictions are provided.« less

Assessment of MELCOR condensation models with the presence of noncondensable gas in natural convection flow regime

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

Yoon, Dhongik S; Jo, HangJin; Corradini, Michael L

Condensation of steam vapor is an important mode of energy removal from the reactor containment. The presence of noncondensable gas complicates the process and makes it difficult to model. MELCOR, one of the more widely used system codes for containment analyses, uses the heat and mass transfer analogy to model condensation heat transfer. To investigate previously reported nodalization-dependence in natural convection flow regime, MELCOR condensation model as well as other models are studied. The nodalization-dependence issue is resolved by using physical length from the actual geometry rather than node size of each control volume as the characteristic length scale formore » MELCOR containment analyses. At the transition to turbulent natural convection regime, the McAdams correlation for convective heat transfer produces a better prediction compared to the original MELCOR model. The McAdams correlation is implemented in MELCOR and the prediction is validated against a set of experiments on a scaled AP600 containment. The MELCOR with our implemented model produces improved predictions. For steam molar fractions in the gas mixture greater than about 0.58, the predictions are within the uncertainty margin of the measurements. The simulation results still underestimate the heat transfer from the gas-steam mixture, implying that conservative predictions are provided.« less

Fine-temporal forecasting of outbreak probability and severity: Ross River virus in Western Australia.

PubMed

Koolhof, I S; Bettiol, S; Carver, S

2017-10-01

Health warnings of mosquito-borne disease risk require forecasts that are accurate at fine-temporal resolutions (weekly scales); however, most forecasting is coarse (monthly). We use environmental and Ross River virus (RRV) surveillance to predict weekly outbreak probabilities and incidence spanning tropical, semi-arid, and Mediterranean regions of Western Australia (1991-2014). Hurdle and linear models were used to predict outbreak probabilities and incidence respectively, using time-lagged environmental variables. Forecast accuracy was assessed by model fit and cross-validation. Residual RRV notification data were also examined against mitigation expenditure for one site, Mandurah 2007-2014. Models were predictive of RRV activity, except at one site (Capel). Minimum temperature was an important predictor of RRV outbreaks and incidence at all predicted sites. Precipitation was more likely to cause outbreaks and greater incidence among tropical and semi-arid sites. While variable, mitigation expenditure coincided positively with increased RRV incidence (r 2 = 0·21). Our research demonstrates capacity to accurately predict mosquito-borne disease outbreaks and incidence at fine-temporal resolutions. We apply our findings, developing a user-friendly tool enabling managers to easily adopt this research to forecast region-specific RRV outbreaks and incidence. Approaches here may be of value to fine-scale forecasting of RRV in other areas of Australia, and other mosquito-borne diseases.

Prediction models for successful external cephalic version: a systematic review.

PubMed

Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein

2015-12-01

To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.

Fluid dynamics model of mitral valve flow: description with in vitro validation.

PubMed

Thomas, J D; Weyman, A E

1989-01-01

A lumped variable fluid dynamics model of mitral valve blood flow is described that is applicable to both Doppler echocardiography and invasive hemodynamic measurement. Given left atrial and ventricular compliance, initial pressures and mitral valve impedance, the model predicts the time course of mitral flow and atrial and ventricular pressure. The predictions of this mathematic formulation have been tested in an in vitro analog of the left heart in which mitral valve area and atrial and ventricular compliance can be accurately controlled. For the situation of constant chamber compliance, transmitral gradient is predicted to decay as a parabolic curve, and this has been confirmed in the in vitro model with r greater than 0.99 in all cases for a range of orifice area from 0.3 to 3.0 cm2, initial pressure gradient from 2.4 to 14.2 mm Hg and net chamber compliance from 16 to 29 cc/mm Hg. This mathematic formulation of transmitral flow should help to unify the Doppler echocardiographic and catheterization assessment of mitral stenosis and left ventricular diastolic dysfunction.

Biomarkers for diet and cancer prevention research: potentials and challenges.

PubMed

Davis, Cindy D; Milner, John A

2007-09-01

As cancer incidence is projected to increase for decades there is a need for effective preventive strategies. Fortunately, evidence continues to mount that altering dietary habits is an effective and cost-efficient approach for reducing cancer risk and for modifying the biological behavior of tumors. Predictive, validated and sensitive biomarkers, including those that reliably evaluate "intake" or exposure to a specific food or bioactive component, that assess one or more specific biological "effects" that are linked to cancer, and that effectively predict individual "susceptibility" as a function of nutrient-nutrient interactions and genetics, are fundamental to evaluating who will benefit most from dietary interventions. These biomarkers must be readily accessible, easily and reliably assayed, and predictive of a key process(es) involved in cancer. The response to a food is determined not only by the effective concentration of the bioactive food component(s) reaching the target tissue, but also by the amount of the target requiring modification. Thus, this threshold response to foods and their components will vary from individual to individual. The key to understanding a personalized response is a greater knowledge of nutrigenomics, proteomics and metabolomics.

Evaluation of potential risks from ash disposal site leachate

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

Mills, W.B.; Loh, J.Y.; Bate, M.C.

1999-04-01

A risk-based approach is used to evaluate potential human health risks associated with a discharge from an ash disposal site into a small stream. The RIVRISK model was used to estimate downstream concentrations and corresponding risks. The modeling and risk analyses focus on boron, the constituent of greatest potential concern to public health at the site investigated, in Riddle Run, Pennsylvania. Prior to performing the risk assessment, the model is validated by comparing observed and predicted results. The comparison is good and an uncertainty analysis is provided to explain the comparison. The hazard quotient (HQ) for boron is predicted tomore » be greater than 1 at presently regulated compliance points over a range of flow rates. The reference dose (RfD) currently recommended by the United States Environmental Protection Agency (US EPA) was used for the analyses. However, the toxicity of boron as expressed by the RfD is now under review by both the U.S. EPA and the World Health Organization. Alternative reference doses being examined would produce predicted boron hazard quotients of less than 1 at nearly all flow conditions.« less

[Methodological approach to the use of artificial neural networks for predicting results in medicine].

PubMed

Trujillano, Javier; March, Jaume; Sorribas, Albert

2004-01-01

In clinical practice, there is an increasing interest in obtaining adequate models of prediction. Within the possible available alternatives, the artificial neural networks (ANN) are progressively more used. In this review we first introduce the ANN methodology, describing the most common type of ANN, the Multilayer Perceptron trained with backpropagation algorithm (MLP). Then we compare the MLP with the Logistic Regression (LR). Finally, we show a practical scheme to make an application based on ANN by means of an example with actual data. The main advantage of the RN is its capacity to incorporate nonlinear effects and interactions between the variables of the model without need to include them a priori. As greater disadvantages, they show a difficult interpretation of their parameters and large empiricism in their process of construction and training. ANN are useful for the computation of probabilities of a given outcome based on a set of predicting variables. Furthermore, in some cases, they obtain better results than LR. Both methodologies, ANN and LR, are complementary and they help us to obtain more valid models.

Is BMI a valid measure of obesity in postmenopausal women?

PubMed

Banack, Hailey R; Wactawski-Wende, Jean; Hovey, Kathleen M; Stokes, Andrew

2018-03-01

Body mass index (BMI) is a widely used indicator of obesity status in clinical settings and population health research. However, there are concerns about the validity of BMI as a measure of obesity in postmenopausal women. Unlike BMI, which is an indirect measure of obesity and does not distinguish lean from fat mass, dual-energy x-ray absorptiometry (DXA) provides a direct measure of body fat and is considered a gold standard of adiposity measurement. The goal of this study is to examine the validity of using BMI to identify obesity in postmenopausal women relative to total body fat percent measured by DXA scan. Data from 1,329 postmenopausal women participating in the Buffalo OsteoPerio Study were used in this analysis. At baseline, women ranged in age from 53 to 85 years. Obesity was defined as BMI ≥ 30 kg/m and body fat percent (BF%) greater than 35%, 38%, or 40%. We calculated sensitivity, specificity, positive predictive value, and negative predictive value to evaluate the validity of BMI-defined obesity relative BF%. We further explored the validity of BMI relative to BF% using graphical tools, such as scatterplots and receiver-operating characteristic curves. Youden's J index was used to determine the empirical optimal BMI cut-point for each level of BF% defined obesity. The sensitivity of BMI-defined obesity was 32.4% for 35% body fat, 44.6% for 38% body fat, and 55.2% for 40% body fat. Corresponding specificity values were 99.3%, 97.1%, and 94.6%, respectively. The empirical optimal BMI cut-point to define obesity is 24.9 kg/m for 35% BF, 26.49 kg/m for 38% BF, and 27.05 kg/m for 40% BF according to the Youden's index. Results demonstrate that a BMI cut-point of 30 kg/m does not appear to be an appropriate indicator of true obesity status in postmenopausal women. Empirical estimates of the validity of BMI from this study may be used by other investigators to account for BMI-related misclassification in older women.

Diagnosis of TIA (DOT) score--design and validation of a new clinical diagnostic tool for transient ischaemic attack.

PubMed

Dutta, Dipankar

2016-02-09

The diagnosis of Transient Ischaemic Attack (TIA) can be difficult and 50-60% of patients seen in TIA clinics turn out to be mimics. Many of these mimics have high ABCD2 scores and fill urgent TIA clinic slots inappropriately. A TIA diagnostic tool may help non-specialists make the diagnosis with greater accuracy and improve TIA clinic triage. The only available diagnostic score (Dawson et al) is limited in scope and not widely used. The Diagnosis of TIA (DOT) Score is a new and internally validated web and mobile app based diagnostic tool which encompasses both brain and retinal TIA. The score was derived retrospectively from a single centre TIA clinic database using stepwise logistic regression by backwards elimination to find the best model. An optimum cutpoint was obtained for the score. The derivation and validation cohorts were separate samples drawn from the years 2010/12 and 2013 respectively. Receiver Operating Characteristic (ROC) curves and area under the curve (AUC) were calculated and the diagnostic accuracy of DOT was compared to the Dawson score. A web and smartphone calculator were designed subsequently. The derivation cohort had 879 patients and the validation cohort 525. The final model had seventeen predictors and had an AUC of 0.91 (95% CI: 0.89-0.93). When tested on the validation cohort, the AUC for DOTS was 0.89 (0.86-0.92) while that of the Dawson score was 0.77 (0.73-0.81). The sensitivity and specificity of the DOT score were 89% (CI: 84%-93%) and 76% (70%-81%) respectively while those of the Dawson score were 83% (78%-88%) and 51% (45%-57%). Other diagnostic accuracy measures (DOT vs. Dawson) include positive predictive values (75% vs. 58%), negative predictive values (89% vs. 79%), positive likelihood ratios (3.67 vs. 1.70) and negative likelihood ratios (0.15 vs. 0.32). The DOT score shows promise as a diagnostic tool for TIA and requires independent external validation before it can be widely used. It could potentially improve the triage of patients assessed for suspected TIA.

Continuous glucose monitoring and its relationship to hemoglobin A1c and oral glucose tolerance testing in obese and prediabetic youth.

PubMed

Chan, Christine L; Pyle, Laura; Newnes, Lindsey; Nadeau, Kristen J; Zeitler, Philip S; Kelsey, Megan M

2015-03-01

The optimal screening test for diabetes and prediabetes in obese youth is controversial. We examined whether glycosylated hemoglobin (HbA1c) or the oral glucose tolerance test (OGTT) is a better predictor of free-living glycemia as measured by continuous glucose monitoring (CGM). This was a cross-sectional study of youth 10-18 years old, body mass index (BMI) 85th percentile or greater, with diabetes risk factors. Participants (n = 118) with BMI 85th percentile or greater, not on medications for glucose management, were recruited from primary care and pediatric endocrinology clinics around Denver, Colorado. HbA1c, fasting plasma glucose, and 2-hour glucose were collected and all participants wore a blinded CGM for 72 hours. CGM outcomes were determined and descriptive statistics calculated. Performance characteristics at current American Diabetes Association cutpoints were compared with CGM outcomes. CGM data were successfully collected on 98 obese youth. Those with prediabetes had significantly higher average glucose, area under the curve (AUC), peak glucose, and time greater than 120 and greater than 140 mg/dL (P < .01) on CGM than youth with normal HbA1c or OGTT. HbA1c had a greater magnitude of correlation to CGM average glucose, AUC, and minimum glucose; 2-hour glucose had a greater magnitude of correlation to CGM SD, peak glucose, and time greater than 140 and greater than 200 mg/dL. However, there were no overall differences in the strength comparisons between 2-hour glucose and HbA1c correlations to CGM outcomes. In obese youth, HbA1c and 2-hour glucose performed equally well at predicting free-living glycemia on CGM, suggesting that both are valid tests for dysglycemia screening.

Validation of the Cannabis Expectancy Questionnaire (CEQ) in adult cannabis users in treatment.

PubMed

Connor, Jason P; Gullo, Matthew J; Feeney, Gerald F X; Young, Ross McD

2011-06-01

Outcome expectancies are a key cognitive construct in the etiology, assessment and treatment of Substance Use Disorders. There is a research and clinical need for a cannabis expectancy measure validated in a clinical sample of cannabis users. The Cannabis Expectancy Questionnaire (CEQ) was subjected to exploratory (n=501, mean age 27.45, 78% male) and confirmatory (n=505, mean age 27.69, 78% male) factor analysis in two separate samples of cannabis users attending an outpatient cannabis treatment program. Weekly cannabis consumption was clinically assessed and patients completed the Severity of Dependence Scale-Cannabis (SDS-C) and the General Health Questionnaire (GHQ-28). Two factors representing Negative Cannabis Expectancies and Positive Cannabis Expectancies were identified. These provided a robust statistical and conceptual fit for the data. Internal reliabilities were high. Negative expectancies were associated with greater dependence severity (as measured by the SDS) and positive expectancies with higher consumption. The interaction of positive and negative expectancies was consistently significantly associated with self-reported functioning across all four GHQ-28 scales (Somatic Concerns, Anxiety, Social Dysfunction and Depression). Specifically, within the context of high positive cannabis expectancy, higher negative expectancy was predictive of more impaired functioning. By contrast, within the context of low positive cannabis expectancy, higher negative expectancy was predictive of better functioning. The CEQ is the first cannabis expectancy measure to be validated in a sample of cannabis users in treatment. Negative and positive cannabis expectancy domains were uniquely associated with consumption, dependence severity and self-reported mental health functioning. Crown Copyright © 2010. Published by Elsevier Ireland Ltd. All rights reserved.

Assessing student engagement and self-regulated learning in a medical gross anatomy course.

PubMed

Pizzimenti, Marc A; Axelson, Rick D

2015-01-01

In courses with large enrollment, faculty members sometimes struggle with an understanding of how individual students are engaging in their courses. Information about the level of student engagement that instructors would likely find most useful can be linked to: (1) the learning strategies that students are using; (2) the barriers to learning that students are encountering; and (3) whether the course materials and activities are yielding the intended learning outcomes. This study drew upon self-regulated learning theory (SRL) to specify relevant information about learning engagement, and how the measures of particular scales might prove useful for student/faculty reflection. We tested the quality of such information as collected via the Motivated Strategies for Learning Questionnaire (MSLQ). MSLQ items were administered through a web-based survey to 150 students in a first-year medical gross anatomy course. The resulting 66 responses (44% response rate) were examined for information quality (internal reliability and predictive validity) and usefulness of the results to the course instructor. Students' final grades in the course were correlated with their MSLQ scale scores to assess the predictive validity of the measures. These results were consistent with the course design and expectations, showing that greater use of learning strategies such as elaboration and critical thinking was associated with higher levels of performance in the course. Motivation subscales for learning were also correlated with the higher levels of performance in the course. The extent to which these scales capture valid and reliable information in other institutional settings and courses needs further investigation. © 2014 American Association of Anatomists.

Validation and Application of the Survey of Teaching Beliefs and Practices for Undergraduates (STEP-U): Identifying Factors Associated with Valuing Important Workplace Skills among Biology Students

PubMed Central

Marbach-Ad, Gili; Rietschel, Carly; Thompson, Katerina V.

2016-01-01

We present a novel assessment tool for measuring biology students’ values and experiences across their undergraduate degree program. Our Survey of Teaching Beliefs and Practices for Undergraduates (STEP-U) assesses the extent to which students value skills needed for the workplace (e.g., ability to work in groups) and their experiences with teaching practices purported to promote such skills (e.g., group work). The survey was validated through factor analyses in a large sample of biology seniors (n = 1389) and through response process analyses (five interviewees). The STEP-U skills items were characterized by two underlying factors: retention (e.g., memorization) and transfer (e.g., knowledge application). Multiple linear regression models were used to examine relationships between classroom experiences, values, and student characteristics (e.g., gender, cumulative grade point average [GPA], and research experience). Student demographic and experiential factors predicted the extent to which students valued particular skills. Students with lower GPAs valued retention skills more than those with higher GPAs. Students with research experience placed greater value on scientific writing and interdisciplinary understanding. Greater experience with specific teaching practices was associated with valuing the corresponding skills more highly. The STEP-U can provide feedback vital for designing curricula that better prepare students for their intended postgraduate careers. PMID:27856547

Risk assessment for juvenile justice: a meta-analysis.

PubMed

Schwalbe, Craig S

2007-10-01

Risk assessment instruments are increasingly employed by juvenile justice settings to estimate the likelihood of recidivism among delinquent juveniles. In concert with their increased use, validation studies documenting their predictive validity have increased in number. The purpose of this study was to assess the average predictive validity of juvenile justice risk assessment instruments and to identify risk assessment characteristics that are associated with higher predictive validity. A search of the published and grey literature yielded 28 studies that estimated the predictive validity of 28 risk assessment instruments. Findings of the meta-analysis were consistent with effect sizes obtained in larger meta-analyses of criminal justice risk assessment instruments and showed that brief risk assessment instruments had smaller effect sizes than other types of instruments. However, this finding is tentative owing to limitations of the literature.

AHP-based spatial analysis of water quality impact assessment due to change in vehicular traffic caused by highway broadening in Sikkim Himalaya

NASA Astrophysics Data System (ADS)

Banerjee, Polash; Ghose, Mrinal Kanti; Pradhan, Ratika

2018-05-01

Spatial analysis of water quality impact assessment of highway projects in mountainous areas remains largely unexplored. A methodology is presented here for Spatial Water Quality Impact Assessment (SWQIA) due to highway-broadening-induced vehicular traffic change in the East district of Sikkim. Pollution load of the highway runoff was estimated using an Average Annual Daily Traffic-Based Empirical model in combination with mass balance model to predict pollution in the rivers within the study area. Spatial interpolation and overlay analysis were used for impact mapping. Analytic Hierarchy Process-Based Water Quality Status Index was used to prepare a composite impact map. Model validation criteria, cross-validation criteria, and spatial explicit sensitivity analysis show that the SWQIA model is robust. The study shows that vehicular traffic is a significant contributor to water pollution in the study area. The model is catering specifically to impact analysis of the concerned project. It can be an aid for decision support system for the project stakeholders. The applicability of SWQIA model needs to be explored and validated in the context of a larger set of water quality parameters and project scenarios at a greater spatial scale.

Further Validation of the Pathways Housing First Fidelity Scale.

PubMed

Goering, Paula; Veldhuizen, Scott; Nelson, Geoffrey B; Stefancic, Ana; Tsemberis, Sam; Adair, Carol E; Distasio, Jino; Aubry, Tim; Stergiopoulos, Vicky; Streiner, David L

2016-01-01

This study examined whether Housing First fidelity ratings correspond to program operation descriptions from administrative data and predict client outcomes. A multisite, randomized controlled trial (At Home/Chez Soi) in five Canadian cities included two assessments of 12 programs over two years. Outcomes for 1,158 clients were measured every six months. Associations between fidelity ratings and administrative data (Spearman correlations) and participant outcomes (mixed-effects modeling) were examined. Fidelity ratings were generally good (mean ± SD=136.6 ± 10.3 out of a possible range of 38-152; 87% of maximum value). Fidelity was significantly associated with three of four measures of program operation, with correlations between .55 and .60. Greater program fidelity was associated with improvement in housing stability, community functioning, and quality of life. Variation in program fidelity was associated with operations and outcomes, supporting scale validity and intervention effectiveness. These findings reinforced the value of using fidelity monitoring to conduct quality assurance and technical assistance activities.

Trait and State Craving as Indicators of Validity of VR-based Software for Binge Eating Treatment.

PubMed

Pla-Sanjuanelo, Joana; Ferrer-Garcia, Marta; Gutiérrez-Maldonado, José; Vilalta-Abella, Ferran; Andreu-Gracia, Alexis; Dakanalis, Antonios; Fernandez-Aranda, Fernando; Fusté-Escolano, Adela; Ribas-Sabaté, Joan; Riva, Giuseppe; Saldaña, Carmina; Sánchez, Isabel

2015-01-01

The aim of this study was to establish whether virtual reality (VR) exposure to food cues is able to produce craving levels consistent with state-craving and trait-craving as assessed by the Spanish and Italian versions of the State and Trait Food Craving Questionnaires (FCQ-T/S). The results were compared in 40 patients with eating disorders (17 with binge eating disorder, 23 with bulimia nervosa) and 78 healthy control subjects without eating disorders. Controls and patients with higher levels of trait-craving and state-craving both showed a greater desire to eat during VR exposure. Results also showed that trait and state craving assessed by FCQ-T/S were able to predict the total mean craving experienced during exposure to the VR software in both clinical and control samples. These findings present preliminary evidence about the validity of a new virtual reality-based application for cue-exposure treatment in patients with eating disorders.

Adaptive disengagement buffers self-esteem from negative social feedback.

PubMed

Leitner, Jordan B; Hehman, Eric; Deegan, Matthew P; Jones, James M

2014-11-01

The degree to which self-esteem hinges on feedback in a domain is known as a contingency of self-worth, or engagement. Although previous research has conceptualized engagement as stable, it would be advantageous for individuals to dynamically regulate engagement. The current research examined whether the tendency to disengage from negative feedback accounts for variability in self-esteem. We created the Adaptive Disengagement Scale (ADS) to capture individual differences in the tendency to disengage self-esteem from negative outcomes. Results demonstrated that the ADS is reliable and valid (Studies 1 and 2). Furthermore, in response to negative social feedback, higher scores on the ADS predicted greater state self-esteem (Study 3), and this relationship was mediated by disengagement (Study 4). These findings demonstrate that adaptive disengagement protects self-esteem from negative outcomes and that the ADS is a valid measure of individual differences in the implementation of this process. © 2014 by the Society for Personality and Social Psychology, Inc.

How valid are self-reports of illness-related absence? Evidence from a university employee health management program.

PubMed

Jenkins, Kristi Rahrig

2014-08-01

The present study uses a focused approach to compare self-reported versus administratively recorded measures of absences related to health or illness. To date, the few studies that focus on this topic produced mixed results. To help shed light on this issue, the present research has 2 related objectives: (1) examine how highly correlated self-reported and administratively recorded measures of absences related to health or illness might be, and (2) how each measure predicts various aspects of health. Using data from the 2012 StayWell® Health Management health risk appraisal (HRA) and 1 year (2011) of administratively recorded timekeeping data, bivariate analyses for continuous variables and generalized linear modeling for variables with greater than 2 response categories were used. For the multivariate analyses, linear regression models controlling for sex, age, race, income, job status, and campus location were calculated for the continuous outcomes (ie, self-rated health and chronic conditions). Results indicate that self-reported and administratively recorded absences related to health or illness were moderately correlated (correlation coefficient of 0.47). In addition, each measure functioned similarly (in direction and magnitude) to predict health outcomes. Both greater self-reported and recorded illness-related absenteeism was associated with poorer self-rated health and greater numbers of chronic conditions. These results suggest that self-rated illness-related absenteeism may be a reasonable way to assess various program outcomes meaningful to employers, particularly if administratively recorded measures are unavailable or too time consuming or expensive to analyze.

Dispositional optimism and perceived risk interact to predict intentions to learn genome sequencing results.

PubMed

Taber, Jennifer M; Klein, William M P; Ferrer, Rebecca A; Lewis, Katie L; Biesecker, Leslie G; Biesecker, Barbara B

2015-07-01

Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. (c) 2015 APA, all rights reserved.

Dispositional Optimism and Perceived Risk Interact to Predict Intentions to Learn Genome Sequencing Results

PubMed Central

Taber, Jennifer M.; Klein, William M. P.; Ferrer, Rebecca A.; Lewis, Katie L.; Biesecker, Leslie G.; Biesecker, Barbara B.

2015-01-01

Objective Dispositional optimism and risk perceptions are each associated with health-related behaviors and decisions and other outcomes, but little research has examined how these constructs interact, particularly in consequential health contexts. The predictive validity of risk perceptions for health-related information seeking and intentions may be improved by examining dispositional optimism as a moderator, and by testing alternate types of risk perceptions, such as comparative and experiential risk. Method Participants (n = 496) had their genomes sequenced as part of a National Institutes of Health pilot cohort study (ClinSeq®). Participants completed a cross-sectional baseline survey of various types of risk perceptions and intentions to learn genome sequencing results for differing disease risks (e.g., medically actionable, nonmedically actionable, carrier status) and to use this information to change their lifestyle/health behaviors. Results Risk perceptions (absolute, comparative, and experiential) were largely unassociated with intentions to learn sequencing results. Dispositional optimism and comparative risk perceptions interacted, however, such that individuals higher in optimism reported greater intentions to learn all 3 types of sequencing results when comparative risk was perceived to be higher than when it was perceived to be lower. This interaction was inconsistent for experiential risk and absent for absolute risk. Independent of perceived risk, participants high in dispositional optimism reported greater interest in learning risks for nonmedically actionable disease and carrier status, and greater intentions to use genome information to change their lifestyle/health behaviors. Conclusions The relationship between risk perceptions and intentions may depend on how risk perceptions are assessed and on degree of optimism. PMID:25313897

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

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

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

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

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Arsenic removal by solar-driven membrane distillation: modeling and experimental investigation with a new flash vaporization module.

PubMed

Pa, Parimal; Manna, Ajay Kumar; Linnanen, Lassi

2013-01-01

A modeling and simulation study was carried out on a new flux-enhancing and solar-driven membrane distillation module for removal of arsenic from contaminated groundwater. The developed new model was validated with rigorous experimental investigations using arsenic-contaminated groundwater. By incorporating flash vaporization dynamics, the model turned out to be substantially different from the existing direct contact membrane distillation models and could successfully predict (with relative error of only 0.042 and a Willmott d-index of 0.997) the performance of such an arsenic removal unit where the existing models exhibited wide variation with experimental findings in the new design. The module with greater than 99% arsenic removal efficiency and greater than 50 L/m2 x h flux could be implemented in arsenic-affected villages in Southeast Asian countries with abundant solar energy, and thus could give relief to millions of affected people. These encouraging results will raise scale-up confidence.

Using CV-GLUE procedure in analysis of wetland model predictive uncertainty.

PubMed

Huang, Chun-Wei; Lin, Yu-Pin; Chiang, Li-Chi; Wang, Yung-Chieh

2014-07-01

This study develops a procedure that is related to Generalized Likelihood Uncertainty Estimation (GLUE), called the CV-GLUE procedure, for assessing the predictive uncertainty that is associated with different model structures with varying degrees of complexity. The proposed procedure comprises model calibration, validation, and predictive uncertainty estimation in terms of a characteristic coefficient of variation (characteristic CV). The procedure first performed two-stage Monte-Carlo simulations to ensure predictive accuracy by obtaining behavior parameter sets, and then the estimation of CV-values of the model outcomes, which represent the predictive uncertainties for a model structure of interest with its associated behavior parameter sets. Three commonly used wetland models (the first-order K-C model, the plug flow with dispersion model, and the Wetland Water Quality Model; WWQM) were compared based on data that were collected from a free water surface constructed wetland with paddy cultivation in Taipei, Taiwan. The results show that the first-order K-C model, which is simpler than the other two models, has greater predictive uncertainty. This finding shows that predictive uncertainty does not necessarily increase with the complexity of the model structure because in this case, the more simplistic representation (first-order K-C model) of reality results in a higher uncertainty in the prediction made by the model. The CV-GLUE procedure is suggested to be a useful tool not only for designing constructed wetlands but also for other aspects of environmental management. Copyright © 2014 Elsevier Ltd. All rights reserved.

The Predictive Validity of the Tilburg Frailty Indicator: Disability, Health Care Utilization, and Quality of Life in a Population at Risk

ERIC Educational Resources Information Center

Gobbens, Robbert J. J.; van Assen, Marcel A. L. M.; Luijkx, Katrien G.; Schols, Jos M. G. A.

2012-01-01

Purpose: To assess the predictive validity of frailty and its domains (physical, psychological, and social), as measured by the Tilburg Frailty Indicator (TFI), for the adverse outcomes disability, health care utilization, and quality of life. Design and Methods: The predictive validity of the TFI was tested in a representative sample of 484…

Validity of the International Classification of Diseases 10th revision code for hospitalisation with hyponatraemia in elderly patients

PubMed Central

Gandhi, Sonja; Shariff, Salimah Z; Fleet, Jamie L; Weir, Matthew A; Jain, Arsh K; Garg, Amit X

2012-01-01

Objective To evaluate the validity of the International Classification of Diseases, 10th Revision (ICD-10) diagnosis code for hyponatraemia (E87.1) in two settings: at presentation to the emergency department and at hospital admission. Design Population-based retrospective validation study. Setting Twelve hospitals in Southwestern Ontario, Canada, from 2003 to 2010. Participants Patients aged 66 years and older with serum sodium laboratory measurements at presentation to the emergency department (n=64 581) and at hospital admission (n=64 499). Main outcome measures Sensitivity, specificity, positive predictive value and negative predictive value comparing various ICD-10 diagnostic coding algorithms for hyponatraemia to serum sodium laboratory measurements (reference standard). Median serum sodium values comparing patients who were code positive and code negative for hyponatraemia. Results The sensitivity of hyponatraemia (defined by a serum sodium ≤132 mmol/l) for the best-performing ICD-10 coding algorithm was 7.5% at presentation to the emergency department (95% CI 7.0% to 8.2%) and 10.6% at hospital admission (95% CI 9.9% to 11.2%). Both specificities were greater than 99%. In the two settings, the positive predictive values were 96.4% (95% CI 94.6% to 97.6%) and 82.3% (95% CI 80.0% to 84.4%), while the negative predictive values were 89.2% (95% CI 89.0% to 89.5%) and 87.1% (95% CI 86.8% to 87.4%). In patients who were code positive for hyponatraemia, the median (IQR) serum sodium measurements were 123 (119–126) mmol/l and 125 (120–130) mmol/l in the two settings. In code negative patients, the measurements were 138 (136–140) mmol/l and 137 (135–139) mmol/l. Conclusions The ICD-10 diagnostic code for hyponatraemia differentiates between two groups of patients with distinct serum sodium measurements at both presentation to the emergency department and at hospital admission. However, these codes underestimate the true incidence of hyponatraemia due to low sensitivity. PMID:23274673

An Individualized Risk Calculator for Research in Prodromal Psychosis

PubMed Central

Cannon, Tyrone D.; Yu, Changhong; Addington, Jean; Bearden, Carrie E.; Cadenhead, Kristin S.; Cornblatt, Barbara A.; Heinssen, Robert; Jeffries, Clark D.; Mathalon, Daniel H.; McGlashan, Thomas H.; Perkins, Diana O.; Seidman, Larry J.; Tsuang, Ming T.; Walker, Elaine F.; Woods, Scott W.; Kattan, Michael

2016-01-01

Objective About 20–35% of individuals aged 12–30 years who meet criteria for a prodromal risk syndrome convert to psychosis within two years. However, this estimate ignores the fact that clinical high-risk (CHR) cases vary considerably in risk. Here we sought to create a risk calculator that can ascertain the probability of conversion to psychosis in individual patients based on profiles of risk indicators. The high risk category predicted by this calculator can inform research criteria going forward. Method Subjects were 596 CHR participants from the second phase of the North American Prodrome Longitudinal Study (NAPLS 2) who were followed up to the time of conversion to psychosis or last contact (up to 2 years). Our scope was limited to predictors supported by prior studies and readily obtainable in general clinical settings. Time-to-event regression was used to build a multivariate model predicting conversion, with internal validation using 1000 bootstrap resamples. Results The 2-year probability of conversion to psychosis in this sample was 16%. Higher levels of unusual thought content and suspiciousness, greater decline in social functioning, lower verbal learning and memory performance, slower speed of processing, and younger age at baseline each contributed to individual risk for psychosis, while stressful life events, traumas, and family history of schizophrenia were not significant predictors. The multivariate model achieved a Concordance index of 0.71, and was validated in an independent external dataset. The results are instantiated in a web-based risk prediction tool envisioned to be most useful in research protocols involving the psychosis prodrome. Conclusions A risk calculator comparable in accuracy to those for cardiovascular disease and cancer is available to predict individualized conversion risks in newly ascertained CHR cases. Given that the risk calculator can only be validly applied for patients who screen positive on the Structured Clinical Interview for Psychosis Risk Syndromes, which requires training to administer, it's most immediate uses will be in research on psychosis risk factors and in research driven clinical (prevention) trials. PMID:27363508

Validity of the International Classification of Diseases 10th revision code for hyperkalaemia in elderly patients at presentation to an emergency department and at hospital admission

PubMed Central

Fleet, Jamie L; Shariff, Salimah Z; Gandhi, Sonja; Weir, Matthew A; Jain, Arsh K; Garg, Amit X

2012-01-01

Objectives Evaluate the validity of the International Classification of Diseases, 10th revision (ICD-10) code for hyperkalaemia (E87.5) in two settings: at presentation to an emergency department and at hospital admission. Design Population-based validation study. Setting 12 hospitals in Southwestern Ontario, Canada, from 2003 to 2010. Participants Elderly patients with serum potassium values at presentation to an emergency department (n=64 579) and at hospital admission (n=64 497). Primary outcome Sensitivity, specificity, positive-predictive value and negative-predictive value. Serum potassium values in patients with and without a hyperkalaemia code (code positive and code negative, respectively). Results The sensitivity of the best-performing ICD-10 coding algorithm for hyperkalaemia (defined by serum potassium >5.5 mmol/l) was 14.1% (95% CI 12.5% to 15.9%) at presentation to an emergency department and 14.6% (95% CI 13.3% to 16.1%) at hospital admission. Both specificities were greater than 99%. In the two settings, the positive-predictive values were 83.2% (95% CI 78.4% to 87.1%) and 62.0% (95% CI 57.9% to 66.0%), while the negative-predictive values were 97.8% (95% CI 97.6% to 97.9%) and 96.9% (95% CI 96.8% to 97.1%). In patients who were code positive for hyperkalaemia, median (IQR) serum potassium values were 6.1 (5.7 to 6.8) mmol/l at presentation to an emergency department and 6.0 (5.1 to 6.7) mmol/l at hospital admission. For code-negative patients median (IQR) serum potassium values were 4.0 (3.7 to 4.4) mmol/l and 4.1 (3.8 to 4.5) mmol/l in each of the two settings, respectively. Conclusions Patients with hospital encounters who were ICD-10 E87.5 hyperkalaemia code positive and negative had distinct higher and lower serum potassium values, respectively. However, due to very low sensitivity, the incidence of hyperkalaemia is underestimated. PMID:23274674

Validation of finite element and boundary element methods for predicting structural vibration and radiated noise

NASA Technical Reports Server (NTRS)

Seybert, A. F.; Wu, X. F.; Oswald, Fred B.

1992-01-01

Analytical and experimental validation of methods to predict structural vibration and radiated noise are presented. A rectangular box excited by a mechanical shaker was used as a vibrating structure. Combined finite element method (FEM) and boundary element method (BEM) models of the apparatus were used to predict the noise radiated from the box. The FEM was used to predict the vibration, and the surface vibration was used as input to the BEM to predict the sound intensity and sound power. Vibration predicted by the FEM model was validated by experimental modal analysis. Noise predicted by the BEM was validated by sound intensity measurements. Three types of results are presented for the total radiated sound power: (1) sound power predicted by the BEM modeling using vibration data measured on the surface of the box; (2) sound power predicted by the FEM/BEM model; and (3) sound power measured by a sound intensity scan. The sound power predicted from the BEM model using measured vibration data yields an excellent prediction of radiated noise. The sound power predicted by the combined FEM/BEM model also gives a good prediction of radiated noise except for a shift of the natural frequencies that are due to limitations in the FEM model.

Attention in aviation. [to aircraft design and pilot performance

NASA Technical Reports Server (NTRS)

Wickens, Christopher D.

1987-01-01

The relevance of four principles or mechanisms of human attention to the design of aviation systems and the performance of pilots in multitask environments, including workload prediction and measurement, control-display integration, and the use of voice and head-up displays is discussed. The principles are: the mental energy that supplies task performance (resources), the resulting cross-talk between tasks as they are made more similar (confusion), the combination of different task elements (integration), and the way in which one task is processed and another is ignored (selection or tunneling). The introduction of greater levels of complexity into the validation of attentional theories in order to approach the demands of the cockpit or ATC console is proposed.

Beyond the Triplet Code: Context Cues Transform Translation.

PubMed

Brar, Gloria A

2016-12-15

The elucidation of the genetic code remains among the most influential discoveries in biology. While innumerable studies have validated the general universality of the code and its value in predicting and analyzing protein coding sequences, established and emerging work has also suggested that full genome decryption may benefit from a greater consideration of a codon's neighborhood within an mRNA than has been broadly applied. This Review examines the evidence for context cues in translation, with a focus on several recent studies that reveal broad roles for mRNA context in programming translation start sites, the rate of translation elongation, and stop codon identity. Copyright © 2016 Elsevier Inc. All rights reserved.

Individualized prediction of perineural invasion in colorectal cancer: development and validation of a radiomics prediction model.

PubMed

Huang, Yanqi; He, Lan; Dong, Di; Yang, Caiyun; Liang, Cuishan; Chen, Xin; Ma, Zelan; Huang, Xiaomei; Yao, Su; Liang, Changhong; Tian, Jie; Liu, Zaiyi

2018-02-01

To develop and validate a radiomics prediction model for individualized prediction of perineural invasion (PNI) in colorectal cancer (CRC). After computed tomography (CT) radiomics features extraction, a radiomics signature was constructed in derivation cohort (346 CRC patients). A prediction model was developed to integrate the radiomics signature and clinical candidate predictors [age, sex, tumor location, and carcinoembryonic antigen (CEA) level]. Apparent prediction performance was assessed. After internal validation, independent temporal validation (separate from the cohort used to build the model) was then conducted in 217 CRC patients. The final model was converted to an easy-to-use nomogram. The developed radiomics nomogram that integrated the radiomics signature and CEA level showed good calibration and discrimination performance [Harrell's concordance index (c-index): 0.817; 95% confidence interval (95% CI): 0.811-0.823]. Application of the nomogram in validation cohort gave a comparable calibration and discrimination (c-index: 0.803; 95% CI: 0.794-0.812). Integrating the radiomics signature and CEA level into a radiomics prediction model enables easy and effective risk assessment of PNI in CRC. This stratification of patients according to their PNI status may provide a basis for individualized auxiliary treatment.

Development and Validation of the Human Papillomavirus Attitudes and Beliefs Scale in a National Canadian Sample.

PubMed

Perez, Samara; Shapiro, Gilla K; Tatar, Ovidiu; Joyal-Desmarais, Keven; Rosberger, Zeev

2016-10-01

Parents' human papillomavirus (HPV) vaccination decision-making is strongly influenced by their attitudes and beliefs toward vaccination. To date, psychometrically evaluated HPV vaccination attitudes scales have been narrow in their range of measured beliefs and often limited to attitudes surrounding female HPV vaccination. The study aimed to develop a comprehensive, validated and reliable HPV vaccination attitudes and beliefs scale among parents of boys. Data were collected from Canadian parents of 9- to 16-year-old boys using an online questionnaire completed in 2 waves with a 7-month interval. Based on existing vaccination attitudes scales, a set of 61 attitude and belief items were developed. Exploratory and confirmatory factor analyses were conducted. Internal consistency was evaluated with Cronbach's α and stability over time with intraclass correlations. The HPV Attitudes and Beliefs Scale (HABS) was informed by 3117 responses at time 1 and 1427 at time 2. The HABS contains 46 items organized in 9 factors: Benefits (10 items), Threat (3 items), Influence (8 items), Harms (6 items), Risk (3 items), Affordability (3 items), Communication (5 items), Accessibility (4 items), and General Vaccination Attitudes (4 items). Model fit at time 2 were: χ/df = 3.13, standardized root mean square residual = 0.056, root mean square error approximation (confidence interval) = 0.039 (0.037-0.04), comparative fit index = 0.962 and Tucker-Lewis index = 0.957. Cronbach's αs were greater than 0.8 and intraclass correlations of factors were greater than 0.6. The HABS is the first psychometrically-tested scale of HPV attitude and beliefs among parents of boys available for use in English and French. Further testing among parents of girls and young adults and assessing predictive validity are warranted.

Validity of self-reported height and weight in 4808 EPIC-Oxford participants.

PubMed

Spencer, Elizabeth A; Appleby, Paul N; Davey, Gwyneth K; Key, Timothy J

2002-08-01

To assess the validity of self-reported height and weight by comparison with measured height and weight in a sample of middle-aged men and women, and to determine the extent of misclassification of body mass index (BMI) arising from differences between self-reported and measured values. Analysis of self-reported and measured height and weight data from participants in the Oxford cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC-Oxford). Four thousand eight hundred and eight British men and women aged 35-76 years. Spearman rank correlations between self-reported and measured height, weight and BMI were high (r > 0.9, P < 0.0001). Height was overestimated by a mean of 1.23 (95% confidence interval (CI) 1.11-1.34) cm in men and 0.60 (0.51-0.70) cm in women; the extent of overestimation was greater in older men and women, shorter men and heavier women. Weight was underestimated by a mean of 1.85 (1.72-1.99) kg in men and 1.40 (1.31-1.49) kg in women; the extent of underestimation was greater in heavier men and women, but did not vary with age or height. Using standard categories of BMI, 22.4% of men and 18.0% of women were classified incorrectly based on self-reported height and weight. After correcting the self-reported values using predictive equations derived from a 10% sample of subjects, misclassification decreased to 15.2% in men and 13.8% in women. Self-reported height and weight data are valid for identifying relationships in epidemiological studies. In analyses where anthropometric factors are the primary variables of interest, measurements in a representative sample of the study population can be used to improve the accuracy of estimates of height, weight and BMI.

Sleep deprivation alters functioning within the neural network underlying the covert orienting of attention.

PubMed

Mander, Bryce A; Reid, Kathryn J; Davuluri, Vijay K; Small, Dana M; Parrish, Todd B; Mesulam, M-Marsel; Zee, Phyllis C; Gitelman, Darren R

2008-06-27

One function of spatial attention is to enable goal-directed interactions with the environment through the allocation of neural resources to motivationally relevant parts of space. Studies have shown that responses are enhanced when spatial attention is predictively biased towards locations where significant events are expected to occur. Previous studies suggest that the ability to bias attention predictively is related to posterior cingulate cortex (PCC) activation [Small, D.M., et al., 2003. The posterior cingulate and medial prefrontal cortex mediate the anticipatory allocation of spatial attention. Neuroimage 18, 633-41]. Sleep deprivation (SD) impairs selective attention and reduces PCC activity [Thomas, M., et al., 2000. Neural basis of alertness and cognitive performance impairments during sleepiness. I. Effects of 24 h of sleep deprivation on waking human regional brain activity. J. Sleep Res. 9, 335-352]. Based on these findings, we hypothesized that SD would affect PCC function and alter the ability to predictively allocate spatial attention. Seven healthy, young adults underwent functional magnetic resonance imaging (fMRI) following normal rest and 34-36 h of SD while performing a task in which attention was shifted in response to peripheral targets preceded by spatially informative (valid), misleading (invalid), or uninformative (neutral) cues. When rested, but not when sleep-deprived, subjects responded more quickly to targets that followed valid cues than those after neutral or invalid cues. Brain activity during validly cued trials with a reaction time benefit was compared to activity in trials with no benefit. PCC activation was greater during trials with a reaction time benefit following normal rest. In contrast, following SD, reaction time benefits were associated with activation in the left intraparietal sulcus, a region associated with receptivity to stimuli at unexpected locations. These changes may render sleep-deprived individuals less able to anticipate the locations of upcoming events, and more susceptible to distraction by stimuli at irrelevant locations.

Measuring the effect of inter-study variability on estimating prediction error.

PubMed

Ma, Shuyi; Sung, Jaeyun; Magis, Andrew T; Wang, Yuliang; Geman, Donald; Price, Nathan D

2014-01-01

The biomarker discovery field is replete with molecular signatures that have not translated into the clinic despite ostensibly promising performance in predicting disease phenotypes. One widely cited reason is lack of classification consistency, largely due to failure to maintain performance from study to study. This failure is widely attributed to variability in data collected for the same phenotype among disparate studies, due to technical factors unrelated to phenotypes (e.g., laboratory settings resulting in "batch-effects") and non-phenotype-associated biological variation in the underlying populations. These sources of variability persist in new data collection technologies. Here we quantify the impact of these combined "study-effects" on a disease signature's predictive performance by comparing two types of validation methods: ordinary randomized cross-validation (RCV), which extracts random subsets of samples for testing, and inter-study validation (ISV), which excludes an entire study for testing. Whereas RCV hardwires an assumption of training and testing on identically distributed data, this key property is lost in ISV, yielding systematic decreases in performance estimates relative to RCV. Measuring the RCV-ISV difference as a function of number of studies quantifies influence of study-effects on performance. As a case study, we gathered publicly available gene expression data from 1,470 microarray samples of 6 lung phenotypes from 26 independent experimental studies and 769 RNA-seq samples of 2 lung phenotypes from 4 independent studies. We find that the RCV-ISV performance discrepancy is greater in phenotypes with few studies, and that the ISV performance converges toward RCV performance as data from additional studies are incorporated into classification. We show that by examining how fast ISV performance approaches RCV as the number of studies is increased, one can estimate when "sufficient" diversity has been achieved for learning a molecular signature likely to translate without significant loss of accuracy to new clinical settings.

Gene Environment Interactions and Predictors of Colorectal Cancer in Family-Based, Multi-Ethnic Groups.

PubMed

Shiao, S Pamela K; Grayson, James; Yu, Chong Ho; Wasek, Brandi; Bottiglieri, Teodoro

2018-02-16

For the personalization of polygenic/omics-based health care, the purpose of this study was to examine the gene-environment interactions and predictors of colorectal cancer (CRC) by including five key genes in the one-carbon metabolism pathways. In this proof-of-concept study, we included a total of 54 families and 108 participants, 54 CRC cases and 54 matched family friends representing four major racial ethnic groups in southern California (White, Asian, Hispanics, and Black). We used three phases of data analytics, including exploratory, family-based analyses adjusting for the dependence within the family for sharing genetic heritage, the ensemble method, and generalized regression models for predictive modeling with a machine learning validation procedure to validate the results for enhanced prediction and reproducibility. The results revealed that despite the family members sharing genetic heritage, the CRC group had greater combined gene polymorphism rates than the family controls ( p < 0.05), on MTHFR C677T , MTR A2756G , MTRR A66G, and DHFR 19 bp except MTHFR A1298C. Four racial groups presented different polymorphism rates for four genes (all p < 0.05) except MTHFR A1298C. Following the ensemble method, the most influential factors were identified, and the best predictive models were generated by using the generalized regression models, with Akaike's information criterion and leave-one-out cross validation methods. Body mass index (BMI) and gender were consistent predictors of CRC for both models when individual genes versus total polymorphism counts were used, and alcohol use was interactive with BMI status. Body mass index status was also interactive with both gender and MTHFR C677T gene polymorphism, and the exposure to environmental pollutants was an additional predictor. These results point to the important roles of environmental and modifiable factors in relation to gene-environment interactions in the prevention of CRC.

Risk prediction models for graft failure in kidney transplantation: a systematic review.

PubMed

Kaboré, Rémi; Haller, Maria C; Harambat, Jérôme; Heinze, Georg; Leffondré, Karen

2017-04-01

Risk prediction models are useful for identifying kidney recipients at high risk of graft failure, thus optimizing clinical care. Our objective was to systematically review the models that have been recently developed and validated to predict graft failure in kidney transplantation recipients. We used PubMed and Scopus to search for English, German and French language articles published in 2005-15. We selected studies that developed and validated a new risk prediction model for graft failure after kidney transplantation, or validated an existing model with or without updating the model. Data on recipient characteristics and predictors, as well as modelling and validation methods were extracted. In total, 39 articles met the inclusion criteria. Of these, 34 developed and validated a new risk prediction model and 5 validated an existing one with or without updating the model. The most frequently predicted outcome was graft failure, defined as dialysis, re-transplantation or death with functioning graft. Most studies used the Cox model. There was substantial variability in predictors used. In total, 25 studies used predictors measured at transplantation only, and 14 studies used predictors also measured after transplantation. Discrimination performance was reported in 87% of studies, while calibration was reported in 56%. Performance indicators were estimated using both internal and external validation in 13 studies, and using external validation only in 6 studies. Several prediction models for kidney graft failure in adults have been published. Our study highlights the need to better account for competing risks when applicable in such studies, and to adequately account for post-transplant measures of predictors in studies aiming at improving monitoring of kidney transplant recipients. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Anastomotic leak after colorectal resection: A population-based study of risk factors and hospital variation.

PubMed

Nikolian, Vahagn C; Kamdar, Neil S; Regenbogen, Scott E; Morris, Arden M; Byrn, John C; Suwanabol, Pasithorn A; Campbell, Darrell A; Hendren, Samantha

2017-06-01

Anastomotic leak is a major source of morbidity in colorectal operations and has become an area of interest in performance metrics. It is unclear whether anastomotic leak is associated primarily with surgeons' technical performance or explained better by patient characteristics and institutional factors. We sought to establish if anastomotic leak could serve as a valid quality metric in colorectal operations by evaluating provider variation after adjusting for patient factors. We performed a retrospective cohort study of colorectal resection patients in the Michigan Surgical Quality Collaborative. Clinically relevant patient and operative factors were tested for association with anastomotic leak. Hierarchical logistic regression was used to derive risk-adjusted rates of anastomotic leak. Of 9,192 colorectal resections, 244 (2.7%) had a documented anastomotic leak. The incidence of anastomotic leak was 3.0% for patients with pelvic anastomoses and 2.5% for those with intra-abdominal anastomoses. Multivariable analysis showed that a greater operative duration, male sex, body mass index >30 kg/m 2 , tobacco use, chronic immunosuppressive medications, thrombocytosis (platelet count >400 × 10 9 /L), and urgent/emergency operations were independently associated with anastomotic leak (C-statistic = 0.75). After accounting for patient and procedural risk factors, 5 hospitals had a significantly greater incidence of postoperative anastomotic leak. This population-based study shows that risk factors for anastomotic leak include male sex, obesity, tobacco use, immunosuppression, thrombocytosis, greater operative duration, and urgent/emergency operation; models including these factors predict most of the variation in anastomotic leak rates. This study suggests that anastomotic leak can serve as a valid metric that can identify opportunities for quality improvement. Copyright © 2017 Elsevier Inc. All rights reserved.

Biomarker validation of a decline in semantic processing in preclinical Alzheimer's disease.

PubMed

Papp, Kathryn V; Mormino, Elizabeth C; Amariglio, Rebecca E; Munro, Catherine; Dagley, Alex; Schultz, Aaron P; Johnson, Keith A; Sperling, Reisa A; Rentz, Dorene M

2016-07-01

Differentially worse performance on category versus letter fluency suggests greater semantic versus retrieval difficulties. This discrepancy, combined with reduced episodic memory, has widespread clinical utility in diagnosing Alzheimer's disease (AD). Our objective was to investigate whether changes in semantic processing, as measured by the discrepancy between category and letter fluency, was detectable in preclinical AD: in clinically normal older adults with abnormal β-amyloid (Aβ) deposition on positron emission tomography (PET) neuroimaging. Clinically normal older adults (mean Mini Mental State Exam (MMSE) score = 29) were classified as Aβ+ (n = 70) or Aβ- (n = 205) using Pittsburgh Compound B-(PET) imaging. Participants completed letter fluency (FAS; word generation to letters F-A-S) and category fluency (CAT; word generation to animals, vegetables, fruits) annually (mean follow-up = 2.42 years). The effect of Aβ status on fluency over time was examined using linear mixed models controlling for age, sex, and education. To dissociate effects related to semantic (CAT) versus retrieval processes (CAT and FAS), we repeated models predicting CAT over time, controlling for FAS and likewise for CAT controlling for FAS. At baseline, the Aβ+ group performed better on FAS compared with the Aβ- group but comparably on CAT. Longitudinally, the Aβ+ group demonstrated greater decline on CAT compared with the Aβ- group (p = .0011). This finding remained significant even when covarying for FAS (p = .0107). Aβ+ participants similarly declined compared with Aβ- participants on FAS (p = .0112), but this effect became insignificant when covarying for CAT (p = .1607). These findings provide biomarker validation for the greater specificity of declines in category versus letter fluency to underlying AD pathology. Our results also suggest that changes in semantic processing occur earlier in the AD trajectory than previously hypothesized. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Predictive value and construct validity of the work functioning screener-healthcare (WFS-H).

PubMed

Boezeman, Edwin J; Nieuwenhuijsen, Karen; Sluiter, Judith K

2016-05-25

To test the predictive value and convergent construct validity of a 6-item work functioning screener (WFS-H). Healthcare workers (249 nurses) completed a questionnaire containing the work functioning screener (WFS-H) and a work functioning instrument (NWFQ) measuring the following: cognitive aspects of task execution and general incidents, avoidance behavior, conflicts and irritation with colleagues, impaired contact with patients and their family, and level of energy and motivation. Productivity and mental health were also measured. Negative and positive predictive values, AUC values, and sensitivity and specificity were calculated to examine the predictive value of the screener. Correlation analysis was used to examine the construct validity. The screener had good predictive value, since the results showed that a negative screener score is a strong indicator of work functioning not hindered by mental health problems (negative predictive values: 94%-98%; positive predictive values: 21%-36%; AUC:.64-.82; sensitivity: 42%-76%; and specificity 85%-87%). The screener has good construct validity due to moderate, but significant (p<.001), associations with productivity (r=.51), mental health (r=.48), and distress (r=.47). The screener (WFS-H) had good predictive value and good construct validity. Its score offers occupational health professionals a helpful preliminary insight into the work functioning of healthcare workers.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Genomic selection across multiple breeding cycles in applied bread wheat breeding.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2016-06-01

We evaluated genomic selection across five breeding cycles of bread wheat breeding. Bias of within-cycle cross-validation and methods for improving the prediction accuracy were assessed. The prospect of genomic selection has been frequently shown by cross-validation studies using the same genetic material across multiple environments, but studies investigating genomic selection across multiple breeding cycles in applied bread wheat breeding are lacking. We estimated the prediction accuracy of grain yield, protein content and protein yield of 659 inbred lines across five independent breeding cycles and assessed the bias of within-cycle cross-validation. We investigated the influence of outliers on the prediction accuracy and predicted protein yield by its components traits. A high average heritability was estimated for protein content, followed by grain yield and protein yield. The bias of the prediction accuracy using populations from individual cycles using fivefold cross-validation was accordingly substantial for protein yield (17-712 %) and less pronounced for protein content (8-86 %). Cross-validation using the cycles as folds aimed to avoid this bias and reached a maximum prediction accuracy of [Formula: see text] = 0.51 for protein content, [Formula: see text] = 0.38 for grain yield and [Formula: see text] = 0.16 for protein yield. Dropping outlier cycles increased the prediction accuracy of grain yield to [Formula: see text] = 0.41 as estimated by cross-validation, while dropping outlier environments did not have a significant effect on the prediction accuracy. Independent validation suggests, on the other hand, that careful consideration is necessary before an outlier correction is undertaken, which removes lines from the training population. Predicting protein yield by multiplying genomic estimated breeding values of grain yield and protein content raised the prediction accuracy to [Formula: see text] = 0.19 for this derived trait.

Bayesian spatiotemporal crash frequency models with mixture components for space-time interactions.

PubMed

Cheng, Wen; Gill, Gurdiljot Singh; Zhang, Yongping; Cao, Zhong

2018-03-01

The traffic safety research has developed spatiotemporal models to explore the variations in the spatial pattern of crash risk over time. Many studies observed notable benefits associated with the inclusion of spatial and temporal correlation and their interactions. However, the safety literature lacks sufficient research for the comparison of different temporal treatments and their interaction with spatial component. This study developed four spatiotemporal models with varying complexity due to the different temporal treatments such as (I) linear time trend; (II) quadratic time trend; (III) Autoregressive-1 (AR-1); and (IV) time adjacency. Moreover, the study introduced a flexible two-component mixture for the space-time interaction which allows greater flexibility compared to the traditional linear space-time interaction. The mixture component allows the accommodation of global space-time interaction as well as the departures from the overall spatial and temporal risk patterns. This study performed a comprehensive assessment of mixture models based on the diverse criteria pertaining to goodness-of-fit, cross-validation and evaluation based on in-sample data for predictive accuracy of crash estimates. The assessment of model performance in terms of goodness-of-fit clearly established the superiority of the time-adjacency specification which was evidently more complex due to the addition of information borrowed from neighboring years, but this addition of parameters allowed significant advantage at posterior deviance which subsequently benefited overall fit to crash data. The Base models were also developed to study the comparison between the proposed mixture and traditional space-time components for each temporal model. The mixture models consistently outperformed the corresponding Base models due to the advantages of much lower deviance. For cross-validation comparison of predictive accuracy, linear time trend model was adjudged the best as it recorded the highest value of log pseudo marginal likelihood (LPML). Four other evaluation criteria were considered for typical validation using the same data for model development. Under each criterion, observed crash counts were compared with three types of data containing Bayesian estimated, normal predicted, and model replicated ones. The linear model again performed the best in most scenarios except one case of using model replicated data and two cases involving prediction without including random effects. These phenomena indicated the mediocre performance of linear trend when random effects were excluded for evaluation. This might be due to the flexible mixture space-time interaction which can efficiently absorb the residual variability escaping from the predictable part of the model. The comparison of Base and mixture models in terms of prediction accuracy further bolstered the superiority of the mixture models as the mixture ones generated more precise estimated crash counts across all four models, suggesting that the advantages associated with mixture component at model fit were transferable to prediction accuracy. Finally, the residual analysis demonstrated the consistently superior performance of random effect models which validates the importance of incorporating the correlation structures to account for unobserved heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluating the Predictive Validity of the Computerized Comprehension Task: Comprehension Predicts Production

PubMed Central

Friend, Margaret; Schmitt, Sara A.; Simpson, Adrianne M.

2017-01-01

Until recently, the challenges inherent in measuring comprehension have impeded our ability to predict the course of language acquisition. The present research reports on a longitudinal assessment of the convergent and predictive validity of the CDI: Words and Gestures and the Computerized Comprehension Task (CCT). The CDI: WG and the CCT evinced good convergent validity however the CCT better predicted subsequent parent reports of language production. Language sample data in the third year confirm this finding: the CCT accounted for 24% of the variance in unique word use. These studies provide evidence for the utility of a behavior-based approach to predicting the course of language acquisition into production. PMID:21928878

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

PubMed

Willis, Michael; Johansen, Pierre; Nilsson, Andreas; Asseburg, Christian

2017-03-01

The Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM) was developed to address study questions pertaining to the cost-effectiveness of treatment alternatives in the care of patients with type 2 diabetes mellitus (T2DM). Naturally, the usefulness of a model is determined by the accuracy of its predictions. A previous version of ECHO-T2DM was validated against actual trial outcomes and the model predictions were generally accurate. However, there have been recent upgrades to the model, which modify model predictions and necessitate an update of the validation exercises. The objectives of this study were to extend the methods available for evaluating model validity, to conduct a formal model validation of ECHO-T2DM (version 2.3.0) in accordance with the principles espoused by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), and secondarily to evaluate the relative accuracy of four sets of macrovascular risk equations included in ECHO-T2DM. We followed the ISPOR/SMDM guidelines on model validation, evaluating face validity, verification, cross-validation, and external validation. Model verification involved 297 'stress tests', in which specific model inputs were modified systematically to ascertain correct model implementation. Cross-validation consisted of a comparison between ECHO-T2DM predictions and those of the seminal National Institutes of Health model. In external validation, study characteristics were entered into ECHO-T2DM to replicate the clinical results of 12 studies (including 17 patient populations), and model predictions were compared to observed values using established statistical techniques as well as measures of average prediction error, separately for the four sets of macrovascular risk equations supported in ECHO-T2DM. Sub-group analyses were conducted for dependent vs. independent outcomes and for microvascular vs. macrovascular vs. mortality endpoints. All stress tests were passed. ECHO-T2DM replicated the National Institutes of Health cost-effectiveness application with numerically similar results. In external validation of ECHO-T2DM, model predictions agreed well with observed clinical outcomes. For all sets of macrovascular risk equations, the results were close to the intercept and slope coefficients corresponding to a perfect match, resulting in high R 2 and failure to reject concordance using an F test. The results were similar for sub-groups of dependent and independent validation, with some degree of under-prediction of macrovascular events. ECHO-T2DM continues to match health outcomes in clinical trials in T2DM, with prediction accuracy similar to other leading models of T2DM.

Estimation of basal metabolic rate in Chinese: are the current prediction equations applicable?

PubMed

Camps, Stefan G; Wang, Nan Xin; Tan, Wei Shuan Kimberly; Henry, C Jeyakumar

2016-08-31

Measurement of basal metabolic rate (BMR) is suggested as a tool to estimate energy requirements. Therefore, BMR prediction equations have been developed in multiple populations because indirect calorimetry is not always feasible. However, there is a paucity of data on BMR measured in overweight and obese adults living in Asia and equations developed for this group of interest. The aim of this study was to develop a new BMR prediction equation for Chinese adults applicable for a large BMI range and compare it with commonly used prediction equations. Subjects were 121 men and 111 women (age: 21-67 years, BMI: 16-41 kg/m(2)). Height, weight, and BMR were measured. Continuous open-circuit indirect calorimetry using a ventilated hood system for 30 min was used to measure BMR. A regression equation was derived using stepwise regression and accuracy was compared to 6 existing equations (Harris-Benedict, Henry, Liu, Yang, Owen and Mifflin). Additionally, the newly derived equation was cross-validated in a separate group of 70 Chinese subjects (26 men and 44 women, age: 21-69 years, BMI: 17-39 kg/m(2)). The equation developed from our data was: BMR (kJ/d) = 52.6 x weight (kg) + 828 x gender + 1960 (women = 0, men = 1; R(2) = 0.81). The accuracy rate (within 10 % accurate) was 78 % which compared well to Owen (70 %), Henry (67 %), Mifflin (67 %), Liu (58 %), Harris-Benedict (45 %) and Yang (37 %) for the whole range of BMI. For a BMI greater than 23, the Singapore equation reached an accuracy rate of 76 %. Cross-validation proved an accuracy rate of 80 %. To date, the newly developed Singapore equation is the most accurate BMR prediction equation in Chinese and is applicable for use in a large BMI range including those overweight and obese.

T2-weighted signal intensity-selected volumetry for prediction of pathological complete response after preoperative chemoradiotherapy in locally advanced rectal cancer.

PubMed

Kim, Sungwon; Han, Kyunghwa; Seo, Nieun; Kim, Hye Jin; Kim, Myeong-Jin; Koom, Woong Sub; Ahn, Joong Bae; Lim, Joon Seok

2018-06-01

To evaluate the diagnostic value of signal intensity (SI)-selected volumetry findings in T2-weighted magnetic resonance imaging (MRI) as a potential biomarker for predicting pathological complete response (pCR) to preoperative chemoradiotherapy (CRT) in patients with rectal cancer. Forty consecutive patients with pCR after preoperative CRT were compared with 80 age- and sex-matched non-pCR patients in a case-control study. SI-selected tumor volume was measured on post-CRT T2-weighted MRI, which included voxels of the treated tumor exceeding the SI (obturator internus muscle SI + [ischiorectal fossa fat SI - obturator internus muscle SI] × 0.2). Three blinded readers independently rated five-point pCR confidence scores and compared the diagnostic outcome with SI-selected volumetry findings. The SI-selected volumetry protocol was validated in 30 additional rectal cancer patients. The area under the receiver-operating characteristic curve (AUC) of SI-selected volumetry for pCR prediction was 0.831, with an optimal cutoff value of 649.6 mm 3 (sensitivity 0.850, specificity 0.725). The AUC of the SI-selected tumor volume was significantly greater than the pooled AUC of readers (0.707, p < 0.001). At this cutoff, the validation trial yielded an accuracy of 0.87. SI-selected volumetry in post-CRT T2-weighted MRI can help predict pCR after preoperative CRT in patients with rectal cancer. • Fibrosis and viable tumor MRI signal intensities (SIs) are difficult to distinguish. • T2 SI-selected volumetry yields high diagnostic performance for assessing pathological complete response. • T2 SI-selected volumetry is significantly more accurate than readers and non-SI-selected volumetry. • Post-chemoradiation therapy T2-weighted MRI SI-selected volumetry facilitates prediction of pathological complete response.

Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk.

PubMed

Shetty, N; Løvendahl, P; Lund, M S; Buitenhuis, A J

2017-01-01

The present study explored the effectiveness of Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for dry matter intake (DMI) and residual feed intake (RFI). The partial least squares regression method was used to develop the prediction models. The models were validated using different external test sets, one randomly leaving out 20% of the records (validation A), the second randomly leaving out 20% of cows (validation B), and a third (for DMI prediction models) randomly leaving out one cow (validation C). The data included 1,044 records from 140 cows; 97 were Danish Holstein and 43 Danish Jersey. Results showed better accuracies for validation A compared with other validation methods. Milk yield (MY) contributed largely to DMI prediction; MY explained 59% of the variation and the validated model error root mean square error of prediction (RMSEP) was 2.24kg. The model was improved by adding live weight (LW) as an additional predictor trait, where the accuracy R 2 increased from 0.59 to 0.72 and error RMSEP decreased from 2.24 to 1.83kg. When only the milk FT-IR spectral profile was used in DMI prediction, a lower prediction ability was obtained, with R 2 =0.30 and RMSEP=2.91kg. However, once the spectral information was added, along with MY and LW as predictors, model accuracy improved and R 2 increased to 0.81 and RMSEP decreased to 1.49kg. Prediction accuracies of RFI changed throughout lactation. The RFI prediction model for the early-lactation stage was better compared with across lactation or mid- and late-lactation stages, with R 2 =0.46 and RMSEP=1.70. The most important spectral wavenumbers that contributed to DMI and RFI prediction models included fat, protein, and lactose peaks. Comparable prediction results were obtained when using infrared-predicted fat, protein, and lactose instead of full spectra, indicating that FT-IR spectral data do not add significant new information to improve DMI and RFI prediction models. Therefore, in practice, if full FT-IR spectral data are not stored, it is possible to achieve similar DMI or RFI prediction results based on standard milk control data. For DMI, the milk fat region was responsible for the major variation in milk spectra; for RFI, the major variation in milk spectra was within the milk protein region. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2013-01-01

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

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

NASA Technical Reports Server (NTRS)

Shastry, Rohit; Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2012-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after groove penetration.

NASA's Evolutionary Xenon Thruster (NEXT) Long-Duration Test as of 736 kg of Propellant Throughput

NASA Technical Reports Server (NTRS)

Shastry, Rohit; Herman, Daniel A.; Soulas, George C.; Patterson, Michael J.

2012-01-01

The NASA s Evolutionary Xenon Thruster (NEXT) program is developing the next-generation solar-electric ion propulsion system with significant enhancements beyond the state-of-the-art NASA Solar Electric Propulsion Technology Application Readiness (NSTAR) ion propulsion system to provide future NASA science missions with enhanced mission capabilities. A Long-Duration Test (LDT) was initiated in June 2005 to validate the thruster service life modeling and to qualify the thruster propellant throughput capability. The thruster has set electric propulsion records for the longest operating duration, highest propellant throughput, and most total impulse demonstrated. At the time of this publication, the NEXT LDT has surpassed 42,100 h of operation, processed more than 736 kg of xenon propellant, and demonstrated greater than 28.1 MN s total impulse. Thruster performance has been steady with negligible degradation. The NEXT thruster design has mitigated several lifetime limiting mechanisms encountered in the NSTAR design, including the NSTAR first failure mode, thereby drastically improving thruster capabilities. Component erosion rates and the progression of the predicted life-limiting erosion mechanism for the thruster compare favorably to pretest predictions based upon semi-empirical ion thruster models used in the thruster service life assessment. Service life model validation has been accomplished by the NEXT LDT. Assuming full-power operation until test article failure, the models and extrapolated erosion data predict penetration of the accelerator grid grooves after more than 45,000 hours of operation while processing over 800 kg of xenon propellant. Thruster failure due to degradation of the accelerator grid structural integrity is expected after

Spinal loads as influenced by external loads: a combined in vivo and in silico investigation.

PubMed

Zander, Thomas; Dreischarf, Marcel; Schmidt, Hendrik; Bergmann, Georg; Rohlmann, Antonius

2015-02-26

Knowledge of in vivo spinal loads and muscle forces remains limited but is necessary for spinal biomechanical research. To assess the in vivo spinal loads, measurements with telemeterised vertebral body replacements were performed in four patients. The following postures were investigated: (a) standing with arms hanging down on sides, (b) holding dumbbells to subject the patient to a vertical load, and (c) the forward elevation of arms for creating an additional flexion moment. The same postures were simulated by an inverse static model for validation purposes, to predict muscle forces, and to assess the spinal loads in subjects without implants. Holding dumbbells on sides increased implant forces by the magnitude of the weight of the dumbbells. In contrast, elevating the arms yielded considerable implant forces with a high correlation between the external flexion moment and the implant force. Predictions agreed well with experimental findings, especially for forward elevation of arms. Flexion moments were mainly compensated by erector spinae muscles. The implant altered the kinematics and, thus, the spinal loads. Elevation of both arms in vivo increased spinal axial forces by approximately 100N; each additional kg of dumbbell weight held in the hands increased the spinal axial forces by 60N. Model predictions suggest that in the intact situation, the force increase is one-third greater for these loads. In vivo measurements are essential for the validation of analytical models, and the combination of both methods can reveal unquantifiable data such as the spinal loads in the intact non-instrumented situation. Copyright © 2015 Elsevier Ltd. All rights reserved.

A comparison of zero-order, first-order, and monod biotransformation models

USGS Publications Warehouse

Bekins, B.A.; Warren, E.; Godsy, E.M.

1998-01-01

Under some conditions, a first-order kinetic model is a poor representation of biodegradation in contaminated aquifers. Although it is well known that the assumption of first-order kinetics is valid only when substrate concentration, S, is much less than the half-saturation constant, K(s), this assumption is often made without verification of this condition. We present a formal error analysis showing that the relative error in the first-order approximation is S/K(S) and in the zero-order approximation the error is K(s)/S. We then examine the problems that arise when the first-order approximation is used outside the range for which it is valid. A series of numerical simulations comparing results of first- and zero-order rate approximations to Monod kinetics for a real data set illustrates that if concentrations observed in the field are higher than K(s), it may better to model degradation using a zero-order rate expression. Compared with Monod kinetics, extrapolation of a first-order rate to lower concentrations under-predicts the biotransformation potential, while extrapolation to higher concentrations may grossly over-predict the transformation rate. A summary of solubilities and Monod parameters for aerobic benzene, toluene, and xylene (BTX) degradation shows that the a priori assumption of first-order degradation kinetics at sites contaminated with these compounds is not valid. In particular, out of six published values of KS for toluene, only one is greater than 2 mg/L, indicating that when toluene is present in concentrations greater than about a part per million, the assumption of first-order kinetics may be invalid. Finally, we apply an existing analytical solution for steady-state one-dimensional advective transport with Monod degradation kinetics to a field data set.A formal error analysis is presented showing that the relative error in the first-order approximation is S/KS and in the zero-order approximation the error is KS/S where S is the substrate concentration and KS is the half-saturation constant. The problems that arise when the first-order approximation is used outside the range for which it is valid are examined. A series of numerical simulations comparing results of first- and zero-order rate approximations to Monod kinetics for a real data set illustrates that if concentrations observed in the field are higher than KS, it may be better to model degradation using a zero-order rate expression.

Dynamic Assessment of Reading Difficulties: Predictive and Incremental Validity on Attitude toward Reading and the Use of Dialogue/Participation Strategies in Classroom Activities.

PubMed

Navarro, Juan-José; Lara, Laura

2017-01-01

Dynamic Assessment (DA) has been shown to have more predictive value than conventional tests for academic performance. However, in relation to reading difficulties, further research is needed to determine the predictive validity of DA for specific aspects of the different processes involved in reading and the differential validity of DA for different subgroups of students with an academic disadvantage. This paper analyzes the implementation of a DA device that evaluates processes involved in reading (EDPL) among 60 students with reading comprehension difficulties between 9 and 16 years of age, of whom 20 have intellectual disabilities, 24 have reading-related learning disabilities, and 16 have socio-cultural disadvantages. We specifically analyze the predictive validity of the EDPL device over attitude toward reading, and the use of dialogue/participation strategies in reading activities in the classroom during the implementation stage. We also analyze if the EDPL device provides additional information to that obtained with a conventionally applied personal-social adjustment scale (APSL). Results showed that dynamic scores, obtained from the implementation of the EDPL device, significantly predict the studied variables. Moreover, dynamic scores showed a significant incremental validity in relation to predictions based on an APSL scale. In relation to differential validity, the results indicated the superior predictive validity for DA for students with intellectual disabilities and reading disabilities than for students with socio-cultural disadvantages. Furthermore, the role of metacognition and its relation to the processes of personal-social adjustment in explaining the results is discussed.

Dynamic Assessment of Reading Difficulties: Predictive and Incremental Validity on Attitude toward Reading and the Use of Dialogue/Participation Strategies in Classroom Activities

PubMed Central

Navarro, Juan-José; Lara, Laura

2017-01-01

Dynamic Assessment (DA) has been shown to have more predictive value than conventional tests for academic performance. However, in relation to reading difficulties, further research is needed to determine the predictive validity of DA for specific aspects of the different processes involved in reading and the differential validity of DA for different subgroups of students with an academic disadvantage. This paper analyzes the implementation of a DA device that evaluates processes involved in reading (EDPL) among 60 students with reading comprehension difficulties between 9 and 16 years of age, of whom 20 have intellectual disabilities, 24 have reading-related learning disabilities, and 16 have socio-cultural disadvantages. We specifically analyze the predictive validity of the EDPL device over attitude toward reading, and the use of dialogue/participation strategies in reading activities in the classroom during the implementation stage. We also analyze if the EDPL device provides additional information to that obtained with a conventionally applied personal-social adjustment scale (APSL). Results showed that dynamic scores, obtained from the implementation of the EDPL device, significantly predict the studied variables. Moreover, dynamic scores showed a significant incremental validity in relation to predictions based on an APSL scale. In relation to differential validity, the results indicated the superior predictive validity for DA for students with intellectual disabilities and reading disabilities than for students with socio-cultural disadvantages. Furthermore, the role of metacognition and its relation to the processes of personal-social adjustment in explaining the results is discussed. PMID:28243215

Modelling soil erosion in rainfed vineyards of northeast of Spain under climate change: effects of increasing rainfall intensity

NASA Astrophysics Data System (ADS)

Concepción Ramos, Maria

2017-04-01

This aim of the research was to analyse the effect of rainfall distribution and intensity on soil erosion in vines cultivated in the Mediterranean under the projected climate change scenario. The simulations were done at plot scale using the WEPP model. Climatic data for the period 1996-2014 were obtained from a meteorological station located 6km far from the plot. Soil characteristics such as texture, organic matter content, water retention capacity and infiltration were analysed. Runoff and soil losses were measured at four locations within the plot during 4 years and used to calibrate and validate the model. According to evidences recorded in the area, changes of rainfall intensities of 10 and 20% were considered for different rainfall distributions. The simulations were extended to the predicted changes for 2030, 2050 and 2070 based on the HadGEM2-CC under the Representative Concentration Pathways (RCPs) 8.5 scenario. WEPP model provided a suitable prediction of the seasonal runoff and erosion as simulated relatively well the runoff and erosion of the most important events although some deficiencies were found for those events that produced low runoff. The simulation confirmed the contribution of the extreme events to annual erosion rates in 70%, on average. The model responded to changes in precipitation predicted under a climate change scenario with a decrease of runoff and erosion, and with higher erosion rates for an increase in rainfall intensity. A 10% increase may imply erosion rates up to 22% greater for the scenario 2030, and despite the predicted decrease in precipitation for the scenario 2050, soil losses may be up to 40% greater than at present for some rainfall distributions and intensity rainfall increases of 20%. These findings show the need of considering rainfall intensity as one of the main driven factors when soil erosion rates under climate change are predicted. Keywords: extreme events, rainfall distribution, runoff, soil losses, wines, WEPP.

Treatment Success of Hip and Core or Knee Strengthening for Patellofemoral Pain: Development of Clinical Prediction Rules.

PubMed

Earl-Boehm, Jennifer E; Bolgla, Lori A; Emory, Carolyn; Hamstra-Wright, Karrie L; Tarima, Sergey; Ferber, Reed

2018-06-12

  Patellofemoral pain (PFP) is a common injury that interferes with quality of life and physical activity. Clinical subgroups of patients may exist, one of which is proximal muscle dysfunction.   To develop clinical prediction rules that predict a positive outcome after either a hip and core- or knee-focused strengthening program for individuals with PFP.   Secondary analysis of data from a randomized control trial.   Four university laboratories.   A total of 199 participants with PFP.   Participants were randomly allocated to either a hip and core-focused (n = 111) or knee-focused (n = 88) rehabilitation group for a 6-week program.   Demographics, self-reported knee pain (visual analog scale) and function (Anterior Knee Pain Scale), hip strength, abdominal muscle endurance, and hip range of motion were evaluated at baseline. Treatment success was defined as a decrease in visual analog scale score by ≥2 cm or an increase in the Anterior Knee Pain Scale score by ≥8 points or both. Bivariate relationships between the outcome (treatment success) and the predictor variables were explored, followed by a forward stepwise logistic regression to predict a successful outcome.   Patients with more pain, better function, greater lateral core endurance, and less anterior core endurance were more likely to have a successful outcome after hip and core strengthening (88% sensitivity and 54% specificity). Patients with lower weight, weaker hip internal rotation, stronger hip extension, and greater trunk-extension endurance were more likely to have success after knee strengthening (82% sensitivity and 58% specificity).   The patients with PFP who have more baseline pain and yet maintain a high level of function may experience additional benefit from hip and core strengthening. The clinical prediction rules from this study remain in the developmental phase and should be applied with caution until externally validated.

Applicability of Monte Carlo cross validation technique for model development and validation using generalised least squares regression

NASA Astrophysics Data System (ADS)

Haddad, Khaled; Rahman, Ataur; A Zaman, Mohammad; Shrestha, Surendra

2013-03-01

SummaryIn regional hydrologic regression analysis, model selection and validation are regarded as important steps. Here, the model selection is usually based on some measurements of goodness-of-fit between the model prediction and observed data. In Regional Flood Frequency Analysis (RFFA), leave-one-out (LOO) validation or a fixed percentage leave out validation (e.g., 10%) is commonly adopted to assess the predictive ability of regression-based prediction equations. This paper develops a Monte Carlo Cross Validation (MCCV) technique (which has widely been adopted in Chemometrics and Econometrics) in RFFA using Generalised Least Squares Regression (GLSR) and compares it with the most commonly adopted LOO validation approach. The study uses simulated and regional flood data from the state of New South Wales in Australia. It is found that when developing hydrologic regression models, application of the MCCV is likely to result in a more parsimonious model than the LOO. It has also been found that the MCCV can provide a more realistic estimate of a model's predictive ability when compared with the LOO.

Self-rated health as a predictor of survival among patients with advanced cancer.

PubMed

Shadbolt, Bruce; Barresi, Jane; Craft, Paul

2002-05-15

Evidence is emerging about the strong predictive relationship between self-rated health (SRH) and survival, although there is little evidence on palliative populations where an accurate prediction of survival is valuable. Thus, the relative importance of SRH in predicting the survival of ambulatory patients with advanced cancer was examined. SRH was compared to clinical assessments of performance status, as well as to quality-of-life measures. By use of a prospective cohort design, 181 patients (76% response rate) with advanced cancer were recruited into the study, resurveyed at 18 weeks, and observed to record deaths. The average age of patients was 62 years (SD = 12). The median survival time was 10 months. SRH was the strongest predictor of survival from baseline. Also, a Cox regression comparing changes in SRH over time yielded hazard ratios suggesting the relative risk (RR) of dying was greater for fair ratings at 18 weeks (approximately 3 times) compared with consistent good or better ratings; the RR was even greater (4.2 and 6.2 times) for poor ratings, especially when ratings were poor at baseline and 18 weeks (31 times). Improvement in SRH over time yielded the lowest RR. SRH is valid, reliable, and responsive to change as a predictor of survival of advanced cancer. These qualities suggest that SRH should be considered as an additional tool by oncologists to assess patients. Similarly, health managers could use SRH as an indicator of disease severity in palliative care case mix. Finally, SRH could provide a key to help us understand the human side of disease and its relationship with medicine.

Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

PubMed Central

Austin, Peter C.; van Klaveren, David; Vergouwe, Yvonne; Nieboer, Daan; Lee, Douglas S.; Steyerberg, Ewout W.

2017-01-01

Objective Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting We illustrated different analytic methods for validation using a sample of 14,857 patients hospitalized with heart failure at 90 hospitals in two distinct time periods. Bootstrap resampling was used to assess internal validity. Meta-analytic methods were used to assess geographic transportability. Each hospital was used once as a validation sample, with the remaining hospitals used for model derivation. Hospital-specific estimates of discrimination (c-statistic) and calibration (calibration intercepts and slopes) were pooled using random effects meta-analysis methods. I2 statistics and prediction interval width quantified geographic transportability. Temporal transportability was assessed using patients from the earlier period for model derivation and patients from the later period for model validation. Results Estimates of reproducibility, pooled hospital-specific performance, and temporal transportability were on average very similar, with c-statistics of 0.75. Between-hospital variation was moderate according to I2 statistics and prediction intervals for c-statistics. Conclusion This study illustrates how performance of prediction models can be assessed in settings with multicenter data at different time periods. PMID:27262237

Parent- and Self-Reported Dimensions of Oppositionality in Youth: Construct Validity, Concurrent Validity, and the Prediction of Criminal Outcomes in Adulthood

ERIC Educational Resources Information Center

Aebi, Marcel; Plattner, Belinda; Metzke, Christa Winkler; Bessler, Cornelia; Steinhausen, Hans-Christoph

2013-01-01

Background: Different dimensions of oppositional defiant disorder (ODD) have been found as valid predictors of further mental health problems and antisocial behaviors in youth. The present study aimed at testing the construct, concurrent, and predictive validity of ODD dimensions derived from parent- and self-report measures. Method: Confirmatory…

Systematic review of the concurrent and predictive validity of MRI biomarkers in OA

PubMed Central

Hunter, D.J.; Zhang, W.; Conaghan, Philip G.; Hirko, K.; Menashe, L.; Li, L.; Reichmann, W.M.; Losina, E.

2012-01-01

SUMMARY Objective To summarize literature on the concurrent and predictive validity of MRI-based measures of osteoarthritis (OA) structural change. Methods An online literature search was conducted of the OVID, EMBASE, CINAHL, PsychInfo and Cochrane databases of articles published up to the time of the search, April 2009. 1338 abstracts obtained with this search were preliminarily screened for relevance by two reviewers. Of these, 243 were selected for data extraction for this analysis on validity as well as separate reviews on discriminate validity and diagnostic performance. Of these 142 manuscripts included data pertinent to concurrent validity and 61 manuscripts for the predictive validity review. For this analysis we extracted data on criterion (concurrent and predictive) validity from both longitudinal and cross-sectional studies for all synovial joint tissues as it relates to MRI measurement in OA. Results Concurrent validity of MRI in OA has been examined compared to symptoms, radiography, histology/pathology, arthroscopy, CT, and alignment. The relation of bone marrow lesions, synovitis and effusion to pain was moderate to strong. There was a weak or no relation of cartilage morphology or meniscal tears to pain. The relation of cartilage morphology to radiographic OA and radiographic joint space was inconsistent. There was a higher frequency of meniscal tears, synovitis and other features in persons with radiographic OA. The relation of cartilage to other constructs including histology and arthroscopy was stronger. Predictive validity of MRI in OA has been examined for ability to predict total knee replacement (TKR), change in symptoms, radiographic progression as well as MRI progression. Quantitative cartilage volume change and presence of cartilage defects or bone marrow lesions are potential predictors of TKR. Conclusion MRI has inherent strengths and unique advantages in its ability to visualize multiple individual tissue pathologies relating to pain and also predict clinical outcome. The complex disease of OA which involves an array of tissue abnormalities is best imaged using this imaging tool. PMID:21396463

External validity of two nomograms for predicting distant brain failure after radiosurgery for brain metastases in a bi-institutional independent patient cohort.

PubMed

Prabhu, Roshan S; Press, Robert H; Boselli, Danielle M; Miller, Katherine R; Lankford, Scott P; McCammon, Robert J; Moeller, Benjamin J; Heinzerling, John H; Fasola, Carolina E; Patel, Kirtesh R; Asher, Anthony L; Sumrall, Ashley L; Curran, Walter J; Shu, Hui-Kuo G; Burri, Stuart H

2018-03-01

Patients treated with stereotactic radiosurgery (SRS) for brain metastases (BM) are at increased risk of distant brain failure (DBF). Two nomograms have been recently published to predict individualized risk of DBF after SRS. The goal of this study was to assess the external validity of these nomograms in an independent patient cohort. The records of consecutive patients with BM treated with SRS at Levine Cancer Institute and Emory University between 2005 and 2013 were reviewed. Three validation cohorts were generated based on the specific nomogram or recursive partitioning analysis (RPA) entry criteria: Wake Forest nomogram (n = 281), Canadian nomogram (n = 282), and Canadian RPA (n = 303) validation cohorts. Freedom from DBF at 1-year in the Wake Forest study was 30% compared with 50% in the validation cohort. The validation c-index for both the 6-month and 9-month freedom from DBF Wake Forest nomograms was 0.55, indicating poor discrimination ability, and the goodness-of-fit test for both nomograms was highly significant (p < 0.001), indicating poor calibration. The 1-year actuarial DBF in the Canadian nomogram study was 43.9% compared with 50.9% in the validation cohort. The validation c-index for the Canadian 1-year DBF nomogram was 0.56, and the goodness-of-fit test was also highly significant (p < 0.001). The validation accuracy and c-index of the Canadian RPA classification was 53% and 0.61, respectively. The Wake Forest and Canadian nomograms for predicting risk of DBF after SRS were found to have limited predictive ability in an independent bi-institutional validation cohort. These results reinforce the importance of validating predictive models in independent patient cohorts.

Psychometric Evaluation of a Persian Version of the Cardiac Depression Scale in Iranian Patients With Acute Myocardial Infarction.

PubMed

Nia, Hamid Sharif; Sharif, Saeed Pahlevan; Froelicher, Erika Sivarajan; Boyle, Christopher; Goudarzian, Amir Hossein; Yaghoobzadeh, Ameneh; Oskouie, Fatemeh

2018-04-01

The aim of this study was to validate a Persian version of the Cardiac Depression Scale (CDS) in Iranian patients with acute myocardial infarction (AMI). The CDS was forward translated from English into Persian and back-translated to English. Validity was assessed using face, content, and construct validity. Also Cronbach's alpha (α), theta (), and McDonald's omega coefficient were used to evaluate the reliability. Construct validity of the scale showed two factors with eigenvalues greater than one. The Cronbach's α, , McDonald's omega, and construct reliability were greater than .70. The Persian version of the CDS has a two-factor structure (i.e., death anxiety and life satisfaction) and has acceptable reliability and validity. Therefore, the validated instrument can be used in future studies to assess depression in patients with AMI in Iranians.

Performance in normal subjects on a novel battery of driving-related sensory-motor and cognitive tests.

PubMed

Innes, Carrie R H; Jones, Richard D; Anderson, Tim J; Hollobon, Susan G; Dalrymple-Alford, John C

2009-05-01

Currently, there is no international standard for the assessment of fitness to drive for cognitively or physically impaired persons. A computerized battery of driving-related sensory-motor and cognitive tests (SMCTests) has been developed, comprising tests of visuoperception, visuomotor ability, complex attention, visual search, decision making, impulse control, planning, and divided attention. Construct validity analysis was conducted in 60 normal, healthy subjects and showed that, overall, the novel cognitive tests assessed cognitive functions similar to a set of standard neuropsychological tests. The novel tests were found to have greater perceived face validity for predicting on-road driving ability than was found in the equivalent standard tests. Test-retest stability and reliability of SMCTests measures, as well as correlations between SMCTests and on-road driving, were determined in a subset of 12 subjects. The majority of test measures were stable and reliable across two sessions, and significant correlations were found between on-road driving scores and measures from ballistic movement, footbrake reaction, hand-control reaction, and complex attention. The substantial face validity, construct validity, stability, and reliability of SMCTests, together with the battery's level of correlation with on-road driving in normal subjects, strengthen our confidence in the ability of SMCTests to detect and identify sensory-motor and cognitive deficits related to unsafe driving and increased risk of accidents.

A novel model to predict gas-phase hydroxyl radical oxidation kinetics of polychlorinated compounds.

PubMed

Luo, Shuang; Wei, Zongsu; Spinney, Richard; Yang, Zhihui; Chai, Liyuan; Xiao, Ruiyang

2017-04-01

In this study, a novel model based on aromatic meta-substituent grouping was presented to predict the second-order rate constants (k) for OH oxidation of PCBs in gas-phase. Since the oxidation kinetics are dependent on the chlorination degree and position, we hypothesized that it may be more accurate for k value prediction if we group PCB congeners based on substitution positions (i.e., ortho (o), meta (m), and para (p)). To test this hypothesis, we examined the correlation of polarizability (α), a quantum chemical based descriptor for k values, with an empirical Hammett constant (σ + ) on each substitution position. Our result shows that α is highly linearly correlated to ∑σ o,m,p + based on aromatic meta-substituents leading to the grouping based predictive model. With the new model, the calculated k values exhibited an excellent agreement with experimental measurements, and greater predictive power than the quantum chemical based quantitative structure activity relationship (QSAR) model. Further, the relationship of α and ∑σ o,m,p + for PCDDs congeners, together with highest occupied molecular orbital (HOMO) distribution, were used to validate the aromatic meta-substituent grouping method. This newly developed model features a combination of good predictability of quantum chemical based QSAR model and simplicity of Hammett relationship, showing a great potential for fast and computational tractable prediction of k values for gas-phase OH oxidation of polychlorinated compounds. Copyright © 2017 Elsevier Ltd. All rights reserved.

Can species distribution models really predict the expansion of invasive species?

PubMed

Barbet-Massin, Morgane; Rome, Quentin; Villemant, Claire; Courchamp, Franck

2018-01-01

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies-with independent data-are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be-at least partially-climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology.

Can species distribution models really predict the expansion of invasive species?

PubMed Central

Rome, Quentin; Villemant, Claire; Courchamp, Franck

2018-01-01

Predictive studies are of paramount importance for biological invasions, one of the biggest threats for biodiversity. To help and better prioritize management strategies, species distribution models (SDMs) are often used to predict the potential invasive range of introduced species. Yet, SDMs have been regularly criticized, due to several strong limitations, such as violating the equilibrium assumption during the invasion process. Unfortunately, validation studies–with independent data–are too scarce to assess the predictive accuracy of SDMs in invasion biology. Yet, biological invasions allow to test SDMs usefulness, by retrospectively assessing whether they would have accurately predicted the latest ranges of invasion. Here, we assess the predictive accuracy of SDMs in predicting the expansion of invasive species. We used temporal occurrence data for the Asian hornet Vespa velutina nigrithorax, a species native to China that is invading Europe with a very fast rate. Specifically, we compared occurrence data from the last stage of invasion (independent validation points) to the climate suitability distribution predicted from models calibrated with data from the early stage of invasion. Despite the invasive species not being at equilibrium yet, the predicted climate suitability of validation points was high. SDMs can thus adequately predict the spread of V. v. nigrithorax, which appears to be—at least partially–climatically driven. In the case of V. v. nigrithorax, SDMs predictive accuracy was slightly but significantly better when models were calibrated with invasive data only, excluding native data. Although more validation studies for other invasion cases are needed to generalize our results, our findings are an important step towards validating the use of SDMs in invasion biology. PMID:29509789

Genome-based prediction of test cross performance in two subsequent breeding cycles.

PubMed

Hofheinz, Nina; Borchardt, Dietrich; Weissleder, Knuth; Frisch, Matthias

2012-12-01

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations >0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy. We conclude that prediction accuracy assessed with cross validation within one cycle of a breeding program can not be used as an indicator for the accuracy of predicting lines of the next cycle. Prediction of lines of the next cycle seems promising for traits with high heritabilities.

Development of estrogen receptor beta binding prediction model using large sets of chemicals.

PubMed

Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

2017-11-03

We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

Predictive validity of the Braden Scale, Norton Scale, and Waterlow Scale in the Czech Republic.

PubMed

Šateková, Lenka; Žiaková, Katarína; Zeleníková, Renáta

2017-02-01

The aim of this study was to determine the predictive validity of the Braden, Norton, and Waterlow scales in 2 long-term care departments in the Czech Republic. Assessing the risk for developing pressure ulcers is the first step in their prevention. At present, many scales are used in clinical practice, but most of them have not been properly validated yet (for example, the Modified Norton Scale in the Czech Republic). In the Czech Republic, only the Braden Scale has been validated so far. This is a prospective comparative instrument testing study. A random sample of 123 patients was recruited. The predictive validity of the pressure ulcer risk assessment scales was evaluated based on sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve. The data were collected from April to August 2014. In the present study, the best predictive validity values were observed for the Norton Scale, followed by the Braden Scale and the Waterlow Scale, in that order. We recommended that the above 3 pressure ulcer risk assessment scales continue to be evaluated in the Czech clinical setting. © 2016 John Wiley & Sons Australia, Ltd.

Validity of Integrity Tests for Predicting Drug and Alcohol Abuse

DTIC Science & Technology

1993-08-31

Wiinkler and Sheridan (1989) found that employees who entered employee assistance programs for treating drug addiction were more likely be absent...August 31, 1993 Final 4. TITLE AND SUBTITLE S. FUNDING NUMBERS Validity of Integrity Tests for Predicting Drug and Alcohol Abuse C No. N00014-92-J...words) This research used psychometric meta-analysis (Hunter & Schmidt, 1990b) to examine the validity of integrity tests for predicting drug and

A Flexible Approach for Assessing Functional Landscape Connectivity, with Application to Greater Sage-Grouse (Centrocercus urophasianus)

PubMed Central

Harju, Seth M.; Olson, Chad V.; Dzialak, Matthew R.; Mudd, James P.; Winstead, Jeff B.

2013-01-01

Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km2 study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape. PMID:24349241

A flexible approach for assessing functional landscape connectivity, with application to greater sage-grouse (Centrocercus urophasianus).

PubMed

Harju, Seth M; Olson, Chad V; Dzialak, Matthew R; Mudd, James P; Winstead, Jeff B

2013-01-01

Connectivity of animal populations is an increasingly prominent concern in fragmented landscapes, yet existing methodological and conceptual approaches implicitly assume the presence of, or need for, discrete corridors. We tested this assumption by developing a flexible conceptual approach that does not assume, but allows for, the presence of discrete movement corridors. We quantified functional connectivity habitat for greater sage-grouse (Centrocercus urophasianus) across a large landscape in central western North America. We assigned sample locations to a movement state (encamped, traveling and relocating), and used Global Positioning System (GPS) location data and conditional logistic regression to estimate state-specific resource selection functions. Patterns of resource selection during different movement states reflected selection for sagebrush and general avoidance of rough topography and anthropogenic features. Distinct connectivity corridors were not common in the 5,625 km(2) study area. Rather, broad areas functioned as generally high or low quality connectivity habitat. A comprehensive map predicting the quality of connectivity habitat across the study area validated well based on a set of GPS locations from independent greater sage-grouse. The functional relationship between greater sage-grouse and the landscape did not always conform to the idea of a discrete corridor. A more flexible consideration of landscape connectivity may improve the efficacy of management actions by aligning those actions with the spatial patterns by which animals interact with the landscape.

Validated Questionnaire of Maternal Attitude and Knowledge for Predicting Caries Risk in Children: Epidemiological Study in North Jakarta, Indonesia.

PubMed

Laksmiastuti, Sri Ratna; Budiardjo, Sarworini Bagio; Sutadi, Heriandi

2017-06-01

Predicting caries risk in children can be done by identifying caries risk factors. It is an important measure which contributes to best understanding of the cariogenic profile of the patient. Identification could be done by clinical examination and answering the questionnaire. We arrange the study to verify the questionnaire validation for predicting caries risk in children. The study was conducted on 62 pairs of mothers and their children, aged between 3 and 5 years. The questionnaire consists of 10 questions concerning mothers' attitude and knowledge about oral health. The reliability and validity test is based on Cronbach's alpha and correlation coefficient value. All question are reliable (Cronbach's alpha = 0.873) and valid (Corrected item-total item correlation >0.4). Five questionnaires of mother's attitude about oral health and five questionnaires of mother's knowledge about oral health are reliable and valid for predicting caries risk in children.

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

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

Valencia, Antoni; Prous, Josep; Mora, Oscar

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90%more » was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests show desirable high sensitivity and high negative predictivity. • The model predicted 14 reportedly difficult to predict drug impurities with accuracy. • The model is suitable to support risk evaluation of potentially mutagenic compounds.« less

Distinct roles of the intraparietal sulcus and temporoparietal junction in attentional capture from distractor features: An individual differences approach.

PubMed

Painter, David R; Dux, Paul E; Mattingley, Jason B

2015-07-01

Setting attention for an elementary visual feature, such as color or motion, results in greater spatial attentional "capture" from items with target compared with distractor features. Thus, capture is contingent on feature-based control settings. Neuroimaging studies suggest that this contingent attentional capture involves interactions between dorsal and ventral frontoparietal networks. To examine the distinct causal influences of these networks on contingent capture, we applied continuous theta-burst stimulation (cTBS) to alter neural excitability within the dorsal intraparietal sulcus (IPS), the ventral temporoparietal junction (TPJ) and a control site, visual area MT. Participants undertook an attentional capture task before and after stimulation, in which they made speeded responses to color-defined targets that were preceded by spatial cues in the target or distractor color. Cues appeared either at the target location (valid) or at a non-target location (invalid). Reaction times were slower for targets preceded by invalid compared with valid cues, demonstrating spatial attentional capture. Cues with the target color captured attention to a greater extent than those with the distractor color, consistent with contingent capture. Effects of cTBS were not evident at the group level, but emerged instead from analyses of individual differences. Target capture magnitude was positively correlated pre- and post-stimulation for all three cortical sites, suggesting that cTBS did not influence target capture. Conversely, distractor capture was positively correlated pre- and post-stimulation of MT, but uncorrelated for IPS and TPJ, suggesting that stimulation of IPS and TPJ selectively disrupted distractor capture. Additionally, the effects of IPS stimulation were predicted by pre-stimulation attentional capture, whereas the effects of TPJ stimulation were predicted by pre-stimulation distractor suppression. The results are consistent with the existence of distinct neural circuits underlying target and distractor capture, as well as distinct roles for the IPS and TPJ. Copyright © 2015 Elsevier Ltd. All rights reserved.

Development and validation of a predictive model for excessive postpartum blood loss: A retrospective, cohort study.

PubMed

Rubio-Álvarez, Ana; Molina-Alarcón, Milagros; Arias-Arias, Ángel; Hernández-Martínez, Antonio

2018-03-01

postpartum haemorrhage is one of the leading causes of maternal morbidity and mortality worldwide. Despite the use of uterotonics agents as preventive measure, it remains a challenge to identify those women who are at increased risk of postpartum bleeding. to develop and to validate a predictive model to assess the risk of excessive bleeding in women with vaginal birth. retrospective cohorts study. "Mancha-Centro Hospital" (Spain). the elaboration of the predictive model was based on a derivation cohort consisting of 2336 women between 2009 and 2011. For validation purposes, a prospective cohort of 953 women between 2013 and 2014 were employed. Women with antenatal fetal demise, multiple pregnancies and gestations under 35 weeks were excluded METHODS: we used a multivariate analysis with binary logistic regression, Ridge Regression and areas under the Receiver Operating Characteristic curves to determine the predictive ability of the proposed model. there was 197 (8.43%) women with excessive bleeding in the derivation cohort and 63 (6.61%) women in the validation cohort. Predictive factors in the final model were: maternal age, primiparity, duration of the first and second stages of labour, neonatal birth weight and antepartum haemoglobin levels. Accordingly, the predictive ability of this model in the derivation cohort was 0.90 (95% CI: 0.85-0.93), while it remained 0.83 (95% CI: 0.74-0.92) in the validation cohort. this predictive model is proved to have an excellent predictive ability in the derivation cohort, and its validation in a latter population equally shows a good ability for prediction. This model can be employed to identify women with a higher risk of postpartum haemorrhage. Copyright © 2017 Elsevier Ltd. All rights reserved.

Status and plans for the ANOPP/HSR prediction system

NASA Technical Reports Server (NTRS)

Nolan, Sandra K.

1992-01-01

ANOPP is a comprehensive prediction system which was developed and validated by NASA. Because ANOPP is a system prediction program, it allows aerospace industry researchers to create trade-off studies with a variety of aircraft noise problems. The extensive validation of ANOPP allows the program results to be used as a benchmark for testing other prediction codes.

How Nonrecidivism Affects Predictive Accuracy: Evidence from a Cross-Validation of the Ontario Domestic Assault Risk Assessment (ODARA)

ERIC Educational Resources Information Center

Hilton, N. Zoe; Harris, Grant T.

2009-01-01

Prediction effect sizes such as ROC area are important for demonstrating a risk assessment's generalizability and utility. How a study defines recidivism might affect predictive accuracy. Nonrecidivism is problematic when predicting specialized violence (e.g., domestic violence). The present study cross-validates the ability of the Ontario…

Prediction and visualization of redox conditions in the groundwater of Central Valley, California

USGS Publications Warehouse

Rosecrans, Celia Z.; Nolan, Bernard T.; Gronberg, JoAnn M.

2017-01-01

Regional-scale, three-dimensional continuous probability models, were constructed for aspects of redox conditions in the groundwater system of the Central Valley, California. These models yield grids depicting the probability that groundwater in a particular location will have dissolved oxygen (DO) concentrations less than selected threshold values representing anoxic groundwater conditions, or will have dissolved manganese (Mn) concentrations greater than selected threshold values representing secondary drinking water-quality contaminant levels (SMCL) and health-based screening levels (HBSL). The probability models were constrained by the alluvial boundary of the Central Valley to a depth of approximately 300 m. Probability distribution grids can be extracted from the 3-D models at any desired depth, and are of interest to water-resource managers, water-quality researchers, and groundwater modelers concerned with the occurrence of natural and anthropogenic contaminants related to anoxic conditions.Models were constructed using a Boosted Regression Trees (BRT) machine learning technique that produces many trees as part of an additive model and has the ability to handle many variables, automatically incorporate interactions, and is resistant to collinearity. Machine learning methods for statistical prediction are becoming increasing popular in that they do not require assumptions associated with traditional hypothesis testing. Models were constructed using measured dissolved oxygen and manganese concentrations sampled from 2767 wells within the alluvial boundary of the Central Valley, and over 60 explanatory variables representing regional-scale soil properties, soil chemistry, land use, aquifer textures, and aquifer hydrologic properties. Models were trained on a USGS dataset of 932 wells, and evaluated on an independent hold-out dataset of 1835 wells from the California Division of Drinking Water. We used cross-validation to assess the predictive performance of models of varying complexity, as a basis for selecting final models. Trained models were applied to cross-validation testing data and a separate hold-out dataset to evaluate model predictive performance by emphasizing three model metrics of fit: Kappa; accuracy; and the area under the receiver operator characteristic curve (ROC). The final trained models were used for mapping predictions at discrete depths to a depth of 304.8 m. Trained DO and Mn models had accuracies of 86–100%, Kappa values of 0.69–0.99, and ROC values of 0.92–1.0. Model accuracies for cross-validation testing datasets were 82–95% and ROC values were 0.87–0.91, indicating good predictive performance. Kappas for the cross-validation testing dataset were 0.30–0.69, indicating fair to substantial agreement between testing observations and model predictions. Hold-out data were available for the manganese model only and indicated accuracies of 89–97%, ROC values of 0.73–0.75, and Kappa values of 0.06–0.30. The predictive performance of both the DO and Mn models was reasonable, considering all three of these fit metrics and the low percentages of low-DO and high-Mn events in the data.

Responsiveness and predictive validity of the tablet-based symbol digit modalities test in patients with stroke.

PubMed

Hsiao, Pei-Chi; Yu, Wan-Hui; Lee, Shih-Chieh; Chen, Mei-Hsiang; Hsieh, Ching-Lin

2018-06-14

The responsiveness and predictive validity of the Tablet-based Symbol Digit Modalities Test (T-SDMT) are unknown, which limits the utility of the T-SDMT in both clinical and research settings. The purpose of this study was to examine the responsiveness and predictive validity of the T-SDMT in inpatients with stroke. A follow-up, repeated-assessments design. One rehabilitation unit at a local medical center. A total of 50 inpatients receiving rehabilitation completed T-SDMT assessments at admission to and discharge from a rehabilitation ward. The median follow-up period was 14 days. The Barthel index (BI) was assessed at discharge and was used as the criterion of the predictive validity. The mean changes in the T-SDMT scores between admission and discharge were statistically significant (paired t-test = 3.46, p = 0.001). The T-SDMT scores showed a nearly moderate standardized response mean (0.49). A moderate association (Pearson's r = 0.47) was found between the scores of the T-SDMT at admission and those of the BI at discharge, indicating good predictive validity of the T-SDMT. Our results support the responsiveness and predictive validity of the T-SDMT in patients with stroke receiving rehabilitation in hospitals. This study provides empirical evidence supporting the use of the T-SDMT as an outcome measure for assessing processingspeed in inpatients with stroke. The scores of the T-SDMT could be used to predict basic activities of daily living function in inpatients with stroke.

Effects of dietary β-mannanase supplementation on the additivity of true metabolizable energy values for broiler diets.

PubMed

Lee, Byung Bo; Yang, Tae Sung; Goo, Doyun; Choi, Hyeon Seok; Pitargue, Franco Martinez; Jung, Hyunjung; Kil, Dong Yong

2018-04-01

This experiment was conducted to determine the effects of dietary β-mannanase on the additivity of true metabolizable energy (TME) and nitrogen-corrected true metabolizable energy (TME n ) for broiler diets. A total of 144 21-day-old broilers were randomly allotted to 12 dietary treatments with 6 replicates. Five treatments consisted of 5 ingredients of corn, wheat, soybean meal, corn distillers dried grains with solubles, or corn gluten meal. One mixed diet containing 200 g/kg of those 5 ingredients also was prepared. Additional 6 treatments were prepared by mixing 0.5 g/kg dietary β-mannanase with those 5 ingredients and the mixed diet. Based on a precision-fed chicken assay, TME and TME n values for 5 ingredients and the mixed diet as affected by dietary β-mannanase were determined. Results indicated that when β-mannanase was not added to the diet, measured TME and TME n values for the diet did not differ from the predicted values for the diet, which validated the additivity. However, for the diet containing β-mannanase, measured TME n value was greater (p<0.05) than predicted TME n value, indicating that the additivity was not validated. In conclusion, the additivity of energy values for the mixed diet may not be guaranteed if the diet contains β-mannanase.

Risk assessments for dating violence in mid to late adolescence and early adulthood.

PubMed

Tapp, James; Moore, Estelle

2016-10-01

The objective of this paper is to review risk instruments that have been used in the assessment of the potential for violence within the dating relationships of young people. A review of the dating violence literature was conducted to identify risk assessment approaches that have been used to predict harmful behaviour within the dating relationships of people aged between 15 and 30 years. Risk assessments were evaluated on recommended quality criteria: predictive validity, accuracy (sensitivity and specificity) and inter-rater reliability. Only five studies describing assessments that focused specifically on dating violence risk factors were selected for review. Three assessments encompassed dating behaviours by victims that have been associated with an increased risk of further victimisation. Drawing on this evidence, we conclude that young people appear to be at greater risk of encountering dating violence if they have experienced violence in earlier attachment relationships; if their skills for coping with conflict and responding to coercion are limited and if the presence of peer influences reinforces offence supportive attitudes. The reliability and validity of existing intimate partner violence risk assessments that conceptually overlap with elements of dating violence risk warrant investigation to inform risk assessment developments in this field and, building on this, possible interventions to minimise future harm. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Performance standard-based validation study for local lymph node assay: 5-bromo-2-deoxyuridine-flow cytometry method.

PubMed

Ahn, Ilyoung; Kim, Tae-Sung; Jung, Eun-Sun; Yi, Jung-Sun; Jang, Won-Hee; Jung, Kyoung-Mi; Park, Miyoung; Jung, Mi-Sook; Jeon, Eun-Young; Yeo, Kyeong-Uk; Jo, Ji-Hoon; Park, Jung-Eun; Kim, Chang-Yul; Park, Yeong-Chul; Seong, Won-Keun; Lee, Ai-Young; Chun, Young Jin; Jeong, Tae Cheon; Jeung, Eui Bae; Lim, Kyung-Min; Bae, SeungJin; Sohn, Soojung; Heo, Yong

2016-10-01

Local lymph node assay: 5-bromo-2-deoxyuridine-flow cytometry method (LLNA: BrdU-FCM) is a modified non-radioisotopic technique with the additional advantages of accommodating multiple endpoints with the introduction of FCM, and refinement and reduction of animal use by using a sophisticated prescreening scheme. Reliability and accuracy of the LLNA: BrdU-FCM was determined according to OECD Test Guideline (TG) No. 429 (Skin Sensitization: Local Lymph Node Assay) performance standards (PS), with the participation of four laboratories. Transferability was demonstrated through successfully producing stimulation index (SI) values for 25% hexyl cinnamic aldehyde (HCA) consistently greater than 3, a predetermined threshold, by all participating laboratories. Within- and between-laboratory reproducibility was shown using HCA and 2,4-dinitrochlorobenzene, in which EC2.7 values (the estimated concentrations eliciting an SI of 2.7, the threshold for LLNA: BrdU-FCM) fell consistently within the acceptance ranges, 0.025-0.1% and 5-20%, respectively. Predictive capacity was tested using the final protocol version 1.3 for the 18 reference chemicals listed in OECD TG 429, of which results showed 84.6% sensitivity, 100% specificity, and 88.9% accuracy compared with the original LLNA. The data presented are considered to meet the performance criteria for the PS, and its predictive capacity was also sufficiently validated. Copyright © 2016 Elsevier Inc. All rights reserved.

Predictive validity of granulation tissue color measured by digital image analysis for deep pressure ulcer healing: a multicenter prospective cohort study.

PubMed

Iizaka, Shinji; Kaitani, Toshiko; Sugama, Junko; Nakagami, Gojiro; Naito, Ayumi; Koyanagi, Hiroe; Konya, Chizuko; Sanada, Hiromi

2013-01-01

This multicenter prospective cohort study examined the predictive validity of granulation tissue color evaluated by digital image analysis for deep pressure ulcer healing. Ninety-one patients with deep pressure ulcers were followed for 3 weeks. From a wound photograph taken at baseline, an image representing the granulation red index (GRI) was processed in which a redder color represented higher values. We calculated the average GRI over granulation tissue and the proportion of pixels exceeding the threshold intensity of 80 for the granulation tissue surface (%GRI80) and wound surface (%wound red index 80). In the receiver operating characteristics curve analysis, most GRI parameters had adequate discriminative values for both improvement of the DESIGN-R total score and wound closure. Ulcers were categorized by the obtained cutoff points of the average GRI (≤80, >80), %GRI80 (≤55, >55-80, >80%), and %wound red index 80 (≤25, >25-50, >50%). In the linear mixed model, higher classes for all GRI parameters showed significantly greater relative improvement in overall wound severity during the 3 weeks after adjustment for patient characteristics and wound locations. Assessment of granulation tissue color by digital image analysis will be useful as an objective monitoring tool for granulation tissue quality or surrogate outcomes of pressure ulcer healing. © 2012 by the Wound Healing Society.

Preliminary development and validation of the Supervisee Attachment Strategies Scale (SASS).

PubMed

Menefee, Deleene S; Day, Susan X; Lopez, Frederick G; McPherson, Robert H

2014-04-01

The influence of counselor trainees' adult attachment orientations in the context of supervision has the potential to inform both training and supervision practice. However, the pursuit of such research requires the availability of appropriate assessment tools. The present study describes the development and validation of the Supervisee Attachment Strategies Scale (SASS), a theory-based measure of counseling trainees' attachment orientations toward their clinical supervisors. Participants were recruited online through their training directors at Association of Psychology Postdoctoral and Internship Centers member programs. Data were nationally collected from 352 trainees representing programs in the United States and Canada. Exploratory factor analysis yielded 2 interpretable factors along the adult attachment dimensions of avoidance vs. engagement and rejection concern vs. security. These 2 factors accounted for 55.85% of the interitem variance in the rotated solution of the 22-item SASS scale. SASS subscale scores were negatively correlated with the supervisory working alliance and predicted greater endorsement of role conflict and role ambiguity in the current supervisory relationship. Higher avoidance (but not rejection concern) predicted diminished perceptions of satisfaction with the overall training experience. Findings from this study suggest that trainees who engaged in adaptive attachment strategies may be more likely to address conflict, negotiate additional explorative opportunities in training, and seek out their supervisors in times of uncertainty. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Effects of dietary β-mannanase supplementation on the additivity of true metabolizable energy values for broiler diets

PubMed Central

Lee, Byung Bo; Yang, Tae Sung; Goo, Doyun; Choi, Hyeon Seok; Pitargue, Franco Martinez; Jung, Hyunjung; Kil, Dong Yong

2018-01-01

Objective This experiment was conducted to determine the effects of dietary β-mannanase on the additivity of true metabolizable energy (TME) and nitrogen-corrected true metabolizable energy (TMEn) for broiler diets. Methods A total of 144 21-day-old broilers were randomly allotted to 12 dietary treatments with 6 replicates. Five treatments consisted of 5 ingredients of corn, wheat, soybean meal, corn distillers dried grains with solubles, or corn gluten meal. One mixed diet containing 200 g/kg of those 5 ingredients also was prepared. Additional 6 treatments were prepared by mixing 0.5 g/kg dietary β-mannanase with those 5 ingredients and the mixed diet. Based on a precision-fed chicken assay, TME and TMEn values for 5 ingredients and the mixed diet as affected by dietary β-mannanase were determined. Results Results indicated that when β-mannanase was not added to the diet, measured TME and TMEn values for the diet did not differ from the predicted values for the diet, which validated the additivity. However, for the diet containing β-mannanase, measured TMEn value was greater (p<0.05) than predicted TMEn value, indicating that the additivity was not validated. Conclusion In conclusion, the additivity of energy values for the mixed diet may not be guaranteed if the diet contains β-mannanase. PMID:29381897

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Validity of Measured Interest for Decided and Undecided Students.

ERIC Educational Resources Information Center

Bartling, Herbert C.; Hood, Albert B.

The usefulness of vocational interest measures has been questioned by those who have studied the predictive validity of expressed choice. The predictive validities of measured interest for decided and undecided students, expressed choice and measured interest, and expressed choice and measured interest when they are congruent and incongruent were…

Validation of bioelectrical impedance analysis (BIA) for estimation of body composition in Black, White and Hispanic adolescent girls

PubMed Central

Going, S.; Nichols, J.; Loftin, M.; Stewart, D.; Lohman, T.; Tuuri, G.; Ring, K.; Pickrel, J.; Blew, R.; J.Stevens

2007-01-01

Aim Equations for estimating % fat mass (%BF) and fat-free mass (FFM) from bioelectrical impedance analysis (BIA) that work in adolescent girls from different racial/ethnic backgrounds are not available. We investigated whether race/ethnicity influences estimation of body composition in adolescent girls. Principal procedures Prediction equations were developed for estimating FFM and %BF from BIA in 166 girls, 10–15 years old, consisting of 51 Black (B), 45 non-Black Hispanic (H), 55 non-Hispanic White (W) and 15 mixed (M) race/ethnicity girls, using dual energy x-ray absorptiometry (DXA) as the criterion method. Findings Black girls had similar %BF compared to other groups, yet were heavier per unit of height according to body mass index (BMI: kg·m−2) due to significantly greater FFM. BIA resistance index, age, weight and race/ethnicity were all significant predictors of FFM (R2 = 0.92, SEE = 1.81 kg). Standardized regression coefficients showed resistance index (0.63) and weight (0.34) were the most important predictors of FFM. Errors in %BF (~2%) and FFM (~1.0 kg) were greater when race/ethnicity was not included in the equation, particularly in Black girls. We conclude the BIA-composition relationship in adolescent girls is influenced by race, and consequently have developed new BIA equations for adolescent girls for predicting FFM and %BF. PMID:17848976

Implicit Physician Biases in Periviability Counseling.

PubMed

Shapiro, Natasha; Wachtel, Elena V; Bailey, Sean M; Espiritu, Michael M

2018-06-01

To assess whether neonatologists show implicit racial and/or socioeconomic biases and whether these are predictive of recommendations at extreme periviability. A nationwide survey using a clinical vignette of a woman in labor at 23 2/7 weeks of gestation asked physicians how likely they were to recommend intensive vs comfort care. Participants were randomized to 1 of 4 versions of the vignette in which racial and socioeconomic stimuli were varied, followed by 2 implicit association tests (IATs). IATs revealed implicit preferences favoring white (mean IAT score = 0.48, P < .001) and greater socioeconomic status (mean IAT score = 0.73, P < .001). Multivariable linear regression analysis showed that physicians with implicit bias toward greater socioeconomic status were more likely than those without bias to recommend comfort care when presented with a patient of high socioeconomic status (P = .037). No significant effect was seen for implicit racial bias. Building on previous demonstrations of unconscious racial and socioeconomic biases among physicians and their predictive validity, our results suggest that unconscious socioeconomic bias influences recommendations when counseling at the limits of viability. Physicians who display a negative socioeconomic bias are less likely to recommend resuscitation when counseling women of high socioeconomic status. The influence of implicit socioeconomic bias on recommendations at periviability may influence neonatal healthcare disparities and should be explored in future studies. Copyright © 2018 Elsevier Inc. All rights reserved.

Prediction of aortic valvular area and gradient by noninvasive techniques.

PubMed

Cousins, A L; Eddleman, E E; Reeves, T J

1978-03-01

Sixty-two patients with isolated aortic valvular stenosis were analyzed by a series of common noninvasive procedures and by cardiac catheterization. The data from 50 of these were evaluated in a retrospective fashion by multiple regression methods to determine significant objectively obtained predictors of aortic-left ventricular gradient and valvular area. Formulae were derived from these analyses and an additional 12 patients were then studied prospectively to evaluate the validity of the predictive formulae. Forty-three of 50 patients (86 per cent) were correctly identified as to a gradient of greater or less than 50 mm. Hg in the initial group, and all those in the prospectively studied sample were correctly classified. Thiry-five of 43 patients (82 per cent) of those with valve area data in the first application were correctly classified as to valve area or greater or less than 0.8 cm.2, and all patients in the prospectively studied group were appropriately identified as to the same area. The combined application of the observations of calcification of the aortic valve, shudder waves on the anacrotic limb, prolonged time to peak of the percussion wave and alteration of the dicrotic notch of the carotid pulse tracing, left ventricular hypertrophy by electrocardiogram, and the altered duration of ventricular ejection time were reliable predictors of elevated aortic-left ventricular gradient and decreased aortic valvular size.

Testing the Predictive Validity of the Hendrich II Fall Risk Model.

PubMed

Jung, Hyesil; Park, Hyeoun-Ae

2018-03-01

Cumulative data on patient fall risk have been compiled in electronic medical records systems, and it is possible to test the validity of fall-risk assessment tools using these data between the times of admission and occurrence of a fall. The Hendrich II Fall Risk Model scores assessed during three time points of hospital stays were extracted and used for testing the predictive validity: (a) upon admission, (b) when the maximum fall-risk score from admission to falling or discharge, and (c) immediately before falling or discharge. Predictive validity was examined using seven predictive indicators. In addition, logistic regression analysis was used to identify factors that significantly affect the occurrence of a fall. Among the different time points, the maximum fall-risk score assessed between admission and falling or discharge showed the best predictive performance. Confusion or disorientation and having a poor ability to rise from a sitting position were significant risk factors for a fall.

Assessing the validity of sales self-efficacy: a cautionary tale.

PubMed

Gupta, Nina; Ganster, Daniel C; Kepes, Sven

2013-07-01

We developed a focused, context-specific measure of sales self-efficacy and assessed its incremental validity against the broad Big 5 personality traits with department store salespersons, using (a) both a concurrent and a predictive design and (b) both objective sales measures and supervisory ratings of performance. We found that in the concurrent study, sales self-efficacy predicted objective and subjective measures of job performance more than did the Big 5 measures. Significant differences between the predictability of subjective and objective measures of performance were not observed. Predictive validity coefficients were generally lower than concurrent validity coefficients. The results suggest that there are different dynamics operating in concurrent and predictive designs and between broad and contextualized measures; they highlight the importance of distinguishing between these designs and measures in meta-analyses. The results also point to the value of focused, context-specific personality predictors in selection research. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Validation of Six Short and Ultra-short Screening Instruments for Depression for People Living with HIV in Ontario: Results from the Ontario HIV Treatment Network Cohort Study.

PubMed

Choi, Stephanie K Y; Boyle, Eleanor; Burchell, Ann N; Gardner, Sandra; Collins, Evan; Grootendorst, Paul; Rourke, Sean B

2015-01-01

Major depression affects up to half of people living with HIV. However, among HIV-positive patients, depression goes unrecognized 60-70% of the time in non-psychiatric settings. We sought to evaluate three screening instruments and their short forms to facilitate the recognition of current depression in HIV-positive patients attending HIV specialty care clinics in Ontario. A multi-centre validation study was conducted in Ontario to examine the validity and accuracy of three instruments (the Center for Epidemiologic Depression Scale [CESD20], the Kessler Psychological Distress Scale [K10], and the Patient Health Questionnaire depression scale [PHQ9]) and their short forms (CESD10, K6, and PHQ2) in diagnosing current major depression among 190 HIV-positive patients in Ontario. Results from the three instruments and their short forms were compared to results from the gold standard measured by Mini International Neuropsychiatric Interview (the "M.I.N.I."). Overall, the three instruments identified depression with excellent accuracy and validity (area under the curve [AUC]>0.9) and good reliability (Kappa statistics: 0.71-0.79; Cronbach's alpha: 0.87-0.93). We did not find that the AUCs differed in instrument pairs (p-value>0.09), or between the instruments and their short forms (p-value>0.3). Except for the PHQ2, the instruments showed good-to-excellent sensitivity (0.86-1.0) and specificity (0.81-0.87), excellent negative predictive value (>0.90), and moderate positive predictive value (0.49-0.58) at their optimal cut-points. Among people in HIV care in Ontario, Canada, the three instruments and their short forms performed equally well and accurately. When further in-depth assessments become available, shorter instruments might find greater clinical acceptance. This could lead to clinical benefits in fast-paced speciality HIV care settings and better management of depression in HIV-positive patients.

Shallow water models as tool for tsunami current predictions in ports and harbors. Validation with Tohoku 2011 field data

NASA Astrophysics Data System (ADS)

Gonzalez Vida, J. M., Sr.; Macias Sanchez, J.; Castro, M. J.; Ortega, S.

2015-12-01

Model ability to compute and predict tsunami flow velocities is of importance in risk assessment and hazard mitigation. Substantial damage can be produced by high velocity flows, particularly in harbors and bays, even when the wave height is small. Besides, an accurate simulation of tsunami flow velocities and accelerations is fundamental for advancing in the study of tsunami sediment transport. These considerations made the National Tsunami Hazard Mitigation Program (NTHMP) proposing a benchmark exercise focused on modeling and simulating tsunami currents. Until recently, few direct measurements of tsunami velocities were available to compare and to validate model results. After Tohoku 2011 many current meters measurement were made, mainly in harbors and channels. In this work we present a part of the contribution made by the EDANYA group from the University of Malaga to the NTHMP workshop organized at Portland (USA), 9-10 of February 2015. We have selected three out of the five proposed benchmark problems. Two of them consist in real observed data from the Tohoku 2011 event, one at Hilo Habour (Hawaii) and the other at Tauranga Bay (New Zealand). The third one consists in laboratory experimental data for the inundation of Seaside City in Oregon. For this model validation the Tsunami-HySEA model, developed by EDANYA group, was used. The overall conclusion that we could extract from this validation exercise was that the Tsunami-HySEA model performed well in all benchmark problems proposed. The greater spatial variability in tsunami velocity than wave height makes it more difficult its precise numerical representation. The larger variability in velocities is likely a result of the behaviour of the flow as it is channelized and as it flows around bathymetric highs and structures. In the other hand wave height do not respond as strongly to chanelized flow as current velocity.

Intellectual Disabilities and Neglectful Parenting: Preliminary Findings on the Role of Cognition in Parenting Risk

PubMed Central

Azar, Sandra T.; Stevenson, Michael T.; Johnson, David R.

2014-01-01

Parents with intellectual disabilities (PID) are over-represented in the child protective services (CPS) system. This study examined a more nuanced view of the role of cognition in parenting risk. Its goal was to validate a social information processing (SIP) model of child neglect that draws on social cognition research and advances in neuroscience. Mothers who had CPS child neglect cases were compared with mothers with no CPS involvement on a set of SIP factors. Mothers with low IQs were oversampled. As predicted, the Neglect group had significantly greater SIP problems than the Comparison mothers. SIP problems were associated with direct measures of neglect (e.g., cognitive stimulation provided children, home hygiene, belief regarding causes of child injuries). Further, for the direct measures that were most closely linked to CPS Neglect Status, IQ did not add significant predictive capacity beyond SIP factors in preliminary model testing. Implications for intervention with PID discussed. PMID:25506405

Prefrontal EEG alpha asymmetry changes while observing disaster happening to other people: cardiac correlates and prediction of emotional impact.

PubMed

Papousek, Ilona; Weiss, Elisabeth M; Schulter, Günter; Fink, Andreas; Reiser, Eva M; Lackner, Helmut K

2014-12-01

Changes of EEG alpha asymmetry in terms of increased right versus left sided activity in prefrontal cortex are considered to index activation of the withdrawal/avoidance motivational system. The present study aimed to add evidence of the validity of individual differences in the EEG alpha asymmetry response and their relevance regarding the impact of emotional events. The magnitude of the EEG alpha asymmetry response while watching a film consisting of scenes of real injury and death correlated with components of transient cardiac responses to sudden horrifying events happening to persons in the film which index withdrawal/avoidance motivation and heightened attention and perceptual intake. Additionally, it predicted greater mood deterioration following the film and film-related intrusive memories and avoidance over the following week. The study provides further evidence for prefrontal EEG alpha asymmetry changes in response to relevant stimuli reflecting an individual's sensitivity to negative social-emotional cues encountered in everyday life. Copyright © 2014 Elsevier B.V. All rights reserved.

Predictive Validity of a Continuous Alternative to Nominal Subtypes of Attention-Deficit Hyperactivity Disorder for DSM-V

PubMed Central

Lahey, Benjamin B.; Willcutt, Erik G.

2010-01-01

Three subtypes of attention-deficit/hyperactivity disorder (ADHD) based on numbers of symptoms of inattention (I) and hyperactivity-impulsivity (HI) were defined in DSM-IV to reduce heterogeneity of the disorder, but the subtypes proved to be highly unstable over time. A continuous alternative to nominal subtyping is evaluated in a longitudinal study of 129 4–6 year old children with ADHD and 130 comparison children. Children who met criteria for all subtypes in year 1 continued to exhibit greater functional impairment than comparison children during years 2–9. Among children with ADHD in year 1, I and HI symptoms differentially predicted teacher-rated need for treatment and reading and mathematics achievement scores over the next 8 years in controlled analyses. Consistent with other studies, these findings suggest that the use of diagnostic modifiers specifying the numbers of I and HI symptoms could reduce heterogeneity and facilitate clinical intervention, prognosis, and research. PMID:21058124

Generic buckling curves for specially orthotropic rectangular plates

NASA Technical Reports Server (NTRS)

Brunnelle, E. J.; Oyibo, G. A.

1983-01-01

Using a double affine transformation, the classical buckling equation for specially orthotropic plates and the corresponding virtual work theorem are presented in a particularly simple fashion. These dual representations are characterized by a single material constant, called the generalized rigidity ratio, whose range is predicted to be the closed interval from 0 to 1 (if this prediction is correct then the numerical results using a ratio greater than 1 in the specially orthotropic plate literature are incorrect); when natural boundary conditions are considered a generalized Poisson's ratio is introduced. Thus the buckling results are valid for any specially orthotropic material; hence the curves presented in the text are generic rather than specific. The solution trends are twofold; the buckling coefficients decrease with decreasing generalized rigidity ratio and, when applicable, they decrease with increasing generalized Poisson's ratio. Since the isotropic plate is one limiting case of the above analysis, it is also true that isotropic buckling coefficients decrease with increasing Poission's ratio.

Predictive validity of a continuous alternative to nominal subtypes of attention-deficit/hyperactivity disorder for DSM-V.

PubMed

Lahey, Benjamin B; Willcutt, Erik G

2010-01-01

Three subtypes of attention-deficit/hyperactivity disorder (ADHD) based on numbers of symptoms of inattention (I) and hyperactivity-impulsivity (HI) were defined in the Diagnostic and Statistical Manual of Mental Disorders (4th ed.) to reduce heterogeneity of the disorder, but the subtypes proved to be highly unstable over time. A continuous alternative to nominal subtyping is evaluated in a longitudinal study of 129 four- to six-year-old children with ADHD and 130 comparison children. Children who met criteria for all subtypes in Year 1 continued to exhibit greater functional impairment than comparison children during Years 2 to 9. Among children with ADHD in Year 1, I and HI symptoms differentially predicted teacher-rated need for treatment and reading and mathematics achievement scores over the next 8 years in controlled analyses. Consistent with other studies, these findings suggest that the use of diagnostic modifiers specifying the numbers of I and HI symptoms could reduce heterogeneity and facilitate clinical intervention, prognosis, and research.

Biomarkers for Psychiatry: The Journey from Fantasy to Fact, a Report of the 2013 CINP Think Tank

PubMed Central

Millan, Mark J.; Bahn, Sabine; Bertolino, Alessandro; Turck, Christoph W.; Kapur, Shitij; Möller, Hans-Jürgen; Dean, Brian

2015-01-01

Background: A think tank sponsored by the Collegium Internationale Neuropsychopharmacologium (CINP) debated the status and prospects of biological markers for psychiatric disorders, focusing on schizophrenia and major depressive disorder. Methods: Discussions covered markers defining and predicting specific disorders or domains of dysfunction, as well as predicting and monitoring medication efficacy. Deliberations included clinically useful and viable biomarkers, why suitable markers are not available, and the need for tightly-controlled sample collection. Results: Different types of biomarkers, appropriate sensitivity, specificity, and broad-based exploitability were discussed. Whilst a number of candidates are in the discovery phases, all will require replication in larger, real-life cohorts. Clinical cost-effectiveness also needs to be established. Conclusions: Since a single measure is unlikely to suffice, multi-modal strategies look more promising, although they bring greater technical and implementation complexities. Identifying reproducible, robust biomarkers will probably require pre-competitive consortia to provide the resources needed to identify, validate, and develop the relevant clinical tests. PMID:25899066

Psychosocial Outcomes in Long-Term Cochlear Implant Users.

PubMed

Castellanos, Irina; Kronenberger, William G; Pisoni, David B

The objectives of this study were to investigate psychosocial outcomes in a sample of prelingually deaf, early-implanted children, adolescents, and young adults who are long-term cochlear implant (CI) users and to examine the extent to which language and executive functioning predict psychosocial outcomes. Psychosocial outcomes were measured using two well-validated, parent-completed checklists: the Behavior Assessment System for Children and the Conduct Hyperactive Attention Problem Oppositional Symptom. Neurocognitive skills were measured using gold standard, performance-based assessments of language and executive functioning. CI users were at greater risk for clinically significant deficits in areas related to attention, oppositional behavior, hyperactivity-impulsivity, and social-adaptive skills compared with their normal-hearing peers, although the majority of CI users scored within average ranges relative to Behavior Assessment System for Children norms. Regression analyses revealed that language, visual-spatial working memory, and inhibition-concentration skills predicted psychosocial outcomes. Findings suggest that underlying delays and deficits in language and executive functioning may place some CI users at a risk for difficulties in psychosocial adjustment.

Screening for potential child maltreatment in parents of a newborn baby: The predictive validity of an Instrument for early identification of Parents At Risk for child Abuse and Neglect (IPARAN).

PubMed

van der Put, Claudia E; Bouwmeester-Landweer, Merian B R; Landsmeer-Beker, Eleonore A; Wit, Jan M; Dekker, Friedo W; Kousemaker, N Pieter J; Baartman, Herman E M

2017-08-01

For preventive purposes it is important to be able to identify families with a high risk of child maltreatment at an early stage. Therefore we developed an actuarial instrument for screening families with a newborn baby, the Instrument for identification of Parents At Risk for child Abuse and Neglect (IPARAN). The aim of this study was to assess the predictive validity of the IPARAN and to examine whether combining actuarial and clinical methods leads to an improvement of the predictive validity. We examined the predictive validity by calculating several performance indicators (i.e., sensitivity, specificity and the Area Under the receiver operating characteristic Curve [AUC]) in a sample of 4692 Dutch families with newborns. The outcome measure was a report of child maltreatment at Child Protection Services during a follow-up of 3 years. For 17 children (.4%) a report of maltreatment was registered. The predictive validity of the IPARAN was significantly better than chance (AUC=.700, 95% CI [.567-.832]), in contrast to a low value for clinical judgement of nurses of the Youth Health Care Centers (AUC=.591, 95% CI [.422-.759]). The combination of the IPARAN and clinical judgement resulted in the highest predictive validity (AUC=.720, 95% CI [.593-.847]), however, the difference between the methods did not reach statistical significance. The good predictive validity of the IPARAN in combination with clinical judgment of the nurse enables professionals to assess risks at an early stage and to make referrals to early intervention programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation and Inter-comparison Against Observations of GODAE Ocean View Ocean Prediction Systems

NASA Astrophysics Data System (ADS)

Xu, J.; Davidson, F. J. M.; Smith, G. C.; Lu, Y.; Hernandez, F.; Regnier, C.; Drevillon, M.; Ryan, A.; Martin, M.; Spindler, T. D.; Brassington, G. B.; Oke, P. R.

2016-02-01

For weather forecasts, validation of forecast performance is done at the end user level as well as by the meteorological forecast centers. In the development of Ocean Prediction Capacity, the same level of care for ocean forecast performance and validation is needed. Herein we present results from a validation against observations of 6 Global Ocean Forecast Systems under the GODAE OceanView International Collaboration Network. These systems include the Global Ocean Ice Forecast System (GIOPS) developed by the Government of Canada, two systems PSY3 and PSY4 from the French Mercator-Ocean Ocean Forecasting Group, the FOAM system from UK met office, HYCOM-RTOFS from NOAA/NCEP/NWA of USA, and the Australian Bluelink-OceanMAPS system from the CSIRO, the Australian Meteorological Bureau and the Australian Navy.The observation data used in the comparison are sea surface temperature, sub-surface temperature, sub-surface salinity, sea level anomaly, and sea ice total concentration data. Results of the inter-comparison demonstrate forecast performance limits, strengths and weaknesses of each of the six systems. This work establishes validation protocols and routines by which all new prediction systems developed under the CONCEPTS Collaborative Network will be benchmarked prior to approval for operations. This includes anticipated delivery of CONCEPTS regional prediction systems over the next two years including a pan Canadian 1/12th degree resolution ice ocean prediction system and limited area 1/36th degree resolution prediction systems. The validation approach of comparing forecasts to observations at the time and location of the observation is called Class 4 metrics. It has been adopted by major international ocean prediction centers, and will be recommended to JCOMM-WMO as routine validation approach for operational oceanography worldwide.

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.

Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills

DTIC Science & Technology

2012-07-01

Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills Dana Broach Civil Aerospace...Medical Institute Federal Aviation Administration Oklahoma City, OK 73125 July 2012 Final Report DOT/FAA/AM- 12 /8 Office of Aerospace Medicine...FAA/AM- 12 /8 4. Title and Subtitle 5. Report Date July 2012 Incremental Validity of Biographical Data in the Prediction of En Route Air

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.

Predicting ionizing radiation exposure using biochemically-inspired genomic machine learning.

PubMed

Zhao, Jonathan Z L; Mucaki, Eliseos J; Rogan, Peter K

2018-01-01

Background: Gene signatures derived from transcriptomic data using machine learning methods have shown promise for biodosimetry testing. These signatures may not be sufficiently robust for large scale testing, as their performance has not been adequately validated on external, independent datasets. The present study develops human and murine signatures with biochemically-inspired machine learning that are strictly validated using k-fold and traditional approaches. Methods: Gene Expression Omnibus (GEO) datasets of exposed human and murine lymphocytes were preprocessed via nearest neighbor imputation and expression of genes implicated in the literature to be responsive to radiation exposure (n=998) were then ranked by Minimum Redundancy Maximum Relevance (mRMR). Optimal signatures were derived by backward, complete, and forward sequential feature selection using Support Vector Machines (SVM), and validated using k-fold or traditional validation on independent datasets. Results: The best human signatures we derived exhibit k-fold validation accuracies of up to 98% ( DDB2 ,  PRKDC , TPP2 , PTPRE , and GADD45A ) when validated over 209 samples and traditional validation accuracies of up to 92% ( DDB2 ,  CD8A ,  TALDO1 ,  PCNA ,  EIF4G2 ,  LCN2 ,  CDKN1A ,  PRKCH ,  ENO1 ,  and PPM1D ) when validated over 85 samples. Some human signatures are specific enough to differentiate between chemotherapy and radiotherapy. Certain multi-class murine signatures have sufficient granularity in dose estimation to inform eligibility for cytokine therapy (assuming these signatures could be translated to humans). We compiled a list of the most frequently appearing genes in the top 20 human and mouse signatures. More frequently appearing genes among an ensemble of signatures may indicate greater impact of these genes on the performance of individual signatures. Several genes in the signatures we derived are present in previously proposed signatures. Conclusions: Gene signatures for ionizing radiation exposure derived by machine learning have low error rates in externally validated, independent datasets, and exhibit high specificity and granularity for dose estimation.

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

PubMed

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

2016-10-01

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

External validation of the Cairns Prediction Model (CPM) to predict conversion from laparoscopic to open cholecystectomy.

PubMed

Hu, Alan Shiun Yew; Donohue, Peter O'; Gunnarsson, Ronny K; de Costa, Alan

2018-03-14

Valid and user-friendly prediction models for conversion to open cholecystectomy allow for proper planning prior to surgery. The Cairns Prediction Model (CPM) has been in use clinically in the original study site for the past three years, but has not been tested at other sites. A retrospective, single-centred study collected ultrasonic measurements and clinical variables alongside with conversion status from consecutive patients who underwent laparoscopic cholecystectomy from 2013 to 2016 in The Townsville Hospital, North Queensland, Australia. An area under the curve (AUC) was calculated to externally validate of the CPM. Conversion was necessary in 43 (4.2%) out of 1035 patients. External validation showed an area under the curve of 0.87 (95% CI 0.82-0.93, p = 1.1 × 10 -14 ). In comparison with most previously published models, which have an AUC of approximately 0.80 or less, the CPM has the highest AUC of all published prediction models both for internal and external validation. Crown Copyright © 2018. Published by Elsevier Inc. All rights reserved.

Validating proposed migration equation and parameters' values as a tool to reproduce and predict 137Cs vertical migration activity in Spanish soils.

PubMed

Olondo, C; Legarda, F; Herranz, M; Idoeta, R

2017-04-01

This paper shows the procedure performed to validate the migration equation and the migration parameters' values presented in a previous paper (Legarda et al., 2011) regarding the migration of 137 Cs in Spanish mainland soils. In this paper, this model validation has been carried out checking experimentally obtained activity concentration values against those predicted by the model. This experimental data come from the measured vertical activity profiles of 8 new sampling points which are located in northern Spain. Before testing predicted values of the model, the uncertainty of those values has been assessed with the appropriate uncertainty analysis. Once establishing the uncertainty of the model, both activity concentration values, experimental versus model predicted ones, have been compared. Model validation has been performed analyzing its accuracy, studying it as a whole and also at different depth intervals. As a result, this model has been validated as a tool to predict 137 Cs behaviour in a Mediterranean environment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Can the absence of prejudice be more threatening than its presence? It depends on one's worldview.

PubMed

Townsend, Sarah S M; Major, Brenda; Sawyer, Pamela J; Mendes, Wendy Berry

2010-12-01

The present research used validated cardiovascular measures to examine threat reactions among members of stigmatized groups when interacting with members of nonstigmatized groups who were, or were not, prejudiced against their group. The authors hypothesized that people's beliefs about the fairness of the status system would moderate their experience of threat during intergroup interactions. The authors predicted that for members of stigmatized groups who believe the status system is fair, interacting with a prejudiced partner, compared with interacting with an unprejudiced partner, would disconfirm their worldview and result in greater threat. In contrast, the authors predicted that for members of stigmatized groups who believe the system is unfair, interacting with a prejudiced partner, compared with interacting with an unprejudiced partner, would confirm their worldview and result in less threat. The authors examined these predictions among Latinas interacting with a White female confederate (Study 1) and White females interacting with a White male confederate (Study 2). As predicted, people's beliefs about the fairness of the status system moderated their experiences of threat during intergroup interactions, indicated both by cardiovascular responses and nonverbal behavior. The specific pattern of the moderation differed across the 2 studies. PsycINFO Database Record (c) 2010 APA, all rights reserved.

Predicting Patient Advocacy Engagement: A Multiple Regression Analysis Using Data From Health Professionals in Acute-Care Hospitals.

PubMed

Jansson, Bruce S; Nyamathi, Adeline; Heidemann, Gretchen; Duan, Lei; Kaplan, Charles

2015-01-01

Although literature documents the need for hospital social workers, nurses, and medical residents to engage in patient advocacy, little information exists about what predicts the extent they do so. This study aims to identify predictors of health professionals' patient advocacy engagement with respect to a broad range of patients' problems. A cross-sectional research design was employed with a sample of 94 social workers, 97 nurses, and 104 medical residents recruited from eight hospitals in Los Angeles. Bivariate correlations explored whether seven scales (Patient Advocacy Eagerness, Ethical Commitment, Skills, Tangible Support, Organizational Receptivity, Belief Other Professionals Engage, and Belief the Hospital Empowers Patients) were associated with patient advocacy engagement, measured by the validated Patient Advocacy Engagement Scale. Regression analysis examined whether these scales, when controlling for sociodemographic and setting variables, predicted patient advocacy engagement. While all seven predictor scales were significantly associated with patient advocacy engagement in correlational analyses, only Eagerness, Skills, and Belief the Hospital Empowers Patients predicted patient advocacy engagement in regression analyses. Additionally, younger professionals engaged in higher levels of patient advocacy than older professionals, and social workers engaged in greater patient advocacy than nurses. Limitations and the utility of these findings for acute-care hospitals are discussed.

Determination and prediction of octanol-air partition coefficients for organophosphate flame retardants.

PubMed

Wang, Qingzhi; Zhao, Hongxia; Wang, Yan; Xie, Qing; Chen, Jingwen; Quan, Xie

2017-11-01

Organophosphate flame retardants (OPFRs) have attracted wide concerns due to their toxicities and ubiquitous occurrence in the environment. In this work, Octanol-air partition coefficient (K OA ) for 14 OPFRs including 4 halogenated alkyl-, 5 aryl- and 5 alkyl-OPFRs, were estimated as a function of temperature using a gas chromatographic retention time (GC-RT) method. Their log K OA-GC values and internal energies of phase transfer (Δ OA U/kJmol -1 ) ranged from 8.03 to 13.0 and from 69.7 to 149, respectively. Substitution pattern and molar volume (V M ) were found to be capable of influencing log K OA-GC values of OPFRs. The halogenated alkyl-OPFRs had higher log K OA-GC values than aryl- or alkyl-OPFRs. The bigger the molar volume was, the greater the log K OA-GC values increased. In addition, a predicted model of log K OA-GC versus different relative retention times (RRTs) was developed with a high cross-validated value (Q 2 (cum) ) of 0.951, indicating a good predictive ability and stability. Therefore, the log K OA-GC values of the remaining OPFRs can be predicted by using their RRTs on different GC columns. Copyright © 2017 Elsevier Inc. All rights reserved.

Predictive Validity Study of the APS Writing and Reading Tests [and] Validating Placement Rules for the APS Writing Test.

ERIC Educational Resources Information Center

College of the Canyons, Valencia, CA. Office of Institutional Development.

California's College of the Canyons has used the College Board Assessment and Placement Services (APS) test to assess students' abilities in basic and college English since spring 1993. These two reports summarize data from a May 1994 study of the predictive validity of the APS writing and reading tests and a June 1994 effort to validate the cut…

Optimal test selection for prediction uncertainty reduction

DOE PAGES

Mullins, Joshua; Mahadevan, Sankaran; Urbina, Angel

2016-12-02

Economic factors and experimental limitations often lead to sparse and/or imprecise data used for the calibration and validation of computational models. This paper addresses resource allocation for calibration and validation experiments, in order to maximize their effectiveness within given resource constraints. When observation data are used for model calibration, the quality of the inferred parameter descriptions is directly affected by the quality and quantity of the data. This paper characterizes parameter uncertainty within a probabilistic framework, which enables the uncertainty to be systematically reduced with additional data. The validation assessment is also uncertain in the presence of sparse and imprecisemore » data; therefore, this paper proposes an approach for quantifying the resulting validation uncertainty. Since calibration and validation uncertainty affect the prediction of interest, the proposed framework explores the decision of cost versus importance of data in terms of the impact on the prediction uncertainty. Often, calibration and validation tests may be performed for different input scenarios, and this paper shows how the calibration and validation results from different conditions may be integrated into the prediction. Then, a constrained discrete optimization formulation that selects the number of tests of each type (calibration or validation at given input conditions) is proposed. Furthermore, the proposed test selection methodology is demonstrated on a microelectromechanical system (MEMS) example.« less

Validity of Futrex-5000 for body composition determination.

PubMed

McLean, K P; Skinner, J S

1992-02-01

Underwater weighing (UWW), skinfolds (SKF), and the Futrex-5000 (FTX) were compared by using UWW as the criterion measure of body fat in 30 male and 31 female Caucasians. Estimates of body fat (% fat) were obtained using The Y's Way to Fitness SKF equations and the standard FTX technique with near-infrared interactance (NIR) measured at the biceps, plus six sites for men and five sites for women. SKF correlated significantly higher with UWW than did FTX with UWW for males (0.95 vs 0.80), females (0.88 vs 0.63), and the whole group (0.94 vs 0.81). Fewer subjects (52%) were within +/- 4% of the UWW value using FTX, compared with 87% with SKF. FTX overestimated body fat in lean subjects with less than 8% fat and underestimated it in subjects with greater than 30% fat. Measuring NIR at additional sites did not improve the predicted variance. Partial F-tests indicate that using body mass index, instead of height and weight, in the FTX equation improved body fat prediction for females. Biceps NIR predicted additional variance in body fat beyond height, weight, frame size, and activity level but little variance above that predicted by these four variables plus SKF (2% more in males and less than 1% in females). Thus, SKF give more information and more accurately predict body fat, especially at the extremes of the body fat continuum.

The prediction of resting energy expenditure in type 2 diabetes mellitus is improved by factoring for glycemia.

PubMed

Gougeon, R; Lamarche, M; Yale, J-F; Venuta, T

2002-12-01

Predictive equations have been reported to overestimate resting energy expenditure (REE) for obese persons. The presence of hyperglycemia results in elevated REE in obese persons with type 2 diabetes, and its effect on the validity of these equations is unknown. We tested whether (1) indicators of diabetes control were independent associates of REE in type 2 diabetes and (2) their inclusion would improve predictive equations. A cross-sectional study of 65 (25 men, 40 women) obese type 2 diabetic subjects. Variables measured were: REE by ventilated-hood indirect calorimetry, body composition by bioimpedance analysis, body circumferences, fasting plasma glucose (FPG) and hemoglobin A(1c). Data were analyzed using stepwise multiple linear regression. REE, corrected for weight, fat-free mass, age and gender, was significantly greater with FPG>10 mmol/l (P=0.017) and correlated with FPG (P=0.013) and hemoglobin A(1c) as percentage upper limit of normal (P=0.02). Weight was the main determinant of REE. Together with hip circumference and FPG, it explained 81% of the variation. FPG improved the predictability of the equation by >3%. With poor glycemic control, it can represent an increase in REE of up to 8%. Our data indicate that in a population of obese subjects with type 2 diabetes mellitus, REE is better predicted when fasting plasma glucose is included as a variable.

European-scale modeling of concentrations and distribution of polybrominated diphenyl ethers in the pentabromodiphenyl ether product.

PubMed

Prevedouros, K; Jones, K C; Sweetman, A J

2004-11-15

The results from a modeling exercise utilizing the European variant (EVn) BETR multimedia environmental fate model are presented for selected polybrominated diphenyl ethers (PBDEs) of the technical penta- (Pe-) bromodiphenyl ether (BDE) product. The objectives of this study were to test PeBDE emission estimates from the literature for Europe by investigating the consistency between model predictions and ambient measurements to address the ability of the model to predict spatial variability and differences between congeners. Concurrently sampled and analyzed passive sampling air data, together with soil and grass data, were used as key model validation tools. The model steady-state simulations gave generally good agreement with measured data for BDE-47 and -99 with greater discrepancies for heavier congeners (e.g., BDE-153). To predict future atmospheric concentration trends, the model was used in its fully dynamic mode over the period 1970--2010. It was predicted that atmospheric concentrations peaked around 1997, declining with an overall "disappearance" half-life of 4.8 years. Soil and grass levels were underestimated by the model; possible reasons for differences with measurement data are further explored. Finally, the importance of temporally and spatially resolved environmental data sets is highlighted, while improved quantification of degradation half-lives is essential to better understand and predict the behavior of BDE congeners in PeBDE.

Animal models of 'anxiety': where next?

PubMed

Rodgers, R J

1997-11-01

Numerous procedures have been developed to facilitate preclinical research on the behavioural pharmacology of anxiety and, as a result of this application, are often referred to as animal models of 'anxiety'. This is an unfortunate misnomer, not only because of the apparent inability of many tests to detect novel anxiolytics consistently, but also because the term implies that anxiety is a unitary emotion. Such difficulties have arisen largely as a consequence of test development strategies which, by emphasizing pharmacological (i.e. benzodiazepine) validation, have yielded models predictive of a specific type of anxiolytic activity. The present review argues that the refinement of existing tests as well as the development of new procedures requires urgent attention to the much neglected issue of behavioural validation. From an evolutionary perspective, normal human anxiety may be conceptualized as a repertoire of defence reactions tailored to meet different forms of threats, and disorders of anxiety as the inappropriate activation or exaggeration of these usually adaptive response patterns. In this context, consideration of the defensive reactions typically observed in our animal models reveals substantially greater commonality in the behavioural effects of benzodiazepine and 5-HT1A anxiolytics than would otherwise be apparent. Therefore, with the exception of the conventional plus-maze paradigm (discussed at some length), better correspondence is seen in tests involving unconditioned response to potential threat (e.g. social interaction, distress vocalizations and light/dark exploration) than in tests of conditioned fear reactions. Even within the latter grouping, however, greater commonality is seen in procedures based on reactions to proximal threat (e.g. freezing, startle, ultrasonic vocalizations, burying) than those involving reactions to distal threat (e.g. avoidance/flight). Significantly, very similar findings have been reported in tests specifically designed to study defensive reactions (e.g. rat and mouse defence test batteries) or which incorporate a more detailed knowledge of defence into established procedures (e.g. ethological plus-maze and defensive burying paradigms). Furthermore, recent evidence also suggests that drugs with proved clinical efficacy in panic attacks/panic disorder have reliably stronger effects on flight responses than other components of the defensive repertoire. It is concluded that a focus on defensive behaviour patterns improves test validity (predictive/face/construct), offers a more rational basis for test selection in drug development programmes, and provides a firmer theoretical framework for future methodological and therapeutic advance.

Criteria of validity for animal models of psychiatric disorders: focus on anxiety disorders and depression

PubMed Central

2011-01-01

Animal models of psychiatric disorders are usually discussed with regard to three criteria first elaborated by Willner; face, predictive and construct validity. Here, we draw the history of these concepts and then try to redraw and refine these criteria, using the framework of the diathesis model of depression that has been proposed by several authors. We thus propose a set of five major criteria (with sub-categories for some of them); homological validity (including species validity and strain validity), pathogenic validity (including ontopathogenic validity and triggering validity), mechanistic validity, face validity (including ethological and biomarker validity) and predictive validity (including induction and remission validity). Homological validity requires that an adequate species and strain be chosen: considering species validity, primates will be considered to have a higher score than drosophila, and considering strains, a high stress reactivity in a strain scores higher than a low stress reactivity in another strain. Pathological validity corresponds to the fact that, in order to shape pathological characteristics, the organism has been manipulated both during the developmental period (for example, maternal separation: ontopathogenic validity) and during adulthood (for example, stress: triggering validity). Mechanistic validity corresponds to the fact that the cognitive (for example, cognitive bias) or biological mechanisms (such as dysfunction of the hormonal stress axis regulation) underlying the disorder are identical in both humans and animals. Face validity corresponds to the observable behavioral (ethological validity) or biological (biomarker validity) outcomes: for example anhedonic behavior (ethological validity) or elevated corticosterone (biomarker validity). Finally, predictive validity corresponds to the identity of the relationship between the triggering factor and the outcome (induction validity) and between the effects of the treatments on the two organisms (remission validity). The relevance of this framework is then discussed regarding various animal models of depression. PMID:22738250

Taking the Next Step: Combining Incrementally Valid Indicators to Improve Recidivism Prediction

ERIC Educational Resources Information Center

Walters, Glenn D.

2011-01-01

The possibility of combining indicators to improve recidivism prediction was evaluated in a sample of released federal prisoners randomly divided into a derivation subsample (n = 550) and a cross-validation subsample (n = 551). Five incrementally valid indicators were selected from five domains: demographic (age), historical (prior convictions),…