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.

Statistical validation of predictive TRANSP simulations of baseline discharges in preparation for extrapolation to JET D-T

NASA Astrophysics Data System (ADS)

Kim, Hyun-Tae; Romanelli, M.; Yuan, X.; Kaye, S.; Sips, A. C. C.; Frassinetti, L.; Buchanan, J.; Contributors, JET

2017-06-01

This paper presents for the first time a statistical validation of predictive TRANSP simulations of plasma temperature using two transport models, GLF23 and TGLF, over a database of 80 baseline H-mode discharges in JET-ILW. While the accuracy of the predicted T e with TRANSP-GLF23 is affected by plasma collisionality, the dependency of predictions on collisionality is less significant when using TRANSP-TGLF, indicating that the latter model has a broader applicability across plasma regimes. TRANSP-TGLF also shows a good matching of predicted T i with experimental measurements allowing for a more accurate prediction of the neutron yields. The impact of input data and assumptions prescribed in the simulations are also investigated in this paper. The statistical validation and the assessment of uncertainty level in predictive TRANSP simulations for JET-ILW-DD will constitute the basis for the extrapolation to JET-ILW-DT experiments.

The Reliability and Validity of the Thoracolumbar Injury Classification System in Pediatric Spine Trauma.

PubMed

Savage, Jason W; Moore, Timothy A; Arnold, Paul M; Thakur, Nikhil; Hsu, Wellington K; Patel, Alpesh A; McCarthy, Kathryn; Schroeder, Gregory D; Vaccaro, Alexander R; Dimar, John R; Anderson, Paul A

2015-09-15

The thoracolumbar injury classification system (TLICS) was evaluated in 20 consecutive pediatric spine trauma cases. The purpose of this study was to determine the reliability and validity of the TLICS in pediatric spine trauma. The TLICS was developed to improve the categorization and management of thoracolumbar trauma. TLICS has been shown to have good reliability and validity in the adult population. The clinical and radiographical findings of 20 pediatric thoracolumbar fractures were prospectively presented to 20 surgeons with disparate levels of training and experience with spinal trauma. These injuries were consecutively scored using the TLICS. Cohen unweighted κ coefficients and Spearman rank order correlation values were calculated for the key parameters (injury morphology, status of posterior ligamentous complex, neurological status, TLICS total score, and proposed management) to assess the inter-rater reliabilities. Five surgeons scored the same cases 3 months later to assess the intra-rater reliability. The actual management of each case was then compared with the treatment recommended by the TLICS algorithm to assess validity. The inter-rater κ statistics of all subgroups (injury morphology, status of the posterior ligamentous complex, neurological status, TLICS total score, and proposed treatment) were within the range of moderate to substantial reproducibility (0.524-0.958). All subgroups had excellent intra-rater reliability (0.748-1.000). The various indices for validity were calculated (80.3% correct, 0.836 sensitivity, 0.785 specificity, 0.676 positive predictive value, 0.899 negative predictive value). Overall, TLICS demonstrated good validity. The TLICS has good reliability and validity when used in the pediatric population. The inter-rater reliability of predicting management and indices for validity are lower than those in adults with thoracolumbar fractures, which is likely due to differences in the way children are treated for certain types of injuries. TLICS can be used to reliably categorize thoracolumbar injuries in the pediatric population; however, modifications may be needed to better guide treatment in this specific patient population. 4.

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

PubMed

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

2010-02-01

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

Validation study of the SCREENIVF: an instrument to screen women or men on risk for emotional maladjustment before the start of a fertility treatment.

PubMed

Ockhuijsen, Henrietta D L; van Smeden, Maarten; van den Hoogen, Agnes; Boivin, Jacky

2017-06-01

To examine construct and criterion validity of the Dutch SCREENIVF among women and men undergoing a fertility treatment. A prospective longitudinal study nested in a randomized controlled trial. University hospital. Couples, 468 women and 383 men, undergoing an IVF/intracytoplasmic sperm injection (ICSI) treatment in a fertility clinic, completed the SCREENIVF. Construct and criteria validity of the SCREENIVF. The comparative fit index and root mean square error of approximation for women and men show a good fit of the factor model. Across time, the sensitivity for Hospital Anxiety and Depression Scale subscale in women ranged from 61%-98%, specificity 53%-65%, predictive value of a positive test (PVP) 13%-56%, predictive value of a negative test (PVN) 70%-99%. The sensitivity scores for men ranged from 38%-100%, specificity 71%-75%, PVP 9%-27%, PVN 92%-100%. A prediction model revealed that for women 68.7% of the variance in the Hospital Anxiety and Depression Scale on time 1 and 42.5% at time 2 and 38.9% at time 3 was explained by the predictors, the sum score scales of the SCREENIVF. For men, 58.1% of the variance in the Hospital Anxiety and Depression Scale on time 1 and 46.5% at time 2 and 37.3% at time 3 was explained by the predictors, the sum score scales of the SCREENIVF. The SCREENIVF has good construct validity but the concurrent validity is better than the predictive validity. SCREENIVF will be most effectively used in fertility clinics at the start of treatment and should not be used as a predictive tool. Copyright © 2017 American Society for Reproductive Medicine. All rights reserved.

Prediction of Outcome after Moderate and Severe Traumatic Brain Injury: External Validation of the IMPACT and CRASH Prognostic Models

PubMed Central

Roozenbeek, Bob; Lingsma, Hester F.; Lecky, Fiona E.; Lu, Juan; Weir, James; Butcher, Isabella; McHugh, Gillian S.; Murray, Gordon D.; Perel, Pablo; Maas, Andrew I.R.; Steyerberg, Ewout W.

2012-01-01

Objective The International Mission on Prognosis and Analysis of Clinical Trials (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models predict outcome after traumatic brain injury (TBI) but have not been compared in large datasets. The objective of this is study is to validate externally and compare the IMPACT and CRASH prognostic models for prediction of outcome after moderate or severe TBI. Design External validation study. Patients We considered 5 new datasets with a total of 9036 patients, comprising three randomized trials and two observational series, containing prospectively collected individual TBI patient data. Measurements Outcomes were mortality and unfavourable outcome, based on the Glasgow Outcome Score (GOS) at six months after injury. To assess performance, we studied the discrimination of the models (by AUCs), and calibration (by comparison of the mean observed to predicted outcomes and calibration slopes). Main Results The highest discrimination was found in the TARN trauma registry (AUCs between 0.83 and 0.87), and the lowest discrimination in the Pharmos trial (AUCs between 0.65 and 0.71). Although differences in predictor effects between development and validation populations were found (calibration slopes varying between 0.58 and 1.53), the differences in discrimination were largely explained by differences in case-mix in the validation studies. Calibration was good, the fraction of observed outcomes generally agreed well with the mean predicted outcome. No meaningful differences were noted in performance between the IMPACT and CRASH models. More complex models discriminated slightly better than simpler variants. Conclusions Since both the IMPACT and the CRASH prognostic models show good generalizability to more recent data, they are valid instruments to quantify prognosis in TBI. PMID:22511138

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.

Prediction of pelvic organ prolapse using an artificial neural network.

PubMed

Robinson, Christopher J; Swift, Steven; Johnson, Donna D; Almeida, Jonas S

2008-08-01

The objective of this investigation was to test the ability of a feedforward artificial neural network (ANN) to differentiate patients who have pelvic organ prolapse (POP) from those who retain good pelvic organ support. Following institutional review board approval, patients with POP (n = 87) and controls with good pelvic organ support (n = 368) were identified from the urogynecology research database. Historical and clinical information was extracted from the database. Data analysis included the training of a feedforward ANN, variable selection, and external validation of the model with an independent data set. Twenty variables were used. The median-performing ANN model used a median of 3 (quartile 1:3 to quartile 3:5) variables and achieved an area under the receiver operator curve of 0.90 (external, independent validation set). Ninety percent sensitivity and 83% specificity were obtained in the external validation by ANN classification. Feedforward ANN modeling is applicable to the identification and prediction of POP.

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.

Reliability and validity of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-30) in Saudi Arabia.

PubMed

Tadakamadla, Santosh Kumar; Quadri, Mir Faeq Ali; Pakpour, Amir H; Zailai, Abdulaziz M; Sayed, Mohammed E; Mashyakhy, Mohammed; Inamdar, Aadil S; Tadakamadla, Jyothi

2014-09-29

To evaluate the reliability and validity of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-30) in Saudi Arabia. A convenience sample of 200 subjects was approached, of which 177 agreed to participate giving a response rate of 88.5%. Rapid Estimate of Adult Literacy in Dentistry (REALD-99), was translated into Arabic to prepare the longer and shorter versions of Arabic Rapid Estimate of Adult Literacy in Dentistry (AREALD-99 and AREALD-30). Each participant was provided with AREALD-99 which also includes words from AREALD-30. A questionnaire containing socio-behavioral information and Arabic Oral Health Impact Profile (A-OHIP-14) was also administered. Reliability of the AREALD-30 was assessed by re-administering it to 20 subjects after two weeks. Convergent and predictive validity of AREALD-30 was evaluated by its correlations with AREALD-99 and self-perceived oral health status, dental visiting habits and A-OHIP-14 respectively. Discriminant validity was assessed in relation to the educational level while construct validity was evaluated by confirmatory factor analysis (CFA). Reliability of AREALD-30 was excellent with intraclass correlation coefficient of 0.99. It exhibited good convergent and discriminant validity but poor predictive validity. CFA showed presence of two factors and infit mean-square statistics for AREALD-30 were all within the desired range of 0.50 - 2.0 in Rasch analysis. AREALD-30 showed excellent reliability, good convergent and concurrent validity, but failed to predict the differences between the subjects categorized based on their oral health outcomes.

Development of an aerobic capacity prediction model from one-mile run/walk performance in adolescents aged 13-16 years.

PubMed

Burns, Ryan D; Hannon, James C; Brusseau, Timothy A; Eisenman, Patricia A; Shultz, Barry B; Saint-Maurice, Pedro F; Welk, Gregory J; Mahar, Matthew T

2016-01-01

A popular algorithm to predict VO2Peak from the one-mile run/walk test (1MRW) includes body mass index (BMI), which manifests practical issues in school settings. The purpose of this study was to develop an aerobic capacity model from 1MRW in adolescents independent of BMI. Cardiorespiratory endurance data were collected on 90 adolescents aged 13-16 years. The 1MRW was administered on an outside track and a laboratory VO2Peak test was conducted using a maximal treadmill protocol. Multiple linear regression was employed to develop the prediction model. Results yielded the following algorithm: VO2Peak = 7.34 × (1MRW speed in m s(-1)) + 0.23 × (age × sex) + 17.75. The New Model displayed a multiple correlation and prediction error of R = 0.81, standard error of the estimate = 4.78 ml kg(-1) · min(-1), with measured VO2Peak and good criterion-referenced (CR) agreement into FITNESSGRAM's Healthy Fitness Zone (Kappa = 0.62; percentage agreement = 84.4%; Φ = 0.62). The New Model was validated using k-fold cross-validation and showed homoscedastic residuals across the range of predicted scores. The omission of BMI did not compromise accuracy of the model. In conclusion, the New Model displayed good predictive accuracy and good CR agreement with measured VO2Peak in adolescents aged 13-16 years.

Journal Article: Infant Exposure to Dioxin-Like Compounds in Breast Milk

EPA Science Inventory

A simple, one-compartment, first-order pharmacokinetic model is used to predict the infant body burden of dioxin-like compounds that results from breast-feeding. Validation testing of the model showed a good match between predictions and measurements of dioxin toxic equivalents ...

Multi-gene genetic programming based predictive models for municipal solid waste gasification in a fluidized bed gasifier.

PubMed

Pandey, Daya Shankar; Pan, Indranil; Das, Saptarshi; Leahy, James J; Kwapinski, Witold

2015-03-01

A multi-gene genetic programming technique is proposed as a new method to predict syngas yield production and the lower heating value for municipal solid waste gasification in a fluidized bed gasifier. The study shows that the predicted outputs of the municipal solid waste gasification process are in good agreement with the experimental dataset and also generalise well to validation (untrained) data. Published experimental datasets are used for model training and validation purposes. The results show the effectiveness of the genetic programming technique for solving complex nonlinear regression problems. The multi-gene genetic programming are also compared with a single-gene genetic programming model to show the relative merits and demerits of the technique. This study demonstrates that the genetic programming based data-driven modelling strategy can be a good candidate for developing models for other types of fuels as well. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

Outcome prediction in home- and community-based brain injury rehabilitation using the Mayo-Portland Adaptability Inventory.

PubMed

Malec, James F; Parrot, Devan; Altman, Irwin M; Swick, Shannon

2015-01-01

The objective of the study was to develop statistical formulas to predict levels of community participation on discharge from post-hospital brain injury rehabilitation using retrospective data analysis. Data were collected from seven geographically distinct programmes in a home- and community-based brain injury rehabilitation provider network. Participants were 642 individuals with post-traumatic brain injury. Interventions consisted of home- and community-based brain injury rehabilitation. The main outcome measure was the Mayo-Portland Adaptability Inventory (MPAI-4) Participation Index. Linear discriminant models using admission MPAI-4 Participation Index score and log chronicity correctly predicted excellent (no to minimal participation limitations), very good (very mild participation limitations), good (mild participation limitations), and limited (significant participation limitations) outcome levels at discharge. Predicting broad outcome categories for post-hospital rehabilitation programmes based on admission assessment data appears feasible and valid. Equations to provide patients and families with probability statements on admission about expected levels of outcome are provided. It is unknown to what degree these prediction equations can be reliably applied and valid in other settings.

A validation study of a clinical prediction rule for screening asymptomatic chlamydia and gonorrhoea infections among heterosexuals in British Columbia.

PubMed

Falasinnu, Titilola; Gilbert, Mark; Gustafson, Paul; Shoveller, Jean

2016-02-01

One component of effective sexually transmitted infections (STIs) control is ensuring those at highest risk of STIs have access to clinical services because terminating transmission in this group will prevent most future cases. Here, we describe the results of a validation study of a clinical prediction rule for identifying individuals at increased risk for chlamydia and gonorrhoea infection derived in Vancouver, British Columbia (BC), against a population of asymptomatic patients attending sexual health clinics in other geographical settings in BC. We examined electronic records (2000-2012) from clinic visits at seven sexual health clinics in geographical locations outside Vancouver. The model's calibration and discrimination were examined by the area under the receiver operating characteristic curve (AUC) and the Hosmer-Lemeshow (H-L) statistic, respectively. We also examined the sensitivity and proportion of patients that would need to be screened at different cut-offs of the risk score. The prevalence of infection was 5.3% (n=10 425) in the geographical validation population. The prediction rule showed good performance in this population (AUC, 0.69; H-L p=0.26). Possible risk scores ranged from -2 to 27. We identified a risk score cut-off point of ≥8 that detected cases with a sensitivity of 86% by screening 63% of the geographical validation population. The prediction rule showed good generalisability in STI clinics outside of Vancouver with improved discriminative performance compared with temporal validation. The prediction rule has the potential for augmenting triaging services in STI clinics and enhancing targeted testing in population-based screening programmes. 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/

Nutrition screening tools: does one size fit all? A systematic review of screening tools for the hospital setting.

PubMed

van Bokhorst-de van der Schueren, Marian A E; Guaitoli, Patrícia Realino; Jansma, Elise P; de Vet, Henrica C W

2014-02-01

Numerous nutrition screening tools for the hospital setting have been developed. The aim of this systematic review is to study construct or criterion validity and predictive validity of nutrition screening tools for the general hospital setting. A systematic review of English, French, German, Spanish, Portuguese and Dutch articles identified via MEDLINE, Cinahl and EMBASE (from inception to the 2nd of February 2012). Additional studies were identified by checking reference lists of identified manuscripts. Search terms included key words for malnutrition, screening or assessment instruments, and terms for hospital setting and adults. Data were extracted independently by 2 authors. Only studies expressing the (construct, criterion or predictive) validity of a tool were included. 83 studies (32 screening tools) were identified: 42 studies on construct or criterion validity versus a reference method and 51 studies on predictive validity on outcome (i.e. length of stay, mortality or complications). None of the tools performed consistently well to establish the patients' nutritional status. For the elderly, MNA performed fair to good, for the adults MUST performed fair to good. SGA, NRS-2002 and MUST performed well in predicting outcome in approximately half of the studies reviewed in adults, but not in older patients. Not one single screening or assessment tool is capable of adequate nutrition screening as well as predicting poor nutrition related outcome. Development of new tools seems redundant and will most probably not lead to new insights. New studies comparing different tools within one patient population are required. Copyright © 2013 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

The Diagnostic Accuracy of the Berg Balance Scale in Predicting Falls.

PubMed

Park, Seong-Hi; Lee, Young-Shin

2017-11-01

This study aimed to evaluate the predictive validity of the Berg Balance Scale (BBS) as a screening tool for fall risks among those with varied levels of balance. A total of 21 studies reporting predictive validity of the BBS of fall risk were meta-analyzed. With regard to the overall predictive validity of the BBS, the pooled sensitivity and specificity were 0.72 and 0.73, respectively; the accuracy curve area was 0.84. The findings showed statistical heterogeneity among studies. Among the sub-groups, the age group of those younger than 65 years, those with neuromuscular disease, those with 2+ falls, and those with a cutoff point of 45 to 49 showed better sensitivity with statistically less heterogeneity. The empirical evidence indicates that the BBS is a suitable tool to screen for the risk of falls and shows good predictability when used with the appropriate criteria and applied to those with neuromuscular disease.

Validation of the 4P's Plus screen for substance use in pregnancy validation of the 4P's Plus.

PubMed

Chasnoff, I J; Wells, A M; McGourty, R F; Bailey, L K

2007-12-01

The purpose of this study is to validate the 4P's Plus screen for substance use in pregnancy. A total of 228 pregnant women enrolled in prenatal care underwent screening with the 4P's Plus and received a follow-up clinical assessment for substance use. Statistical analyses regarding reliability, sensitivity, specificity, and positive and negative predictive validity of the 4Ps Plus were conducted. The overall reliability for the five-item measure was 0.62. Seventy-four (32.5%) of the women had a positive screen. Sensitivity and specificity were very good, at 87 and 76%, respectively. Positive predictive validity was low (36%), but negative predictive validity was quite high (97%). Of the 31 women who had a positive clinical assessment, 45% were using less than 1 day per week. The 4P's Plus reliably and effectively screens pregnant women for risk of substance use, including those women typically missed by other perinatal screening methodologies.

The preliminary analysis of the reliability and validity of the Chinese Edition of the CSBS DP.

PubMed

Lin, Chu-Sui; Chang, Shu-Hui; Cheng, Shu-Fen; Chao, Pen-Chiang; Chiu, Chun-Hao

2015-03-01

This study marked a preliminary attempt to standardize the Chinese Edition of the Communication and Symbolic Behavior Scales Developmental Profile (Wetherby & Prizant, 2002; CSBS DP) to assist in the early identification of young children with special needs in Taiwan. The study was conducted among 171 infants and toddlers aged 1-2. It also included a follow-up study one year after the initial test. Three domestically developed standardized child development inventories were used to measure the concurrent validity and predictive validity. The Chinese Edition of the CSBS DP demonstrated overall good test-retest and inter-rater reliability. It also showed good concurrent and predictive validity. The current study yields preliminary evidence that the Chinese Edition of the CSBS DP could be a valuable assessment tool worthy of wider distribution. Future research should employ random sampling to establish a true national norm. Additionally, the follow-up study needs to include atypical groups and to expand to children aged 6-12 months to strengthen the applicability of the instrument in Taiwan. Copyright © 2014 Elsevier Ltd. All rights reserved.

A predictive scoring instrument for tuberculosis lost to follow-up outcome

PubMed Central

2012-01-01

Background Adherence to tuberculosis (TB) treatment is troublesome, due to long therapy duration, quick therapeutic response which allows the patient to disregard about the rest of their treatment and the lack of motivation on behalf of the patient for improved. The objective of this study was to develop and validate a scoring system to predict the probability of lost to follow-up outcome in TB patients as a way to identify patients suitable for directly observed treatments (DOT) and other interventions to improve adherence. Methods Two prospective cohorts, were used to develop and validate a logistic regression model. A scoring system was constructed, based on the coefficients of factors associated with a lost to follow-up outcome. The probability of lost to follow-up outcome associated with each score was calculated. Predictions in both cohorts were tested using receiver operating characteristic curves (ROC). Results The best model to predict lost to follow-up outcome included the following characteristics: immigration (1 point value), living alone (1 point) or in an institution (2 points), previous anti-TB treatment (2 points), poor patient understanding (2 points), intravenous drugs use (IDU) (4 points) or unknown IDU status (1 point). Scores of 0, 1, 2, 3, 4 and 5 points were associated with a lost to follow-up probability of 2,2% 5,4% 9,9%, 16,4%, 15%, and 28%, respectively. The ROC curve for the validation group demonstrated a good fit (AUC: 0,67 [95% CI; 0,65-0,70]). Conclusion This model has a good capacity to predict a lost to follow-up outcome. Its use could help TB Programs to determine which patients are good candidates for DOT and other strategies to improve TB treatment adherence. PMID:22938040

Rapid learning in practice: A lung cancer survival decision support system in routine patient care data

PubMed Central

Dekker, Andre; Vinod, Shalini; Holloway, Lois; Oberije, Cary; George, Armia; Goozee, Gary; Delaney, Geoff P.; Lambin, Philippe; Thwaites, David

2016-01-01

Background and purpose A rapid learning approach has been proposed to extract and apply knowledge from routine care data rather than solely relying on clinical trial evidence. To validate this in practice we deployed a previously developed decision support system (DSS) in a typical, busy clinic for non-small cell lung cancer (NSCLC) patients. Material and methods Gender, age, performance status, lung function, lymph node status, tumor volume and survival were extracted without review from clinical data sources for lung cancer patients. With these data the DSS was tested to predict overall survival. Results 3919 lung cancer patients were identified with 159 eligible for inclusion, due to ineligible histology or stage, non-radical dose, missing tumor volume or survival. The DSS successfully identified a good prognosis group and a medium/poor prognosis group (2 year OS 69% vs. 27/30%, p < 0.001). Stage was less discriminatory (2 year OS 47% for stage I–II vs. 36% for stage IIIA–IIIB, p = 0.12) with most good prognosis patients having higher stage disease. The DSS predicted a large absolute overall survival benefit (~40%) for a radical dose compared to a non-radical dose in patients with a good prognosis, while no survival benefit of radical radiotherapy was predicted for patients with a poor prognosis. Conclusions A rapid learning environment is possible with the quality of clinical data sufficient to validate a DSS. It uses patient and tumor features to identify prognostic groups in whom therapy can be individualized based on predicted outcomes. Especially the survival benefit of a radical versus non-radical dose predicted by the DSS for various prognostic groups has clinical relevance, but needs to be prospectively validated. PMID:25241994

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.

Validation of SAPS3 admission score and its customization for use in Korean intensive care unit patients: a prospective multicentre study.

PubMed

Lim, So Yeon; Koh, Shin Ok; Jeon, Kyeongman; Na, Sungwon; Lim, Chae-Man; Choi, Won-Il; Lee, Young-Joo; Kim, Seok Chan; Chon, Gyu Rak; Kim, Je Hyeong; Kim, Jae Yeol; Lim, Jaemin; Rhee, Chin Kook; Park, Sunghoon; Kim, Ho Cheol; Lee, Jin Hwa; Lee, Ji Hyun; Park, Jisook; Koh, Younsuck; Suh, Gee Young

2013-08-01

To externally validate the simplified acute physiology score 3 (SAPS3) and to customize it for use in Korean intensive care unit (ICU) patients. This is a prospective multicentre cohort study involving 22 ICUs from 15 centres throughout Korea. The study population comprised patients who were consecutively admitted to participating ICUs from 1 July 2010 to 31 January 2011. A total of 4617 patients were enrolled. ICU mortality was 14.3%, and hospital mortality was 20.6%. The patients were randomly assigned into one of two cohorts: a development (n = 2309) or validation (n = 2308) cohort. In the development cohort, the general SAPS3 had good discrimination (area under the receiver operating characteristics curve = 0.829), but poor calibration (Hosmer-Lemeshow goodness-of-fit test H = 123.06, P < 0.001, C = 118.45, P < 0.001). The Australasia SAPS3 did not improve calibration (H = 73.53, P < 0.001, C = 70.52, P < 0.001). Customization was achieved by altering the logit of the original SAPS3 equation. The new equation for Korean ICU patients was validated in the validation cohort, and demonstrated both good discrimination (area under the receiver operating characteristics curve = 0.835) and good calibration (H = 4.61, P = 0.799, C = 5.67, P = 0.684). General and regional Australasia SAPS3 admission scores showed poor calibration for use in Korean ICU patients, but the prognostic power of the SAPS3 was significantly improved by customization. Prediction models should be customized before being used to predict mortality in different regions of the world. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

Measuring motivation using the transtheoretical (stages of change) model: A follow-up study of people who failed an online hearing screening.

PubMed

Ingo, Elisabeth; Brännström, K Jonas; Andersson, Gerhard; Lunner, Thomas; Laplante-Lévesque, Ariane

2016-07-01

Acceptance and readiness to seek professional help have shown to be important factors for favourable audiological rehabilitation outcomes. Theories from health psychology such as the transtheoretical (stages-of-change) model could help understand behavioural change in people with hearing impairment. In recent studies, the University of Rhode Island change assessment (URICA) has been found to have good predictive validity. In a previous study, 224 Swedish adults who had failed an online hearing screening completed URICA and two other measures of stages of change. This follow-up aimed to: (1) determine prevalence of help-seeking at a hearing clinic and hearing aid uptake, and (2) explore the predictive validity of the stages of change measures by a follow-up on the 224 participants who had failed a hearing screening 18 months previously. A total of 122 people (54%) completed the follow-up online questionnaire, including the three measures and questions regarding experience with hearing help-seeking and hearing aid uptake. Since failing the online hearing screening, 61% of participants had sought help. A good predictive validity for a one-item measure of stages of change was reported. The Staging algorithm was the stages of change measure with the best ability to predict help-seeking 18 months later.

Prediction of fracture load and stiffness of the proximal femur by CT-based specimen specific finite element analysis: cadaveric validation study.

PubMed

Miura, Michiaki; Nakamura, Junichi; Matsuura, Yusuke; Wako, Yasushi; Suzuki, Takane; Hagiwara, Shigeo; Orita, Sumihisa; Inage, Kazuhide; Kawarai, Yuya; Sugano, Masahiko; Nawata, Kento; Ohtori, Seiji

2017-12-16

Finite element analysis (FEA) of the proximal femur has been previously validated with large mesh size, but these were insufficient to simulate the model with small implants in recent studies. This study aimed to validate the proximal femoral computed tomography (CT)-based specimen-specific FEA model with smaller mesh size using fresh frozen cadavers. Twenty proximal femora from 10 cadavers (mean age, 87.1 years) were examined. CT was performed on all specimens with a calibration phantom. Nonlinear FEA prediction with stance configuration was performed using Mechanical Finder (mesh,1.5 mm tetrahedral elements; shell thickness, 0.2 mm; Poisson's coefficient, 0.3), in comparison with mechanical testing. Force was applied at a fixed vertical displacement rate, and the magnitude of the applied load and displacement were continuously recorded. The fracture load and stiffness were calculated from force-displacement curve, and the correlation between mechanical testing and FEA prediction was examined. A pilot study with one femur revealed that the equations proposed by Keller for vertebra were the most reproducible for calculating Young's modulus and the yield stress of elements of the proximal femur. There was a good linear correlation between fracture loads of mechanical testing and FEA prediction (R 2 = 0.6187) and between the stiffness of mechanical testing and FEA prediction (R 2 = 0.5499). There was a good linear correlation between fracture load and stiffness (R 2 = 0.6345) in mechanical testing and an excellent correlation between these (R 2 = 0.9240) in FEA prediction. CT-based specimen-specific FEA model of the proximal femur with small element size was validated using fresh frozen cadavers. The equations proposed by Keller for vertebra were found to be the most reproducible for the proximal femur in elderly people.

Parametric convergence sensitivity and validation of a finite element model of the human lumbar spine.

PubMed

Ayturk, Ugur M; Puttlitz, Christian M

2011-08-01

The primary objective of this study was to generate a finite element model of the human lumbar spine (L1-L5), verify mesh convergence for each tissue constituent and perform an extensive validation using both kinematic/kinetic and stress/strain data. Mesh refinement was accomplished via convergence of strain energy density (SED) predictions for each spinal tissue. The converged model was validated based on range of motion, intradiscal pressure, facet force transmission, anterolateral cortical bone strain and anterior longitudinal ligament deformation predictions. Changes in mesh resolution had the biggest impact on SED predictions under axial rotation loading. Nonlinearity of the moment-rotation curves was accurately simulated and the model predictions on the aforementioned parameters were in good agreement with experimental data. The validated and converged model will be utilised to study the effects of degeneration on the lumbar spine biomechanics, as well as to investigate the mechanical underpinning of the contemporary treatment strategies.

Predictive validity of the Biomedical Admissions Test: an evaluation and case study.

PubMed

McManus, I C; Ferguson, Eamonn; Wakeford, Richard; Powis, David; James, David

2011-01-01

There has been an increase in the use of pre-admission selection tests for medicine. Such tests need to show good psychometric properties. Here, we use a paper by Emery and Bell [2009. The predictive validity of the Biomedical Admissions Test for pre-clinical examination performance. Med Educ 43:557-564] as a case study to evaluate and comment on the reporting of psychometric data in the field of medical student selection (and the comments apply to many papers in the field). We highlight pitfalls when reliability data are not presented, how simple zero-order associations can lead to inaccurate conclusions about the predictive validity of a test, and how biases need to be explored and reported. We show with BMAT that it is the knowledge part of the test which does all the predictive work. We show that without evidence of incremental validity it is difficult to assess the value of any selection tests for medicine.

The predictive validity of a situational judgement test, a clinical problem solving test and the core medical training selection methods for performance in specialty training .

PubMed

Patterson, Fiona; Lopes, Safiatu; Harding, Stephen; Vaux, Emma; Berkin, Liz; Black, David

2017-02-01

The aim of this study was to follow up a sample of physicians who began core medical training (CMT) in 2009. This paper examines the long-term validity of CMT and GP selection methods in predicting performance in the Membership of Royal College of Physicians (MRCP(UK)) examinations. We performed a longitudinal study, examining the extent to which the GP and CMT selection methods (T1) predict performance in the MRCP(UK) examinations (T2). A total of 2,569 applicants from 2008-09 who completed CMT and GP selection methods were included in the study. Looking at MRCP(UK) part 1, part 2 written and PACES scores, both CMT and GP selection methods show evidence of predictive validity for the outcome variables, and hierarchical regressions show the GP methods add significant value to the CMT selection process. CMT selection methods predict performance in important outcomes and have good evidence of validity; the GP methods may have an additional role alongside the CMT selection methods. © Royal College of Physicians 2017. All rights reserved.

Can Heterosexism Harm Organizations? Predicting the Perceived Organizational Citizenship Behaviors of Gay and Lesbian Employees

ERIC Educational Resources Information Center

Brenner, Bradley R.; Lyons, Heather Z.; Fassinger, Ruth E.

2010-01-01

An initial test and validation of a model predicting perceived organizational citizenship behaviors (OCBs) of lesbian and gay employees were conducted using structural equation modeling. The proposed structural model demonstrated acceptable goodness of ft and structural invariance across 2 samples (ns = 311 and 295), which suggested that…

External validation of a 5-year survival prediction model after elective abdominal aortic aneurysm repair.

PubMed

DeMartino, Randall R; Huang, Ying; Mandrekar, Jay; Goodney, Philip P; Oderich, Gustavo S; Kalra, Manju; Bower, Thomas C; Cronenwett, Jack L; Gloviczki, Peter

2018-01-01

The benefit of prophylactic repair of abdominal aortic aneurysms (AAAs) is based on the risk of rupture exceeding the risk of death from other comorbidities. The purpose of this study was to validate a 5-year survival prediction model for patients undergoing elective repair of asymptomatic AAA <6.5 cm to assist in optimal selection of patients. All patients undergoing elective repair for asymptomatic AAA <6.5 cm (open or endovascular) from 2002 to 2011 were identified from a single institutional database (validation group). We assessed the ability of a prior published Vascular Study Group of New England (VSGNE) model (derivation group) to predict survival in our cohort. The model was assessed for discrimination (concordance index), calibration (calibration slope and calibration in the large), and goodness of fit (score test). The VSGNE derivation group consisted of 2367 patients (70% endovascular). Major factors associated with survival in the derivation group were age, coronary disease, chronic obstructive pulmonary disease, renal function, and antiplatelet and statin medication use. Our validation group consisted of 1038 patients (59% endovascular). The validation group was slightly older (74 vs 72 years; P < .01) and had a higher proportion of men (76% vs 68%; P < .01). In addition, the derivation group had higher rates of advanced cardiac disease, chronic obstructive pulmonary disease, and baseline creatinine concentration (1.2 vs 1.1 mg/dL; P < .01). Despite slight differences in preoperative patient factors, 5-year survival was similar between validation and derivation groups (75% vs 77%; P = .33). The concordance index of the validation group was identical between derivation and validation groups at 0.659 (95% confidence interval, 0.63-0.69). Our validation calibration in the large value was 1.02 (P = .62, closer to 1 indicating better calibration), calibration slope of 0.84 (95% confidence interval, 0.71-0.97), and score test of P = .57 (>.05 indicating goodness of fit). Across different populations of patients, assessment of age and level of cardiac, pulmonary, and renal disease can accurately predict 5-year survival in patients with AAA <6.5 cm undergoing repair. This risk prediction model is a valid method to assess mortality risk in determining potential overall survival benefit from elective AAA repair. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

A prediction algorithm for first onset of major depression in the general population: development and validation.

PubMed

Wang, JianLi; Sareen, Jitender; Patten, Scott; Bolton, James; Schmitz, Norbert; Birney, Arden

2014-05-01

Prediction algorithms are useful for making clinical decisions and for population health planning. However, such prediction algorithms for first onset of major depression do not exist. The objective of this study was to develop and validate a prediction algorithm for first onset of major depression in the general population. Longitudinal study design with approximate 3-year follow-up. The study was based on data from a nationally representative sample of the US general population. A total of 28 059 individuals who participated in Waves 1 and 2 of the US National Epidemiologic Survey on Alcohol and Related Conditions and who had not had major depression at Wave 1 were included. The prediction algorithm was developed using logistic regression modelling in 21 813 participants from three census regions. The algorithm was validated in participants from the 4th census region (n=6246). Major depression occurred since Wave 1 of the National Epidemiologic Survey on Alcohol and Related Conditions, assessed by the Alcohol Use Disorder and Associated Disabilities Interview Schedule-diagnostic and statistical manual for mental disorders IV. A prediction algorithm containing 17 unique risk factors was developed. The algorithm had good discriminative power (C statistics=0.7538, 95% CI 0.7378 to 0.7699) and excellent calibration (F-adjusted test=1.00, p=0.448) with the weighted data. In the validation sample, the algorithm had a C statistic of 0.7259 and excellent calibration (Hosmer-Lemeshow χ(2)=3.41, p=0.906). The developed prediction algorithm has good discrimination and calibration capacity. It can be used by clinicians, mental health policy-makers and service planners and the general public to predict future risk of having major depression. The application of the algorithm may lead to increased personalisation of treatment, better clinical decisions and more optimal mental health service planning.

Coupled CFD/CSD Analysis of an Active-Twist Rotor in a Wind Tunnel with Experimental Validation

NASA Technical Reports Server (NTRS)

Massey, Steven J.; Kreshock, Andrew R.; Sekula, Martin K.

2015-01-01

An unsteady Reynolds averaged Navier-Stokes analysis loosely coupled with a comprehensive rotorcraft code is presented for a second-generation active-twist rotor. High fidelity Navier-Stokes results for three configurations: an isolated rotor, a rotor with fuselage, and a rotor with fuselage mounted in a wind tunnel, are compared to lifting-line theory based comprehensive rotorcraft code calculations and wind tunnel data. Results indicate that CFD/CSD predictions of flapwise bending moments are in good agreement with wind tunnel measurements for configurations with a fuselage, and that modeling the wind tunnel environment does not significantly enhance computed results. Actuated rotor results for the rotor with fuselage configuration are also validated for predictions of vibratory blade loads and fixed-system vibratory loads. Varying levels of agreement with wind tunnel measurements are observed for blade vibratory loads, depending on the load component (flap, lag, or torsion) and the harmonic being examined. Predicted trends in fixed-system vibratory loads are in good agreement with wind tunnel measurements.

Development and validation of a prediction model for functional decline in older medical inpatients.

PubMed

Takada, Toshihiko; Fukuma, Shingo; Yamamoto, Yosuke; Tsugihashi, Yukio; Nagano, Hiroyuki; Hayashi, Michio; Miyashita, Jun; Azuma, Teruhisa; Fukuhara, Shunichi

2018-05-17

To prevent functional decline in older inpatients, identification of high-risk patients is crucial. The aim of this study was to develop and validate a prediction model to assess the risk of functional decline in older medical inpatients. In this retrospective cohort study, patients ≥65 years admitted acutely to medical wards were included. The healthcare database of 246 acute care hospitals (n = 229,913) was used for derivation, and two acute care hospitals (n = 1767 and 5443, respectively) were used for validation. Data were collected using a national administrative claims and discharge database. Functional decline was defined as a decline of the Katz score at discharge compared with on admission. About 6% of patients in the derivation cohort and 9% and 2% in each validation cohort developed functional decline. A model with 7 items, age, body mass index, living in a nursing home, ambulance use, need for assistance in walking, dementia, and bedsore, was developed. On internal validation, it demonstrated a c-statistic of 0.77 (95% confidence interval (CI) = 0.767-0.771) and good fit on the calibration plot. On external validation, the c-statistics were 0.79 (95% CI = 0.77-0.81) and 0.75 (95% CI = 0.73-0.77) for each cohort, respectively. Calibration plots showed good fit in one cohort and overestimation in the other one. A prediction model for functional decline in older medical inpatients was derived and validated. It is expected that use of the model would lead to early identification of high-risk patients and introducing early intervention. Copyright © 2018 Elsevier B.V. All rights reserved.

Cross-cultural adaptation and psychometric evaluation of oral health impact profile among school teacher community

PubMed Central

Vyas, Shaleen; Nagarajappa, Sandesh; Dasar, Pralhad L.; Mishra, Prashant

2018-01-01

AIM: To translate OHIP-14 into Hindi and test its psychometric properties among school teacher community. METHODS: The OHIP-14 was translated to OHIP-14-H using WHO recommended translation protocol. During pre-testing, an expert panel assessed content validity of the questionnaire. Face validity was assessed on a sample of 10 individuals. The OHIP-14-H was administered on a random sample of 170 primary school teachers. Internal consistency and test-retest reliability were assessed using Cronbach's alpha and Intra-class correlation coefficient (ICC) respectively, with 2 weeks interval. Predictive validity was tested by comparing OHIP-14-H scores with clinical parameters. The concurrent validity was assessed using self-reported oral health and discriminant validity was ascertained through negative association with sociodemographic variables. RESULTS: The mean OHIP-14-H score was 9.57 (S.D = 4.58). ICC and Cronbach's alpha for OHIP-14-H was 0.96 and 0.92 respectively. Concurrent validity using binomial regression model indicated that good (OR = 0.56, 95% CI = 0.55 – 4.47) and moderate (OR = 0.25, 95% CI = 0.17 – 1.87) OHIP-14-H scores were negative but significant risk indicators of poor self reported oral health (P < 0.009). Significant predictive validity was observed between OHIP-14-H scores and clinical parameters (P < 0.000). CONCLUSION: Translated and culturally adapted OHIP-14-H indicates good reliability and validity among primary school teachers. PMID:29417064

A Quantitative Structure Activity Relationship for acute oral toxicity of pesticides on rats: Validation, domain of application and prediction.

PubMed

Hamadache, Mabrouk; Benkortbi, Othmane; Hanini, Salah; Amrane, Abdeltif; Khaouane, Latifa; Si Moussa, Cherif

2016-02-13

Quantitative Structure Activity Relationship (QSAR) models are expected to play an important role in the risk assessment of chemicals on humans and the environment. In this study, we developed a validated QSAR model to predict acute oral toxicity of 329 pesticides to rats because a few QSAR models have been devoted to predict the Lethal Dose 50 (LD50) of pesticides on rats. This QSAR model is based on 17 molecular descriptors, and is robust, externally predictive and characterized by a good applicability domain. The best results were obtained with a 17/9/1 Artificial Neural Network model trained with the Quasi Newton back propagation (BFGS) algorithm. The prediction accuracy for the external validation set was estimated by the Q(2)ext and the root mean square error (RMS) which are equal to 0.948 and 0.201, respectively. 98.6% of external validation set is correctly predicted and the present model proved to be superior to models previously published. Accordingly, the model developed in this study provides excellent predictions and can be used to predict the acute oral toxicity of pesticides, particularly for those that have not been tested as well as new pesticides. Copyright © 2015 Elsevier B.V. All rights reserved.

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.

Developing symptom-based predictive models of endometriosis as a clinical screening tool: results from a multicenter study

PubMed Central

Nnoaham, Kelechi E.; Hummelshoj, Lone; Kennedy, Stephen H.; Jenkinson, Crispin; Zondervan, Krina T.

2012-01-01

Objective To generate and validate symptom-based models to predict endometriosis among symptomatic women prior to undergoing their first laparoscopy. Design Prospective, observational, two-phase study, in which women completed a 25-item questionnaire prior to surgery. Setting Nineteen hospitals in 13 countries. Patient(s) Symptomatic women (n = 1,396) scheduled for laparoscopy without a previous surgical diagnosis of endometriosis. Intervention(s) None. Main Outcome Measure(s) Sensitivity and specificity of endometriosis diagnosis predicted by symptoms and patient characteristics from optimal models developed using multiple logistic regression analyses in one data set (phase I), and independently validated in a second data set (phase II) by receiver operating characteristic (ROC) curve analysis. Result(s) Three hundred sixty (46.7%) women in phase I and 364 (58.2%) in phase II were diagnosed with endometriosis at laparoscopy. Menstrual dyschezia (pain on opening bowels) and a history of benign ovarian cysts most strongly predicted both any and stage III and IV endometriosis in both phases. Prediction of any-stage endometriosis, although improved by ultrasound scan evidence of cyst/nodules, was relatively poor (area under the curve [AUC] = 68.3). Stage III and IV disease was predicted with good accuracy (AUC = 84.9, sensitivity of 82.3% and specificity 75.8% at an optimal cut-off of 0.24). Conclusion(s) Our symptom-based models predict any-stage endometriosis relatively poorly and stage III and IV disease with good accuracy. Predictive tools based on such models could help to prioritize women for surgical investigation in clinical practice and thus contribute to reducing time to diagnosis. We invite other researchers to validate the key models in additional populations. PMID:22657249

Validity and reliability of a questionnaire to assess social skills in traumatic brain injury: A preliminary study.

PubMed

Francis, Heather M; Osborne-Crowley, Katherine; McDonald, Skye

2017-01-01

To describe the reliability and validity of a new measure, the Social Skills Questionnaire for Traumatic Brain Injury (SSQ-TBI). Fifty-one adults with severe TBI completed the SSQ-TBI questionnaire. Scores were compared to informant- and self-report on questionnaires addressing frontal lobe mediated behaviour, as well as performance on an objective measure of social cognition and neuropsychological tasks, in order to provide evidence of concurrent, divergent and predictive validity. Internal consistency was excellent at α = 0.90. Convergent validity was good, with informant ratings on the SSQ-TBI significantly correlated with Neuropsychiatric Inventory Disinhibition sub-scales (r = 0.50-63), the Current Behaviour Scale (r = 0.39-0.48) and Frontal Systems Behaviour Scale (r = 0.60-0.83). However, no relationship was seen with an objective measure of social skills or neuropsychological tasks of disinhibition. There was a significant relationship with real-world psychosocial outcomes on the Sydney Psychosocial Reintegration Scale-2 (r = -0.38--0.69) Conclusions: This study provides preliminary findings of good internal consistency and convergent and predictive validity of a social skills questionnaire adapted to be appropriate for individuals with TBI. Further assessment of psychometric properties such as test-re-test reliability and factor structure is warranted.

Learned helplessness: validity and reliability of depressive-like states in mice.

PubMed

Chourbaji, S; Zacher, C; Sanchis-Segura, C; Dormann, C; Vollmayr, B; Gass, P

2005-12-01

The learned helplessness paradigm is a depression model in which animals are exposed to unpredictable and uncontrollable stress, e.g. electroshocks, and subsequently develop coping deficits for aversive but escapable situations (J.B. Overmier, M.E. Seligman, Effects of inescapable shock upon subsequent escape and avoidance responding, J. Comp. Physiol. Psychol. 63 (1967) 28-33 ). It represents a model with good similarity to the symptoms of depression, construct, and predictive validity in rats. Despite an increased need to investigate emotional, in particular depression-like behaviors in transgenic mice, so far only a few studies have been published using the learned helplessness paradigm. One reason may be the fact that-in contrast to rats (B. Vollmayr, F.A. Henn, Learned helplessness in the rat: improvements in validity and reliability, Brain Res. Brain Res. Protoc. 8 (2001) 1-7)--there is no generally accepted learned helplessness protocol available for mice. This prompted us to develop a reliable helplessness procedure in C57BL/6N mice, to exclude possible artifacts, and to establish a protocol, which yields a consistent fraction of helpless mice following the shock exposure. Furthermore, we validated this protocol pharmacologically using the tricyclic antidepressant imipramine. Here, we present a mouse model with good face and predictive validity that can be used for transgenic, behavioral, and pharmacological studies.

A Severe Sepsis Mortality Prediction Model and Score for Use with Administrative Data

PubMed Central

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

2016-01-01

Objective Administrative data is used for research, quality improvement, and health policy in severe sepsis. However, there is not a sepsis-specific tool applicable to administrative data with which to adjust for illness severity. Our objective was to develop, internally validate, and externally validate a severe sepsis mortality prediction model and associated mortality prediction score. Design Retrospective cohort study using 2012 administrative data from five US states. Three cohorts of patients with severe sepsis were created: 1) ICD-9-CM codes for severe sepsis/septic shock, 2) ‘Martin’ approach, and 3) ‘Angus’ approach. The model was developed and internally validated in ICD-9-CM cohort and externally validated in other cohorts. Integer point values for each predictor variable were generated to create a sepsis severity score. Setting Acute care, non-federal hospitals in NY, MD, FL, MI, and WA Subjects Patients in one of three severe sepsis cohorts: 1) explicitly coded (n=108,448), 2) Martin cohort (n=139,094), and 3) Angus cohort (n=523,637) Interventions None Measurements and Main Results Maximum likelihood estimation logistic regression to develop a predictive model for in-hospital mortality. Model calibration and discrimination assessed via Hosmer-Lemeshow goodness-of-fit (GOF) and C-statistics respectively. Primary cohort subset into risk deciles and observed versus predicted mortality plotted. GOF demonstrated p>0.05 for each cohort demonstrating sound calibration. C-statistic ranged from low of 0.709 (sepsis severity score) to high of 0.838 (Angus cohort) suggesting good to excellent model discrimination. Comparison of observed versus expected mortality was robust although accuracy decreased in highest risk decile. Conclusions Our sepsis severity model and score is a tool that provides reliable risk adjustment for administrative data. PMID:26496452

Further Validation of the Learning Alliance Inventory: The Roles of Working Alliance, Rapport, and Immediacy in Student Learning

ERIC Educational Resources Information Center

Rogers, Daniel T.

2015-01-01

This study further examined the reliability and validity of the Learning Alliance Inventory (LAI), a self-report measure designed to assess the working alliance between a student and a teacher. The LAI was found to have good internal consistency and test--retest reliability, and it demonstrated the predicted convergence with measures of immediacy…

Numerical simulation of cavitating flows in shipbuilding

NASA Astrophysics Data System (ADS)

Bagaev, D.; Yegorov, S.; Lobachev, M.; Rudnichenko, A.; Taranov, A.

2018-05-01

The paper presents validation of numerical simulations of cavitating flows around different marine objects carried out at the Krylov State Research Centre (KSRC). Preliminary validation was done with reference to international test objects. The main part of the paper contains results of solving practical problems of ship propulsion design. The validation of numerical simulations by comparison with experimental data shows a good accuracy of the supercomputer technologies existing at Krylov State Research Centre for both hydrodynamic and cavitation characteristics prediction.

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.

Prognostic models for complete recovery in ischemic stroke: a systematic review and meta-analysis.

PubMed

Jampathong, Nampet; Laopaiboon, Malinee; Rattanakanokchai, Siwanon; Pattanittum, Porjai

2018-03-09

Prognostic models have been increasingly developed to predict complete recovery in ischemic stroke. However, questions arise about the performance characteristics of these models. The aim of this study was to systematically review and synthesize performance of existing prognostic models for complete recovery in ischemic stroke. We searched journal publications indexed in PUBMED, SCOPUS, CENTRAL, ISI Web of Science and OVID MEDLINE from inception until 4 December, 2017, for studies designed to develop and/or validate prognostic models for predicting complete recovery in ischemic stroke patients. Two reviewers independently examined titles and abstracts, and assessed whether each study met the pre-defined inclusion criteria and also independently extracted information about model development and performance. We evaluated validation of the models by medians of the area under the receiver operating characteristic curve (AUC) or c-statistic and calibration performance. We used a random-effects meta-analysis to pool AUC values. We included 10 studies with 23 models developed from elderly patients with a moderately severe ischemic stroke, mainly in three high income countries. Sample sizes for each study ranged from 75 to 4441. Logistic regression was the only analytical strategy used to develop the models. The number of various predictors varied from one to 11. Internal validation was performed in 12 models with a median AUC of 0.80 (95% CI 0.73 to 0.84). One model reported good calibration. Nine models reported external validation with a median AUC of 0.80 (95% CI 0.76 to 0.82). Four models showed good discrimination and calibration on external validation. The pooled AUC of the two validation models of the same developed model was 0.78 (95% CI 0.71 to 0.85). The performance of the 23 models found in the systematic review varied from fair to good in terms of internal and external validation. Further models should be developed with internal and external validation in low and middle income countries.

A valid model for predicting responsible nerve roots in lumbar degenerative disease with diagnostic doubt.

PubMed

Li, Xiaochuan; Bai, Xuedong; Wu, Yaohong; Ruan, Dike

2016-03-15

To construct and validate a model to predict responsible nerve roots in lumbar degenerative disease with diagnostic doubt (DD). From January 2009-January 2013, 163 patients with DD were assigned to the construction (n = 106) or validation sample (n = 57) according to different admission times to hospital. Outcome was assessed according to the Japanese Orthopedic Association (JOA) recovery rate as excellent, good, fair, and poor. The first two results were considered as effective clinical outcome (ECO). Baseline patient and clinical characteristics were considered as secondary variables. A multivariate logistic regression model was used to construct a model with the ECO as a dependent variable and other factors as explanatory variables. The odds ratios (ORs) of each risk factor were adjusted and transformed into a scoring system. Area under the curve (AUC) was calculated and validated in both internal and external samples. Moreover, calibration plot and predictive ability of this scoring system were also tested for further validation. Patients with DD with ECOs in both construction and validation models were around 76 % (76.4 and 75.5 % respectively). more preoperative visual analog pain scale (VAS) score (OR = 1.56, p < 0.01), stenosis levels of L4/5 or L5/S1 (OR = 1.44, p = 0.04), stenosis locations with neuroforamen (OR = 1.95, p = 0.01), neurological deficit (OR = 1.62, p = 0.01), and more VAS improvement of selective nerve route block (SNRB) (OR = 3.42, p = 0.02). the internal area under the curve (AUC) was 0.85, and the external AUC was 0.72, with a good calibration plot of prediction accuracy. Besides, the predictive ability of ECOs was not different from the actual results (p = 0.532). We have constructed and validated a predictive model for confirming responsible nerve roots in patients with DD. The associated risk factors were preoperative VAS score, stenosis levels of L4/5 or L5/S1, stenosis locations with neuroforamen, neurological deficit, and VAS improvement of SNRB. A tool such as this is beneficial in the preoperative counseling of patients, shared surgical decision making, and ultimately improving safety in spine surgery.

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.

Using the Johns Hopkins' Aggregated Diagnosis Groups (ADGs) to predict 1-year mortality in population-based cohorts of patients with diabetes in Ontario, Canada.

PubMed

Austin, P C; Shah, B R; Newman, A; Anderson, G M

2012-09-01

There are limited validated methods to ascertain comorbidities for risk adjustment in ambulatory populations of patients with diabetes using administrative health-care databases. The objective was to examine the ability of the Johns Hopkins' Aggregated Diagnosis Groups to predict mortality in population-based ambulatory samples of both incident and prevalent subjects with diabetes. Retrospective cohorts constructed using population-based administrative data. The incident cohort consisted of all 346,297 subjects diagnosed with diabetes between 1 April 2004 and 31 March 2008. The prevalent cohort consisted of all 879,849 subjects with pre-existing diabetes on 1 January, 2007. The outcome was death within 1 year of the subject's index date. A logistic regression model consisting of age, sex and indicator variables for 22 of the 32 Johns Hopkins' Aggregated Diagnosis Group categories had excellent discrimination for predicting mortality in incident diabetes patients: the c-statistic was 0.87 in an independent validation sample. A similar model had excellent discrimination for predicting mortality in prevalent diabetes patients: the c-statistic was 0.84 in an independent validation sample. Both models demonstrated very good calibration, denoting good agreement between observed and predicted mortality across the range of predicted mortality in which the large majority of subjects lay. For comparative purposes, regression models incorporating the Charlson comorbidity index, age and sex, age and sex, and age alone had poorer discrimination than the model that incorporated the Johns Hopkins' Aggregated Diagnosis Groups. Logistical regression models using age, sex and the John Hopkins' Aggregated Diagnosis Groups were able to accurately predict 1-year mortality in population-based samples of patients with diabetes. © 2011 The Authors. Diabetic Medicine © 2011 Diabetes UK.

Predicting the 10-Year Risks of Atherosclerotic Cardiovascular Disease in Chinese Population: The China-PAR Project (Prediction for ASCVD Risk in China).

PubMed

Yang, Xueli; Li, Jianxin; Hu, Dongsheng; Chen, Jichun; Li, Ying; Huang, Jianfeng; Liu, Xiaoqing; Liu, Fangchao; Cao, Jie; Shen, Chong; Yu, Ling; Lu, Fanghong; Wu, Xianping; Zhao, Liancheng; Wu, Xigui; Gu, Dongfeng

2016-11-08

The accurate assessment of individual risk can be of great value to guiding and facilitating the prevention of atherosclerotic cardiovascular disease (ASCVD). However, prediction models in common use were formulated primarily in white populations. The China-PAR project (Prediction for ASCVD Risk in China) is aimed at developing and validating 10-year risk prediction equations for ASCVD from 4 contemporary Chinese cohorts. Two prospective studies followed up together with a unified protocol were used as the derivation cohort to develop 10-year ASCVD risk equations in 21 320 Chinese participants. The external validation was evaluated in 2 independent Chinese cohorts with 14 123 and 70 838 participants. Furthermore, model performance was compared with the Pooled Cohort Equations reported in the American College of Cardiology/American Heart Association guideline. Over 12 years of follow-up in the derivation cohort with 21 320 Chinese participants, 1048 subjects developed a first ASCVD event. Sex-specific equations had C statistics of 0.794 (95% confidence interval, 0.775-0.814) for men and 0.811 (95% confidence interval, 0.787-0.835) for women. The predicted rates were similar to the observed rates, as indicated by a calibration χ 2 of 13.1 for men (P=0.16) and 12.8 for women (P=0.17). Good internal and external validations of our equations were achieved in subsequent analyses. Compared with the Chinese equations, the Pooled Cohort Equations had lower C statistics and much higher calibration χ 2 values in men. Our project developed effective tools with good performance for 10-year ASCVD risk prediction among a Chinese population that will help to improve the primary prevention and management of cardiovascular disease. © 2016 American Heart Association, Inc.

External validation and comparison of two nomograms predicting the probability of Gleason sum upgrading between biopsy and radical prostatectomy pathology in two patient populations: a retrospective cohort study.

PubMed

Utsumi, Takanobu; Oka, Ryo; Endo, Takumi; Yano, Masashi; Kamijima, Shuichi; Kamiya, Naoto; Fujimura, Masaaki; Sekita, Nobuyuki; Mikami, Kazuo; Hiruta, Nobuyuki; Suzuki, Hiroyoshi

2015-11-01

The aim of this study is to validate and compare the predictive accuracy of two nomograms predicting the probability of Gleason sum upgrading between biopsy and radical prostatectomy pathology among representative patients with prostate cancer. We previously developed a nomogram, as did Chun et al. In this validation study, patients originated from two centers: Toho University Sakura Medical Center (n = 214) and Chibaken Saiseikai Narashino Hospital (n = 216). We assessed predictive accuracy using area under the curve values and constructed calibration plots to grasp the tendency for each institution. Both nomograms showed a high predictive accuracy in each institution, although the constructed calibration plots of the two nomograms underestimated the actual probability in Toho University Sakura Medical Center. Clinicians need to use calibration plots for each institution to correctly understand the tendency of each nomogram for their patients, even if each nomogram has a good predictive accuracy. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predictive validity of a selection centre testing non-technical skills for recruitment to training in anaesthesia.

PubMed

Gale, T C E; Roberts, M J; Sice, P J; Langton, J A; Patterson, F C; Carr, A S; Anderson, I R; Lam, W H; Davies, P R F

2010-11-01

Assessment centres are an accepted method of recruitment in industry and are gaining popularity within medicine. We describe the development and validation of a selection centre for recruitment to speciality training in anaesthesia based on an assessment centre model incorporating the rating of candidate's non-technical skills. Expert consensus identified non-technical skills suitable for assessment at the point of selection. Four stations-structured interview, portfolio review, presentation, and simulation-were developed, the latter two being realistic scenarios of work-related tasks. Evaluation of the selection centre focused on applicant and assessor feedback ratings, inter-rater agreement, and internal consistency reliability coefficients. Predictive validity was sought via correlations of selection centre scores with subsequent workplace-based ratings of appointed trainees. Two hundred and twenty-four candidates were assessed over two consecutive annual recruitment rounds; 68 were appointed and followed up during training. Candidates and assessors demonstrated strong approval of the selection centre with more than 70% of ratings 'good' or 'excellent'. Mean inter-rater agreement coefficients ranged from 0.62 to 0.77 and internal consistency reliability of the selection centre score was high (Cronbach's α=0.88-0.91). The overall selection centre score was a good predictor of workplace performance during the first year of appointment. An assessment centre model based on the rating of non-technical skills can produce a reliable and valid selection tool for recruitment to speciality training in anaesthesia. Early results on predictive validity are encouraging and justify further development and evaluation.

Endoscopic third ventriculostomy in the treatment of childhood hydrocephalus.

PubMed

Kulkarni, Abhaya V; Drake, James M; Mallucci, Conor L; Sgouros, Spyros; Roth, Jonathan; Constantini, Shlomi

2009-08-01

To develop a model to predict the probability of endoscopic third ventriculostomy (ETV) success in the treatment for hydrocephalus on the basis of a child's individual characteristics. We analyzed 618 ETVs performed consecutively on children at 12 international institutions to identify predictors of ETV success at 6 months. A multivariable logistic regression model was developed on 70% of the dataset (training set) and validated on 30% of the dataset (validation set). In the training set, 305/455 ETVs (67.0%) were successful. The regression model (containing patient age, cause of hydrocephalus, and previous cerebrospinal fluid shunt) demonstrated good fit (Hosmer-Lemeshow, P = .78) and discrimination (C statistic = 0.70). In the validation set, 105/163 ETVs (64.4%) were successful and the model maintained good fit (Hosmer-Lemeshow, P = .45), discrimination (C statistic = 0.68), and calibration (calibration slope = 0.88). A simplified ETV Success Score was devised that closely approximates the predicted probability of ETV success. Children most likely to succeed with ETV can now be accurately identified and spared the long-term complications of CSF shunting.

The Smoking Consequences Questionnaire: Factor structure and predictive validity among Spanish-speaking Latino smokers in the United States.

PubMed

Vidrine, Jennifer Irvin; Vidrine, Damon J; Costello, Tracy J; Mazas, Carlos; Cofta-Woerpel, Ludmila; Mejia, Luz Maria; Wetter, David W

2009-11-01

Much of the existing research on smoking outcome expectancies has been guided by the Smoking Consequences Questionnaire (SCQ ). Although the original version of the SCQ has been modified over time for use in different populations, none of the existing versions have been evaluated for use among Spanish-speaking Latino smokers in the United States. The present study evaluated the factor structure and predictive validity of the 3 previously validated versions of the SCQ--the original, the SCQ-Adult, and the SCQ-Spanish, which was developed with Spanish-speaking smokers in Spain--among Spanish-speaking Latino smokers in Texas. The SCQ-Spanish represented the least complex solution. Each of the SCQ-Spanish scales had good internal consistency, and the predictive validity of the SCQ-Spanish was partially supported. Nearly all the SCQ-Spanish scales predicted withdrawal severity even after controlling for demographics and dependence. Boredom Reduction predicted smoking relapse across the 5- and 12-week follow-up assessments in a multivariate model that also controlled for demographics and dependence. Our results support use of the SCQ-Spanish with Spanish-speaking Latino smokers in the United States.

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.

The Structured Assessment of Violence Risk in Adults with Intellectual Disability: A Systematic Review.

PubMed

Hounsome, J; Whittington, R; Brown, A; Greenhill, B; McGuire, J

2018-01-01

While structured professional judgement approaches to assessing and managing the risk of violence have been extensively examined in mental health/forensic settings, the application of the findings to people with an intellectual disability is less extensively researched and reviewed. This review aimed to assess whether risk assessment tools have adequate predictive validity for violence in adults with an intellectual disability. Standard systematic review methodology was used to identify and synthesize appropriate studies. A total of 14 studies were identified as meeting the inclusion criteria. These studies assessed the predictive validity of 18 different risk assessment tools, mainly in forensic settings. All studies concluded that the tools assessed were successful in predicting violence. Studies were generally of a high quality. There is good quality evidence that risk assessment tools are valid for people with intellectual disability who offend but further research is required to validate tools for use with people with intellectual disability who offend. © 2016 John Wiley & Sons Ltd.

A diagnostic model for studying daytime urban air quality trends

NASA Technical Reports Server (NTRS)

Brewer, D. A.; Remsberg, E. E.; Woodbury, G. E.

1981-01-01

A single cell Eulerian photochemical air quality simulation model was developed and validated for selected days of the 1976 St. Louis Regional Air Pollution Study (RAPS) data sets; parameterizations of variables in the model and validation studies using the model are discussed. Good agreement was obtained between measured and modeled concentrations of NO, CO, and NO2 for all days simulated. The maximum concentration of O3 was also predicted well. Predicted species concentrations were relatively insensitive to small variations in CO and NOx emissions and to the concentrations of species which are entrained as the mixed layer rises.

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

PubMed

Stræde, Mia; Brabrand, Mikkel

2014-01-01

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

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

PubMed

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

2018-01-01

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

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.

Predicting outcome of status epilepticus.

PubMed

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

2015-08-01

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

Development and validation of a predictive score for perioperative transfusion in patients with hepatocellular carcinoma undergoing liver resection.

PubMed

Wang, Hai-Qing; Yang, Jian; Yang, Jia-Yin; Wang, Wen-Tao; Yan, Lu-Nan

2015-08-01

Liver resection is a major surgery requiring perioperative blood transfusion. Predicting the need for blood transfusion for patients undergoing liver resection is of great importance. The present study aimed to develop and validate a model for predicting transfusion requirement in HBV-related hepatocellular carcinoma patients undergoing liver resection. A total of 1543 consecutive liver resections were included in the study. Randomly selected sample set of 1080 cases (70% of the study cohort) were used to develop a predictive score for transfusion requirement and the remaining 30% (n=463) was used to validate the score. Based on the preoperative and predictable intraoperative parameters, logistic regression was used to identify risk factors and to create an integer score for the prediction of transfusion requirement. Extrahepatic procedure, major liver resection, hemoglobin level and platelets count were identified as independent predictors for transfusion requirement by logistic regression analysis. A score system integrating these 4 factors was stratified into three groups which could predict the risk of transfusion, with a rate of 11.4%, 24.7% and 57.4% for low, moderate and high risk, respectively. The prediction model appeared accurate with good discriminatory abilities, generating an area under the receiver operating characteristic curve of 0.736 in the development set and 0.709 in the validation set. We have developed and validated an integer-based risk score to predict perioperative transfusion for patients undergoing liver resection in a high-volume surgical center. This score allows identifying patients at a high risk and may alter transfusion practices.

Predicting stress urinary incontinence during pregnancy: combination of pelvic floor ultrasound parameters and clinical factors.

PubMed

Chen, Ling; Luo, Dan; Yu, Xiajuan; Jin, Mei; Cai, Wenzhi

2018-05-12

The aim of this study was to develop and validate a predictive tool that combining pelvic floor ultrasound parameters and clinical factors for stress urinary incontinence during pregnancy. A total of 535 women in first or second trimester were included for an interview and transperineal ultrasound assessment from two hospitals. Imaging data sets were analyzed offline to assess for bladder neck vertical position, urethra angles (α, β, and γ angles), hiatal area and bladder neck funneling. All significant continuous variables at univariable analysis were analyzed by receiver-operating characteristics. Three multivariable logistic models were built on clinical factor, and combined with ultrasound parameters. The final predictive model with best performance and fewest variables was selected to establish a nomogram. Internal and external validation of the nomogram were performed by both discrimination represented by C-index and calibration measured by Hosmer-Lemeshow test. A decision curve analysis was conducted to determine the clinical utility of the nomogram. After excluding 14 women with invalid data, 521 women were analyzed. β angle, γ angle and hiatal area had limited predictive value for stress urinary incontinence during pregnancy, with area under curves of 0.558-0.648. The final predictive model included body mass index gain since pregnancy, constipation, previous delivery mode, β angle at rest, and bladder neck funneling. The nomogram based on the final model showed good discrimination with a C-index of 0.789 and satisfactory calibration (P=0.828), both of which were supported by external validation. Decision curve analysis showed that the nomogram was clinical useful. The nomogram incorporating both the pelvic floor ultrasound parameters and clinical factors has been validated to show good discrimination and calibration, and could be an important tool for stress urinary incontinence risk prediction at an early stage of pregnancy. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

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

Niemeyer, Kyle E.; Sung, Chih-Jen

Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, suchmore » as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.« less

Mechanism reduction for multicomponent surrogates: A case study using toluene reference fuels

DOE PAGES

Niemeyer, Kyle E.; Sung, Chih-Jen

2014-11-01

Strategies and recommendations for performing skeletal reductions of multicomponent surrogate fuels are presented, through the generation and validation of skeletal mechanisms for a three-component toluene reference fuel. Using the directed relation graph with error propagation and sensitivity analysis method followed by a further unimportant reaction elimination stage, skeletal mechanisms valid over comprehensive and high-temperature ranges of conditions were developed at varying levels of detail. These skeletal mechanisms were generated based on autoignition simulations, and validation using ignition delay predictions showed good agreement with the detailed mechanism in the target range of conditions. When validated using phenomena other than autoignition, suchmore » as perfectly stirred reactor and laminar flame propagation, tight error control or more restrictions on the reduction during the sensitivity analysis stage were needed to ensure good agreement. In addition, tight error limits were needed for close prediction of ignition delay when varying the mixture composition away from that used for the reduction. In homogeneous compression-ignition engine simulations, the skeletal mechanisms closely matched the point of ignition and accurately predicted species profiles for lean to stoichiometric conditions. Furthermore, the efficacy of generating a multicomponent skeletal mechanism was compared to combining skeletal mechanisms produced separately for neat fuel components; using the same error limits, the latter resulted in a larger skeletal mechanism size that also lacked important cross reactions between fuel components. Based on the present results, general guidelines for reducing detailed mechanisms for multicomponent fuels are discussed.« less

Web-based tool for dynamic functional outcome after acute ischemic stroke and comparison with existing models.

PubMed

Ji, Ruijun; Du, Wanliang; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Zhao, Xingquan; Wang, Yongjun

2014-11-25

Acute ischemic stroke (AIS) is one of the leading causes of death and adult disability worldwide. In the present study, we aimed to develop a web-based risk model for predicting dynamic functional status at discharge, 3-month, 6-month, and 1-year after acute ischemic stroke (Dynamic Functional Status after Acute Ischemic Stroke, DFS-AIS). The DFS-AIS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Good functional outcome was defined as modified Rankin Scale (mRS) score ≤ 2 at discharge, 3-month, 6-month, and 1-year after AIS, respectively. Independent predictors of each outcome measure were obtained using multivariable logistic regression. The area under the receiver operating characteristic curve (AUROC) and plot of observed and predicted risk were used to assess model discrimination and calibration. A total of 12,026 patients were included and the median age was 67 (interquartile range: 57-75). The proportion of patients with good functional outcome at discharge, 3-month, 6-month, and 1-year after AIS was 67.9%, 66.5%, 66.9% and 66.9%, respectively. Age, gender, medical history of diabetes mellitus, stroke or transient ischemic attack, current smoking and atrial fibrillation, pre-stroke dependence, pre-stroke statins using, admission National Institutes of Health Stroke Scale score, admission blood glucose were identified as independent predictors of functional outcome at different time points after AIS. The DFS-AIS was developed from sets of predictors of mRS ≤ 2 at different time points following AIS. The DFS-AIS demonstrated good discrimination in the derivation and validation cohorts (AUROC range: 0.837-0.845). Plots of observed versus predicted likelihood showed excellent calibration in the derivation and validation cohorts (all r = 0.99, P < 0.001). When compared to 8 existing models, the DFS-AIS showed significantly better discrimination for good functional outcome and mortality at discharge, 3-month, 6-month, and 1-year after AIS (all P < 0.0001). The DFS-AIS is a valid risk model to predict functional outcome at discharge, 3-month, 6-month, and 1-year after AIS.

Risk score to predict gastrointestinal bleeding after acute ischemic stroke.

PubMed

Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Singhal, Aneesh B; Wang, Yongjun

2014-07-25

Gastrointestinal bleeding (GIB) is a common and often serious complication after stroke. Although several risk factors for post-stroke GIB have been identified, no reliable or validated scoring system is currently available to predict GIB after acute stroke in routine clinical practice or clinical trials. In the present study, we aimed to develop and validate a risk model (acute ischemic stroke associated gastrointestinal bleeding score, the AIS-GIB score) to predict in-hospital GIB after acute ischemic stroke. The AIS-GIB score was developed from data in the China National Stroke Registry (CNSR). Eligible patients in the CNSR were randomly divided into derivation (60%) and internal validation (40%) cohorts. External validation was performed using data from the prospective Chinese Intracranial Atherosclerosis Study (CICAS). Independent predictors of in-hospital GIB were obtained using multivariable logistic regression in the derivation cohort, and β-coefficients were used to generate point scoring system for the AIS-GIB. The area under the receiver operating characteristic curve (AUROC) and the Hosmer-Lemeshow goodness-of-fit test were used to assess model discrimination and calibration, respectively. A total of 8,820, 5,882, and 2,938 patients were enrolled in the derivation, internal validation and external validation cohorts. The overall in-hospital GIB after AIS was 2.6%, 2.3%, and 1.5% in the derivation, internal, and external validation cohort, respectively. An 18-point AIS-GIB score was developed from the set of independent predictors of GIB including age, gender, history of hypertension, hepatic cirrhosis, peptic ulcer or previous GIB, pre-stroke dependence, admission National Institutes of Health stroke scale score, Glasgow Coma Scale score and stroke subtype (Oxfordshire). The AIS-GIB score showed good discrimination in the derivation (0.79; 95% CI, 0.764-0.825), internal (0.78; 95% CI, 0.74-0.82) and external (0.76; 95% CI, 0.71-0.82) validation cohorts. The AIS-GIB score was well calibrated in the derivation (P = 0.42), internal (P = 0.45) and external (P = 0.86) validation cohorts. The AIS-GIB score is a valid clinical grading scale to predict in-hospital GIB after AIS. Further studies on the effect of the AIS-GIB score on reducing GIB and improving outcome after AIS are warranted.

Incremental Validity of the Trait Emotional Intelligence Questionnaire-Short Form (TEIQue-SF).

PubMed

Siegling, A B; Vesely, Ashley K; Petrides, K V; Saklofske, Donald H

2015-01-01

This study examined the incremental validity of the adult short form of the Trait Emotional Intelligence Questionnaire (TEIQue-SF) in predicting 7 construct-relevant criteria beyond the variance explained by the Five-factor model and coping strategies. Additionally, the relative contributions of the questionnaire's 4 subscales were assessed. Two samples of Canadian university students completed the TEIQue-SF, along with measures of the Big Five, coping strategies (Sample 1 only), and emotion-laden criteria. The TEIQue-SF showed consistent incremental effects beyond the Big Five or the Big Five and coping strategies, predicting all 7 criteria examined across the 2 samples. Furthermore, 2 of the 4 TEIQue-SF subscales accounted for the measure's incremental validity. Although the findings provide good support for the validity and utility of the TEIQue-SF, directions for further research are emphasized.

Identifying patients with undetected colorectal cancer: an independent validation of QCancer (Colorectal).

PubMed

Collins, G S; Altman, D G

2012-07-10

Early identification of colorectal cancer is an unresolved challenge and the predictive value of single symptoms is limited. We evaluated the performance of QCancer (Colorectal) prediction model for predicting the absolute risk of colorectal cancer in an independent UK cohort of patients from general practice records. A total of 2.1 million patients registered with a general practice surgery between 01 January 2000 and 30 June 2008, aged 30-84 years (3.7 million person-years) with 3712 colorectal cancer cases were included in the analysis. Colorectal cancer was defined as incident diagnosis of colorectal cancer during the 2 years after study entry. The results from this independent and external validation of QCancer (Colorectal) prediction model demonstrated good performance data on a large cohort of general practice patients. QCancer (Colorectal) had very good discrimination with an area under the ROC curve of 0.92 (women) and 0.91 (men), and explained 68% (women) and 66% (men) of the variation. QCancer (Colorectal) was well calibrated across all tenths of risk and over all age ranges with predicted risks closely matching observed risks. QCancer (Colorectal) appears to be a useful tool for identifying undetected cases of undiagnosed colorectal cancer in primary care in the United Kingdom.

The diagnostic value of specific IgE to Ara h 2 to predict peanut allergy in children is comparable to a validated and updated diagnostic prediction model.

PubMed

Klemans, Rob J B; Otte, Dianne; Knol, Mirjam; Knol, Edward F; Meijer, Yolanda; Gmelig-Meyling, Frits H J; Bruijnzeel-Koomen, Carla A F M; Knulst, André C; Pasmans, Suzanne G M A

2013-01-01

A diagnostic prediction model for peanut allergy in children was recently published, using 6 predictors: sex, age, history, skin prick test, peanut specific immunoglobulin E (sIgE), and total IgE minus peanut sIgE. To validate this model and update it by adding allergic rhinitis, atopic dermatitis, and sIgE to peanut components Ara h 1, 2, 3, and 8 as candidate predictors. To develop a new model based only on sIgE to peanut components. Validation was performed by testing discrimination (diagnostic value) with an area under the receiver operating characteristic curve and calibration (agreement between predicted and observed frequencies of peanut allergy) with the Hosmer-Lemeshow test and a calibration plot. The performance of the (updated) models was similarly analyzed. Validation of the model in 100 patients showed good discrimination (88%) but poor calibration (P < .001). In the updating process, age, history, and additional candidate predictors did not significantly increase discrimination, being 94%, and leaving only 4 predictors of the original model: sex, skin prick test, peanut sIgE, and total IgE minus sIgE. When building a model with sIgE to peanut components, Ara h 2 was the only predictor, with a discriminative ability of 90%. Cutoff values with 100% positive and negative predictive values could be calculated for both the updated model and sIgE to Ara h 2. In this way, the outcome of the food challenge could be predicted with 100% accuracy in 59% (updated model) and 50% (Ara h 2) of the patients. Discrimination of the validated model was good; however, calibration was poor. The discriminative ability of Ara h 2 was almost comparable to that of the updated model, containing 4 predictors. With both models, the need for peanut challenges could be reduced by at least 50%. Copyright © 2012 American Academy of Allergy, Asthma & Immunology. Published by Mosby, Inc. All rights reserved.

Use of the color trails test as an embedded measure of performance validity.

PubMed

Henry, George K; Algina, James

2013-01-01

One hundred personal injury litigants and disability claimants referred for a forensic neuropsychological evaluation were administered both portions of the Color Trails Test (CTT) as part of a more comprehensive battery of standardized tests. Subjects who failed two or more free-standing tests of cognitive performance validity formed the Failed Performance Validity (FPV) group, while subjects who passed all free-standing performance validity measures were assigned to the Passed Performance Validity (PPV) group. A cutscore of ≥45 seconds to complete Color Trails 1 (CT1) was associated with a classification accuracy of 78%, good sensitivity (66%) and high specificity (90%), while a cutscore of ≥84 seconds to complete Color Trails 2 (CT2) was associated with a classification accuracy of 82%, good sensitivity (74%) and high specificity (90%). A CT1 cutscore of ≥58 seconds, and a CT2 cutscore ≥100 seconds was associated with 100% positive predictive power at base rates from 20 to 50%.

Development and validation of an attributional style questionnaire for adolescents.

PubMed

Rodríguez-Naranjo, Carmen; Caño, Antonio

2010-12-01

We describe the development and psychometric characteristics of a new version of the Attributional Style Questionnaire (ASQ; Seligman, Abramson, Semmell, & Von Baeyer, 1979)--a version called the Attributional Style Questionnaire for Adolescents (ASQ-A)--using 3 samples (Ns = 547, 438, and 240) of Spanish secondary school students. In Study 1, the initial pool of 87 items was reduced to 54. Study 2 further analyzed the 54 scale items and revealed that the Internality, Stability, and Globality subscale scores had good reliability, good factorial construct validity, and satisfactory associations with maladaptive mood ratings. In Study 3, the regression analyses showed good and specific predictive validities of ASQ-A subscales for the attributions that the adolescents made about a particular real-life stressful situation. Study 4 showed that over an 8-month period the changes in the Stability and Globality subscales depended on the intensity of stressful life events experienced in this period. Overall, the studies revealed that the new ASQ-A served as an appropriate instrument to assess attributional style in adolescents.

Novel CPR system that predicts return of spontaneous circulation from amplitude spectral area before electric shock in ventricular fibrillation.

PubMed

Nakagawa, Yoshihide; Amino, Mari; Inokuchi, Sadaki; Hayashi, Satoshi; Wakabayashi, Tsutomu; Noda, Tatsuya

2017-04-01

Amplitude spectral area (AMSA), an index for analysing ventricular fibrillation (VF) waveforms, is thought to predict the return of spontaneous circulation (ROSC) after electric shocks, but its validity is unconfirmed. We developed an equation to predict ROSC, where the change in AMSA (ΔAMSA) is added to AMSA measured immediately before the first shock (AMSA1). We examine the validity of this equation by comparing it with the conventional AMSA1-only equation. We retrospectively investigated 285 VF patients given prehospital electric shocks by emergency medical services. ΔAMSA was calculated by subtracting AMSA1 from last AMSA immediately before the last prehospital electric shock. Multivariate logistic regression analysis was performed using post-shock ROSC as a dependent variable. Analysis data were subjected to receiver operating characteristic curve analysis, goodness-of-fit testing using a likelihood ratio test, and the bootstrap method. AMSA1 (odds ratio (OR) 1.151, 95% confidence interval (CI) 1.086-1.220) and ΔAMSA (OR 1.289, 95% CI 1.156-1.438) were independent factors influencing ROSC induction by electric shock. Area under the curve (AUC) for predicting ROSC was 0.851 for AMSA1-only and 0.891 for AMSA1+ΔAMSA. Compared with the AMSA1-only equation, the AMSA1+ΔAMSA equation had significantly better goodness-of-fit (likelihood ratio test P<0.001) and showed good fit in the bootstrap method. Post-shock ROSC was accurately predicted by adding ΔAMSA to AMSA1. AMSA-based ROSC prediction enables application of electric shock to only those patients with high probability of ROSC, instead of interrupting chest compressions and delivering unnecessary shocks to patients with low probability of ROSC. Copyright © 2017 Elsevier B.V. All rights reserved.

The ACTA PORT-score for predicting perioperative risk of blood transfusion for adult cardiac surgery.

PubMed

Klein, A A; Collier, T; Yeates, J; Miles, L F; Fletcher, S N; Evans, C; Richards, T

2017-09-01

A simple and accurate scoring system to predict risk of transfusion for patients undergoing cardiac surgery is lacking. We identified independent risk factors associated with transfusion by performing univariate analysis, followed by logistic regression. We then simplified the score to an integer-based system and tested it using the area under the receiver operator characteristic (AUC) statistic with a Hosmer-Lemeshow goodness-of-fit test. Finally, the scoring system was applied to the external validation dataset and the same statistical methods applied to test the accuracy of the ACTA-PORT score. Several factors were independently associated with risk of transfusion, including age, sex, body surface area, logistic EuroSCORE, preoperative haemoglobin and creatinine, and type of surgery. In our primary dataset, the score accurately predicted risk of perioperative transfusion in cardiac surgery patients with an AUC of 0.76. The external validation confirmed accuracy of the scoring method with an AUC of 0.84 and good agreement across all scores, with a minor tendency to under-estimate transfusion risk in very high-risk patients. The ACTA-PORT score is a reliable, validated tool for predicting risk of transfusion for patients undergoing cardiac surgery. This and other scores can be used in research studies for risk adjustment when assessing outcomes, and might also be incorporated into a Patient Blood Management programme. © The Author 2017. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Validating a measure to assess factors that affect assistive technology use by students with disabilities in elementary and secondary education.

PubMed

Zapf, Susan A; Scherer, Marcia J; Baxter, Mary F; H Rintala, Diana

2016-01-01

The purpose of this study was to measure the predictive validity, internal consistency and clinical utility of the Matching Assistive Technology to Child & Augmentative Communication Evaluation Simplified (MATCH-ACES) assessment. Twenty-three assistive technology team evaluators assessed 35 children using the MATCH-ACES assessment. This quasi-experimental study examined the internal consistency, predictive validity and clinical utility of the MATCH-ACES assessment. The MATCH-ACES assessment predisposition scales had good internal consistency across all three scales. A significant relationship was found between (a) high student perseverance and need for assistive technology and (b) high teacher comfort and interest in technology use (p = (0).002). Study results indicate that the MATCH-ACES assessment has good internal consistency and validity. Predisposition characteristics of student and teacher combined can influence the level of assistive technology use; therefore, assistive technology teams should assess predisposition factors of the user when recommending assistive technology. Implications for Rehabilitation Educational and medical professionals should be educated on evidence-based assistive technology assessments. Personal experience and psychosocial factors can influence the outcome use of assistive technology. Assistive technology assessments must include an intervention plan for assistive technology service delivery to measure effective outcome use.

Three-dimensional water droplet trajectory code validation using an ECS inlet geometry

NASA Technical Reports Server (NTRS)

Breer, Marlin D.; Goodman, Mark P.

1993-01-01

A task was completed under NASA contract, the purpose of which was to validate a three-dimensional particle trajectory code with existing test data obtained from the Icing Research Tunnel at NASA-LeRC. The geometry analyzed was a flush-mounted environmental control system (ECS) inlet. Results of the study indicated good overall agreement between analytical predictions and wind tunnel test results at most flight conditions. Difficulties were encountered when predicting impingement characteristics of the droplets less than or equal to 13.5 microns in diameter. This difficulty was corrected to some degree by modifications to a module of the particle trajectory code; however, additional modifications will be required to accurately predict impingement characteristics of smaller droplets.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Validating a benchmarking tool for audit of early outcomes after operations for head and neck cancer.

PubMed

Tighe, D; Sassoon, I; McGurk, M

2017-04-01

INTRODUCTION In 2013 all UK surgical specialties, with the exception of head and neck surgery, published outcome data adjusted for case mix for indicator operations. This paper reports a pilot study to validate a previously published risk adjustment score on patients from separate UK cancer centres. METHODS A case note audit was performed of 1,075 patients undergoing 1,218 operations for head and neck squamous cell carcinoma under general anaesthesia in 4 surgical centres. A logistic regression equation predicting for all complications, previously validated internally at sites A-C, was tested on a fourth external validation sample (site D, 172 operations) using receiver operating characteristic curves, Hosmer-Lemeshow goodness of fit analysis and Brier scores. RESULTS Thirty-day complication rates varied widely (34-51%) between the centres. The predictive score allowed imperfect risk adjustment (area under the curve: 0.70), with Hosmer-Lemeshow analysis suggesting good calibration. The Brier score changed from 0.19 for sites A-C to 0.23 when site D was also included, suggesting poor accuracy overall. CONCLUSIONS Marked differences in operative risk and patient case mix captured by the risk adjustment score do not explain all the differences in observed outcomes. Further investigation with different methods is recommended to improve modelling of risk. Morbidity is common, and usually has a major impact on patient recovery, ward occupancy, hospital finances and patient perception of quality of care. We hope comparative audit will highlight good performance and challenge underperformance where it exists.

Validating a benchmarking tool for audit of early outcomes after operations for head and neck cancer

PubMed Central

Sassoon, I; McGurk, M

2017-01-01

INTRODUCTION In 2013 all UK surgical specialties, with the exception of head and neck surgery, published outcome data adjusted for case mix for indicator operations. This paper reports a pilot study to validate a previously published risk adjustment score on patients from separate UK cancer centres. METHODS A case note audit was performed of 1,075 patients undergoing 1,218 operations for head and neck squamous cell carcinoma under general anaesthesia in 4 surgical centres. A logistic regression equation predicting for all complications, previously validated internally at sites A–C, was tested on a fourth external validation sample (site D, 172 operations) using receiver operating characteristic curves, Hosmer–Lemeshow goodness of fit analysis and Brier scores. RESULTS Thirty-day complication rates varied widely (34–51%) between the centres. The predictive score allowed imperfect risk adjustment (area under the curve: 0.70), with Hosmer–Lemeshow analysis suggesting good calibration. The Brier score changed from 0.19 for sites A–C to 0.23 when site D was also included, suggesting poor accuracy overall. CONCLUSIONS Marked differences in operative risk and patient case mix captured by the risk adjustment score do not explain all the differences in observed outcomes. Further investigation with different methods is recommended to improve modelling of risk. Morbidity is common, and usually has a major impact on patient recovery, ward occupancy, hospital finances and patient perception of quality of care. We hope comparative audit will highlight good performance and challenge underperformance where it exists. PMID:27917662

Prognostic score to predict mortality during TB treatment in TB/HIV co-infected patients.

PubMed

Nguyen, Duc T; Jenkins, Helen E; Graviss, Edward A

2018-01-01

Estimating mortality risk during TB treatment in HIV co-infected patients is challenging for health professionals, especially in a low TB prevalence population, due to the lack of a standardized prognostic system. The current study aimed to develop and validate a simple mortality prognostic scoring system for TB/HIV co-infected patients. Using data from the CDC's Tuberculosis Genotyping Information Management System of TB patients in Texas reported from 01/2010 through 12/2016, age ≥15 years, HIV(+), and outcome being "completed" or "died", we developed and internally validated a mortality prognostic score using multiple logistic regression. Model discrimination was determined by the area under the receiver operating characteristic (ROC) curve (AUC). The model's good calibration was determined by a non-significant Hosmer-Lemeshow's goodness of fit test. Among the 450 patients included in the analysis, 57 (12.7%) died during TB treatment. The final prognostic score used six characteristics (age, residence in long-term care facility, meningeal TB, chest x-ray, culture positive, and culture not converted/unknown), which are routinely collected by TB programs. Prognostic scores were categorized into three groups that predicted mortality: low-risk (<20 points), medium-risk (20-25 points) and high-risk (>25 points). The model had good discrimination and calibration (AUC = 0.82; 0.80 in bootstrap validation), and a non-significant Hosmer-Lemeshow test p = 0.71. Our simple validated mortality prognostic scoring system can be a practical tool for health professionals in identifying TB/HIV co-infected patients with high mortality risk.

Predictive and concurrent validity of the Braden scale in long-term care: a meta-analysis.

PubMed

Wilchesky, Machelle; Lungu, Ovidiu

2015-01-01

Pressure ulcer prevention is an important long-term care (LTC) quality indicator. While the Braden Scale is a recommended risk assessment tool, there is a paucity of information specifically pertaining to its validity within the LTC setting. We, therefore, undertook a systematic review and meta-analysis comparing Braden Scale predictive and concurrent validity within this context. We searched the Medline, EMBASE, PsychINFO and PubMed databases from 1985-2014 for studies containing the requisite information to analyze tool validity. Our initial search yielded 3,773 articles. Eleven datasets emanating from nine published studies describing 40,361 residents met all meta-analysis inclusion criteria and were analyzed using random effects models. Pooled sensitivity, specificity, positive predictive value (PPV), and negative predictive values were 86%, 38%, 28%, and 93%, respectively. Specificity was poorer in concurrent samples as compared with predictive samples (38% vs. 72%), while PPV was low in both sample types (25 and 37%). Though random effects model results showed that the Scale had good overall predictive ability [RR, 4.33; 95% CI, 3.28-5.72], none of the concurrent samples were found to have "optimal" sensitivity and specificity. In conclusion, the appropriateness of the Braden Scale in LTC is questionable given its low specificity and PPV, in particular in concurrent validity studies. Future studies should further explore the extent to which the apparent low validity of the Scale in LTC is due to the choice of cutoff point and/or preventive strategies implemented by LTC staff as a matter of course. © 2015 by the Wound Healing Society.

Development and validation of a risk-prediction algorithm for the recurrence of panic disorder.

PubMed

Liu, Yan; Sareen, Jitender; Bolton, James; Wang, JianLi

2015-05-01

To develop and validate a risk prediction algorithm for the recurrence of panic disorder. Three-year longitudinal data were taken from the National Epidemiologic Survey on Alcohol and Related Conditions (2001/2002-2004/2005). One thousand six hundred and eighty one participants with a lifetime panic disorder and who had not had panic attacks for at least 2 months at baseline were included. The development cohort included 949 participants; 732 from different census regions were in the validation cohort. Recurrence of panic disorder over the follow-up period was assessed using the Alcohol Use Disorder and Associated Disabilities Interview Schedule, based on the DSM-IV criteria. Logistic regression was used for deriving the algorithm. Discrimination and calibration were assessed in the development and the validation cohorts. The developed algorithm consisted of 11 predictors: age, sex, panic disorder in the past 12 months, nicotine dependence, rapid heartbeat/tachycardia, taking medication for panic attacks, feelings of choking and persistent worry about having another panic attack, two personality traits, and childhood trauma. The algorithm had good discriminative power (C statistic = 0.7863, 95% CI: 0.7487, 0.8240). The C statistic was 0.7283 (95% CI: 0.6889, 0.7764) in the external validation data set. The developed risk algorithm for predicting the recurrence of panic disorder has good discrimination and excellent calibration. Data related to the predictors can be easily attainable in routine clinical practice. It can be used by clinicians to calculate the probability of recurrence of panic disorder in the next 3 years for individual patients, communicate with patients regarding personal risks, and thus improve personalized treatment approaches. © 2015 Wiley Periodicals, Inc.

Nomogram predicting response after chemoradiotherapy in rectal cancer using sequential PETCT imaging: a multicentric prospective study with external validation.

PubMed

van Stiphout, Ruud G P M; Valentini, Vincenzo; Buijsen, Jeroen; Lammering, Guido; Meldolesi, Elisa; van Soest, Johan; Leccisotti, Lucia; Giordano, Alessandro; Gambacorta, Maria A; Dekker, Andre; Lambin, Philippe

2014-11-01

To develop and externally validate a predictive model for pathologic complete response (pCR) for locally advanced rectal cancer (LARC) based on clinical features and early sequential (18)F-FDG PETCT imaging. Prospective data (i.a. THUNDER trial) were used to train (N=112, MAASTRO Clinic) and validate (N=78, Università Cattolica del S. Cuore) the model for pCR (ypT0N0). All patients received long-course chemoradiotherapy (CRT) and surgery. Clinical parameters were age, gender, clinical tumour (cT) stage and clinical nodal (cN) stage. PET parameters were SUVmax, SUVmean, metabolic tumour volume (MTV) and maximal tumour diameter, for which response indices between pre-treatment and intermediate scan were calculated. Using multivariate logistic regression, three probability groups for pCR were defined. The pCR rates were 21.4% (training) and 23.1% (validation). The selected predictive features for pCR were cT-stage, cN-stage, response index of SUVmean and maximal tumour diameter during treatment. The models' performances (AUC) were 0.78 (training) and 0.70 (validation). The high probability group for pCR resulted in 100% correct predictions for training and 67% for validation. The model is available on the website www.predictcancer.org. The developed predictive model for pCR is accurate and externally validated. This model may assist in treatment decisions during CRT to select complete responders for a wait-and-see policy, good responders for extra RT boost and bad responders for additional chemotherapy. Copyright © 2014 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Predicting discharge mortality after acute ischemic stroke using balanced data.

PubMed

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

2014-01-01

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

Reliability and Validity of the Work and Well-Being Inventory (WBI) for Employees.

PubMed

Vendrig, A A; Schaafsma, F G

2018-06-01

Purpose The purpose of this study is to measure the psychometric properties of the Work and Wellbeing Inventory (WBI) (in Dutch: VAR-2), a screening tool that is used within occupational health care and rehabilitation. Our research question focused on the reliability and validity of this inventory. Methods Over the years seven different samples of workers, patients and sick listed workers varying in size between 89 and 912 participants (total: 2514), were used to measure the test-retest reliability, the internal consistency, the construct and concurrent validity, and the criterion and predictive validity. Results The 13 scales displayed good internal consistency and test-retest reliability. The constructive validity of the WBI could clearly be demonstrated in both patients and healthy workers. Confirmative factor analyses revealed a CFI >.90 for all scales. The depression scale predicted future work absenteeism (>6 weeks) because of a common mental disorder in healthy workers. The job strain scale and the illness behavior scale predicted long term absenteeism (>3 months) in workers with short-term absenteeism. The illness behavior scale moderately predicted return to work in rehab patients attending an intensive multidisciplinary program. Conclusions The WBI is a valid and reliable tool for occupational health practitioners to screen for risk factors for prolonged or future sickness absence. With this tool they will have reliable indications for further advice and interventions to restore the work ability.

Risk score to predict hospital-acquired pneumonia after spontaneous intracerebral hemorrhage.

PubMed

Ji, Ruijun; Shen, Haipeng; Pan, Yuesong; Du, Wanliang; Wang, Penglian; Liu, Gaifen; Wang, Yilong; Li, Hao; Zhao, Xingquan; Wang, Yongjun

2014-09-01

We aimed to develop a risk score (intracerebral hemorrhage-associated pneumonia score, ICH-APS) for predicting hospital-acquired stroke-associated pneumonia (SAP) after ICH. The ICH-APS was developed based on the China National Stroke Registry (CNSR), in which eligible patients were randomly divided into derivation (60%) and validation (40%) cohorts. Variables routinely collected at presentation were used for predicting SAP after ICH. For testing the added value of hematoma volume measure, we separately developed 2 models with (ICH-APS-B) and without (ICH-APS-A) hematoma volume included. Multivariable logistic regression was performed to identify independent predictors. The area under the receiver operating characteristic curve (AUROC), Hosmer-Lemeshow goodness-of-fit test, and integrated discrimination index were used to assess model discrimination, calibration, and reclassification, respectively. The SAP was 16.4% and 17.7% in the overall derivation (n=2998) and validation (n=2000) cohorts, respectively. A 23-point ICH-APS-A was developed based on a set of predictors and showed good discrimination in the overall derivation (AUROC, 0.75; 95% confidence interval, 0.72-0.77) and validation (AUROC, 0.76; 95% confidence interval, 0.71-0.79) cohorts. The ICH-APS-A was more sensitive for patients with length of stay >48 hours (AUROC, 0.78; 95% confidence interval, 0.75-0.81) than those with length of stay <48 hours (AUROC, 0.64; 95% confidence interval, 0.55-0.73). The ICH-APS-A was well calibrated (Hosmer-Lemeshow test) in the derivation (P=0.20) and validation (P=0.66) cohorts. Similarly, a 26-point ICH-APS-B was established. The ICH-APS-A and ICH-APS-B were not significantly different in discrimination and reclassification for SAP after ICH. The ICH-APSs are valid risk scores for predicting SAP after ICH, especially for patients with length of stay >48 hours. © 2014 American Heart Association, Inc.

Measuring implicit attitudes of 4-year-olds: the preschool implicit association test.

PubMed

Cvencek, Dario; Greenwald, Anthony G; Meltzoff, Andrew N

2011-06-01

The Preschool Implicit Association Test (PSIAT) is an adaptation of an established social cognition measure (IAT) for use with preschool children. Two studies with 4-year-olds found that the PSIAT was effective in evaluating (a) attitudes toward commonly liked objects (flowers=good) and (b) gender attitudes (girl=good or boy=good). The gender attitude PSIAT was positively correlated with corresponding explicit attitude measures and also children's actual sex. The new implicit and explicit measures of gender attitudes demonstrated discriminant validity; each predicted variance in children's gendered play activities beyond that predicted by the other. Discussion describes potential uses of the PSIAT to investigate development of societally significant attitudes and stereotypes at younger ages than are achievable with currently available methods. Copyright © 2010 Elsevier Inc. All rights reserved.

Predictors of treatment failure in young patients undergoing in vitro fertilization.

PubMed

Jacobs, Marni B; Klonoff-Cohen, Hillary; Agarwal, Sanjay; Kritz-Silverstein, Donna; Lindsay, Suzanne; Garzo, V Gabriel

2016-08-01

The purpose of the study was to evaluate whether routinely collected clinical factors can predict in vitro fertilization (IVF) failure among young, "good prognosis" patients predominantly with secondary infertility who are less than 35 years of age. Using de-identified clinic records, 414 women <35 years undergoing their first autologous IVF cycle were identified. Logistic regression was used to identify patient-driven clinical factors routinely collected during fertility treatment that could be used to model predicted probability of cycle failure. One hundred ninety-seven patients with both primary and secondary infertility had a failed IVF cycle, and 217 with secondary infertility had a successful live birth. None of the women with primary infertility had a successful live birth. The significant predictors for IVF cycle failure among young patients were fewer previous live births, history of biochemical pregnancies or spontaneous abortions, lower baseline antral follicle count, higher total gonadotropin dose, unknown infertility diagnosis, and lack of at least one fair to good quality embryo. The full model showed good predictive value (c = 0.885) for estimating risk of cycle failure; at ≥80 % predicted probability of failure, sensitivity = 55.4 %, specificity = 97.5 %, positive predictive value = 95.4 %, and negative predictive value = 69.8 %. If this predictive model is validated in future studies, it could be beneficial for predicting IVF failure in good prognosis women under the age of 35 years.

Thermo-mechanical simulations of early-age concrete cracking with durability predictions

NASA Astrophysics Data System (ADS)

Havlásek, Petr; Šmilauer, Vít; Hájková, Karolina; Baquerizo, Luis

2017-09-01

Concrete performance is strongly affected by mix design, thermal boundary conditions, its evolving mechanical properties, and internal/external restraints with consequences to possible cracking with impaired durability. Thermo-mechanical simulations are able to capture those relevant phenomena and boundary conditions for predicting temperature, strains, stresses or cracking in reinforced concrete structures. In this paper, we propose a weakly coupled thermo-mechanical model for early age concrete with an affinity-based hydration model for thermal part, taking into account concrete mix design, cement type and thermal boundary conditions. The mechanical part uses B3/B4 model for concrete creep and shrinkage with isotropic damage model for cracking, able to predict a crack width. All models have been implemented in an open-source OOFEM software package. Validations of thermo-mechanical simulations will be presented on several massive concrete structures, showing excellent temperature predictions. Likewise, strain validation demonstrates good predictions on a restrained reinforced concrete wall and concrete beam. Durability predictions stem from induction time of reinforcement corrosion, caused by carbonation and/or chloride ingress influenced by crack width. Reinforcement corrosion in concrete struts of a bridge will serve for validation.

Predicting Performance in Higher Education Using Proximal Predictors.

PubMed

Niessen, A Susan M; Meijer, Rob R; Tendeiro, Jorge N

2016-01-01

We studied the validity of two methods for predicting academic performance and student-program fit that were proximal to important study criteria. Applicants to an undergraduate psychology program participated in a selection procedure containing a trial-studying test based on a work sample approach, and specific skills tests in English and math. Test scores were used to predict academic achievement and progress after the first year, achievement in specific course types, enrollment, and dropout after the first year. All tests showed positive significant correlations with the criteria. The trial-studying test was consistently the best predictor in the admission procedure. We found no significant differences between the predictive validity of the trial-studying test and prior educational performance, and substantial shared explained variance between the two predictors. Only applicants with lower trial-studying scores were significantly less likely to enroll in the program. In conclusion, the trial-studying test yielded predictive validities similar to that of prior educational performance and possibly enabled self-selection. In admissions aimed at student-program fit, or in admissions in which past educational performance is difficult to use, a trial-studying test is a good instrument to predict academic performance.

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.

Reliability and validity of the Tilburg Frailty Indicator (TFI) among Chinese community-dwelling older people.

PubMed

Dong, Lijuan; Liu, Na; Tian, Xiaoyu; Qiao, Xiaoxia; Gobbens, Robbert J J; Kane, Robert L; Wang, Cuili

2017-11-01

To translate the Tilburg Frailty Indicator (TFI) into Chinese and assess its reliability and validity. A sample of 917 community-dwelling older people, aged ≥60 years, in a Chinese city was included between August 2015 and March 2016. Construct validity was assessed using alternative measures corresponding to the TFI items, including self-rated health status (SRH), unintentional weight loss, walking speed, timed-up-and-go tests (TUGT), making telephone calls, grip strength, exhaustion, Short Portable Mental Status Questionnaire (SPMSQ), Geriatric Depression scale (GDS-15), emotional role, Adaptability Partnership Growth Affection and Resolve scale (APGAR) and Social Support Rating Scale (SSRS). Fried's phenotype and frailty index were measured to evaluate criterion validity. Adverse health outcomes (ADL and IADL disability, healthcare utilization, GDS-15, SSRS) were used to assess predictive (concurrent) validity. The internal consistency reliability was good (Cronbach's α=0.71). The test-retest reliability was strong (r=0.88). Kappa coefficients showed agreements between the TFI items and corresponding alternative measures. Alternative measures correlated as expected with the three domains of TFI, with an exclusion that alternative psychological measures had similar correlations with psychological and physical domains of the TFI. The Chinese TFI had excellent criterion validity with the AUCs regarding physical phenotype and frailty index of 0.87 and 0.86, respectively. The predictive (concurrent) validities of the adverse health outcomes and healthcare utilization were acceptable (AUCs: 0.65-0.83). The Chinese TFI has good validity and reliability as an integral instrument to measure frailty of older people living in the community in China. Copyright © 2017 Elsevier B.V. All rights reserved.

Breastfeeding Self-Efficacy Scale: Validation of the Italian Version and Correlation With Breast-feeding at 3 Months.

PubMed

Petrozzi, Angela; Gagliardi, Luigi

2016-01-01

Psychological factors can influence breast-feeding. We translated into Italian and validated the Breastfeeding Self-Efficacy Scale Short Form (BSES-SF) and investigated its predictive ability and its relation with postpartum depression symptoms.BSES-SF and Edinburgh Postnatal Depression Scale (EPDS) were administered 2 to 3 days after delivery to 122 mothers. Breast-feeding was assessed at 3 months.The BSES-SF displayed good validity (receiver operating characteristic area = 0.69) for predicting full breast-feeding at 3 months. In multivariate analysis, the probability of full breast-feeding increased 2.4% for 1-point increase of BSES-SF. The BSES-SF and EPDS scores were inversely correlated. BSES-SF is a useful tool to identify the risk of early breast-feeding attrition.

Calculation of Shuttle Base Heating Environments and Comparison with Flight Data

NASA Technical Reports Server (NTRS)

Greenwood, T. F.; Lee, Y. C.; Bender, R. L.; Carter, R. E.

1983-01-01

The techniques, analytical tools, and experimental programs used initially to generate and later to improve and validate the Shuttle base heating design environments are discussed. In general, the measured base heating environments for STS-1 through STS-5 were in good agreement with the preflight predictions. However, some changes were made in the methodology after reviewing the flight data. The flight data is described, preflight predictions are compared with the flight data, and improvements in the prediction methodology based on the data are discussed.

Towards more efficient burn care: Identifying factors associated with good quality of life post-burn.

PubMed

Finlay, V; Phillips, M; Allison, G T; Wood, F M; Ching, D; Wicaksono, D; Plowman, S; Hendrie, D; Edgar, D W

2015-11-01

As minor burn patients constitute the vast majority of a developed nation case-mix, streamlining care for this group can promote efficiency from a service-wide perspective. This study tested the hypothesis that a predictive nomogram model that estimates likelihood of good long-term quality of life (QoL) post-burn is a valid way to optimise patient selection and risk management when applying a streamlined model of care. A sample of 224 burn patients managed by the Burn Service of Western Australia who provided both short and long-term outcomes was used to estimate the probability of achieving a good QoL defined as 150 out of a possible 160 points on the Burn Specific Health Scale-Brief (BSHS-B) at least six months from injury. A multivariate logistic regression analysis produced a predictive model provisioned as a nomogram for clinical application. A second, independent cohort of consecutive patients (n=106) was used to validate the predictive merit of the nomogram. Male gender (p=0.02), conservative management (p=0.03), upper limb burn (p=0.04) and high BSHS-B score within one month of burn (p<0.001) were significant predictors of good outcome at six months and beyond. A Receiver Operating Curve (ROC) analysis demonstrated excellent (90%) accuracy overall. At 80% probability of good outcome, the false positive risk was 14%. The nomogram was validated by running a second ROC analysis of the model in an independent cohort. The analysis confirmed high (86%) overall accuracy of the model, the risk of false positive was reduced to 10% at a lower (70%) probability. This affirms the stability of the nomogram model in different patient groups over time. An investigation of the effect of missing data on sample selection determined that a greater proportion of younger patients with smaller TBSA burns were excluded due to loss to follow up. For clinicians managing comparable burn populations, the BSWA burns nomogram is an effective tool to assist the selection of patients to a streamlined care pathway with the aim of improving efficiency of service delivery. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

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

PubMed Central

Stræde, Mia; Brabrand, Mikkel

2014-01-01

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

Clinical risk scoring for predicting non-alcoholic fatty liver disease in metabolic syndrome patients (NAFLD-MS score).

PubMed

Saokaew, Surasak; Kanchanasuwan, Shada; Apisarnthanarak, Piyaporn; Charoensak, Aphinya; Charatcharoenwitthaya, Phunchai; Phisalprapa, Pochamana; Chaiyakunapruk, Nathorn

2017-10-01

Non-alcoholic fatty liver disease (NAFLD) can progress from simple steatosis to hepatocellular carcinoma. None of tools have been developed specifically for high-risk patients. This study aimed to develop a simple risk scoring to predict NAFLD in patients with metabolic syndrome (MetS). A total of 509 patients with MetS were recruited. All were diagnosed by clinicians with ultrasonography-confirmed whether they were patients with NAFLD. Patients were randomly divided into derivation (n=400) and validation (n=109) cohort. To develop the risk score, clinical risk indicators measured at the time of recruitment were built by logistic regression. Regression coefficients were transformed into item scores and added up to a total score. A risk scoring scheme was developed from clinical predictors: BMI ≥25, AST/ALT ≥1, ALT ≥40, type 2 diabetes mellitus and central obesity. The scoring scheme was applied in validation cohort to test the performance. The scheme explained, by area under the receiver operating characteristic curve (AuROC), 76.8% of being NAFLD with good calibration (Hosmer-Lemeshow χ 2 =4.35; P=.629). The positive likelihood ratio of NAFLD in patients with low risk (scores below 3) and high risk (scores 5 and over) were 2.32 (95% CI: 1.90-2.82) and 7.77 (95% CI: 2.47-24.47) respectively. When applied in validation cohort, the score showed good performance with AuROC 76.7%, and illustrated 84%, and 100% certainty in low- and high-risk groups respectively. A simple and non-invasive scoring scheme of five predictors provides good prediction indices for NAFLD in MetS patients. This scheme may help clinicians in order to take further appropriate action. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Further Validation of a CFD Code for Calculating the Performance of Two-Stage Light Gas Guns

NASA Technical Reports Server (NTRS)

Bogdanoff, David W.

2017-01-01

Earlier validations of a higher-order Godunov code for modeling the performance of two-stage light gas guns are reviewed. These validation comparisons were made between code predictions and experimental data from the NASA Ames 1.5" and 0.28" guns and covered muzzle velocities of 6.5 to 7.2 km/s. In the present report, five more series of code validation comparisons involving experimental data from the Ames 0.22" (1.28" pump tube diameter), 0.28", 0.50", 1.00" and 1.50" guns are presented. The total muzzle velocity range of the validation data presented herein is 3 to 11.3 km/s. The agreement between the experimental data and CFD results is judged to be very good. Muzzle velocities were predicted within 0.35 km/s for 74% of the cases studied with maximum differences being 0.5 km/s and for 4 out of 50 cases, 0.5 - 0.7 km/s.

Towards cheminformatics-based estimation of drug therapeutic index: Predicting the protective index of anticonvulsants using a new quantitative structure-index relationship approach.

PubMed

Chen, Shangying; Zhang, Peng; Liu, Xin; Qin, Chu; Tao, Lin; Zhang, Cheng; Yang, Sheng Yong; Chen, Yu Zong; Chui, Wai Keung

2016-06-01

The overall efficacy and safety profile of a new drug is partially evaluated by the therapeutic index in clinical studies and by the protective index (PI) in preclinical studies. In-silico predictive methods may facilitate the assessment of these indicators. Although QSAR and QSTR models can be used for predicting PI, their predictive capability has not been evaluated. To test this capability, we developed QSAR and QSTR models for predicting the activity and toxicity of anticonvulsants at accuracy levels above the literature-reported threshold (LT) of good QSAR models as tested by both the internal 5-fold cross validation and external validation method. These models showed significantly compromised PI predictive capability due to the cumulative errors of the QSAR and QSTR models. Therefore, in this investigation a new quantitative structure-index relationship (QSIR) model was devised and it showed improved PI predictive capability that superseded the LT of good QSAR models. The QSAR, QSTR and QSIR models were developed using support vector regression (SVR) method with the parameters optimized by using the greedy search method. The molecular descriptors relevant to the prediction of anticonvulsant activities, toxicities and PIs were analyzed by a recursive feature elimination method. The selected molecular descriptors are primarily associated with the drug-like, pharmacological and toxicological features and those used in the published anticonvulsant QSAR and QSTR models. This study suggested that QSIR is useful for estimating the therapeutic index of drug candidates. Copyright © 2016. Published by Elsevier Inc.

Application of transit data analysis and artificial neural network in the prediction of discharge of Lor River, NW Spain.

PubMed

Astray, G; Soto, B; Lopez, D; Iglesias, M A; Mejuto, J C

2016-01-01

Transit data analysis and artificial neural networks (ANNs) have proven to be a useful tool for characterizing and modelling non-linear hydrological processes. In this paper, these methods have been used to characterize and to predict the discharge of Lor River (North Western Spain), 1, 2 and 3 days ahead. Transit data analyses show a coefficient of correlation of 0.53 for a lag between precipitation and discharge of 1 day. On the other hand, temperature and discharge has a negative coefficient of correlation (-0.43) for a delay of 19 days. The ANNs developed provide a good result for the validation period, with R(2) between 0.92 and 0.80. Furthermore, these prediction models have been tested with discharge data from a period 16 years later. Results of this testing period also show a good correlation, with R(2) between 0.91 and 0.64. Overall, results indicate that ANNs are a good tool to predict river discharge with a small number of input variables.

Sustained Implementation Support Scale: Validation of a Measure of Program Characteristics and Workplace Functioning for Sustained Program Implementation.

PubMed

Hodge, Lauren M; Turner, Karen M T; Sanders, Matthew R; Filus, Ania

2017-07-01

An evaluation measure of enablers and inhibitors to sustained evidence-based program (EBP) implementation may provide a useful tool to enhance organizations' capacity. This paper outlines preliminary validation of such a measure. An expert informant and consumer feedback approach was used to tailor constructs from two existing measures assessing key domains associated with sustained implementation. Validity and reliability were evaluated for an inventory composed of five subscales: Program benefits, Program burden, Workplace support, Workplace cohesion, and Leadership style. Exploratory and confirmatory factor analysis with a sample of 593 Triple P-Positive Parenting Program-practitioners led to a 28-item scale with good reliability and good convergent, discriminant, and predictive validity. Practitioners sustaining implementation at least 3 years post-training were more likely to have supervision/peer support, reported higher levels of program benefit, workplace support, and positive leadership style, and lower program burden compared to practitioners who were non-sustainers.

Validity, reliability and responsiveness of a short version of the Stroke-Specific Quality of Life Scale in patients receiving rehabilitation.

PubMed

Chen, Hui-fang; Wu, Ching-yi; Lin, Keh-chung; Li, Ming-wei; Yu, Hung-wen

2012-07-01

To examine the measurement properties of a short version of the Stroke-Specific Quality of Life Scale (SS-QoL-12). Self-report survey of patients with mild to moderate upper extremity dysfunction. A total of 126 patients provided 252 observations before and after treatment. The construct validity and reliability was examined using the Rasch model; the concurrent and predictive validity was estimated using Spearman's rank correlation coefficients. Paired t-test and the standardized response mean (SRM) were performed to estimate the responsiveness of the SS-QoL-12. The 2-factor model (psychosocial and physical domains) fit the data better with smaller deviances. All but 1 item showed acceptable fit, and no item biases were detected. The reliability of the subscales and the whole scale ranged from 0.67 to 0.99. The total score showed fair correlations with the criterion measures at pretreatment (ρ = 0.28-0.40) and fair to good correlations at post-treatment (ρ = 0.39-0.54). The subscales had low to fair correlations at pretreatment (ρ = 0.19-0.49) and fair to good correlations at post-treatment (ρ = 0.31-0.56). The total and the subscales had low to good predictions at baseline (ρ = 0.22-0.52). The whole scale and the psychosocial subscale were mildly responsive to change (SRM = 0.22), but the physical subscale was not responsive to change (SRM = 0.08). The SS-QoL-12 has acceptable to good measurement properties, with an advantage of requiring less time to administer than other scales. The use of the subscale and total scores depends on the purpose of research. Future studies should recruit stroke patients with a broad range of dysfunction and use a large sample size to validate the findings.

Validation of the DRAGON Score in a Chinese Population to Predict Functional Outcome of Intravenous Thrombolysis-Treated Stroke Patients.

PubMed

Zhang, Xinmiao; Liao, Xiaoling; Wang, Chunjuan; Liu, Liping; Wang, Chunxue; Zhao, Xingquan; Pan, Yuesong; Wang, Yilong; Wang, Yongjun

2015-08-01

The DRAGON score predicts functional outcome of ischemic stroke patients treated with intravenous thrombolysis. Our aim was to evaluate its utility in a Chinese stroke population. Patients with acute ischemic stroke treated with intravenous thrombolysis were prospectively registered in the Thrombolysis Implementation and Monitor of acute ischemic Stroke in China. We excluded patients with basilar artery occlusion and missing data, leaving 970 eligible patients. We calculated the DRAGON score, and the clinical outcome was measured by the modified Rankin Scale at 3 months. Model discrimination was quantified by calculating the C statistic. Calibration was assessed using Pearson correlation coefficient. The C statistic was .73 (.70-.76) for good outcome and .75 (.70-.79) for miserable outcome. Proportions of patients with good outcome were 94%, 83%, 70%, and 0% for 0 to 1, 2, 3, and 8 to 10 score points, respectively. Proportions of patients with miserable outcome were 0%, 3%, 9%, and 50% for 0 to 1, 2, 3, and 8 to 10 points, respectively. There was high correlation between predicted and observed probability of 3-month favorable and miserable outcome in the external validation cohort (Pearson correlation coefficient, .98 and .98, respectively, both P < .0001). The DRAGON score showed good performance to predict functional outcome after tissue-type plasminogen activator treatment in the Chinese population. This study demonstrated the accuracy and usability of the DRAGON score in the Chinese population in daily practice. Copyright © 2015 National Stroke Association. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2015-01-01

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

Prediction models for clustered data: comparison of a random intercept and standard regression model

PubMed Central

2013-01-01

Background When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Methods Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. Results The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. Conclusion The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters. PMID:23414436

Prediction models for clustered data: comparison of a random intercept and standard regression model.

PubMed

Bouwmeester, Walter; Twisk, Jos W R; Kappen, Teus H; van Klei, Wilton A; Moons, Karel G M; Vergouwe, Yvonne

2013-02-15

When study data are clustered, standard regression analysis is considered inappropriate and analytical techniques for clustered data need to be used. For prediction research in which the interest of predictor effects is on the patient level, random effect regression models are probably preferred over standard regression analysis. It is well known that the random effect parameter estimates and the standard logistic regression parameter estimates are different. Here, we compared random effect and standard logistic regression models for their ability to provide accurate predictions. Using an empirical study on 1642 surgical patients at risk of postoperative nausea and vomiting, who were treated by one of 19 anesthesiologists (clusters), we developed prognostic models either with standard or random intercept logistic regression. External validity of these models was assessed in new patients from other anesthesiologists. We supported our results with simulation studies using intra-class correlation coefficients (ICC) of 5%, 15%, or 30%. Standard performance measures and measures adapted for the clustered data structure were estimated. The model developed with random effect analysis showed better discrimination than the standard approach, if the cluster effects were used for risk prediction (standard c-index of 0.69 versus 0.66). In the external validation set, both models showed similar discrimination (standard c-index 0.68 versus 0.67). The simulation study confirmed these results. For datasets with a high ICC (≥15%), model calibration was only adequate in external subjects, if the used performance measure assumed the same data structure as the model development method: standard calibration measures showed good calibration for the standard developed model, calibration measures adapting the clustered data structure showed good calibration for the prediction model with random intercept. The models with random intercept discriminate better than the standard model only if the cluster effect is used for predictions. The prediction model with random intercept had good calibration within clusters.

Predictive validity of the Sødring Motor Evaluation of Stroke Patients (SMES).

PubMed

Wyller, T B; Sødring, K M; Sveen, U; Ljunggren, A E; Bautz-Holter, E

1996-12-01

The Sødring Motor Evaluation of Stroke Patients (SMES) has been developed as an instrument for the evaluation by physiotherapists of motor function and activities in stroke patients. The predictive validity of the instrument was studied in a consecutive sample of 93 acute stroke patients, assessed in the acute phase and after one year. The outcome measures were: survival, residence at home or in institution, the Barthel ADL index (dichotomized at 19/20), and the Frenchay Activities Index (FAI) (dichotomized at 9/10). The SMES, scored in the acute phase, demonstrated a marginally significant predictive power regarding survival, but was a highly significant predictor regarding the other outcomes. The adjusted odds ratio for a good versus a poor outcome for patients in the upper versus the lower tertile of the SMES arm subscore was 5.4 (95% confidence interval 0.9-59) for survival, 11.5 (2.1-88) for living at home, 86.3 (11-infinity) for a high Barthel score, and 31.4 (5.2-288) for a high FAI score. We conclude that SMES has high predictive validity.

External Validation of the Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale Score for Predicting Pneumonia After Stroke Using Data From the China National Stroke Registry.

PubMed

Zhang, Runhua; Ji, Ruijun; Pan, Yuesong; Jiang, Yong; Liu, Gaifen; Wang, Yilong; Wang, Yongjun

2017-05-01

Pneumonia is an important risk factor for mortality and morbidity after stroke. The Prestroke Independence, Sex, Age, National Institutes of Health Stroke Scale (ISAN) score was shown to be a useful tool for predicting stroke-associated pneumonia based on UK multicenter cohort study. We aimed to externally validate the score using data from the China National Stroke Registry (CNSR). Eligible patients with acute ischemic stroke (AIS) and intracerebral hemorrhage (ICH) in the CNSR from 2007 to 2008 were included. The area under the receiver operating characteristic (AUC) curve was used to evaluate discrimination. The Hosmer-Lemeshow goodness of fit test and Pearson correlation coefficient were performed to assess calibration of the model. A total of 19,333 patients (AIS = 14400; ICH = 4933) were included and the overall pneumonia rate was 12.7%. The AUC was .76 (95% confidence interval [CI]: .75-.78) for the subgroup of AIS and .70 (95% CI: .68-.72) for the subgroup of ICH. The Hosmer-Lemeshow test showed the ISAN score with the good calibration for AIS and ICH (P = .177 and .405, respectively). The plot of observed versus predicted pneumonia rates suggested higher correlation for patients with AIS than with ICH (Pearson correlation coefficient = .99 and .83, respectively). The ISAN score was a useful tool for predicting in-hospital pneumonia after acute stroke, especially for patients with AIS. Further validations need to be done in different populations. Copyright © 2017 National Stroke Association. Published by Elsevier Inc. All rights reserved.

Modelling Predictors of Molecular Response to Frontline Imatinib for Patients with Chronic Myeloid Leukaemia

PubMed Central

Brown, Fred; Adelson, David; White, Deborah; Hughes, Timothy; Chaudhri, Naeem

2017-01-01

Background Treatment of patients with chronic myeloid leukaemia (CML) has become increasingly difficult in recent years due to the variety of treatment options available and challenge deciding on the most appropriate treatment strategy for an individual patient. To facilitate the treatment strategy decision, disease assessment should involve molecular response to initial treatment for an individual patient. Patients predicted not to achieve major molecular response (MMR) at 24 months to frontline imatinib may be better treated with alternative frontline therapies, such as nilotinib or dasatinib. The aims of this study were to i) understand the clinical prediction ‘rules’ for predicting MMR at 24 months for CML patients treated with imatinib using clinical, molecular, and cell count observations (predictive factors collected at diagnosis and categorised based on available knowledge) and ii) develop a predictive model for CML treatment management. This predictive model was developed, based on CML patients undergoing imatinib therapy enrolled in the TIDEL II clinical trial with an experimentally identified achieving MMR group and non-achieving MMR group, by addressing the challenge as a machine learning problem. The recommended model was validated externally using an independent data set from King Faisal Specialist Hospital and Research Centre, Saudi Arabia. Principle Findings The common prognostic scores yielded similar sensitivity performance in testing and validation datasets and are therefore good predictors of the positive group. The G-mean and F-score values in our models outperformed the common prognostic scores in testing and validation datasets and are therefore good predictors for both the positive and negative groups. Furthermore, a high PPV above 65% indicated that our models are appropriate for making decisions at diagnosis and pre-therapy. Study limitations include that prior knowledge may change based on varying expert opinions; hence, representing the category boundaries of each predictive factor could dramatically change performance of the models. PMID:28045960

Predicting survival of de novo metastatic breast cancer in Asian women: systematic review and validation study.

PubMed

Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G M; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M

2014-01-01

In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48-0.53) to 0.63 (95% CI, 0.60-0.66). The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making.

Conceptualizing and measuring illness self-concept: a comparison with self-esteem and optimism in predicting fibromyalgia adjustment.

PubMed

Morea, Jessica M; Friend, Ronald; Bennett, Robert M

2008-12-01

Illness self-concept (ISC), or the extent to which individuals are consumed by their illness, was theoretically described and evaluated with the Illness Self-Concept Scale (ISCS), a new 23-item scale, to predict adjustment in fibromyalgia. To establish convergent and discriminant validity, illness self-concept was compared to self-esteem and optimism in predicting health status, illness intrusiveness, depression, and life satisfaction. The ISCS demonstrated good reliability (alpha = .94; test-retest r = .80) and was a strong predictor of outcomes, even after controlling for optimism or self-esteem. The ISCS predicted unique variance in health-related outcomes; optimism and self-esteem did not, providing construct validation. Illness self-concept may play a significant role in coping with fibromyalgia and may prove useful in the evaluation of other chronic illnesses. (c) 2008 Wiley Periodicals, Inc.

Validation of Shoulder Response of Human Body Finite-Element Model (GHBMC) Under Whole Body Lateral Impact Condition.

PubMed

Park, Gwansik; Kim, Taewung; Panzer, Matthew B; Crandall, Jeff R

2016-08-01

In previous shoulder impact studies, the 50th-percentile male GHBMC human body finite-element model was shown to have good biofidelity regarding impact force, but under-predicted shoulder deflection by 80% compared to those observed in the experiment. The goal of this study was to validate the response of the GHBMC M50 model by focusing on three-dimensional shoulder kinematics under a whole-body lateral impact condition. Five modifications, focused on material properties and modeling techniques, were introduced into the model and a supplementary sensitivity analysis was done to determine the influence of each modification to the biomechanical response of the body. The modified model predicted substantially improved shoulder response and peak shoulder deflection within 10% of the observed experimental data, and showed good correlation in the scapula kinematics on sagittal and transverse planes. The improvement in the biofidelity of the shoulder region was mainly due to the modifications of material properties of muscle, the acromioclavicular joint, and the attachment region between the pectoralis major and ribs. Predictions of rib fracture and chest deflection were also improved because of these modifications.

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

PubMed

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

2012-01-01

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

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

PubMed

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

2018-05-01

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

A New Lebanese Medication Adherence Scale: Validation in Lebanese Hypertensive Adults.

PubMed

Bou Serhal, R; Salameh, P; Wakim, N; Issa, C; Kassem, B; Abou Jaoude, L; Saleh, N

2018-01-01

A new Lebanese scale measuring medication adherence considered socioeconomic and cultural factors not taken into account by the eight-item Morisky Medication Adherence Scale (MMAS-8). Objectives were to validate the new adherence scale and its prediction of hypertension control, compared to MMAS-8, and to assess adherence rates and factors. A cross-sectional study, including 405 patients, was performed in outpatient cardiology clinics of three hospitals in Beirut. Blood pressure was measured, a questionnaire filled, and sodium intake estimated by a urine test. Logistic regression defined predictors of hypertension control and adherence. 54.9% had controlled hypertension. 82.4% were adherent by the new scale, which showed good internal consistency, adequate questions (KMO coefficient = 0.743), and four factors. It predicted hypertension control (OR = 1.217; p value = 0.003), unlike MMAS-8, but the scores were correlated (ICC average measure = 0.651; p value < 0.001). Stress and smoking predicted nonadherence. This study elaborated a validated, practical, and useful tool measuring adherence to medications in Lebanese hypertensive patients.

The Reliability and Predictive Validity of the Stalking Risk Profile.

PubMed

McEwan, Troy E; Shea, Daniel E; Daffern, Michael; MacKenzie, Rachel D; Ogloff, James R P; Mullen, Paul E

2018-03-01

This study assessed the reliability and validity of the Stalking Risk Profile (SRP), a structured measure for assessing stalking risks. The SRP was administered at the point of assessment or retrospectively from file review for 241 adult stalkers (91% male) referred to a community-based forensic mental health service. Interrater reliability was high for stalker type, and moderate-to-substantial for risk judgments and domain scores. Evidence for predictive validity and discrimination between stalking recidivists and nonrecidivists for risk judgments depended on follow-up duration. Discrimination was moderate (area under the curve = 0.66-0.68) and positive and negative predictive values good over the full follow-up period ( Mdn = 170.43 weeks). At 6 months, discrimination was better than chance only for judgments related to stalking of new victims (area under the curve = 0.75); however, high-risk stalkers still reoffended against their original victim(s) 2 to 4 times as often as low-risk stalkers. Implications for the clinical utility and refinement of the SRP are discussed.

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.

A quantitative structure-activity relationship to predict efficacy of granular activated carbon adsorption to control emerging contaminants.

PubMed

Kennicutt, A R; Morkowchuk, L; Krein, M; Breneman, C M; Kilduff, J E

2016-08-01

A quantitative structure-activity relationship was developed to predict the efficacy of carbon adsorption as a control technology for endocrine-disrupting compounds, pharmaceuticals, and components of personal care products, as a tool for water quality professionals to protect public health. Here, we expand previous work to investigate a broad spectrum of molecular descriptors including subdivided surface areas, adjacency and distance matrix descriptors, electrostatic partial charges, potential energy descriptors, conformation-dependent charge descriptors, and Transferable Atom Equivalent (TAE) descriptors that characterize the regional electronic properties of molecules. We compare the efficacy of linear (Partial Least Squares) and non-linear (Support Vector Machine) machine learning methods to describe a broad chemical space and produce a user-friendly model. We employ cross-validation, y-scrambling, and external validation for quality control. The recommended Support Vector Machine model trained on 95 compounds having 23 descriptors offered a good balance between good performance statistics, low error, and low probability of over-fitting while describing a wide range of chemical features. The cross-validated model using a log-uptake (qe) response calculated at an aqueous equilibrium concentration (Ce) of 1 μM described the training dataset with an r(2) of 0.932, had a cross-validated r(2) of 0.833, and an average residual of 0.14 log units.

Rapid and non-invasive analysis of deoxynivalenol in durum and common wheat by Fourier-Transform Near Infrared (FT-NIR) spectroscopy.

PubMed

De Girolamo, A; Lippolis, V; Nordkvist, E; Visconti, A

2009-06-01

Fourier transform near-infrared spectroscopy (FT-NIR) was used for rapid and non-invasive analysis of deoxynivalenol (DON) in durum and common wheat. The relevance of using ground wheat samples with a homogeneous particle size distribution to minimize measurement variations and avoid DON segregation among particles of different sizes was established. Calibration models for durum wheat, common wheat and durum + common wheat samples, with particle size <500 microm, were obtained by using partial least squares (PLS) regression with an external validation technique. Values of root mean square error of prediction (RMSEP, 306-379 microg kg(-1)) were comparable and not too far from values of root mean square error of cross-validation (RMSECV, 470-555 microg kg(-1)). Coefficients of determination (r(2)) indicated an "approximate to good" level of prediction of the DON content by FT-NIR spectroscopy in the PLS calibration models (r(2) = 0.71-0.83), and a "good" discrimination between low and high DON contents in the PLS validation models (r(2) = 0.58-0.63). A "limited to good" practical utility of the models was ascertained by range error ratio (RER) values higher than 6. A qualitative model, based on 197 calibration samples, was developed to discriminate between blank and naturally contaminated wheat samples by setting a cut-off at 300 microg kg(-1) DON to separate the two classes. The model correctly classified 69% of the 65 validation samples with most misclassified samples (16 of 20) showing DON contamination levels quite close to the cut-off level. These findings suggest that FT-NIR analysis is suitable for the determination of DON in unprocessed wheat at levels far below the maximum permitted limits set by the European Commission.

Predictive Accuracy of the Liverpool Lung Project Risk Model for Stratifying Patients for Computed Tomography Screening for Lung Cancer

PubMed Central

Raji, Olaide Y.; Duffy, Stephen W.; Agbaje, Olorunshola F.; Baker, Stuart G.; Christiani, David C.; Cassidy, Adrian; Field, John K.

2013-01-01

Background External validation of existing lung cancer risk prediction models is limited. Using such models in clinical practice to guide the referral of patients for computed tomography (CT) screening for lung cancer depends on external validation and evidence of predicted clinical benefit. Objective To evaluate the discrimination of the Liverpool Lung Project (LLP) risk model and demonstrate its predicted benefit for stratifying patients for CT screening by using data from 3 independent studies from Europe and North America. Design Case–control and prospective cohort study. Setting Europe and North America. Patients Participants in the European Early Lung Cancer (EUELC) and Harvard case–control studies and the LLP population-based prospective cohort (LLPC) study. Measurements 5-year absolute risks for lung cancer predicted by the LLP model. Results The LLP risk model had good discrimination in both the Harvard (area under the receiver-operating characteristic curve [AUC], 0.76 [95% CI, 0.75 to 0.78]) and the LLPC (AUC, 0.82 [CI, 0.80 to 0.85]) studies and modest discrimination in the EUELC (AUC, 0.67 [CI, 0.64 to 0.69]) study. The decision utility analysis, which incorporates the harms and benefit of using a risk model to make clinical decisions, indicates that the LLP risk model performed better than smoking duration or family history alone in stratifying high-risk patients for lung cancer CT screening. Limitations The model cannot assess whether including other risk factors, such as lung function or genetic markers, would improve accuracy. Lack of information on asbestos exposure in the LLPC limited the ability to validate the complete LLP risk model. Conclusion Validation of the LLP risk model in 3 independent external data sets demonstrated good discrimination and evidence of predicted benefits for stratifying patients for lung cancer CT screening. Further studies are needed to prospectively evaluate model performance and evaluate the optimal population risk thresholds for initiating lung cancer screening. Primary Funding Source Roy Castle Lung Cancer Foundation. PMID:22910935

Prediction of Mass Evaporation of During Measurements of Thermophysical Properties Using an Electrostatic Levitator

NASA Astrophysics Data System (ADS)

Lee, J.; Matson, D. M.

2014-10-01

This paper describes the prediction of mass evaporation of at% alloys during thermophysical property measurements using the electrostatic levitator at NASA Marshall Space Flight Center in Huntsville, AL. The final mass, final composition, and activity of individual component are considered in the calculation of mass evaporation. The predicted reduction in mass and variation in composition are validated with six ESL samples which underwent different thermal cycles. The predicted mass evaporation and composition shift show good agreement with experiments with the maximum relative errors of 4.8 % and 1.7 %, respectively.

Simple prediction scores predict good and devastating outcomes after stroke more accurately than physicians.

PubMed

Reid, John Michael; Dai, Dingwei; Delmonte, Susanna; Counsell, Carl; Phillips, Stephen J; MacLeod, Mary Joan

2017-05-01

physicians are often asked to prognosticate soon after a patient presents with stroke. This study aimed to compare two outcome prediction scores (Five Simple Variables [FSV] score and the PLAN [Preadmission comorbidities, Level of consciousness, Age, and focal Neurologic deficit]) with informal prediction by physicians. demographic and clinical variables were prospectively collected from consecutive patients hospitalised with acute ischaemic or haemorrhagic stroke (2012-13). In-person or telephone follow-up at 6 months established vital and functional status (modified Rankin score [mRS]). Area under the receiver operating curves (AUC) was used to establish prediction score performance. five hundred and seventy-five patients were included; 46% female, median age 76 years, 88% ischaemic stroke. Six months after stroke, 47% of patients had a good outcome (alive and independent, mRS 0-2) and 26% a devastating outcome (dead or severely dependent, mRS 5-6). The FSV and PLAN scores were superior to physician prediction (AUCs of 0.823-0.863 versus 0.773-0.805, P < 0.0001) for good and devastating outcomes. The FSV score was superior to the PLAN score for predicting good outcomes and vice versa for devastating outcomes (P < 0.001). Outcome prediction was more accurate for those with later presentations (>24 hours from onset). the FSV and PLAN scores are validated in this population for outcome prediction after both ischaemic and haemorrhagic stroke. The FSV score is the least complex of all developed scores and can assist outcome prediction by physicians. © The Author 2016. Published by Oxford University Press on behalf of the British Geriatrics Society. All rights reserved. For permissions, please email: journals.permissions@oup.com

Multifactorial risk index for prediction of intraoperative blood transfusion in endovascular aneurysm repair.

PubMed

Mahmood, Eitezaz; Matyal, Robina; Mueller, Ariel; Mahmood, Feroze; Tung, Avery; Montealegre-Gallegos, Mario; Schermerhorn, Marc; Shahul, Sajid

2018-03-01

In some institutions, the current blood ordering practice does not discriminate minimally invasive endovascular aneurysm repair (EVAR) from open procedures, with consequent increasing costs and likelihood of blood product wastage for EVARs. This limitation in practice can possibly be addressed with the development of a reliable prediction model for transfusion risk in EVAR patients. We used the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) database to create a model for prediction of intraoperative blood transfusion occurrence in patients undergoing EVAR. Afterward, we tested our predictive model on the Vascular Study Group of New England (VSGNE) database. We used the ACS NSQIP database for patients who underwent EVAR from 2011 to 2013 (N = 4709) as our derivation set for identifying a risk index for predicting intraoperative blood transfusion. We then developed a clinical risk score and validated this model using patients who underwent EVAR from 2003 to 2014 in the VSGNE database (N = 4478). The transfusion rates were 8.4% and 6.1% for the ACS NSQIP (derivation set) and VSGNE (validation) databases, respectively. Hemoglobin concentration, American Society of Anesthesiologists class, age, and aneurysm diameter predicted blood transfusion in the derivation set. When it was applied on the validation set, our risk index demonstrated good discrimination in both the derivation and validation set (C statistic = 0.73 and 0.70, respectively) and calibration using the Hosmer-Lemeshow test (P = .27 and 0.31) for both data sets. We developed and validated a risk index for predicting the likelihood of intraoperative blood transfusion in EVAR patients. Implementation of this index may facilitate the blood management strategies specific for EVAR. Copyright © 2017 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

An Empiric HIV Risk Scoring Tool to Predict HIV-1 Acquisition in African Women.

PubMed

Balkus, Jennifer E; Brown, Elizabeth; Palanee, Thesla; Nair, Gonasagrie; Gafoor, Zakir; Zhang, Jingyang; Richardson, Barbra A; Chirenje, Zvavahera M; Marrazzo, Jeanne M; Baeten, Jared M

2016-07-01

To develop and validate an HIV risk assessment tool to predict HIV acquisition among African women. Data were analyzed from 3 randomized trials of biomedical HIV prevention interventions among African women (VOICE, HPTN 035, and FEM-PrEP). We implemented standard methods for the development of clinical prediction rules to generate a risk-scoring tool to predict HIV acquisition over the course of 1 year. Performance of the score was assessed through internal and external validations. The final risk score resulting from multivariable modeling included age, married/living with a partner, partner provides financial or material support, partner has other partners, alcohol use, detection of a curable sexually transmitted infection, and herpes simplex virus 2 serostatus. Point values for each factor ranged from 0 to 2, with a maximum possible total score of 11. Scores ≥5 were associated with HIV incidence >5 per 100 person-years and identified 91% of incident HIV infections from among only 64% of women. The area under the curve (AUC) for predictive ability of the score was 0.71 (95% confidence interval [CI]: 0.68 to 0.74), indicating good predictive ability. Risk score performance was generally similar with internal cross-validation (AUC = 0.69; 95% CI: 0.66 to 0.73) and external validation in HPTN 035 (AUC = 0.70; 95% CI: 0.65 to 0.75) and FEM-PrEP (AUC = 0.58; 95% CI: 0.51 to 0.65). A discrete set of characteristics that can be easily assessed in clinical and research settings was predictive of HIV acquisition over 1 year. The use of a validated risk score could improve efficiency of recruitment into HIV prevention research and inform scale-up of HIV prevention strategies in women at highest risk.

Development and Validation of Decision Forest Model for Estrogen Receptor Binding Prediction of Chemicals Using Large Data Sets.

PubMed

Ng, Hui Wen; Doughty, Stephen W; Luo, Heng; Ye, Hao; Ge, Weigong; Tong, Weida; Hong, Huixiao

2015-12-21

Some chemicals in the environment possess the potential to interact with the endocrine system in the human body. Multiple receptors are involved in the endocrine system; estrogen receptor α (ERα) plays very important roles in endocrine activity and is the most studied receptor. Understanding and predicting estrogenic activity of chemicals facilitates the evaluation of their endocrine activity. Hence, we have developed a decision forest classification model to predict chemical binding to ERα using a large training data set of 3308 chemicals obtained from the U.S. Food and Drug Administration's Estrogenic Activity Database. We tested the model using cross validations and external data sets of 1641 chemicals obtained from the U.S. Environmental Protection Agency's ToxCast project. The model showed good performance in both internal (92% accuracy) and external validations (∼ 70-89% relative balanced accuracies), where the latter involved the validations of the model across different ER pathway-related assays in ToxCast. The important features that contribute to the prediction ability of the model were identified through informative descriptor analysis and were related to current knowledge of ER binding. Prediction confidence analysis revealed that the model had both high prediction confidence and accuracy for most predicted chemicals. The results demonstrated that the model constructed based on the large training data set is more accurate and robust for predicting ER binding of chemicals than the published models that have been developed using much smaller data sets. The model could be useful for the evaluation of ERα-mediated endocrine activity potential of environmental chemicals.

Predicting Esophagitis After Chemoradiation Therapy for Non-Small Cell Lung Cancer: An Individual Patient Data Meta-Analysis

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

Palma, David A., E-mail: david.palma@uwo.ca; Senan, Suresh; Oberije, Cary

Purpose: Concurrent chemoradiation therapy (CCRT) improves survival compared with sequential treatment for locally advanced non-small cell lung cancer, but it increases toxicity, particularly radiation esophagitis (RE). Validated predictors of RE for clinical use are lacking. We performed an individual-patient-data meta-analysis to determine factors predictive of clinically significant RE. Methods and Materials: After a systematic review of the literature, data were obtained on 1082 patients who underwent CCRT, including patients from Europe, North America, Asia, and Australia. Patients were randomly divided into training and validation sets (2/3 vs 1/3 of patients). Factors predictive of RE (grade ≥2 and grade ≥3) weremore » assessed using logistic modeling, with the concordance statistic (c statistic) used to evaluate the performance of each model. Results: The median radiation therapy dose delivered was 65 Gy, and the median follow-up time was 2.1 years. Most patients (91%) received platinum-containing CCRT regimens. The development of RE was common, scored as grade 2 in 348 patients (32.2%), grade 3 in 185 (17.1%), and grade 4 in 10 (0.9%). There were no RE-related deaths. On univariable analysis using the training set, several baseline factors were statistically predictive of RE (P<.05), but only dosimetric factors had good discrimination scores (c > .60). On multivariable analysis, the esophageal volume receiving ≥60 Gy (V60) alone emerged as the best predictor of grade ≥2 and grade ≥3 RE, with good calibration and discrimination. Recursive partitioning identified 3 risk groups: low (V60 <0.07%), intermediate (V60 0.07% to 16.99%), and high (V60 ≥17%). With use of the validation set, the predictive model performed inferiorly for the grade ≥2 endpoint (c = .58) but performed well for the grade ≥3 endpoint (c = .66). Conclusions: Clinically significant RE is common, but life-threatening complications occur in <1% of patients. Although several factors are statistically predictive of RE, the V60 alone provides the best predictive ability. Efforts to reduce the V60 should be prioritized, with further research needed to identify and validate new predictive factors.« less

Assessing the capability of numerical methods to predict earthquake ground motion: the Euroseistest verification and validation project

NASA Astrophysics Data System (ADS)

Chaljub, E. O.; Bard, P.; Tsuno, S.; Kristek, J.; Moczo, P.; Franek, P.; Hollender, F.; Manakou, M.; Raptakis, D.; Pitilakis, K.

2009-12-01

During the last decades, an important effort has been dedicated to develop accurate and computationally efficient numerical methods to predict earthquake ground motion in heterogeneous 3D media. The progress in methods and increasing capability of computers have made it technically feasible to calculate realistic seismograms for frequencies of interest in seismic design applications. In order to foster the use of numerical simulation in practical prediction, it is important to (1) evaluate the accuracy of current numerical methods when applied to realistic 3D applications where no reference solution exists (verification) and (2) quantify the agreement between recorded and numerically simulated earthquake ground motion (validation). Here we report the results of the Euroseistest verification and validation project - an ongoing international collaborative work organized jointly by the Aristotle University of Thessaloniki, Greece, the Cashima research project (supported by the French nuclear agency, CEA, and the Laue-Langevin institute, ILL, Grenoble), and the Joseph Fourier University, Grenoble, France. The project involves more than 10 international teams from Europe, Japan and USA. The teams employ the Finite Difference Method (FDM), the Finite Element Method (FEM), the Global Pseudospectral Method (GPSM), the Spectral Element Method (SEM) and the Discrete Element Method (DEM). The project makes use of a new detailed 3D model of the Mygdonian basin (about 5 km wide, 15 km long, sediments reach about 400 m depth, surface S-wave velocity is 200 m/s). The prime target is to simulate 8 local earthquakes with magnitude from 3 to 5. In the verification, numerical predictions for frequencies up to 4 Hz for a series of models with increasing structural and rheological complexity are analyzed and compared using quantitative time-frequency goodness-of-fit criteria. Predictions obtained by one FDM team and the SEM team are close and different from other predictions (consistent with the ESG2006 exercise which targeted the Grenoble Valley). Diffractions off the basin edges and induced surface-wave propagation mainly contribute to differences between predictions. The differences are particularly large in the elastic models but remain important also in models with attenuation. In the validation, predictions are compared with the recordings by a local array of 19 surface and borehole accelerometers. The level of agreement is found event-dependent. For the largest-magnitude event the agreement is surprisingly good even at high frequencies.

Measuring Work Functioning: Validity of a Weighted Composite Work Functioning Approach.

PubMed

Boezeman, Edwin J; Sluiter, Judith K; Nieuwenhuijsen, Karen

2015-09-01

To examine the construct validity of a weighted composite work functioning measurement approach. Workers (health-impaired/healthy) (n = 117) completed a composite measure survey that recorded four central work functioning aspects with existing scales: capacity to work, quality of work performance, quantity of work, and recovery from work. Previous derived weights reflecting the relative importance of these aspects of work functioning were used to calculate the composite weighted work functioning score of the workers. Work role functioning, productivity, and quality of life were used for validation. Correlations were calculated and norms applied to examine convergent and divergent construct validity. A t test was conducted and a norm applied to examine discriminative construct validity. Overall the weighted composite work functioning measure demonstrated construct validity. As predicted, the weighted composite score correlated (p < .001) strongly (r > .60) with work role functioning and productivity (convergent construct validity), and moderately (.30 < r < .60) with physical quality of life and less strongly than work role functioning and productivity with mental quality of life (divergent validity). Further, the weighted composite measure detected that health-impaired workers show with a large effect size (Cohen's d > .80) significantly worse work functioning than healthy workers (discriminative validity). The weighted composite work functioning measurement approach takes into account the relative importance of the different work functioning aspects and demonstrated good convergent, fair divergent, and good discriminative construct validity.

The reliability and validity of ultrasound to quantify muscles in older adults: a systematic review

PubMed Central

Scafoglieri, Aldo; Jager‐Wittenaar, Harriët; Hobbelen, Johannes S.M.; van der Schans, Cees P.

2017-01-01

Abstract This review evaluates the reliability and validity of ultrasound to quantify muscles in older adults. The databases PubMed, Cochrane, and Cumulative Index to Nursing and Allied Health Literature were systematically searched for studies. In 17 studies, the reliability (n = 13) and validity (n = 8) of ultrasound to quantify muscles in community‐dwelling older adults (≥60 years) or a clinical population were evaluated. Four out of 13 reliability studies investigated both intra‐rater and inter‐rater reliability. Intraclass correlation coefficient (ICC) scores for reliability ranged from −0.26 to 1.00. The highest ICC scores were found for the vastus lateralis, rectus femoris, upper arm anterior, and the trunk (ICC = 0.72 to 1.000). All included validity studies found ICC scores ranging from 0.92 to 0.999. Two studies describing the validity of ultrasound to predict lean body mass showed good validity as compared with dual‐energy X‐ray absorptiometry (r 2 = 0.92 to 0.96). This systematic review shows that ultrasound is a reliable and valid tool for the assessment of muscle size in older adults. More high‐quality research is required to confirm these findings in both clinical and healthy populations. Furthermore, ultrasound assessment of small muscles needs further evaluation. Ultrasound to predict lean body mass is feasible; however, future research is required to validate prediction equations in older adults with varying function and health. PMID:28703496

Can generic paediatric mortality scores calculated 4 hours after admission be used as inclusion criteria for clinical trials?

PubMed Central

Leteurtre, Stéphane; Leclerc, Francis; Wirth, Jessica; Noizet, Odile; Magnenant, Eric; Sadik, Ahmed; Fourier, Catherine; Cremer, Robin

2004-01-01

Introduction Two generic paediatric mortality scoring systems have been validated in the paediatric intensive care unit (PICU). Paediatric RISk of Mortality (PRISM) requires an observation period of 24 hours, and PRISM III measures severity at two time points (at 12 hours and 24 hours) after admission, which represents a limitation for clinical trials that require earlier inclusion. The Paediatric Index of Mortality (PIM) is calculated 1 hour after admission but does not take into account the stabilization period following admission. To avoid these limitations, we chose to conduct assessments 4 hours after PICU admission. The aim of the present study was to validate PRISM, PRISM III and PIM at the time points for which they were developed, and to compare their accuracy in predicting mortality at those times with their accuracy at 4 hours. Methods All children admitted from June 1998 to May 2000 in one tertiary PICU were prospectively included. Data were collected to generate scores and predictions using PRISM, PRISM III and PIM. Results There were 802 consecutive admissions with 80 deaths. For the time points for which the scores were developed, observed and predicted mortality rates were significantly different for the three scores (P < 0.01) whereas all exhibited good discrimination (area under the receiver operating characteristic curve ≥0.83). At 4 hours after admission only the PIM had good calibration (P = 0.44), but all three scores exhibited good discrimination (area under the receiver operating characteristic curve ≥0.82). Conclusions Among the three scores calculated at 4 hours after admission, all had good discriminatory capacity but only the PIM score was well calibrated. Further studies are required before the PIM score at 4 hours can be used as an inclusion criterion in clinical trials. PMID:15312217

Application of Multivariable Analysis and FTIR-ATR Spectroscopy to the Prediction of Properties in Campeche Honey

PubMed Central

Pat, Lucio; Ali, Bassam; Guerrero, Armando; Córdova, Atl V.; Garduza, José P.

2016-01-01

Attenuated total reflectance-Fourier transform infrared spectrometry and chemometrics model was used for determination of physicochemical properties (pH, redox potential, free acidity, electrical conductivity, moisture, total soluble solids (TSS), ash, and HMF) in honey samples. The reference values of 189 honey samples of different botanical origin were determined using Association Official Analytical Chemists, (AOAC), 1990; Codex Alimentarius, 2001, International Honey Commission, 2002, methods. Multivariate calibration models were built using partial least squares (PLS) for the measurands studied. The developed models were validated using cross-validation and external validation; several statistical parameters were obtained to determine the robustness of the calibration models: (PCs) optimum number of components principal, (SECV) standard error of cross-validation, (R 2 cal) coefficient of determination of cross-validation, (SEP) standard error of validation, and (R 2 val) coefficient of determination for external validation and coefficient of variation (CV). The prediction accuracy for pH, redox potential, electrical conductivity, moisture, TSS, and ash was good, while for free acidity and HMF it was poor. The results demonstrate that attenuated total reflectance-Fourier transform infrared spectrometry is a valuable, rapid, and nondestructive tool for the quantification of physicochemical properties of honey. PMID:28070445

Development and validation of a risk prediction algorithm for the recurrence of suicidal ideation among general population with low mood.

PubMed

Liu, Y; Sareen, J; Bolton, J M; Wang, J L

2016-03-15

Suicidal ideation is one of the strongest predictors of recent and future suicide attempt. This study aimed to develop and validate a risk prediction algorithm for the recurrence of suicidal ideation among population with low mood 3035 participants from U.S National Epidemiologic Survey on Alcohol and Related Conditions with suicidal ideation at their lowest mood at baseline were included. The Alcohol Use Disorder and Associated Disabilities Interview Schedule, based on the DSM-IV criteria was used. Logistic regression modeling was conducted to derive the algorithm. Discrimination and calibration were assessed in the development and validation cohorts. In the development data, the proportion of recurrent suicidal ideation over 3 years was 19.5 (95% CI: 17.7, 21.5). The developed algorithm consisted of 6 predictors: age, feelings of emptiness, sudden mood changes, self-harm history, depressed mood in the past 4 weeks, interference with social activities in the past 4 weeks because of physical health or emotional problems and emptiness was the most important risk factor. The model had good discriminative power (C statistic=0.8273, 95% CI: 0.8027, 0.8520). The C statistic was 0.8091 (95% CI: 0.7786, 0.8395) in the external validation dataset and was 0.8193 (95% CI: 0.8001, 0.8385) in the combined dataset. This study does not apply to people with suicidal ideation who are not depressed. The developed risk algorithm for predicting the recurrence of suicidal ideation has good discrimination and excellent calibration. Clinicians can use this algorithm to stratify the risk of recurrence in patients and thus improve personalized treatment approaches, make advice and further intensive monitoring. Copyright © 2016 Elsevier B.V. All rights reserved.

A Novel Model for Predicting Incident Moderate to Severe Anemia and Iron Deficiency in Patients with Newly Diagnosed Ulcerative Colitis.

PubMed

Khan, Nabeel; Patel, Dhruvan; Shah, Yash; Yang, Yu-Xiao

2017-05-01

Anemia and iron deficiency are common complications of ulcerative colitis (UC). We aimed to develop and internally validate a prediction model for the incidence of moderate to severe anemia and iron deficiency anemia (IDA) in newly diagnosed patients with UC. Multivariable logistic regression was performed among a nationwide cohort of patients who were newly diagnosed with UC in the VA health-care system. Model development was performed in a random two-third of the total cohort and then validated in the remaining one-third of the cohort. As candidate predictors, we examined routinely available data at the time of UC diagnosis including demographics, medications, laboratory results, and endoscopy findings. A total of 789 patients met the inclusion criteria. For the outcome of moderate to severe anemia, age, albumin level and mild anemia at UC diagnosis were predictors selected for the model. The AUC for this model was 0.69 (95% CI 0.64-0.74). For the outcome of moderate to severe anemia with evidence of iron deficiency, the predictors included African-American ethnicity, mild anemia, age, and albumin level at UC diagnosis. The AUC was 0.76, (95% CI 0.69-0.82). Calibration was consistently good in all models (Hosmer-Lemeshow goodness of fit p > 0.05). The models performed similarly in the internal validation cohort. We developed and internally validated a prognostic model for predicting the risk of moderate to severe anemia and IDA among newly diagnosed patients with UC. This will help identify patients at high risk of these complications, who could benefit from surveillance and preventive measures.

Prognostic indices for early mortality in ischaemic stroke - meta-analysis.

PubMed

Mattishent, K; Kwok, C S; Mahtani, A; Pelpola, K; Myint, P K; Loke, Y K

2016-01-01

Several models have been developed to predict mortality in ischaemic stroke. We aimed to evaluate systematically the performance of published stroke prognostic scores. We searched MEDLINE and EMBASE in February 2014 for prognostic models (published between 2003 and 2014) used in predicting early mortality (<6 months) after ischaemic stroke. We evaluated discriminant ability of the tools through meta-analysis of the area under the curve receiver operating characteristic curve (AUROC) or c-statistic. We evaluated the following components of study validity: collection of prognostic variables, neuroimaging, treatment pathways and missing data. We identified 18 articles (involving 163 240 patients) reporting on the performance of prognostic models for mortality in ischaemic stroke, with 15 articles providing AUC for meta-analysis. Most studies were either retrospective, or post hoc analyses of prospectively collected data; all but three reported validation data. The iSCORE had the largest number of validation cohorts (five) within our systematic review and showed good performance in four different countries, pooled AUC 0.84 (95% CI 0.82-0.87). We identified other potentially useful prognostic tools that have yet to be as extensively validated as iSCORE - these include SOAR (2 studies, pooled AUC 0.79, 95% CI 0.78-0.80), GWTG (2 studies, pooled AUC 0.72, 95% CI 0.72-0.72) and PLAN (1 study, pooled AUC 0.85, 95% CI 0.84-0.87). Our meta-analysis has identified and summarized the performance of several prognostic scores with modest to good predictive accuracy for early mortality in ischaemic stroke, with the iSCORE having the broadest evidence base. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A Comparison of Three Job Engagement Measures: Examining their Factorial and Criterion-Related Validity.

PubMed

Wefald, Andrew J; Mills, Maura J; Smith, Michael R; Downey, Ronald G

2012-03-01

Engagement is an emerging job attitude that purports to measure employees' psychological presence at and involvement in their work. This research compares three academic approaches to engagement, and makes recommendations regarding the most appropriate conceptualisation and measurement of the construct in future research. The current research also investigates whether any of these three approaches to engagement contribute unique variance to the prediction of turnover intentions above and beyond the predictive capacity of alternative constructs. An online survey was taken by 382 employees and managers from a mid-sized financial institution. Results failed to support either a multi- or unidimensional factor structure for the Utrecht Work Engagement Scale (UWES) engagement measure. For the Shirom-Melamed Vigor Measure (SMVM), a multi-dimensional structure was identified as a good fit, while a unidimensional structure fit poorly. The uni-factorial structure of Britt's engagement measure was confirmed. The Schaufeli measure of engagement was a strong predictor of work outcomes; however, when controlling for job satisfaction and affective commitment, that measure lost its ability to predict intentions to leave. Two components of the Shirom vigor measure held their predictive validity. Collectively, these findings suggest that the Shirom vigor measure may provide better insight into whether and how much a person is 'into' his or her job. The Schaufeli measure was a good predictor of important work outcomes, but when job satisfaction and affective commitment were controlled, it lost its predictive validity. We were not able to confirm the three-factor structure of the Schaufeli measure. Two components of the Shirom vigor measure predicted turnover intentions after controlling for job satisfaction and affective commitment, suggesting less overlap with those constructs than the Schaufeli measure of engagement. This research adds important information on the nature of engagement and is expected to contribute toward a better understanding of the construct itself, as well as its measurement. © 2011 The Authors. Applied Psychology: Health and Well-Being © 2011 The International Association of Applied Psychology.

Hyperspectral imaging using near infrared spectroscopy to monitor coat thickness uniformity in the manufacture of a transdermal drug delivery system.

PubMed

Pavurala, Naresh; Xu, Xiaoming; Krishnaiah, Yellela S R

2017-05-15

Hyperspectral imaging using near infrared spectroscopy (NIRS) integrates spectroscopy and conventional imaging to obtain both spectral and spatial information of materials. The non-invasive and rapid nature of hyperspectral imaging using NIRS makes it a valuable process analytical technology (PAT) tool for in-process monitoring and control of the manufacturing process for transdermal drug delivery systems (TDS). The focus of this investigation was to develop and validate the use of Near Infra-red (NIR) hyperspectral imaging to monitor coat thickness uniformity, a critical quality attribute (CQA) for TDS. Chemometric analysis was used to process the hyperspectral image and a partial least square (PLS) model was developed to predict the coat thickness of the TDS. The goodness of model fit and prediction were 0.9933 and 0.9933, respectively, indicating an excellent fit to the training data and also good predictability. The % Prediction Error (%PE) for internal and external validation samples was less than 5% confirming the accuracy of the PLS model developed in the present study. The feasibility of the hyperspectral imaging as a real-time process analytical tool for continuous processing was also investigated. When the PLS model was applied to detect deliberate variation in coating thickness, it was able to predict both the small and large variations as well as identify coating defects such as non-uniform regions and presence of air bubbles. Published by Elsevier B.V.

Anthropometric predictors of body fat in a large population of 9-year-old school-aged children.

PubMed

Almeida, Sílvia M; Furtado, José M; Mascarenhas, Paulo; Ferraz, Maria E; Silva, Luís R; Ferreira, José C; Monteiro, Mariana; Vilanova, Manuel; Ferraz, Fernando P

2016-09-01

To develop and cross-validate predictive models for percentage body fat (%BF) from anthropometric measurements [including BMI z -score (zBMI) and calf circumference (CC)] excluding skinfold thickness. A descriptive study was carried out in 3,084 pre-pubertal children. Regression models and neural network were developed with %BF measured by Bioelectrical Impedance Analysis (BIA) as the dependent variables and age, sex and anthropometric measurements as independent predictors. All %BF grade predictive models presented a good global accuracy (≥91.3%) for obesity discrimination. Both overfat/obese and obese prediction models presented respectively good sensitivity (78.6% and 71.0%), specificity (98.0% and 99.2%) and reliability for positive or negative test results (≥82% and ≥96%). For boys, the order of parameters, by relative weight in the predictive model, was zBMI, height, waist-circumference-to-height-ratio (WHtR) squared variable (_Q), age, weight, CC_Q and hip circumference (HC)_Q (adjusted r 2  = 0.847 and RMSE = 2.852); for girls it was zBMI, WHtR_Q, height, age, HC_Q and CC_Q (adjusted r 2  = 0.872 and RMSE = 2.171). %BF can be graded and predicted with relative accuracy from anthropometric measurements excluding skinfold thickness. Fitness and cross-validation results showed that our multivariable regression model performed better in this population than did some previously published models.

Temporal and external validation of a prediction model for adverse outcomes among inpatients with diabetes.

PubMed

Adderley, N J; Mallett, S; Marshall, T; Ghosh, S; Rayman, G; Bellary, S; Coleman, J; Akiboye, F; Toulis, K A; Nirantharakumar, K

2018-06-01

To temporally and externally validate our previously developed prediction model, which used data from University Hospitals Birmingham to identify inpatients with diabetes at high risk of adverse outcome (mortality or excessive length of stay), in order to demonstrate its applicability to other hospital populations within the UK. Temporal validation was performed using data from University Hospitals Birmingham and external validation was performed using data from both the Heart of England NHS Foundation Trust and Ipswich Hospital. All adult inpatients with diabetes were included. Variables included in the model were age, gender, ethnicity, admission type, intensive therapy unit admission, insulin therapy, albumin, sodium, potassium, haemoglobin, C-reactive protein, estimated GFR and neutrophil count. Adverse outcome was defined as excessive length of stay or death. Model discrimination in the temporal and external validation datasets was good. In temporal validation using data from University Hospitals Birmingham, the area under the curve was 0.797 (95% CI 0.785-0.810), sensitivity was 70% (95% CI 67-72) and specificity was 75% (95% CI 74-76). In external validation using data from Heart of England NHS Foundation Trust, the area under the curve was 0.758 (95% CI 0.747-0.768), sensitivity was 73% (95% CI 71-74) and specificity was 66% (95% CI 65-67). In external validation using data from Ipswich, the area under the curve was 0.736 (95% CI 0.711-0.761), sensitivity was 63% (95% CI 59-68) and specificity was 69% (95% CI 67-72). These results were similar to those for the internally validated model derived from University Hospitals Birmingham. The prediction model to identify patients with diabetes at high risk of developing an adverse event while in hospital performed well in temporal and external validation. The externally validated prediction model is a novel tool that can be used to improve care pathways for inpatients with diabetes. Further research to assess clinical utility is needed. © 2018 Diabetes UK.

Risk prediction models of breast cancer: a systematic review of model performances.

PubMed

Anothaisintawee, Thunyarat; Teerawattananon, Yot; Wiratkapun, Chollathip; Kasamesup, Vijj; Thakkinstian, Ammarin

2012-05-01

The number of risk prediction models has been increasingly developed, for estimating about breast cancer in individual women. However, those model performances are questionable. We therefore have conducted a study with the aim to systematically review previous risk prediction models. The results from this review help to identify the most reliable model and indicate the strengths and weaknesses of each model for guiding future model development. We searched MEDLINE (PubMed) from 1949 and EMBASE (Ovid) from 1974 until October 2010. Observational studies which constructed models using regression methods were selected. Information about model development and performance were extracted. Twenty-five out of 453 studies were eligible. Of these, 18 developed prediction models and 7 validated existing prediction models. Up to 13 variables were included in the models and sample sizes for each study ranged from 550 to 2,404,636. Internal validation was performed in four models, while five models had external validation. Gail and Rosner and Colditz models were the significant models which were subsequently modified by other scholars. Calibration performance of most models was fair to good (expected/observe ratio: 0.87-1.12), but discriminatory accuracy was poor to fair both in internal validation (concordance statistics: 0.53-0.66) and in external validation (concordance statistics: 0.56-0.63). Most models yielded relatively poor discrimination in both internal and external validation. This poor discriminatory accuracy of existing models might be because of a lack of knowledge about risk factors, heterogeneous subtypes of breast cancer, and different distributions of risk factors across populations. In addition the concordance statistic itself is insensitive to measure the improvement of discrimination. Therefore, the new method such as net reclassification index should be considered to evaluate the improvement of the performance of a new develop model.

Predicting Survival of De Novo Metastatic Breast Cancer in Asian Women: Systematic Review and Validation Study

PubMed Central

Miao, Hui; Hartman, Mikael; Bhoo-Pathy, Nirmala; Lee, Soo-Chin; Taib, Nur Aishah; Tan, Ern-Yu; Chan, Patrick; Moons, Karel G. M.; Wong, Hoong-Seam; Goh, Jeremy; Rahim, Siti Mastura; Yip, Cheng-Har; Verkooijen, Helena M.

2014-01-01

Background In Asia, up to 25% of breast cancer patients present with distant metastases at diagnosis. Given the heterogeneous survival probabilities of de novo metastatic breast cancer, individual outcome prediction is challenging. The aim of the study is to identify existing prognostic models for patients with de novo metastatic breast cancer and validate them in Asia. Materials and Methods We performed a systematic review to identify prediction models for metastatic breast cancer. Models were validated in 642 women with de novo metastatic breast cancer registered between 2000 and 2010 in the Singapore Malaysia Hospital Based Breast Cancer Registry. Survival curves for low, intermediate and high-risk groups according to each prognostic score were compared by log-rank test and discrimination of the models was assessed by concordance statistic (C-statistic). Results We identified 16 prediction models, seven of which were for patients with brain metastases only. Performance status, estrogen receptor status, metastatic site(s) and disease-free interval were the most common predictors. We were able to validate nine prediction models. The capacity of the models to discriminate between poor and good survivors varied from poor to fair with C-statistics ranging from 0.50 (95% CI, 0.48–0.53) to 0.63 (95% CI, 0.60–0.66). Conclusion The discriminatory performance of existing prediction models for de novo metastatic breast cancer in Asia is modest. Development of an Asian-specific prediction model is needed to improve prognostication and guide decision making. PMID:24695692

Predicting the risk for colorectal cancer with personal characteristics and fecal immunochemical test.

PubMed

Li, Wen; Zhao, Li-Zhong; Ma, Dong-Wang; Wang, De-Zheng; Shi, Lei; Wang, Hong-Lei; Dong, Mo; Zhang, Shu-Yi; Cao, Lei; Zhang, Wei-Hua; Zhang, Xi-Peng; Zhang, Qing-Huai; Yu, Lin; Qin, Hai; Wang, Xi-Mo; Chen, Sam Li-Sheng

2018-05-01

We aimed to predict colorectal cancer (CRC) based on the demographic features and clinical correlates of personal symptoms and signs from Tianjin community-based CRC screening data.A total of 891,199 residents who were aged 60 to 74 and were screened in 2012 were enrolled. The Lasso logistic regression model was used to identify the predictors for CRC. Predictive validity was assessed by the receiver operating characteristic (ROC) curve. Bootstrapping method was also performed to validate this prediction model.CRC was best predicted by a model that included age, sex, education level, occupations, diarrhea, constipation, colon mucosa and bleeding, gallbladder disease, a stressful life event, family history of CRC, and a positive fecal immunochemical test (FIT). The area under curve (AUC) for the questionnaire with a FIT was 84% (95% CI: 82%-86%), followed by 76% (95% CI: 74%-79%) for a FIT alone, and 73% (95% CI: 71%-76%) for the questionnaire alone. With 500 bootstrap replications, the estimated optimism (<0.005) shows good discrimination in validation of prediction model.A risk prediction model for CRC based on a series of symptoms and signs related to enteric diseases in combination with a FIT was developed from first round of screening. The results of the current study are useful for increasing the awareness of high-risk subjects and for individual-risk-guided invitations or strategies to achieve mass screening for CRC.

Validity and reliability of an online visual-spatial working memory task for self-reliant administration in school-aged children.

PubMed

Van de Weijer-Bergsma, Eva; Kroesbergen, Evelyn H; Prast, Emilie J; Van Luit, Johannes E H

2015-09-01

Working memory is an important predictor of academic performance, and of math performance in particular. Most working memory tasks depend on one-to-one administration by a testing assistant, which makes the use of such tasks in large-scale studies time-consuming and costly. Therefore, an online, self-reliant visual-spatial working memory task (the Lion game) was developed for primary school children (6-12 years of age). In two studies, the validity and reliability of the Lion game were investigated. The results from Study 1 (n = 442) indicated satisfactory six-week test-retest reliability, excellent internal consistency, and good concurrent and predictive validity. The results from Study 2 (n = 5,059) confirmed the results on the internal consistency and predictive validity of the Lion game. In addition, multilevel analysis revealed that classroom membership influenced Lion game scores. We concluded that the Lion game is a valid and reliable instrument for the online computerized and self-reliant measurement of visual-spatial working memory (i.e., updating).

Risk model of prolonged intensive care unit stay in Chinese patients undergoing heart valve surgery.

PubMed

Wang, Chong; Zhang, Guan-xin; Zhang, Hao; Lu, Fang-lin; Li, Bai-ling; Xu, Ji-bin; Han, Lin; Xu, Zhi-yun

2012-11-01

The aim of this study was to develop a preoperative risk prediction model and an scorecard for prolonged intensive care unit length of stay (PrlICULOS) in adult patients undergoing heart valve surgery. This is a retrospective observational study of collected data on 3925 consecutive patients older than 18 years, who had undergone heart valve surgery between January 2000 and December 2010. Data were randomly split into a development dataset (n=2401) and a validation dataset (n=1524). A multivariate logistic regression analysis was undertaken using the development dataset to identify independent risk factors for PrlICULOS. Performance of the model was then assessed by observed and expected rates of PrlICULOS on the development and validation dataset. Model calibration and discriminatory ability were analysed by the Hosmer-Lemeshow goodness-of-fit statistic and the area under the receiver operating characteristic (ROC) curve, respectively. There were 491 patients that required PrlICULOS (12.5%). Preoperative independent predictors of PrlICULOS are shown with odds ratio as follows: (1) age, 1.4; (2) chronic obstructive pulmonary disease (COPD), 1.8; (3) atrial fibrillation, 1.4; (4) left bundle branch block, 2.7; (5) ejection fraction, 1.4; (6) left ventricle weight, 1.5; (7) New York Heart Association class III-IV, 1.8; (8) critical preoperative state, 2.0; (9) perivalvular leakage, 6.4; (10) tricuspid valve replacement, 3.8; (11) concurrent CABG, 2.8; and (12) concurrent other cardiac surgery, 1.8. The Hosmer-Lemeshow goodness-of-fit statistic was not statistically significant in both development and validation dataset (P=0.365 vs P=0.310). The ROC curve for the prediction of PrlICULOS in development and validation dataset was 0.717 and 0.700, respectively. We developed and validated a local risk prediction model for PrlICULOS after adult heart valve surgery. This model can be used to calculate patient-specific risk with an equivalent predicted risk at our centre in future clinical practice. Copyright © 2012 Australian and New Zealand Society of Cardiac and Thoracic Surgeons (ANZSCTS) and the Cardiac Society of Australia and New Zealand (CSANZ). Published by Elsevier B.V. All rights reserved.

Prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy: a systematic review and external validation study.

PubMed

Hilkens, N A; Algra, A; Greving, J P

2016-01-01

ESSENTIALS: Prediction models may help to identify patients at high risk of bleeding on antiplatelet therapy. We identified existing prediction models for bleeding and validated them in patients with cerebral ischemia. Five prediction models were identified, all of which had some methodological shortcomings. Performance in patients with cerebral ischemia was poor. Background Antiplatelet therapy is widely used in secondary prevention after a transient ischemic attack (TIA) or ischemic stroke. Bleeding is the main adverse effect of antiplatelet therapy and is potentially life threatening. Identification of patients at increased risk of bleeding may help target antiplatelet therapy. This study sought to identify existing prediction models for intracranial hemorrhage or major bleeding in patients on antiplatelet therapy and evaluate their performance in patients with cerebral ischemia. We systematically searched PubMed and Embase for existing prediction models up to December 2014. The methodological quality of the included studies was assessed with the CHARMS checklist. Prediction models were externally validated in the European Stroke Prevention Study 2, comprising 6602 patients with a TIA or ischemic stroke. We assessed discrimination and calibration of included prediction models. Five prediction models were identified, of which two were developed in patients with previous cerebral ischemia. Three studies assessed major bleeding, one studied intracerebral hemorrhage and one gastrointestinal bleeding. None of the studies met all criteria of good quality. External validation showed poor discriminative performance, with c-statistics ranging from 0.53 to 0.64 and poor calibration. A limited number of prediction models is available that predict intracranial hemorrhage or major bleeding in patients on antiplatelet therapy. The methodological quality of the models varied, but was generally low. Predictive performance in patients with cerebral ischemia was poor. In order to reliably predict the risk of bleeding in patients with cerebral ischemia, development of a prediction model according to current methodological standards is needed. © 2015 International Society on Thrombosis and Haemostasis.

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

PubMed

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

2015-10-01

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

An updated PREDICT breast cancer prognostication and treatment benefit prediction model with independent validation.

PubMed

Candido Dos Reis, Francisco J; Wishart, Gordon C; Dicks, Ed M; Greenberg, David; Rashbass, Jem; Schmidt, Marjanka K; van den Broek, Alexandra J; Ellis, Ian O; Green, Andrew; Rakha, Emad; Maishman, Tom; Eccles, Diana M; Pharoah, Paul D P

2017-05-22

PREDICT is a breast cancer prognostic and treatment benefit model implemented online. The overall fit of the model has been good in multiple independent case series, but PREDICT has been shown to underestimate breast cancer specific mortality in women diagnosed under the age of 40. Another limitation is the use of discrete categories for tumour size and node status resulting in 'step' changes in risk estimates on moving between categories. We have refitted the PREDICT prognostic model using the original cohort of cases from East Anglia with updated survival time in order to take into account age at diagnosis and to smooth out the survival function for tumour size and node status. Multivariable Cox regression models were used to fit separate models for ER negative and ER positive disease. Continuous variables were fitted using fractional polynomials and a smoothed baseline hazard was obtained by regressing the baseline cumulative hazard for each patients against time using fractional polynomials. The fit of the prognostic models were then tested in three independent data sets that had also been used to validate the original version of PREDICT. In the model fitting data, after adjusting for other prognostic variables, there is an increase in risk of breast cancer specific mortality in younger and older patients with ER positive disease, with a substantial increase in risk for women diagnosed before the age of 35. In ER negative disease the risk increases slightly with age. The association between breast cancer specific mortality and both tumour size and number of positive nodes was non-linear with a more marked increase in risk with increasing size and increasing number of nodes in ER positive disease. The overall calibration and discrimination of the new version of PREDICT (v2) was good and comparable to that of the previous version in both model development and validation data sets. However, the calibration of v2 improved over v1 in patients diagnosed under the age of 40. The PREDICT v2 is an improved prognostication and treatment benefit model compared with v1. The online version should continue to aid clinical decision making in women with early breast cancer.

Reliability and validity of the Microsoft Kinect for evaluating static foot posture

PubMed Central

2013-01-01

Background The evaluation of foot posture in a clinical setting is useful to screen for potential injury, however disagreement remains as to which method has the greatest clinical utility. An inexpensive and widely available imaging system, the Microsoft Kinect™, may possess the characteristics to objectively evaluate static foot posture in a clinical setting with high accuracy. The aim of this study was to assess the intra-rater reliability and validity of this system for assessing static foot posture. Methods Three measures were used to assess static foot posture; traditional visual observation using the Foot Posture Index (FPI), a 3D motion analysis (3DMA) system and software designed to collect and analyse image and depth data from the Kinect. Spearman’s rho was used to assess intra-rater reliability and concurrent validity of the Kinect to evaluate foot posture, and a linear regression was used to examine the ability of the Kinect to predict total visual FPI score. Results The Kinect demonstrated moderate to good intra-rater reliability for four FPI items of foot posture (ρ = 0.62 to 0.78) and moderate to good correlations with the 3DMA system for four items of foot posture (ρ = 0.51 to 0.85). In contrast, intra-rater reliability of visual FPI items was poor to moderate (ρ = 0.17 to 0.63), and correlations with the Kinect and 3DMA systems were poor (absolute ρ = 0.01 to 0.44). Kinect FPI items with moderate to good reliability predicted 61% of the variance in total visual FPI score. Conclusions The majority of the foot posture items derived using the Kinect were more reliable than the traditional visual assessment of FPI, and were valid when compared to a 3DMA system. Individual foot posture items recorded using the Kinect were also shown to predict a moderate degree of variance in the total visual FPI score. Combined, these results support the future potential of the Kinect to accurately evaluate static foot posture in a clinical setting. PMID:23566934

Development and Validation of Discriminant Analysis Models for Student Loan Defaultees and Non-Defaultees.

ERIC Educational Resources Information Center

Myers, Greeley; Siera, Steven

1980-01-01

Default on guaranteed student loans has been increasing. The use of discriminant analysis as a technique to identify "good" v "bad" student loans based on information available from the loan application is discussed. Research to test the ability of models to such predictions is reported. (Author/MLW)

Social Support, Network Structure, and the Inventory of Socially Supportive Behaviors.

ERIC Educational Resources Information Center

Stokes, Joseph P.; Wilson, Diane Grimard

The Inventory of Socially Supportive Behaviors (ISSB) appears to be a satisfactory measure of social support with good reliability and some evidence of validity. To investigate the dimensionality of the ISSB through factor analytic procedures and to predict social support from social network variables, 179 college students (97 male, 82 female)…

Comparing current definitions of return to work: a measurement approach.

PubMed

Steenstra, I A; Lee, H; de Vroome, E M M; Busse, J W; Hogg-Johnson, S J

2012-09-01

Return-to-work (RTW) status is an often used outcome in work and health research. In low back pain, work is regarded as a normal activity a worker should return to in order to fully recover. Comparing outcomes across studies and even jurisdictions using different definitions of RTW can be challenging for readers in general and when performing a systematic review in particular. In this study, the measurement properties of previously defined RTW outcomes were examined with data from two studies from two countries. Data on RTW in low back pain (LBP) from the Canadian Early Claimant Cohort (ECC); a workers' compensation based study, and the Dutch Amsterdam Sherbrooke Evaluation (ASE) study were analyzed. Correlations between outcomes, differences in predictive validity when using different outcomes and construct validity when comparing outcomes to a functional status outcome were analyzed. In the ECC all definitions were highly correlated and performed similarly in predictive validity. When compared to functional status, RTW definitions in the ECC study performed fair to good on all time points. In the ASE study all definitions were highly correlated and performed similarly in predictive validity. The RTW definitions, however, failed to compare or compared poorly with functional status. Only one definition compared fairly on one time point. Differently defined outcomes are highly correlated, give similar results in prediction, but seem to differ in construct validity when compared to functional status depending on societal context or possibly birth cohort. Comparison of studies using different RTW definitions appears valid as long as RTW status is not considered as a measure of functional status.

Hybrid optimal descriptors as a tool to predict skin sensitization in accordance to OECD principles.

PubMed

Toropova, Alla P; Toropov, Andrey A

2017-06-05

Skin sensitization (allergic contact dermatitis) is a widespread problem arising from the contact of chemicals with the skin. The detection of molecular features with undesired effect for skin is complex task owing to unclear biochemical mechanisms and unclearness of conditions of action of chemicals to skin. The development of computational methods for estimation of this endpoint in order to reduce animal testing is recommended (Cosmetics Directive EC regulation 1907/2006; EU Regulation, Regulation, 1223/2009). The CORAL software (http://www.insilico.eu/coral) gives good predictive models for the skin sensitization. Simplified molecular input-line entry system (SMILES) together with molecular graph are used to represent the molecular structure for these models. So-called hybrid optimal descriptors are used to establish quantitative structure-activity relationships (QSARs). The aim of this study is the estimation of the predictive potential of the hybrid descriptors. Three different distributions into the training (≈70%), calibration (≈15%), and validation (≈15%) sets are studied. QSAR for these three distributions are built up with using the Monte Carlo technique. The statistical characteristics of these models for external validation set are used as a measure of predictive potential of these models. The best model, according to the above criterion, is characterized by n validation =29, r 2 validation =0.8596, RMSE validation =0.489. Mechanistic interpretation and domain of applicability for these models are defined. Copyright © 2017 Elsevier B.V. All rights reserved.

Does my patient have chronic Chagas disease? Development and temporal validation of a diagnostic risk score.

PubMed

Brasil, Pedro Emmanuel Alvarenga Americano do; Xavier, Sergio Salles; Holanda, Marcelo Teixeira; Hasslocher-Moreno, Alejandro Marcel; Braga, José Ueleres

2016-01-01

With the globalization of Chagas disease, unexperienced health care providers may have difficulties in identifying which patients should be examined for this condition. This study aimed to develop and validate a diagnostic clinical prediction model for chronic Chagas disease. This diagnostic cohort study included consecutive volunteers suspected to have chronic Chagas disease. The clinical information was blindly compared to serological tests results, and a logistic regression model was fit and validated. The development cohort included 602 patients, and the validation cohort included 138 patients. The Chagas disease prevalence was 19.9%. Sex, age, referral from blood bank, history of living in a rural area, recognizing the kissing bug, systemic hypertension, number of siblings with Chagas disease, number of relatives with a history of stroke, ECG with low voltage, anterosuperior divisional block, pathologic Q wave, right bundle branch block, and any kind of extrasystole were included in the final model. Calibration and discrimination in the development and validation cohorts (ROC AUC 0.904 and 0.912, respectively) were good. Sensitivity and specificity analyses showed that specificity reaches at least 95% above the predicted 43% risk, while sensitivity is at least 95% below the predicted 7% risk. Net benefit decision curves favor the model across all thresholds. A nomogram and an online calculator (available at http://shiny.ipec.fiocruz.br:3838/pedrobrasil/chronic_chagas_disease_prediction/) were developed to aid in individual risk estimation.

A preliminary correlation of the orbiter stability and control aerodynamics from the first two Space Shuttle flights /STS-1 & 2/ with preflight predictions

NASA Technical Reports Server (NTRS)

Underwood, J. M.; Cooke, D. R.

1982-01-01

A correlation of the stability and control derivatives from flight (STS-1 & 2) with preflight predictions is presented across the Mach range from 0.9 to 25. Flight data obtained from specially designed flight test maneuvers as well as from conventional bank maneuvers generally indicate good agreement with predicted data. However, the vehicle appears to be lateral-directionally more stable than predicted in the transonic regime. Aerodynamic 'reasonableness tests' are employed to test for validity of flight data. The importance of testing multiple models in multiple wind tunnels at the same test conditions is demonstrated.

Validation of the Arabic Version of the Iowa Infant Feeding Attitude Scale among Lebanese Women.

PubMed

Charafeddine, Lama; Tamim, Hani; Soubra, Marwa; de la Mora, Arlene; Nabulsi, Mona

2016-05-01

There is need in the Arab world for validated instruments that can reliably assess infant feeding attitudes among women. The 17-item Iowa Infant Feeding Attitude Scale (IIFAS) has consistently shown good reliability and validity in different cultures and the ability to predict breastfeeding intention and exclusivity. This study assessed the psychometric properties of the Arabic version of the IIFAS (IIFAS-A). After translating to classical Arabic and back-translating to English, the IIFAS-A was pilot tested among 20 women for comprehension, clarity, length, and cultural appropriateness. The IIFAS-A was then validated among 170 women enrolled in a breastfeeding promotion and support clinical trial in Lebanon. The IIFAS-A showed acceptable internal consistency reliability (Cronbach's α = 0.640), with principal components analysis revealing that it is unidimensional. The 17 items had good interitem reliabilities ranging between 0.599 and 0.665. The number of breastfed children was the only predictor of the overall IIFAS-A score in a multivariate stepwise regression model (β = 1.531, P < .0001). The 17-item IIFAS-A is a reliable and valid instrument for measuring women's infant feeding attitudes in the Arab context. © The Author(s) 2015.

Development and external validation of a prediction rule for an unfavorable course of late-life depression: A multicenter cohort study.

PubMed

Maarsingh, O R; Heymans, M W; Verhaak, P F; Penninx, B W J H; Comijs, H C

2018-08-01

Given the poor prognosis of late-life depression, it is crucial to identify those at risk. Our objective was to construct and validate a prediction rule for an unfavourable course of late-life depression. For development and internal validation of the model, we used The Netherlands Study of Depression in Older Persons (NESDO) data. We included participants with a major depressive disorder (MDD) at baseline (n = 270; 60-90 years), assessed with the Composite International Diagnostic Interview (CIDI). For external validation of the model, we used The Netherlands Study of Depression and Anxiety (NESDA) data (n = 197; 50-66 years). The outcome was MDD after 2 years of follow-up, assessed with the CIDI. Candidate predictors concerned sociodemographics, psychopathology, physical symptoms, medication, psychological determinants, and healthcare setting. Model performance was assessed by calculating calibration and discrimination. 111 subjects (41.1%) had MDD after 2 years of follow-up. Independent predictors of MDD after 2 years were (older) age, (early) onset of depression, severity of depression, anxiety symptoms, comorbid anxiety disorder, fatigue, and loneliness. The final model showed good calibration and reasonable discrimination (AUC of 0.75; 0.70 after external validation). The strongest individual predictor was severity of depression (AUC of 0.69; 0.68 after external validation). The model was developed and validated in The Netherlands, which could affect the cross-country generalizability. Based on rather simple clinical indicators, it is possible to predict the 2-year course of MDD. The prediction rule can be used for monitoring MDD patients and identifying those at risk of an unfavourable outcome. Copyright © 2018 Elsevier B.V. All rights reserved.

The wavelength dependence and an interpretation of the photometric parameters of Mars

NASA Technical Reports Server (NTRS)

Weaver, W. R.; Meador, W. E.

1976-01-01

The photometric function developed by Meador and Weaver has been used with photometric data from the bright desert areas of Mars to determine the wavelength dependence of the three photometric parameters of that function and to provide some predictions about the physical properties of the surface. Knowledge of the parameters permits the brightness of these areas of Mars to be determined for scattering geometry over the wavelength range of 0.45 to 0.70 micrometer. The changes in the photometric parameters with wavelength are shown to be consistent with qualitative theoretical predictions, and the predictions of surface properties are shown to be consistent with conditions that might exist in these regions of Mars. The photometric function is shown to have good potential as a diagnostic tool for the determination of surface properties, and the consistency of the behavior of the photometric parameters is shown to be good support for the validity of the photometric function.

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.

Factor structure, validity and reliability of the Cambridge Worry Scale in a pregnant population.

PubMed

Green, Josephine M; Kafetsios, Konstantinos; Statham, Helen E; Snowdon, Claire M

2003-11-01

This article presents the Cambridge Worry Scale (CWS), a content-based measure for assessing worries, and discusses its psychometric properties based on a longitudinal study of 1,207 pregnant women. Principal components analysis revealed a four-factor structure of women's concerns during pregnancy: socio-medical, own health, socio-economic and relational. The measure demonstrated good reliability and validity. Total CWS scores were strongly associated with state and trait anxiety (convergent validity) but also had significant and unique predictive value for mood outcomes (discriminant validity). The CWS discriminated better between women with different reproductive histories than measures of state and trait anxiety. We conclude that the CWS is a reliable and valid tool for assessing the extent and content of worries in specific situations.

The Meaning and Predictive Value of Self-rated Mental Health among Persons with a Mental Health Problem.

PubMed

McAlpine, Donna D; McCreedy, Ellen; Alang, Sirry

2018-06-01

Self-rated health is a valid measure of health that predicts quality of life, morbidity, and mortality. Its predictive value reflects a conceptualization of health that goes beyond a traditional medical model. However, less is known about self-rated mental health (SRMH). Using data from the Medical Expenditure Panel Survey ( N = 2,547), we examine how rating your mental health as good-despite meeting criteria for a mental health problem-predicts outcomes. We found that 62% of people with a mental health problem rated their mental health positively. Persons who rated their mental health as good (compared to poor) had 30% lower odds of having a mental health problem at follow-up. Even without treatment, persons with a mental health problem did better if they perceived their mental health positively. SRMH might comprise information beyond the experience of symptoms. Understanding the unobserved information individuals incorporate into SRMH will help us improve screening and treatment interventions.

The photographic knee pain map: locating knee pain with an instrument developed for diagnostic, communication and research purposes.

PubMed

Elson, D W; Jones, S; Caplan, N; Stewart, S; St Clair Gibson, A; Kader, D F

2011-12-01

Pain maps are used to determine the location of pain. Knee pain maps have previously been described, but only one study has reported on reliability and none report validity. The present study describes the generation of a photographic knee pain map (PKPM) together with its validity and reliability. A photographic representation of a pair of knees was chosen by 26 patients, (66.7%) from a group of 39. The selected photograph was modified and a template of anatomical zones was generated. The opinions of 25 independent subject matter experts were canvassed and validity ratios calculated for these zones, ranged from 0.28 to 0.84. Hypothetical comparisons were made between the PKPM and an alternative knee pain map, in a cross-sectional group of 26 patients (35 knees). Convergent patterns of validity were found where hypothesised. Reliability was determined using a different cohort of 44 patients (58 knees) who completed the PKPM before and after a sampling delay. Four of these patients were excluded with a short sampling delay. Calculated agreement of test-retest reproducibility was fair to good. All of the completed PKPM (151 knees) were then subject to further analysis where inter-rater reproducibility was good to very good and intra-rater reproducibility was very good. The PKPM is readily accessible to patients with low completion burden. It is both valid and reliable and we suggest it can be used in both clinical and research settings. Further studies are planned to explore its predictive ability as a diagnostic tool. The PKPM can be found at www.photographickneepainmap.com. Copyright © 2010 Elsevier B.V. All rights reserved.

External Validation and Evaluation of Reliability and Validity of the Modified Seoul National University Renal Stone Complexity Scoring System to Predict Stone-Free Status After Retrograde Intrarenal Surgery.

PubMed

Park, Juhyun; Kang, Minyong; Jeong, Chang Wook; Oh, Sohee; Lee, Jeong Woo; Lee, Seung Bae; Son, Hwancheol; Jeong, Hyeon; Cho, Sung Yong

2015-08-01

The modified Seoul National University Renal Stone Complexity scoring system (S-ReSC-R) for retrograde intrarenal surgery (RIRS) was developed as a tool to predict stone-free rate (SFR) after RIRS. We externally validated the S-ReSC-R. We retrospectively reviewed 159 patients who underwent RIRS. The S-ReSC-R was assigned from 1 to 12 according to the location and number of sites involved. The stone-free status was defined as no evidence of a stone or with clinically insignificant residual fragment stones less than 2 mm. Interobserver and test-retest reliabilities were evaluated. Statistical performance of the prediction model was assessed by its predictive accuracy, predictive probability, and clinical usefulness. Overall SFR was 73.0%. The SFRs were 86.7%, 70.2%, and 48.6% in low-score (1-2), intermediate-score (3-4), and high-score (5-12) groups, respectively (p<0.001). External validation of S-ReSC-R revealed an area under the curve (AUC) of 0.731 (95% CI 0.650-0.813). The AUC of the three-titered S-ReSC-R was 0.701 (95% CI 0.609-0.794). The calibration plot showed that the predicted probability of SFR had a concordance comparable to that of observed frequency. The Hosmer-Lemeshow goodness of fit test revealed a p-value of 0.01 for the S-ReSC-R and 0.90 for the three-titered S-ReSC-R. Interobserver and test-retest reliabilities revealed an almost perfect level of agreement. The present study proved the predictive value of S-ReSC-R to predict SFR following RIRS in an independent cohort. Interobserver and test-retest reliabilities confirmed that S-ReSC-R was reliable and valid.

Comparing measures of attachment: "To whom one turns in times of stress", parental warmth, and partner satisfaction.

PubMed

Lindberg, Marc A; Fugett, April; Thomas, Stuart W

2012-01-01

The Attachment and Clinical Issues Questionnaire (ACIQ; M. A. Lindberg & S. W. Thomas, 2011), was developed over an 18-year period containing 29 scales. The purpose of the present study was to test (a) the validity of the attachment scales in terms of how they predict to whom one turns in times of stress and for affective sharing, and (b) how the attachment scales compared with the Experiences in Close Relationship Questionnaire (ECR) in terms of concurrent, convergent, and discriminant evidence. The relevant secure scales of the ACIQ predicted to whom one turned in study 1, and study 2 demonstrated good convergent evidence with the ECR, but superior concurrent evidence in predicting partner satisfaction, and superior discriminant evidence in differentially correlating with mother and father warmth. Thus, the ACIQ passed essential validity and psychometric tests and was a more robust measure than the ECR with these defining characteristics of attachment.

Performance prediction of a ducted rocket combustor

NASA Astrophysics Data System (ADS)

Stowe, Robert

2001-07-01

The ducted rocket is a supersonic flight propulsion system that takes the exhaust from a solid fuel gas generator, mixes it with air, and burns it to produce thrust. To develop such systems, the use of numerical models based on Computational Fluid Dynamics (CFD) is increasingly popular, but their application to reacting flow requires specific attention and validation. Through a careful examination of the governing equations and experimental measurements, a CFD-based method was developed to predict the performance of a ducted rocket combustor. It uses an equilibrium-chemistry Probability Density Function (PDF) combustion model, with a gaseous and a separate stream of 75 nm diameter carbon spheres to represent the fuel. After extensive validation with water tunnel and direct-connect combustion experiments over a wide range of geometries and test conditions, this CFD-based method was able to predict, within a good degree of accuracy, the combustion efficiency of a ducted rocket combustor.

Novel pyrrolopyridinone derivatives as anticancer inhibitors towards Cdc7: QSAR studies based on dockings by solvation score approach.

PubMed

Wu, Xiangxiang; Zeng, Huahui; Zhu, Xin; Ma, Qiujuan; Hou, Yimin; Wu, Xuefen

2013-11-20

A series of pyrrolopyridinone derivatives as specific inhibitors towards the cell division cycle 7 (Cdc7) was taken into account, and the efficacy of these compounds was analyzed by QSAR and docking approaches to gain deeper insights into the interaction mechanism and ligands selectivity for Cdc7. By regression analysis the prediction models based on Grid score and Zou-GB/SA score were found, respectively with good quality of fits (r(2)=0.748, 0.951; r(cv)(2)=0.712, 0.839). The accuracy of the models was validated by test set and the deviation of the predicted values in validation set using Zou-GB/SA score was smaller than that using Grid score, suggesting that the model based on Zou-GB/SA score provides a more effective method for predicting potencies of Cdc7 inhibitors. Copyright © 2013 Elsevier B.V. All rights reserved.

Psychometric properties and the predictive validity of the insomnia daytime worry scale: a pilot study.

PubMed

Kallestad, Håvard; Hansen, Bjarne; Langsrud, Knut; Hjemdal, Odin; Stiles, Tore C

2010-01-01

The relationship between presleep worry and insomnia has been investigated in previous studies, but less attention has been given to the role of daytime worry and symptoms of insomnia. The aims of the current study were (a) to assess the psychometric properties of a novel scale measuring insomnia-specific worry during daytime and (b) to examine whether levels of daytime worry predict severity of insomnia symptoms. Participants (N = 353) completed the Insomnia Daytime Worry Scale (IDWS) and the Insomnia Severity Index. An explorative principal-axis factor analysis extracted two factors from the IDWS, accounting for 70.5% of the variance. The IDWS demonstrated good reliability. The total score of IDWS and both factors predicted levels of insomnia severity in two separate hierarchical regression analyses. This preliminary evidence suggests that the IDWS is a valid and reliable scale to measure daytime worry in insomnia.

Validation of the Integrated Medical Model Using Historical Space Flight Data

NASA Technical Reports Server (NTRS)

Kerstman, Eric L.; Minard, Charles G.; FreiredeCarvalho, Mary H.; Walton, Marlei E.; Myers, Jerry G., Jr.; Saile, Lynn G.; Lopez, Vilma; Butler, Douglas J.; Johnson-Throop, Kathy A.

2010-01-01

The Integrated Medical Model (IMM) utilizes Monte Carlo methodologies to predict the occurrence of medical events, utilization of resources, and clinical outcomes during space flight. Real-world data may be used to demonstrate the accuracy of the model. For this analysis, IMM predictions were compared to data from historical shuttle missions, not yet included as model source input. Initial goodness of fit test-ing on International Space Station data suggests that the IMM may overestimate the number of occurrences for three of the 83 medical conditions in the model. The IMM did not underestimate the occurrence of any medical condition. Initial comparisons with shuttle data demonstrate the importance of understanding crew preference (i.e., preferred analgesic) for accurately predicting the utilization of re-sources. The initial analysis demonstrates the validity of the IMM for its intended use and highlights areas for improvement.

Development of PRIME for irradiation performance analysis of U-Mo/Al dispersion fuel

NASA Astrophysics Data System (ADS)

Jeong, Gwan Yoon; Kim, Yeon Soo; Jeong, Yong Jin; Park, Jong Man; Sohn, Dong-Seong

2018-04-01

A prediction code for the thermo-mechanical performance of research reactor fuel (PRIME) has been developed with the implementation of developed models to analyze the irradiation behavior of U-Mo dispersion fuel. The code is capable of predicting the two-dimensional thermal and mechanical performance of U-Mo dispersion fuel during irradiation. A finite element method was employed to solve the governing equations for thermal and mechanical equilibria. Temperature- and burnup-dependent material properties of the fuel meat constituents and cladding were used. The numerical solution schemes in PRIME were verified by benchmarking solutions obtained using a commercial finite element analysis program (ABAQUS). The code was validated using irradiation data from RERTR, HAMP-1, and E-FUTURE tests. The measured irradiation data used in the validation were IL thickness, volume fractions of fuel meat constituents for the thermal analysis, and profiles of the plate thickness changes and fuel meat swelling for the mechanical analysis. The prediction results were in good agreement with the measurement data for both thermal and mechanical analyses, confirming the validity of the code.

A New Lebanese Medication Adherence Scale: Validation in Lebanese Hypertensive Adults

PubMed Central

Wakim, N.; Issa, C.; Kassem, B.; Abou Jaoude, L.; Saleh, N.

2018-01-01

Background A new Lebanese scale measuring medication adherence considered socioeconomic and cultural factors not taken into account by the eight-item Morisky Medication Adherence Scale (MMAS-8). Objectives were to validate the new adherence scale and its prediction of hypertension control, compared to MMAS-8, and to assess adherence rates and factors. Methodology A cross-sectional study, including 405 patients, was performed in outpatient cardiology clinics of three hospitals in Beirut. Blood pressure was measured, a questionnaire filled, and sodium intake estimated by a urine test. Logistic regression defined predictors of hypertension control and adherence. Results 54.9% had controlled hypertension. 82.4% were adherent by the new scale, which showed good internal consistency, adequate questions (KMO coefficient = 0.743), and four factors. It predicted hypertension control (OR = 1.217; p value = 0.003), unlike MMAS-8, but the scores were correlated (ICC average measure = 0.651; p value < 0.001). Stress and smoking predicted nonadherence. Conclusion This study elaborated a validated, practical, and useful tool measuring adherence to medications in Lebanese hypertensive patients. PMID:29887993

Validation of the thermophysiological model by Fiala for prediction of local skin temperatures

NASA Astrophysics Data System (ADS)

Martínez, Natividad; Psikuta, Agnes; Kuklane, Kalev; Quesada, José Ignacio Priego; de Anda, Rosa María Cibrián Ortiz; Soriano, Pedro Pérez; Palmer, Rosario Salvador; Corberán, José Miguel; Rossi, René Michel; Annaheim, Simon

2016-12-01

The most complete and realistic physiological data are derived from direct measurements during human experiments; however, they present some limitations such as ethical concerns, time and cost burden. Thermophysiological models are able to predict human thermal response in a wide range of environmental conditions, but their use is limited due to lack of validation. The aim of this work was to validate the thermophysiological model by Fiala for prediction of local skin temperatures against a dedicated database containing 43 different human experiments representing a wide range of conditions. The validation was conducted based on root-mean-square deviation (rmsd) and bias. The thermophysiological model by Fiala showed a good precision when predicting core and mean skin temperature (rmsd 0.26 and 0.92 °C, respectively) and also local skin temperatures for most body sites (average rmsd for local skin temperatures 1.32 °C). However, an increased deviation of the predictions was observed for the forehead skin temperature (rmsd of 1.63 °C) and for the thigh during exercising exposures (rmsd of 1.41 °C). Possible reasons for the observed deviations are lack of information on measurement circumstances (hair, head coverage interference) or an overestimation of the sweat evaporative cooling capacity for the head and thigh, respectively. This work has highlighted the importance of collecting details about the clothing worn and how and where the sensors were attached to the skin for achieving more precise results in the simulations.

DES Prediction of Cavitation Erosion and Its Validation for a Ship Scale Propeller

NASA Astrophysics Data System (ADS)

Ponkratov, Dmitriy, Dr

2015-12-01

Lloyd's Register Technical Investigation Department (LR TID) have developed numerical functions for the prediction of cavitation erosion aggressiveness within Computational Fluid Dynamics (CFD) simulations. These functions were previously validated for a model scale hydrofoil and ship scale rudder [1]. For the current study the functions were applied to a cargo ship's full scale propeller, on which the severe cavitation erosion was reported. The performed Detach Eddy Simulation (DES) required a fine computational mesh (approximately 22 million cells), together with a very small time step (2.0E-4 s). As the cavitation for this type of vessel is primarily caused by a highly non-uniform wake, the hull was also included in the simulation. The applied method under predicted the cavitation extent and did not fully resolve the tip vortex; however, the areas of cavitation collapse were captured successfully. Consequently, the developed functions showed a very good prediction of erosion areas, as confirmed by comparison with underwater propeller inspection results.

Predictive modeling of addiction lapses in a mobile health application.

PubMed

Chih, Ming-Yuan; Patton, Timothy; McTavish, Fiona M; Isham, Andrew J; Judkins-Fisher, Chris L; Atwood, Amy K; Gustafson, David H

2014-01-01

The chronically relapsing nature of alcoholism leads to substantial personal, family, and societal costs. Addiction-comprehensive health enhancement support system (A-CHESS) is a smartphone application that aims to reduce relapse. To offer targeted support to patients who are at risk of lapses within the coming week, a Bayesian network model to predict such events was constructed using responses on 2,934 weekly surveys (called the Weekly Check-in) from 152 alcohol-dependent individuals who recently completed residential treatment. The Weekly Check-in is a self-monitoring service, provided in A-CHESS, to track patients' recovery progress. The model showed good predictability, with the area under receiver operating characteristic curve of 0.829 in the 10-fold cross-validation and 0.912 in the external validation. The sensitivity/specificity table assists the tradeoff decisions necessary to apply the model in practice. This study moves us closer to the goal of providing lapse prediction so that patients might receive more targeted and timely support. © 2013.

Numerical Simulation and Artificial Neural Network Modeling for Predicting Welding-Induced Distortion in Butt-Welded 304L Stainless Steel Plates

NASA Astrophysics Data System (ADS)

Narayanareddy, V. V.; Chandrasekhar, N.; Vasudevan, M.; Muthukumaran, S.; Vasantharaja, P.

2016-02-01

In the present study, artificial neural network modeling has been employed for predicting welding-induced angular distortions in autogenous butt-welded 304L stainless steel plates. The input data for the neural network have been obtained from a series of three-dimensional finite element simulations of TIG welding for a wide range of plate dimensions. Thermo-elasto-plastic analysis was carried out for 304L stainless steel plates during autogenous TIG welding employing double ellipsoidal heat source. The simulated thermal cycles were validated by measuring thermal cycles using thermocouples at predetermined positions, and the simulated distortion values were validated by measuring distortion using vertical height gauge for three cases. There was a good agreement between the model predictions and the measured values. Then, a multilayer feed-forward back propagation neural network has been developed using the numerically simulated data. Artificial neural network model developed in the present study predicted the angular distortion accurately.

Predictive Modeling of Addiction Lapses in a Mobile Health Application

PubMed Central

Chih, Ming-Yuan; Patton, Timothy; McTavish, Fiona M.; Isham, Andrew; Judkins-Fisher, Chris L.; Atwood, Amy K.; Gustafson, David H.

2013-01-01

The chronically relapsing nature of alcoholism leads to substantial personal, family, and societal costs. Addiction-Comprehensive Health Enhancement Support System (A-CHESS) is a smartphone application that aims to reduce relapse. To offer targeted support to patients who are at risk of lapses within the coming week, a Bayesian network model to predict such events was constructed using responses on 2,934 weekly surveys (called the Weekly Check-in) from 152 alcohol-dependent individuals who recently completed residential treatment. The Weekly Check-in is a self-monitoring service, provided in A-CHESS, to track patients’ recovery progress. The model showed good predictability, with the area under receiver operating characteristic curve of 0.829 in the 10-fold cross-validation and 0.912 in the external validation. The sensitivity/specificity table assists the tradeoff decisions necessary to apply the model in practice. This study moves us closer to the goal of providing lapse prediction so that patients might receive more targeted and timely support. PMID:24035143

Physician Enabling Skills Questionnaire

PubMed Central

Hudon, Catherine; Lambert, Mireille; Almirall, José

2015-01-01

Abstract Objective To evaluate the reliability and validity of the newly developed Physician Enabling Skills Questionnaire (PESQ) by assessing its internal consistency, test-retest reliability, concurrent validity with patient-centred care, and predictive validity with patient activation and patient enablement. Design Validation study. Setting Saguenay, Que. Participants One hundred patients with at least 1 chronic disease who presented in a waiting room of a regional health centre family medicine unit. Main outcome measures Family physicians’ enabling skills, measured with the PESQ at 2 points in time (ie, while in the waiting room at the family medicine unit and 2 weeks later through a mail survey); patient-centred care, assessed with the Patient Perception of Patient-Centredness instrument; patient activation, assessed with the Patient Activation Measure; and patient enablement, assessed with the Patient Enablement Instrument. Results The internal consistency of the 6 subscales of the PESQ was adequate (Cronbach α = .69 to .92). The test-retest reliability was very good (r = 0.90; 95% CI 0.84 to 0.93). Concurrent validity with the Patient Perception of Patient-Centredness instrument was good (r = −0.67; 95% CI −0.78 to −0.53; P < .001). The PESQ accounts for 11% of the total variance with the Patient Activation Measure (r2 = 0.11; P = .002) and 19% of the variance with the Patient Enablement Instrument (r2 = 0.19; P < .001). Conclusion The newly developed PESQ presents good psychometric properties, allowing for its use in practice and research. PMID:26889507

Preliminary validation of the Yale Food Addiction Scale.

PubMed

Gearhardt, Ashley N; Corbin, William R; Brownell, Kelly D

2009-04-01

Previous research has found similarities between addiction to psychoactive substances and excessive food consumption. Further exploration is needed to evaluate the concept of "food addiction," as there is currently a lack of psychometrically validated measurement tools in this area. The current study represents a preliminary exploration of the Yale Food Addiction Scale (YFAS), designed to identify those exhibiting signs of addiction towards certain types of foods (e.g., high fat and high sugar). Survey data were collected from 353 respondents from a stratified random sample of young adults. In addition to the YFAS, the survey assessed eating pathology, alcohol consumption and other health behaviors. The YFAS exhibited adequate internal reliability, and showed good convergent validity with measures of similar constructs and good discriminant validity relative to related but dissimilar constructs. Additionally, the YFAS predicted binge-eating behavior above and beyond existing measures of eating pathology, demonstrating incremental validity. The YFAS is a sound tool for identifying eating patterns that are similar to behaviors seen in classic areas of addiction. Further evaluation of the scale is needed, especially due to a low response rate of 24.5% and a non-clinical sample, but confirmation of the reliability and validity of the scale has the potential to facilitate empirical research on the concept of "food addiction".

Prediction of light aircraft interior sound pressure level from the measured sound power flowing in to the cabin

NASA Technical Reports Server (NTRS)

Atwal, Mahabir S.; Heitman, Karen E.; Crocker, Malcolm J.

1986-01-01

The validity of the room equation of Crocker and Price (1982) for predicting the cabin interior sound pressure level was experimentally tested using a specially constructed setup for simultaneous measurements of transmitted sound intensity and interior sound pressure levels. Using measured values of the reverberation time and transmitted intensities, the equation was used to predict the space-averaged interior sound pressure level for three different fuselage conditions. The general agreement between the room equation and experimental test data is considered good enough for this equation to be used for preliminary design studies.

3D-quantitative structure-activity relationship studies on benzothiadiazepine hydroxamates as inhibitors of tumor necrosis factor-alpha converting enzyme.

PubMed

Murumkar, Prashant R; Giridhar, Rajani; Yadav, Mange Ram

2008-04-01

A set of 29 benzothiadiazepine hydroxamates having selective tumor necrosis factor-alpha converting enzyme inhibitory activity were used to compare the quality and predictive power of 3D-quantitative structure-activity relationship, comparative molecular field analysis, and comparative molecular similarity indices models for the atom-based, centroid/atom-based, data-based, and docked conformer-based alignment. Removal of two outliers from the initial training set of molecules improved the predictivity of models. Among the 3D-quantitative structure-activity relationship models developed using the above four alignments, the database alignment provided the optimal predictive comparative molecular field analysis model for the training set with cross-validated r(2) (q(2)) = 0.510, non-cross-validated r(2) = 0.972, standard error of estimates (s) = 0.098, and F = 215.44 and the optimal comparative molecular similarity indices model with cross-validated r(2) (q(2)) = 0.556, non-cross-validated r(2) = 0.946, standard error of estimates (s) = 0.163, and F = 99.785. These models also showed the best test set prediction for six compounds with predictive r(2) values of 0.460 and 0.535, respectively. The contour maps obtained from 3D-quantitative structure-activity relationship studies were appraised for activity trends for the molecules analyzed. The comparative molecular similarity indices models exhibited good external predictivity as compared with that of comparative molecular field analysis models. The data generated from the present study helped us to further design and report some novel and potent tumor necrosis factor-alpha converting enzyme inhibitors.

Desire thinking as a confounder in the relationship between mindfulness and craving: Evidence from a cross-cultural validation of the Desire Thinking Questionnaire.

PubMed

Chakroun-Baggioni, Nadia; Corman, Maya; Spada, Marcantonio M; Caselli, Gabriele; Gierski, Fabien

2017-10-01

Desire thinking and mindfulness have been associated with craving. The aim of the present study was to validate the French version of the Desire Thinking Questionnaire (DTQ) and to investigate the relationship between mindfulness, desire thinking and craving among a sample of university students. Four hundred and ninety six university students completed the DTQ and measures of mindfulness, craving and alcohol use. Results from confirmatory factor analyses showed that the two-factor structure proposed in the original DTQ exhibited suitable goodness-of-fit statistics. The DTQ also demonstrated good internal reliability, temporal stability and predictive validity. A set of linear regressions revealed that desire thinking had a confounding effect in the relationship between mindfulness and craving. The confounding role of desire thinking in the relationship between mindfulness and craving suggests that interrupting desire thinking may be a viable clinical option aimed at reducing craving. Copyright © 2017 Elsevier B.V. All rights reserved.

Shift Verification and Validation

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

Pandya, Tara M.; Evans, Thomas M.; Davidson, Gregory G

2016-09-07

This documentation outlines the verification and validation of Shift for the Consortium for Advanced Simulation of Light Water Reactors (CASL). Five main types of problems were used for validation: small criticality benchmark problems; full-core reactor benchmarks for light water reactors; fixed-source coupled neutron-photon dosimetry benchmarks; depletion/burnup benchmarks; and full-core reactor performance benchmarks. We compared Shift results to measured data and other simulated Monte Carlo radiation transport code results, and found very good agreement in a variety of comparison measures. These include prediction of critical eigenvalue, radial and axial pin power distributions, rod worth, leakage spectra, and nuclide inventories over amore » burn cycle. Based on this validation of Shift, we are confident in Shift to provide reference results for CASL benchmarking.« less

External Validation of a Tool Predicting 7-Year Risk of Developing Cardiovascular Disease, Type 2 Diabetes or Chronic Kidney Disease.

PubMed

Rauh, Simone P; Rutters, Femke; van der Heijden, Amber A W A; Luimes, Thomas; Alssema, Marjan; Heymans, Martijn W; Magliano, Dianna J; Shaw, Jonathan E; Beulens, Joline W; Dekker, Jacqueline M

2018-02-01

Chronic cardiometabolic diseases, including cardiovascular disease (CVD), type 2 diabetes (T2D) and chronic kidney disease (CKD), share many modifiable risk factors and can be prevented using combined prevention programs. Valid risk prediction tools are needed to accurately identify individuals at risk. We aimed to validate a previously developed non-invasive risk prediction tool for predicting the combined 7-year-risk for chronic cardiometabolic diseases. The previously developed tool is stratified for sex and contains the predictors age, BMI, waist circumference, use of antihypertensives, smoking, family history of myocardial infarction/stroke, and family history of diabetes. This tool was externally validated, evaluating model performance using area under the receiver operating characteristic curve (AUC)-assessing discrimination-and Hosmer-Lemeshow goodness-of-fit (HL) statistics-assessing calibration. The intercept was recalibrated to improve calibration performance. The risk prediction tool was validated in 3544 participants from the Australian Diabetes, Obesity and Lifestyle Study (AusDiab). Discrimination was acceptable, with an AUC of 0.78 (95% CI 0.75-0.81) in men and 0.78 (95% CI 0.74-0.81) in women. Calibration was poor (HL statistic: p < 0.001), but improved considerably after intercept recalibration. Examination of individual outcomes showed that in men, AUC was highest for CKD (0.85 [95% CI 0.78-0.91]) and lowest for T2D (0.69 [95% CI 0.65-0.74]). In women, AUC was highest for CVD (0.88 [95% CI 0.83-0.94)]) and lowest for T2D (0.71 [95% CI 0.66-0.75]). Validation of our previously developed tool showed robust discriminative performance across populations. Model recalibration is recommended to account for different disease rates. Our risk prediction tool can be useful in large-scale prevention programs for identifying those in need of further risk profiling because of their increased risk for chronic cardiometabolic diseases.

Binary Decision Trees for Preoperative Periapical Cyst Screening Using Cone-beam Computed Tomography.

PubMed

Pitcher, Brandon; Alaqla, Ali; Noujeim, Marcel; Wealleans, James A; Kotsakis, Georgios; Chrepa, Vanessa

2017-03-01

Cone-beam computed tomographic (CBCT) analysis allows for 3-dimensional assessment of periradicular lesions and may facilitate preoperative periapical cyst screening. The purpose of this study was to develop and assess the predictive validity of a cyst screening method based on CBCT volumetric analysis alone or combined with designated radiologic criteria. Three independent examiners evaluated 118 presurgical CBCT scans from cases that underwent apicoectomies and had an accompanying gold standard histopathological diagnosis of either a cyst or granuloma. Lesion volume, density, and specific radiologic characteristics were assessed using specialized software. Logistic regression models with histopathological diagnosis as the dependent variable were constructed for cyst prediction, and receiver operating characteristic curves were used to assess the predictive validity of the models. A conditional inference binary decision tree based on a recursive partitioning algorithm was constructed to facilitate preoperative screening. Interobserver agreement was excellent for volume and density, but it varied from poor to good for the radiologic criteria. Volume and root displacement were strong predictors for cyst screening in all analyses. The binary decision tree classifier determined that if the volume of the lesion was >247 mm 3 , there was 80% probability of a cyst. If volume was <247 mm 3 and root displacement was present, cyst probability was 60% (78% accuracy). The good accuracy and high specificity of the decision tree classifier renders it a useful preoperative cyst screening tool that can aid in clinical decision making but not a substitute for definitive histopathological diagnosis after biopsy. Confirmatory studies are required to validate the present findings. Published by Elsevier Inc.

Investigation of Super Learner Methodology on HIV-1 Small Sample: Application on Jaguar Trial Data.

PubMed

Houssaïni, Allal; Assoumou, Lambert; Marcelin, Anne Geneviève; Molina, Jean Michel; Calvez, Vincent; Flandre, Philippe

2012-01-01

Background. Many statistical models have been tested to predict phenotypic or virological response from genotypic data. A statistical framework called Super Learner has been introduced either to compare different methods/learners (discrete Super Learner) or to combine them in a Super Learner prediction method. Methods. The Jaguar trial is used to apply the Super Learner framework. The Jaguar study is an "add-on" trial comparing the efficacy of adding didanosine to an on-going failing regimen. Our aim was also to investigate the impact on the use of different cross-validation strategies and different loss functions. Four different repartitions between training set and validations set were tested through two loss functions. Six statistical methods were compared. We assess performance by evaluating R(2) values and accuracy by calculating the rates of patients being correctly classified. Results. Our results indicated that the more recent Super Learner methodology of building a new predictor based on a weighted combination of different methods/learners provided good performance. A simple linear model provided similar results to those of this new predictor. Slight discrepancy arises between the two loss functions investigated, and slight difference arises also between results based on cross-validated risks and results from full dataset. The Super Learner methodology and linear model provided around 80% of patients correctly classified. The difference between the lower and higher rates is around 10 percent. The number of mutations retained in different learners also varys from one to 41. Conclusions. The more recent Super Learner methodology combining the prediction of many learners provided good performance on our small dataset.

Derivation and validation of a novel risk score for safe discharge after acute lower gastrointestinal bleeding: a modelling study.

PubMed

Oakland, Kathryn; Jairath, Vipul; Uberoi, Raman; Guy, Richard; Ayaru, Lakshmana; Mortensen, Neil; Murphy, Mike F; Collins, Gary S

2017-09-01

Acute lower gastrointestinal bleeding is a common reason for emergency hospital admission, and identification of patients at low risk of harm, who are therefore suitable for outpatient investigation, is a clinical and research priority. We aimed to develop and externally validate a simple risk score to identify patients with lower gastrointestinal bleeding who could safely avoid hospital admission. We undertook model development with data from the National Comparative Audit of Lower Gastrointestinal Bleeding from 143 hospitals in the UK in 2015. Multivariable logistic regression modelling was used to identify predictors of safe discharge, defined as the absence of rebleeding, blood transfusion, therapeutic intervention, 28 day readmission, or death. The model was converted into a simplified risk scoring system and was externally validated in 288 patients admitted with lower gastrointestinal bleeding (184 safely discharged) from two UK hospitals (Charing Cross Hospital, London, and Hammersmith Hospital, London) that had not contributed data to the development cohort. We calculated C statistics for the new model and did a comparative assessment with six previously developed risk scores. Of 2336 prospectively identified admissions in the development cohort, 1599 (68%) were safely discharged. Age, sex, previous admission for lower gastrointestinal bleeding, rectal examination findings, heart rate, systolic blood pressure, and haemoglobin concentration strongly discriminated safe discharge in the development cohort (C statistic 0·84, 95% CI 0·82-0·86) and in the validation cohort (0·79, 0·73-0·84). Calibration plots showed the new risk score to have good calibration in the validation cohort. The score was better than the Rockall, Blatchford, Strate, BLEED, AIMS65, and NOBLADS scores in predicting safe discharge. A score of 8 or less predicts a 95% probability of safe discharge. We developed and validated a novel clinical prediction model with good discriminative performance to identify patients with lower gastrointestinal bleeding who are suitable for safe outpatient management, which has important economic and resource implications. Bowel Disease Research Foundation and National Health Service Blood and Transplant. Copyright © 2017 Elsevier Ltd. All rights reserved.

Validation of biomarkers to predict response to immunotherapy in cancer: Volume II - clinical validation and regulatory considerations.

PubMed

Dobbin, Kevin K; Cesano, Alessandra; Alvarez, John; Hawtin, Rachael; Janetzki, Sylvia; Kirsch, Ilan; Masucci, Giuseppe V; Robbins, Paul B; Selvan, Senthamil R; Streicher, Howard Z; Zhang, Jenny; Butterfield, Lisa H; Thurin, Magdalena

2016-01-01

There is growing recognition that immunotherapy is likely to significantly improve health outcomes for cancer patients in the coming years. Currently, while a subset of patients experience substantial clinical benefit in response to different immunotherapeutic approaches, the majority of patients do not but are still exposed to the significant drug toxicities. Therefore, a growing need for the development and clinical use of predictive biomarkers exists in the field of cancer immunotherapy. Predictive cancer biomarkers can be used to identify the patients who are or who are not likely to derive benefit from specific therapeutic approaches. In order to be applicable in a clinical setting, predictive biomarkers must be carefully shepherded through a step-wise, highly regulated developmental process. Volume I of this two-volume document focused on the pre-analytical and analytical phases of the biomarker development process, by providing background, examples and "good practice" recommendations. In the current Volume II, the focus is on the clinical validation, validation of clinical utility and regulatory considerations for biomarker development. Together, this two volume series is meant to provide guidance on the entire biomarker development process, with a particular focus on the unique aspects of developing immune-based biomarkers. Specifically, knowledge about the challenges to clinical validation of predictive biomarkers, which has been gained from numerous successes and failures in other contexts, will be reviewed together with statistical methodological issues related to bias and overfitting. The different trial designs used for the clinical validation of biomarkers will also be discussed, as the selection of clinical metrics and endpoints becomes critical to establish the clinical utility of the biomarker during the clinical validation phase of the biomarker development. Finally, the regulatory aspects of submission of biomarker assays to the U.S. Food and Drug Administration as well as regulatory considerations in the European Union will be covered.

Analytical and experimental validation of the Oblique Detonation Wave Engine concept

NASA Technical Reports Server (NTRS)

Adelman, Henry G.; Cambier, Jean-Luc; Menees, Gene P.; Balboni, John A.

1988-01-01

The Oblique Detonation Wave Engine (ODWE) for hypersonic flight has been analytically studied by NASA using the CFD codes which fully couple finite rate chemistry with fluid dynamics. Fuel injector designs investigated included wall and strut injectors, and the in-stream strut injectors were chosen to provide good mixing with minimal stagnation pressure losses. Plans for experimentally validating the ODWE concept in an arc-jet hypersonic wind tunnel are discussed. Measurements of the flow field properties behind the oblique wave will be compared to analytical predictions.

Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women.

PubMed

Kulkarni, Bharati; Kuper, Hannah; Taylor, Amy; Wells, Jonathan C; Radhakrishna, K V; Kinra, Sanjay; Ben-Shlomo, Yoav; Smith, George Davey; Ebrahim, Shah; Byrne, Nuala M; Hills, Andrew P

2013-10-15

Lean body mass (LBM) and muscle mass remain difficult to quantify in large epidemiological studies due to the unavailability of inexpensive methods. We therefore developed anthropometric prediction equations to estimate the LBM and appendicular lean soft tissue (ALST) using dual-energy X-ray absorptiometry (DXA) as a reference method. Healthy volunteers (n = 2,220; 36% women; age 18-79 yr), representing a wide range of body mass index (14-44 kg/m(2)), participated in this study. Their LBM, including ALST, was assessed by DXA along with anthropometric measurements. The sample was divided into prediction (60%) and validation (40%) sets. In the prediction set, a number of prediction models were constructed using DXA-measured LBM and ALST estimates as dependent variables and a combination of anthropometric indices as independent variables. These equations were cross-validated in the validation set. Simple equations using age, height, and weight explained >90% variation in the LBM and ALST in both men and women. Additional variables (hip and limb circumferences and sum of skinfold thicknesses) increased the explained variation by 5-8% in the fully adjusted models predicting LBM and ALST. More complex equations using all of the above anthropometric variables could predict the DXA-measured LBM and ALST accurately, as indicated by low standard error of the estimate (LBM: 1.47 kg and 1.63 kg for men and women, respectively), as well as good agreement by Bland-Altman analyses (Bland JM, Altman D. Lancet 1: 307-310, 1986). These equations could be a valuable tool in large epidemiological studies assessing these body compartments in Indians and other population groups with similar body composition.

Development and validation of anthropometric prediction equations for estimation of lean body mass and appendicular lean soft tissue in Indian men and women

PubMed Central

Kuper, Hannah; Taylor, Amy; Wells, Jonathan C.; Radhakrishna, K. V.; Kinra, Sanjay; Ben-Shlomo, Yoav; Smith, George Davey; Ebrahim, Shah; Byrne, Nuala M.; Hills, Andrew P.

2013-01-01

Lean body mass (LBM) and muscle mass remain difficult to quantify in large epidemiological studies due to the unavailability of inexpensive methods. We therefore developed anthropometric prediction equations to estimate the LBM and appendicular lean soft tissue (ALST) using dual-energy X-ray absorptiometry (DXA) as a reference method. Healthy volunteers (n = 2,220; 36% women; age 18-79 yr), representing a wide range of body mass index (14–44 kg/m2), participated in this study. Their LBM, including ALST, was assessed by DXA along with anthropometric measurements. The sample was divided into prediction (60%) and validation (40%) sets. In the prediction set, a number of prediction models were constructed using DXA-measured LBM and ALST estimates as dependent variables and a combination of anthropometric indices as independent variables. These equations were cross-validated in the validation set. Simple equations using age, height, and weight explained >90% variation in the LBM and ALST in both men and women. Additional variables (hip and limb circumferences and sum of skinfold thicknesses) increased the explained variation by 5–8% in the fully adjusted models predicting LBM and ALST. More complex equations using all of the above anthropometric variables could predict the DXA-measured LBM and ALST accurately, as indicated by low standard error of the estimate (LBM: 1.47 kg and 1.63 kg for men and women, respectively), as well as good agreement by Bland-Altman analyses (Bland JM, Altman D. Lancet 1: 307–310, 1986). These equations could be a valuable tool in large epidemiological studies assessing these body compartments in Indians and other population groups with similar body composition. PMID:23950165

Developing prediction equations and a mobile phone application to identify infants at risk of obesity.

PubMed

Santorelli, Gillian; Petherick, Emily S; Wright, John; Wilson, Brad; Samiei, Haider; Cameron, Noël; Johnson, William

2013-01-01

Advancements in knowledge of obesity aetiology and mobile phone technology have created the opportunity to develop an electronic tool to predict an infant's risk of childhood obesity. The study aims were to develop and validate equations for the prediction of childhood obesity and integrate them into a mobile phone application (App). Anthropometry and childhood obesity risk data were obtained for 1868 UK-born White or South Asian infants in the Born in Bradford cohort. Logistic regression was used to develop prediction equations (at 6 ± 1.5, 9 ± 1.5 and 12 ± 1.5 months) for risk of childhood obesity (BMI at 2 years >91(st) centile and weight gain from 0-2 years >1 centile band) incorporating sex, birth weight, and weight gain as predictors. The discrimination accuracy of the equations was assessed by the area under the curve (AUC); internal validity by comparing area under the curve to those obtained in bootstrapped samples; and external validity by applying the equations to an external sample. An App was built to incorporate six final equations (two at each age, one of which included maternal BMI). The equations had good discrimination (AUCs 86-91%), with the addition of maternal BMI marginally improving prediction. The AUCs in the bootstrapped and external validation samples were similar to those obtained in the development sample. The App is user-friendly, requires a minimum amount of information, and provides a risk assessment of low, medium, or high accompanied by advice and website links to government recommendations. Prediction equations for risk of childhood obesity have been developed and incorporated into a novel App, thereby providing proof of concept that childhood obesity prediction research can be integrated with advancements in technology.

A Computational Fluid Dynamics Study of Transitional Flows in Low-Pressure Turbines under a Wide Range of Operating Conditions

NASA Technical Reports Server (NTRS)

Suzen, Y. B.; Huang, P. G.; Ashpis, D. E.; Volino, R. J.; Corke, T. C.; Thomas, F. O.; Huang, J.; Lake, J. P.; King, P. I.

2007-01-01

A transport equation for the intermittency factor is employed to predict the transitional flows in low-pressure turbines. The intermittent behavior of the transitional flows is taken into account and incorporated into computations by modifying the eddy viscosity, mu(sub p) with the intermittency factor, gamma. Turbulent quantities are predicted using Menter's two-equation turbulence model (SST). The intermittency factor is obtained from a transport equation model which can produce both the experimentally observed streamwise variation of intermittency and a realistic profile in the cross stream direction. The model had been previously validated against low-pressure turbine experiments with success. In this paper, the model is applied to predictions of three sets of recent low-pressure turbine experiments on the Pack B blade to further validate its predicting capabilities under various flow conditions. Comparisons of computational results with experimental data are provided. Overall, good agreement between the experimental data and computational results is obtained. The new model has been shown to have the capability of accurately predicting transitional flows under a wide range of low-pressure turbine conditions.

Development and validation of the Good Outcome Following Attempted Resuscitation (GO-FAR) score to predict neurologically intact survival after in-hospital cardiopulmonary resuscitation.

PubMed

Ebell, Mark H; Jang, Woncheol; Shen, Ye; Geocadin, Romergryko G

2013-11-11

Informing patients and providers of the likelihood of survival after in-hospital cardiac arrest (IHCA), neurologically intact or with minimal deficits, may be useful when discussing do-not-attempt-resuscitation orders. To develop a simple prearrest point score that can identify patients unlikely to survive IHCA, neurologically intact or with minimal deficits. The study included 51,240 inpatients experiencing an index episode of IHCA between January 1, 2007, and December 31, 2009, in 366 hospitals participating in the Get With the Guidelines-Resuscitation registry. Dividing data into training (44.4%), test (22.2%), and validation (33.4%) data sets, we used multivariate methods to select the best independent predictors of good neurologic outcome, created a series of candidate decision models, and used the test data set to select the model that best classified patients as having a very low (<1%), low (1%-3%), average (>3%-15%), or higher than average (>15%) likelihood of survival after in-hospital cardiopulmonary resuscitation for IHCA with good neurologic status. The final model was evaluated using the validation data set. Survival to discharge after in-hospital cardiopulmonary resuscitation for IHCA with good neurologic status (neurologically intact or with minimal deficits) based on a Cerebral Performance Category score of 1. The best performing model was a simple point score based on 13 prearrest variables. The C statistic was 0.78 when applied to the validation set. It identified the likelihood of a good outcome as very low in 9.4% of patients (good outcome in 0.9%), low in 18.9% (good outcome in 1.7%), average in 54.0% (good outcome in 9.4%), and above average in 17.7% (good outcome in 27.5%). Overall, the score can identify more than one-quarter of patients as having a low or very low likelihood of survival to discharge, neurologically intact or with minimal deficits after IHCA (good outcome in 1.4%). The Good Outcome Following Attempted Resuscitation (GO-FAR) scoring system identifies patients who are unlikely to benefit from a resuscitation attempt should they experience IHCA. This information can be used as part of a shared decision regarding do-not-attempt-resuscitation orders.

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.

Validation of the German version of the Nurse-Work Instability Scale: baseline survey findings of a prospective study of a cohort of geriatric care workers

PubMed Central

2013-01-01

Background A prospective study of a cohort of nursing staff from nursing homes was undertaken to validate the Nurse-Work Instability Scale (Nurse-WIS). Baseline investigation data was used to test reliability, construct validity and criterion validity. Method A survey of nursing staff from nursing homes was conducted using a questionnaire containing the Nurse-WIS along with other survey instruments (including SF-12, WAI, SPE). The self-reported number of days’ sick leave taken and if a pension for reduced work capacity was drawn were recorded. The reliability of the scale was checked by item difficulty (P), item discrimination (rjt) and by internal consistency according to Cronbach’s coefficient. The hypotheses for checking construct validity were tested on the basis of correlations. Pearson’s chi-square was used to test concurrent criterion validity; discriminant validity was tested by means of binary logistic regression. Results 396 persons answered the questionnaire (21.3% response rate). More than 80% were female and mostly work full-time in a rotating shift pattern. Following the test for item discrimination, two items were removed from the Nurse-WIS test. According to Cronbach’s (0.927) the scale provides a high degree of measuring accuracy. All hypotheses and assumptions used to test validity were confirmed: As the Nurse-WIS risk increases, health-related quality of life, work ability and job satisfaction decline. Depressive symptoms and a poor subjective prognosis of earning capacity are also more frequent. Musculoskeletal disorders and impairments of psychological well-being are more frequent. Age also influences the Nurse-WIS result. While 12.0% of those below the age of 35 had an increased risk, the figure for those aged over 55 was 50%. Conclusion This study is the first validation study of the Nurse-WIS to date. The Nurse-WIS shows good reliability, good validity and a good level of measuring accuracy. It appears to be suitable for recording prevention and rehabilitation needs among health care workers. If, in the follow-up, the Nurse-WIS likewise proves to be a reliable screening instrument with good predictive validity, it could ensure that suitable action is taken at an early stage, thereby helping to counteract early retirement and the anticipated shortage of health care workers. PMID:24330532

Derivation, Validation and Application of a Pragmatic Risk Prediction Index for Benchmarking of Surgical Outcomes.

PubMed

Spence, Richard T; Chang, David C; Kaafarani, Haytham M A; Panieri, Eugenio; Anderson, Geoffrey A; Hutter, Matthew M

2018-02-01

Despite the existence of multiple validated risk assessment and quality benchmarking tools in surgery, their utility outside of high-income countries is limited. We sought to derive, validate and apply a scoring system that is both (1) feasible, and (2) reliably predicts mortality in a middle-income country (MIC) context. A 5-step methodology was used: (1) development of a de novo surgical outcomes database modeled around the American College of Surgeons' National Surgical Quality Improvement Program (ACS-NSQIP) in South Africa (SA dataset), (2) use of the resultant data to identify all predictors of in-hospital death with more than 90% capture indicating feasibility of collection, (3) use these predictors to derive and validate an integer-based score that reliably predicts in-hospital death in the 2012 ACS-NSQIP, (4) apply the score in the original SA dataset and demonstrate its performance, (5) identify threshold cutoffs of the score to prompt action and drive quality improvement. Following step one-three above, the 13 point Codman's score was derived and validated on 211,737 and 109,079 patients, respectively, and includes: age 65 (1), partially or completely dependent functional status (1), preoperative transfusions ≥4 units (1), emergency operation (2), sepsis or septic shock (2) American Society of Anesthesia score ≥3 (3) and operative procedure (1-3). Application of the score to 373 patients in the SA dataset showed good discrimination and calibration to predict an in-hospital death. A Codman Score of 8 is an optimal cutoff point for defining expected and unexpected deaths. We have designed a novel risk prediction score specific for a MIC context. The Codman Score can prove useful for both (1) preoperative decision-making and (2) benchmarking the quality of surgical care in MIC's.

Clinical Nomograms to Predict Stone-Free Rates after Shock-Wave Lithotripsy: Development and Internal-Validation

PubMed Central

Kim, Jung Kwon; Ha, Seung Beom; Jeon, Chan Hoo; Oh, Jong Jin; Cho, Sung Yong; Oh, Seung-June; Kim, Hyeon Hoe; Jeong, Chang Wook

2016-01-01

Purpose Shock-wave lithotripsy (SWL) is accepted as the first line treatment modality for uncomplicated upper urinary tract stones; however, validated prediction models with regards to stone-free rates (SFRs) are still needed. We aimed to develop nomograms predicting SFRs after the first and within the third session of SWL. Computed tomography (CT) information was also modeled for constructing nomograms. Materials and Methods From March 2006 to December 2013, 3028 patients were treated with SWL for ureter and renal stones at our three tertiary institutions. Four cohorts were constructed: Total-development, Total-validation, CT-development, and CT-validation cohorts. The nomograms were developed using multivariate logistic regression models with selected significant variables in a univariate logistic regression model. A C-index was used to assess the discrimination accuracy of nomograms and calibration plots were used to analyze the consistency of prediction. Results The SFR, after the first and within the third session, was 48.3% and 68.8%, respectively. Significant variables were sex, stone location, stone number, and maximal stone diameter in the Total-development cohort, and mean Hounsfield unit (HU) and grade of hydronephrosis (HN) were additional parameters in the CT-development cohort. The C-indices were 0.712 and 0.723 for after the first and within the third session of SWL in the Total-development cohort, and 0.755 and 0.756, in the CT-development cohort, respectively. The calibration plots showed good correspondences. Conclusions We constructed and validated nomograms to predict SFR after SWL. To the best of our knowledge, these are the first graphical nomograms to be modeled with CT information. These may be useful for patient counseling and treatment decision-making. PMID:26890006

Prediction model for obtaining spermatozoa with testicular sperm extraction in men with non-obstructive azoospermia.

PubMed

Cissen, M; Meijerink, A M; D'Hauwers, K W; Meissner, A; van der Weide, N; Mochtar, M H; de Melker, A A; Ramos, L; Repping, S; Braat, D D M; Fleischer, K; van Wely, M

2016-09-01

Can an externally validated model, based on biological variables, be developed to predict successful sperm retrieval with testicular sperm extraction (TESE) in men with non-obstructive azoospermia (NOA) using a large nationwide cohort? Our prediction model including six variables was able to make a good distinction between men with a good chance and men with a poor chance of obtaining spermatozoa with TESE. Using ICSI in combination with TESE even men suffering from NOA are able to father their own biological child. Only in approximately half of the patients with NOA can testicular sperm be retrieved successfully. The few models that have been developed to predict the chance of obtaining spermatozoa with TESE were based on small datasets and none of them have been validated externally. We performed a retrospective nationwide cohort study. Data from 1371 TESE procedures were collected between June 2007 and June 2015 in the two fertility centres. All men with NOA undergoing their first TESE procedure as part of a fertility treatment were included. The primary end-point was the presence of one or more spermatozoa (regardless of their motility) in the testicular biopsies.We constructed a model for the prediction of successful sperm retrieval, using univariable and multivariable binary logistic regression analysis and the dataset from one centre. This model was then validated using the dataset from the other centre. The area under the receiver-operating characteristic curve (AUC) was calculated and model calibration was assessed. There were 599 (43.7%) successful sperm retrievals after a first TESE procedure. The prediction model, built after multivariable logistic regression analysis, demonstrated that higher male age, higher levels of serum testosterone and lower levels of FSH and LH were predictive for successful sperm retrieval. Diagnosis of idiopathic NOA and the presence of an azoospermia factor c gene deletion were predictive for unsuccessful sperm retrieval. The AUC was 0.69 (95% confidence interval (CI): 0.66-0.72). The difference between the mean observed chance and the mean predicted chance was <2.0% in all groups, indicating good calibration. In validation, the model had moderate discriminative capacity (AUC 0.65, 95% CI: 0.62-0.72) and moderate calibration: the predicted probability never differed by more than 9.2% of the mean observed probability. The percentage of men with Klinefelter syndrome among men diagnosed with NOA is expected to be higher than in our study population, which is a potential selection bias. The ability of the sperm retrieved to fertilize an oocyte and produce a live birth was not tested. This model can help in clinical decision-making in men with NOA by reliably predicting the chance of obtaining spermatozoa with TESE. This study was partly supported by an unconditional grant from Merck Serono (to D.D.M.B. and K.F.) and by the Department of Obstetrics and Gynaecology of Radboud University Medical Center, Nijmegen, The Netherlands, the Department of Obstetrics and Gynaecology, Jeroen Bosch Hospital, Den Bosch, The Netherlands, and the Department of Obstetrics and Gynaecology, Academic Medical Center, Amsterdam, The Netherlands. Merck Serono had no influence in concept, design nor elaboration of this study. Not applicable. © The Author 2016. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Predicting survival across chronic interstitial lung disease: the ILD-GAP model.

PubMed

Ryerson, Christopher J; Vittinghoff, Eric; Ley, Brett; Lee, Joyce S; Mooney, Joshua J; Jones, Kirk D; Elicker, Brett M; Wolters, Paul J; Koth, Laura L; King, Talmadge E; Collard, Harold R

2014-04-01

Risk prediction is challenging in chronic interstitial lung disease (ILD) because of heterogeneity in disease-specific and patient-specific variables. Our objective was to determine whether mortality is accurately predicted in patients with chronic ILD using the GAP model, a clinical prediction model based on sex, age, and lung physiology, that was previously validated in patients with idiopathic pulmonary fibrosis. Patients with idiopathic pulmonary fibrosis (n=307), chronic hypersensitivity pneumonitis (n=206), connective tissue disease-associated ILD (n=281), idiopathic nonspecific interstitial pneumonia (n=45), or unclassifiable ILD (n=173) were selected from an ongoing database (N=1,012). Performance of the previously validated GAP model was compared with novel prediction models in each ILD subtype and the combined cohort. Patients with follow-up pulmonary function data were used for longitudinal model validation. The GAP model had good performance in all ILD subtypes (c-index, 74.6 in the combined cohort), which was maintained at all stages of disease severity and during follow-up evaluation. The GAP model had similar performance compared with alternative prediction models. A modified ILD-GAP Index was developed for application across all ILD subtypes to provide disease-specific survival estimates using a single risk prediction model. This was done by adding a disease subtype variable that accounted for better adjusted survival in connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and idiopathic nonspecific interstitial pneumonia. The GAP model accurately predicts risk of death in chronic ILD. The ILD-GAP model accurately predicts mortality in major chronic ILD subtypes and at all stages of disease.

Assessing participation in community-based physical activity programs in Brazil.

PubMed

Reis, Rodrigo S; Yan, Yan; Parra, Diana C; Brownson, Ross C

2014-01-01

This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14-4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16-2.53), reporting a good health (OR = 1.58, 95% CI = 1.02-2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05-2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26-2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18-2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil.

Comparison of Three Contemporary Risk Scores for Mortality Following Elective Abdominal Aortic Aneurysm Repair

PubMed Central

Grant, S.W.; Hickey, G.L.; Carlson, E.D.; McCollum, C.N.

2014-01-01

Objective/background A number of contemporary risk prediction models for mortality following elective abdominal aortic aneurysm (AAA) repair have been developed. Before a model is used either in clinical practice or to risk-adjust surgical outcome data it is important that its performance is assessed in external validation studies. Methods The British Aneurysm Repair (BAR) score, Medicare, and Vascular Governance North West (VGNW) models were validated using an independent prospectively collected sample of multicentre clinical audit data. Consecutive, data on 1,124 patients undergoing elective AAA repair at 17 hospitals in the north-west of England and Wales between April 2011 and March 2013 were analysed. The outcome measure was in-hospital mortality. Model calibration (observed to expected ratio with chi-square test, calibration plots, calibration intercept and slope) and discrimination (area under receiver operating characteristic curve [AUC]) were assessed in the overall cohort and procedural subgroups. Results The mean age of the population was 74.4 years (SD 7.7); 193 (17.2%) patients were women and the majority of patients (759, 67.5%) underwent endovascular aneurysm repair. All three models demonstrated good calibration in the overall cohort and procedural subgroups. Overall discrimination was excellent for the BAR score (AUC 0.83, 95% confidence interval [CI] 0.76–0.89), and acceptable for the Medicare and VGNW models, with AUCs of 0.78 (95% CI 0.70–0.86) and 0.75 (95% CI 0.65–0.84) respectively. Only the BAR score demonstrated good discrimination in procedural subgroups. Conclusion All three models demonstrated good calibration and discrimination for the prediction of in-hospital mortality following elective AAA repair and are potentially useful. The BAR score has a number of advantages, which include being developed on the most contemporaneous data, excellent overall discrimination, and good performance in procedural subgroups. Regular model validations and recalibration will be essential. PMID:24837173

Comparison of three contemporary risk scores for mortality following elective abdominal aortic aneurysm repair.

PubMed

Grant, S W; Hickey, G L; Carlson, E D; McCollum, C N

2014-07-01

A number of contemporary risk prediction models for mortality following elective abdominal aortic aneurysm (AAA) repair have been developed. Before a model is used either in clinical practice or to risk-adjust surgical outcome data it is important that its performance is assessed in external validation studies. The British Aneurysm Repair (BAR) score, Medicare, and Vascular Governance North West (VGNW) models were validated using an independent prospectively collected sample of multicentre clinical audit data. Consecutive, data on 1,124 patients undergoing elective AAA repair at 17 hospitals in the north-west of England and Wales between April 2011 and March 2013 were analysed. The outcome measure was in-hospital mortality. Model calibration (observed to expected ratio with chi-square test, calibration plots, calibration intercept and slope) and discrimination (area under receiver operating characteristic curve [AUC]) were assessed in the overall cohort and procedural subgroups. The mean age of the population was 74.4 years (SD 7.7); 193 (17.2%) patients were women and the majority of patients (759, 67.5%) underwent endovascular aneurysm repair. All three models demonstrated good calibration in the overall cohort and procedural subgroups. Overall discrimination was excellent for the BAR score (AUC 0.83, 95% confidence interval [CI] 0.76-0.89), and acceptable for the Medicare and VGNW models, with AUCs of 0.78 (95% CI 0.70-0.86) and 0.75 (95% CI 0.65-0.84) respectively. Only the BAR score demonstrated good discrimination in procedural subgroups. All three models demonstrated good calibration and discrimination for the prediction of in-hospital mortality following elective AAA repair and are potentially useful. The BAR score has a number of advantages, which include being developed on the most contemporaneous data, excellent overall discrimination, and good performance in procedural subgroups. Regular model validations and recalibration will be essential. Copyright © 2014 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Validation of a Deterministic Vibroacoustic Response Prediction Model

NASA Technical Reports Server (NTRS)

Caimi, Raoul E.; Margasahayam, Ravi

1997-01-01

This report documents the recently completed effort involving validation of a deterministic theory for the random vibration problem of predicting the response of launch pad structures in the low-frequency range (0 to 50 hertz). Use of the Statistical Energy Analysis (SEA) methods is not suitable in this range. Measurements of launch-induced acoustic loads and subsequent structural response were made on a cantilever beam structure placed in close proximity (200 feet) to the launch pad. Innovative ways of characterizing random, nonstationary, non-Gaussian acoustics are used for the development of a structure's excitation model. Extremely good correlation was obtained between analytically computed responses and those measured on the cantilever beam. Additional tests are recommended to bound the problem to account for variations in launch trajectory and inclination.

Development and validation of a prognostic nomogram for terminally ill cancer patients.

PubMed

Feliu, Jaime; Jiménez-Gordo, Ana María; Madero, Rosario; Rodríguez-Aizcorbe, José Ramón; Espinosa, Enrique; Castro, Javier; Acedo, Jesús Domingo; Martínez, Beatriz; Alonso-Babarro, Alberto; Molina, Raquel; Cámara, Juan Carlos; García-Paredes, María Luisa; González-Barón, Manuel

2011-11-02

Determining life expectancy in terminally ill cancer patients is a difficult task. We aimed to develop and validate a nomogram to predict the length of survival in patients with terminal disease. From February 1, 2003, to December 31, 2005, 406 consecutive terminally ill patients were entered into the study. We analyzed 38 features prognostic of life expectancy among terminally ill patients by multivariable Cox regression and identified the most accurate and parsimonious model by backward variable elimination according to the Akaike information criterion. Five clinical and laboratory variables were built into a nomogram to estimate the probability of patient survival at 15, 30, and 60 days. We validated and calibrated the nomogram with an external validation cohort of 474 patients who were treated from June 1, 2006, through December 31, 2007. The median overall survival was 29.1 days for the training set and 18.3 days for the validation set. Eastern Cooperative Oncology Group performance status, lactate dehydrogenase levels, lymphocyte levels, albumin levels, and time from initial diagnosis to diagnosis of terminal disease were retained in the multivariable Cox proportional hazards model as independent prognostic factors of survival and formed the basis of the nomogram. The nomogram had high predictive performance, with a bootstrapped corrected concordance index of 0.70, and it showed good calibration. External independent validation revealed 68% predictive accuracy. We developed a highly accurate tool that uses basic clinical and analytical information to predict the probability of survival at 15, 30, and 60 days in terminally ill cancer patients. This tool can help physicians making decisions on clinical care at the end of life.

Personalized Prediction of Psychosis: External validation of the NAPLS2 Psychosis Risk Calculator with the EDIPPP project

PubMed Central

Carrión, Ricardo E.; Cornblatt, Barbara A.; Burton, Cynthia Z.; Tso, Ivy F; Auther, Andrea; Adelsheim, Steven; Calkins, Roderick; Carter, Cameron S.; Niendam, Tara; Taylor, Stephan F.; McFarlane, William R.

2016-01-01

Objective In the current issue, Cannon and colleagues, as part of the second phase of the North American Prodrome Longitudinal Study (NAPLS2), report on a risk calculator for the individualized prediction of developing a psychotic disorder in a 2-year period. The present study represents an external validation of the NAPLS2 psychosis risk calculator using an independent sample of subjects at clinical high risk for psychosis collected as part of the Early Detection, Intervention, and Prevention of Psychosis Program (EDIPPP). Methods 176 subjects with follow-up (from the total EDIPPP sample of 210) rated as clinical high-risk (CHR) based on the Structured Interview for Prodromal Syndromes were used to construct a new prediction model with the 6 significant predictor variables in the NAPLS2 psychosis risk calculator (unusual thoughts, suspiciousness, Symbol Coding, verbal learning, social functioning decline, baseline age, and family history). Discrimination performance was assessed with the area under the receiver operating curve (AUC). The NAPLS2 risk calculator was then used to generate a psychosis risk estimate for each case in the external validation sample. Results The external validation model showed good discrimination, with an AUC of 79% (95% CI 0.644–0.937). In addition, the personalized risk generated by the NAPLS calculator provided a solid estimation of the actual conversion outcome in the validation sample. Conclusions In the companion papers in this issue, two independent samples of CHR subjects converge to validate the NAPLS2 psychosis risk calculator. This prediction calculator represents a meaningful step towards early intervention and personalized treatment of psychotic disorders. PMID:27363511

Predictive and construct validity of the Bayley Scales of Infant Development and the Wechsler Preschool and Primary Scale of Intelligence with the Taiwan Birth Cohort Study instrument.

PubMed

Lung, For-Wey; Chen, Po-Fei; Shu, Bih-Ching

2012-08-01

This study aimed to investigate the concurrent validity of the parent-report Taiwan Birth Cohort Study Developmental Instrument (TBCS-DI) with the Bayley Scales of Infant Development-Second Edition (BSID-II) and the Wechsler Preschool and Primary Scale of Intelligence-Revised (WPPSI-R) at 6, 18, 36, and 60 months. 100 children were recruited at 6 months, 88 children followed-up at 18 months, 71 at 36 months, and 53 at 60 months. Longitudinally, the parent-report TBCS-DI, with the professional psychological assessments of the BSID-II and the WPPSI-R showed predictive validity. Looking at each time point in cross section, at 6 and 18 months the TBCS-DI had good concurrent validity with the BSID-II, and at 36 and 60 months the TBCS-DI was correlated only with the motor and performance domains of the BSID-II and WPPSI-R. With further investigation, the TBCS-DI may be used both in research and in clinical settings.

Communication: Limitations of the stochastic quasi-steady-state approximation in open biochemical reaction networks

NASA Astrophysics Data System (ADS)

Thomas, Philipp; Straube, Arthur V.; Grima, Ramon

2011-11-01

It is commonly believed that, whenever timescale separation holds, the predictions of reduced chemical master equations obtained using the stochastic quasi-steady-state approximation are in very good agreement with the predictions of the full master equations. We use the linear noise approximation to obtain a simple formula for the relative error between the predictions of the two master equations for the Michaelis-Menten reaction with substrate input. The reduced approach is predicted to overestimate the variance of the substrate concentration fluctuations by as much as 30%. The theoretical results are validated by stochastic simulations using experimental parameter values for enzymes involved in proteolysis, gluconeogenesis, and fermentation.

Testing Pearl Model In Three European Sites

NASA Astrophysics Data System (ADS)

Bouraoui, F.; Bidoglio, G.

The Plant Protection Product Directive (91/414/EEC) stresses the need of validated models to calculate predicted environmental concentrations. The use of models has become an unavoidable step before pesticide registration. In this context, European Commission, and in particular DGVI, set up a FOrum for the Co-ordination of pes- ticide fate models and their USe (FOCUS). In a complementary effort, DG research supported the APECOP project, with one of its objective being the validation and im- provement of existing pesticide fate models. The main topic of research presented here is the validation of the PEARL model for different sites in Europe. The PEARL model, actually used in the Dutch pesticide registration procedure, was validated in three well- instrumented sites: Vredepeel (the Netherlands), Brimstone (UK), and Lanna (Swe- den). A step-wise procedure was used for the validation of the PEARL model. First the water transport module was calibrated, and then the solute transport module, using tracer measurements keeping unchanged the water transport parameters. The Vrede- peel site is characterised by a sandy soil. Fourteen months of measurements were used for the calibration. Two pesticides were applied on the site: bentazone and etho- prophos. PEARL predictions were very satisfactory for both soil moisture content, and pesticide concentration in the soil profile. The Brimstone site is characterised by a cracking clay soil. The calibration was conducted on a time series measurement of 7 years. The validation consisted in comparing predictions and measurement of soil moisture at different soil depths, and in comparing the predicted and measured con- centration of isoproturon in the drainage water. The results, even if in good agreement with the measuremens, highlighted the limitation of the model when the preferential flow becomes a dominant process. PEARL did not reproduce well soil moisture pro- file during summer months, and also under-predicted the arrival of isoproturon to the drains. The Lanna site is characterised by s structured clay soil. PEARL was success- ful in predicting soil moisture profiles and the draining water. PEARL performed well in predicting the soil concentration of bentazone at different depth. However, since PEARL does not consider cracks in the soil, it did not predict well the peak concen- trations of bentazone in the drainage water. Along with the validation results for the three sites, a sensitivity analysis of the model is presented.

Development of a novel score for the prediction of hospital mortality in patients with severe sepsis: the use of electronic healthcare records with LASSO regression.

PubMed

Zhang, Zhongheng; Hong, Yucai

2017-07-25

There are several disease severity scores being used for the prediction of mortality in critically ill patients. However, none of them was developed and validated specifically for patients with severe sepsis. The present study aimed to develop a novel prediction score for severe sepsis. A total of 3206 patients with severe sepsis were enrolled, including 1054 non-survivors and 2152 survivors. The LASSO score showed the best discrimination (area under curve: 0.772; 95% confidence interval: 0.735-0.810) in the validation cohort as compared with other scores such as simplified acute physiology score II, acute physiological score III, Logistic organ dysfunction system, sequential organ failure assessment score, and Oxford Acute Severity of Illness Score. The calibration slope was 0.889 and Brier value was 0.173. The study employed a single center database called Medical Information Mart for Intensive Care-III) MIMIC-III for analysis. Severe sepsis was defined as infection and acute organ dysfunction. Clinical and laboratory variables used in clinical routines were included for screening. Subjects without missing values were included, and the whole dataset was split into training and validation cohorts. The score was coined LASSO score because variable selection was performed using the least absolute shrinkage and selection operator (LASSO) technique. Finally, the LASSO score was evaluated for its discrimination and calibration in the validation cohort. The study developed the LASSO score for mortality prediction in patients with severe sepsis. Although the score had good discrimination and calibration in a randomly selected subsample, external validations are still required.

A novel method for structure-based prediction of ion channel conductance properties.

PubMed Central

Smart, O S; Breed, J; Smith, G R; Sansom, M S

1997-01-01

A rapid and easy-to-use method of predicting the conductance of an ion channel from its three-dimensional structure is presented. The method combines the pore dimensions of the channel as measured in the HOLE program with an Ohmic model of conductance. An empirically based correction factor is then applied. The method yielded good results for six experimental channel structures (none of which were included in the training set) with predictions accurate to within an average factor of 1.62 to the true values. The predictive r2 was equal to 0.90, which is indicative of a good predictive ability. The procedure is used to validate model structures of alamethicin and phospholamban. Two genuine predictions for the conductance of channels with known structure but without reported conductances are given. A modification of the procedure that calculates the expected results for the effect of the addition of nonelectrolyte polymers on conductance is set out. Results for a cholera toxin B-subunit crystal structure agree well with the measured values. The difficulty in interpreting such studies is discussed, with the conclusion that measurements on channels of known structure are required. Images FIGURE 1 FIGURE 3 FIGURE 4 FIGURE 6 FIGURE 10 PMID:9138559

Comparing spatial regression to random forests for large ...

EPA Pesticide Factsheets

Environmental data may be “large” due to number of records, number of covariates, or both. Random forests has a reputation for good predictive performance when using many covariates, whereas spatial regression, when using reduced rank methods, has a reputation for good predictive performance when using many records. In this study, we compare these two techniques using a data set containing the macroinvertebrate multimetric index (MMI) at 1859 stream sites with over 200 landscape covariates. Our primary goal is predicting MMI at over 1.1 million perennial stream reaches across the USA. For spatial regression modeling, we develop two new methods to accommodate large data: (1) a procedure that estimates optimal Box-Cox transformations to linearize covariate relationships; and (2) a computationally efficient covariate selection routine that takes into account spatial autocorrelation. We show that our new methods lead to cross-validated performance similar to random forests, but that there is an advantage for spatial regression when quantifying the uncertainty of the predictions. Simulations are used to clarify advantages for each method. This research investigates different approaches for modeling and mapping national stream condition. We use MMI data from the EPA's National Rivers and Streams Assessment and predictors from StreamCat (Hill et al., 2015). Previous studies have focused on modeling the MMI condition classes (i.e., good, fair, and po

Self-esteem recognition based on gait pattern using Kinect.

PubMed

Sun, Bingli; Zhang, Zhan; Liu, Xingyun; Hu, Bin; Zhu, Tingshao

2017-10-01

Self-esteem is an important aspect of individual's mental health. When subjects are not able to complete self-report questionnaire, behavioral assessment will be a good supplement. In this paper, we propose to use gait data collected by Kinect as an indicator to recognize self-esteem. 178 graduate students without disabilities participate in our study. Firstly, all participants complete the 10-item Rosenberg Self-Esteem Scale (RSS) to acquire self-esteem score. After completing the RRS, each participant walks for two minutes naturally on a rectangular red carpet, and the gait data are recorded using Kinect sensor. After data preprocessing, we extract a few behavioral features to train predicting model by machine learning. Based on these features, we build predicting models to recognize self-esteem. For self-esteem prediction, the best correlation coefficient between predicted score and self-report score is 0.45 (p<0.001). We divide the participants according to gender, and for males, the correlation coefficient is 0.43 (p<0.001), for females, it is 0.59 (p<0.001). Using gait data captured by Kinect sensor, we find that the gait pattern could be used to recognize self-esteem with a fairly good criterion validity. The gait predicting model can be taken as a good supplementary method to measure self-esteem. Copyright © 2017 Elsevier B.V. All rights reserved.

Neonatal intensive care unit: predictive models for length of stay.

PubMed

Bender, G J; Koestler, D; Ombao, H; McCourt, M; Alskinis, B; Rubin, L P; Padbury, J F

2013-02-01

Hospital length of stay (LOS) is important to administrators and families of neonates admitted to the neonatal intensive care unit (NICU). A prediction model for NICU LOS was developed using predictors birth weight, gestational age and two severity of illness tools, the score for neonatal acute physiology, perinatal extension (SNAPPE) and the morbidity assessment index for newborns (MAIN). Consecutive admissions (n=293) to a New England regional level III NICU were retrospectively collected. Multiple predictive models were compared for complexity and goodness-of-fit, coefficient of determination (R (2)) and predictive error. The optimal model was validated prospectively with consecutive admissions (n=615). Observed and expected LOS was compared. The MAIN models had best Akaike's information criterion, highest R (2) (0.786) and lowest predictive error. The best SNAPPE model underestimated LOS, with substantial variability, yet was fairly well calibrated by birthweight category. LOS was longer in the prospective cohort than the retrospective cohort, without differences in birth weight, gestational age, MAIN or SNAPPE. LOS prediction is improved by accounting for severity of illness in the first week of life, beyond factors known at birth. Prospective validation of both MAIN and SNAPPE models is warranted.

Prediction of liver disease in patients whose liver function tests have been checked in primary care: model development and validation using population-based observational cohorts.

PubMed

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

2014-06-02

To derive and validate a clinical prediction model to estimate the risk of liver disease diagnosis following liver function tests (LFTs) and to convert the model to a simplified scoring tool for use in primary care. Population-based observational cohort study of patients in Tayside Scotland identified as having their LFTs performed in primary care and followed for 2 years. Biochemistry data were linked to secondary care, prescriptions and mortality data to ascertain baseline characteristics of the derivation cohort. A separate validation cohort was obtained from 19 general practices across the rest of Scotland to externally validate the final model. Primary care, Tayside, Scotland. Derivation cohort: LFT results from 310 511 patients. After exclusions (including: patients under 16 years, patients having initial LFTs measured in secondary care, bilirubin >35 μmol/L, liver complications within 6 weeks and history of a liver condition), the derivation cohort contained 95 977 patients with no clinically apparent liver condition. Validation cohort: after exclusions, this cohort contained 11 653 patients. Diagnosis of a liver condition within 2 years. From the derivation cohort (n=95 977), 481 (0.5%) were diagnosed with a liver disease. The model showed good discrimination (C-statistic=0.78). Given the low prevalence of liver disease, the negative predictive values were high. Positive predictive values were low but rose to 20-30% for high-risk patients. This study successfully developed and validated a clinical prediction model and subsequent scoring tool, the Algorithm for Liver Function Investigations (ALFI), which can predict liver disease risk in patients with no clinically obvious liver disease who had their initial LFTs taken in primary care. ALFI can help general practitioners focus referral on a small subset of patients with higher predicted risk while continuing to address modifiable liver disease risk factors in those at lower risk. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

A Computational Model for Predicting RNase H Domain of Retrovirus.

PubMed

Wu, Sijia; Zhang, Xinman; Han, Jiuqiang

2016-01-01

RNase H (RNH) is a pivotal domain in retrovirus to cleave the DNA-RNA hybrid for continuing retroviral replication. The crucial role indicates that RNH is a promising drug target for therapeutic intervention. However, annotated RNHs in UniProtKB database have still been insufficient for a good understanding of their statistical characteristics so far. In this work, a computational RNH model was proposed to annotate new putative RNHs (np-RNHs) in the retroviruses. It basically predicts RNH domains through recognizing their start and end sites separately with SVM method. The classification accuracy rates are 100%, 99.01% and 97.52% respectively corresponding to jack-knife, 10-fold cross-validation and 5-fold cross-validation test. Subsequently, this model discovered 14,033 np-RNHs after scanning sequences without RNH annotations. All these predicted np-RNHs and annotated RNHs were employed to analyze the length, hydrophobicity and evolutionary relationship of RNH domains. They are all related to retroviral genera, which validates the classification of retroviruses to a certain degree. In the end, a software tool was designed for the application of our prediction model. The software together with datasets involved in this paper can be available for free download at https://sourceforge.net/projects/rhtool/files/?source=navbar.

Validation of Field Methods to Assess Body Fat Percentage in Elite Youth Soccer Players.

PubMed

Munguia-Izquierdo, Diego; Suarez-Arrones, Luis; Di Salvo, Valter; Paredes-Hernandez, Victor; Alcazar, Julian; Ara, Ignacio; Kreider, Richard; Mendez-Villanueva, Alberto

2018-05-01

This study determined the most effective field method for quantifying body fat percentage in male elite youth soccer players and developed prediction equations based on anthropometric variables. Forty-four male elite-standard youth soccer players aged 16.3-18.0 years underwent body fat percentage assessments, including bioelectrical impedance analysis and the calculation of various skinfold-based prediction equations. Dual X-ray absorptiometry provided a criterion measure of body fat percentage. Correlation coefficients, bias, limits of agreement, and differences were used as validity measures, and regression analyses were used to develop soccer-specific prediction equations. The equations from Sarria et al. (1998) and Durnin & Rahaman (1967) reached very large correlations and the lowest biases, and they reached neither the practically worthwhile difference nor the substantial difference between methods. The new youth soccer-specific skinfold equation included a combination of triceps and supraspinale skinfolds. None of the practical methods compared in this study are adequate for estimating body fat percentage in male elite youth soccer players, except for the equations from Sarria et al. (1998) and Durnin & Rahaman (1967). The new youth soccer-specific equation calculated in this investigation is the only field method specifically developed and validated in elite male players, and it shows potentially good predictive power. © Georg Thieme Verlag KG Stuttgart · New York.

Initial Validation of a Comprehensive Assessment Instrument for Bereavement-Related Grief Symptoms and Risk of Complications: The Indicator of Bereavement Adaptation—Cruse Scotland (IBACS)

PubMed Central

Schut, Henk; Stroebe, Margaret S.; Wilson, Stewart; Birrell, John

2016-01-01

Objective This study assessed the validity of the Indicator of Bereavement Adaptation Cruse Scotland (IBACS). Designed for use in clinical and non-clinical settings, the IBACS measures severity of grief symptoms and risk of developing complications. Method N = 196 (44 male, 152 female) help-seeking, bereaved Scottish adults participated at two timepoints: T1 (baseline) and T2 (after 18 months). Four validated assessment instruments were administered: CORE-R, ICG-R, IES-R, SCL-90-R. Discriminative ability was assessed using ROC curve analysis. Concurrent validity was tested through correlation analysis at T1. Predictive validity was assessed using correlation analyses and ROC curve analysis. Optimal IBACS cutoff values were obtained by calculating a maximal Youden index J in ROC curve analysis. Clinical implications were compared across instruments. Results ROC curve analysis results (AUC = .84, p < .01, 95% CI between .77 and .90) indicated the IBACS is a good diagnostic instrument for assessing complicated grief. Positive correlations (p < .01, 2-tailed) with all four instruments at T1 demonstrated the IBACS' concurrent validity, strongest with complicated grief measures (r = .82). Predictive validity was shown to be fair in T2 ROC curve analysis results (n = 67, AUC = .78, 95% CI between .65 and .92; p < .01). Predictive validity was also supported by stable positive correlations between IBACS and other instruments at T2. Clinical indications were found not to differ across instruments. Conclusions The IBACS offers effective grief symptom and risk assessment for use by non-clinicians. Indications are sufficient to support intake assessment for a stepped model of bereavement intervention. PMID:27741246

Validation of a new measure of availability and accommodation of health care that is valid for rural and urban contexts.

PubMed

Haggerty, Jeannie L; Levesque, Jean-Frédéric

2017-04-01

Patients are the most valid source for evaluating the accessibility of services, but a previous study observed differential psychometric performance of instruments in rural and urban respondents. To validate a measure of organizational accessibility free of differential rural-urban performance that predicts consequences of difficult access for patient-initiated care. Sequential qualitative-quantitative study. Qualitative findings used to adapt or develop evaluative and reporting items. Quantitative validation study. Primary data by telephone from 750 urban, rural and remote respondents in Quebec, Canada; follow-up mailed questionnaire to a subset of 316. Items were developed for barriers along the care trajectory. We used common factor and confirmatory factor analysis to identify constructs and compare models. We used item response theory analysis to test for differential rural-urban performance; examine individual item performance; adjust response options; and exclude redundant or non-discriminatory items. We used logistic regression to examine predictive validity of the subscale on access difficulty (outcome). Initial factor resolution suggested geographic and organizational dimensions, plus consequences of access difficulty. After second administration, organizational accommodation and geographic indicators were integrated into a 6-item subscale of Effective Availability and Accommodation, which demonstrates good variability and internal consistency (α = 0.84) and no differential functioning by geographic area. Each unit increase predicts decreased likelihood of consequences of access difficulties (unmet need and problem aggravation). The new subscale is a practical, valid and reliable measure for patients to evaluate first-contact health services accessibility, yielding valid comparisons between urban and rural contexts. © 2016 The Authors. Health Expectations published by John Wiley & Sons Ltd.

Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations.

NASA Astrophysics Data System (ADS)

Ángel Prósper Fernández, Miguel; Casal, Carlos Otero; Canoura Fernández, Felipe; Miguez-Macho, Gonzalo

2017-04-01

Regional meteorological models are becoming a generalized tool for forecasting wind resource, due to their capacity to simulate local flow dynamics impacting wind farm production. This study focuses on the production forecast and validation of a real onshore wind farm using high horizontal and vertical resolution WRF (Weather Research and Forecasting) model simulations. The wind farm is located in Galicia, in the northwest of Spain, in a complex terrain region with high wind resource. Utilizing the Fitch scheme, specific for wind farms, a period of one year is simulated with a daily operational forecasting set-up. Power and wind predictions are obtained and compared with real data provided by the management company. Results show that WRF is able to yield good wind power operational predictions for this kind of wind farms, due to a good representation of the planetary boundary layer behaviour of the region and the good performance of the Fitch scheme under these conditions.

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

PubMed

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

2013-01-01

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

Development and validation of a radiomics nomogram for progression-free survival prediction in stage IV EGFR-mutant non-small cell lung cancer

NASA Astrophysics Data System (ADS)

Song, Jiangdian; Zang, Yali; Li, Weimin; Zhong, Wenzhao; Shi, Jingyun; Dong, Di; Fang, Mengjie; Liu, Zaiyi; Tian, Jie

2017-03-01

Accurately predict the risk of disease progression and benefit of tyrosine kinase inhibitors (TKIs) therapy for stage IV non-small cell lung cancer (NSCLC) patients with activing epidermal growth factor receptor (EGFR) mutations by current staging methods are challenge. We postulated that integrating a classifier consisted of multiple computed tomography (CT) phenotypic features, and other clinicopathological risk factors into a single model could improve risk stratification and prediction of progression-free survival (PFS) of EGFR TKIs for these patients. Patients confirmed as stage IV EGFR-mutant NSCLC received EGFR TKIs with no resection; pretreatment contrast enhanced CT performed at approximately 2 weeks before the treatment was enrolled. A six-CT-phenotypic-feature-based classifier constructed by the LASSO Cox regression model, and three clinicopathological factors: pathologic N category, performance status (PS) score, and intrapulmonary metastasis status were used to construct a nomogram in a training set of 115 patients. The prognostic and predictive accuracy of this nomogram was then subjected to an external independent validation of 107 patients. PFS between the training and independent validation set is no statistical difference by Mann-Whitney U test (P = 0.2670). PFS of the patients could be predicted with good consistency compared with the actual survival. C-index of the proposed individualized nomogram in the training set (0·707, 95%CI: 0·643, 0·771) and the independent validation set (0·715, 95%CI: 0·650, 0·780) showed the potential of clinical prognosis to predict PFS of stage IV EGFR-mutant NSCLC from EGFR TKIs. The individualized nomogram might facilitate patient counselling and individualise management of patients with this disease.

A predictive score to identify hospitalized patients' risk of discharge to a post-acute care facility

PubMed Central

Louis Simonet, Martine; Kossovsky, Michel P; Chopard, Pierre; Sigaud, Philippe; Perneger, Thomas V; Gaspoz, Jean-Michel

2008-01-01

Background Early identification of patients who need post-acute care (PAC) may improve discharge planning. The purposes of the study were to develop and validate a score predicting discharge to a post-acute care (PAC) facility and to determine its best assessment time. Methods We conducted a prospective study including 349 (derivation cohort) and 161 (validation cohort) consecutive patients in a general internal medicine service of a teaching hospital. We developed logistic regression models predicting discharge to a PAC facility, based on patient variables measured on admission (day 1) and on day 3. The value of each model was assessed by its area under the receiver operating characteristics curve (AUC). A simple numerical score was derived from the best model, and was validated in a separate cohort. Results Prediction of discharge to a PAC facility was as accurate on day 1 (AUC: 0.81) as on day 3 (AUC: 0.82). The day-3 model was more parsimonious, with 5 variables: patient's partner inability to provide home help (4 pts); inability to self-manage drug regimen (4 pts); number of active medical problems on admission (1 pt per problem); dependency in bathing (4 pts) and in transfers from bed to chair (4 pts) on day 3. A score ≥ 8 points predicted discharge to a PAC facility with a sensitivity of 87% and a specificity of 63%, and was significantly associated with inappropriate hospital days due to discharge delays. Internal and external validations confirmed these results. Conclusion A simple score computed on the 3rd hospital day predicted discharge to a PAC facility with good accuracy. A score > 8 points should prompt early discharge planning. PMID:18647410

Predicting the Individual Risk of Acute Severe Colitis at Diagnosis

PubMed Central

Cesarini, Monica; Collins, Gary S.; Rönnblom, Anders; Santos, Antonieta; Wang, Lai Mun; Sjöberg, Daniel; Parkes, Miles; Keshav, Satish

2017-01-01

Abstract Background and Aims: Acute severe colitis [ASC] is associated with major morbidity. We aimed to develop and externally validate an index that predicted ASC within 3 years of diagnosis. Methods: The development cohort included patients aged 16–89 years, diagnosed with ulcerative colitis [UC] in Oxford and followed for 3 years. Primary outcome was hospitalization for ASC, excluding patients admitted within 1 month of diagnosis. Multivariable logistic regression examined the adjusted association of seven risk factors with ASC. Backwards elimination produced a parsimonious model that was simplified to create an easy-to-use index. External validation occurred in separate cohorts from Cambridge, UK, and Uppsala, Sweden. Results: The development cohort [Oxford] included 34/111 patients who developed ASC within a median 14 months [range 1–29]. The final model applied the sum of 1 point each for extensive disease, C-reactive protein [CRP] > 10mg/l, or haemoglobin < 12g/dl F or < 14g/dl M at diagnosis, to give a score from 0/3 to 3/3. This predicted a 70% risk of developing ASC within 3 years [score 3/3]. Validation cohorts included different proportions with ASC [Cambridge = 25/96; Uppsala = 18/298]. Of those scoring 3/3 at diagnosis, 18/18 [Cambridge] and 12/13 [Uppsala] subsequently developed ASC. Discriminant ability [c-index, where 1.0 = perfect discrimination] was 0.81 [Oxford], 0.95 [Cambridge], 0.97 [Uppsala]. Internal validation using bootstrapping showed good calibration, with similar predicted risk across all cohorts. A nomogram predicted individual risk. Conclusions: An index applied at diagnosis reliably predicts the risk of ASC within 3 years in different populations. Patients with a score 3/3 at diagnosis may merit early immunomodulator therapy. PMID:27647858

Machine Learning Meta-analysis of Large Metagenomic Datasets: Tools and Biological Insights.

PubMed

Pasolli, Edoardo; Truong, Duy Tin; Malik, Faizan; Waldron, Levi; Segata, Nicola

2016-07-01

Shotgun metagenomic analysis of the human associated microbiome provides a rich set of microbial features for prediction and biomarker discovery in the context of human diseases and health conditions. However, the use of such high-resolution microbial features presents new challenges, and validated computational tools for learning tasks are lacking. Moreover, classification rules have scarcely been validated in independent studies, posing questions about the generality and generalization of disease-predictive models across cohorts. In this paper, we comprehensively assess approaches to metagenomics-based prediction tasks and for quantitative assessment of the strength of potential microbiome-phenotype associations. We develop a computational framework for prediction tasks using quantitative microbiome profiles, including species-level relative abundances and presence of strain-specific markers. A comprehensive meta-analysis, with particular emphasis on generalization across cohorts, was performed in a collection of 2424 publicly available metagenomic samples from eight large-scale studies. Cross-validation revealed good disease-prediction capabilities, which were in general improved by feature selection and use of strain-specific markers instead of species-level taxonomic abundance. In cross-study analysis, models transferred between studies were in some cases less accurate than models tested by within-study cross-validation. Interestingly, the addition of healthy (control) samples from other studies to training sets improved disease prediction capabilities. Some microbial species (most notably Streptococcus anginosus) seem to characterize general dysbiotic states of the microbiome rather than connections with a specific disease. Our results in modelling features of the "healthy" microbiome can be considered a first step toward defining general microbial dysbiosis. The software framework, microbiome profiles, and metadata for thousands of samples are publicly available at http://segatalab.cibio.unitn.it/tools/metaml.

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies

PubMed Central

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-01-01

Background The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study Aim To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. Design and setting A three-part longitudinal predictive validity study of selection into training for UK general practice. Method In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Results Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. Conclusion In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered. PMID:24267856

The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

PubMed

Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

2013-11-01

The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

CFD Validation with Experiment and Verification with Physics of a Propellant Damping Device

NASA Technical Reports Server (NTRS)

Yang, H. Q.; Peugeot, John

2011-01-01

This paper will document our effort in validating a coupled fluid-structure interaction CFD tool in predicting a damping device performance in the laboratory condition. Consistently good comparisons of "blind" CFD predictions against experimental data under various operation conditions, design parameters, and cryogenic environment will be presented. The power of the coupled CFD-structures interaction code in explaining some unexpected phenomena of the device observed during the technology development will be illustrated. The evolution of the damper device design inside the LOX tank will be used to demonstrate the contribution of the tool in understanding, optimization and implementation of LOX damper in Ares I vehicle. It is due to the present validation effort, the LOX damper technology has matured to TRL 5. The present effort has also contributed to the transition of the technology from an early conceptual observation to the baseline design of thrust oscillation mitigation for the Ares I within a 10 month period.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control Over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

GRACE risk score: Sex-based validity of in-hospital mortality prediction in Canadian patients with acute coronary syndrome.

PubMed

Gong, Inna Y; Goodman, Shaun G; Brieger, David; Gale, Chris P; Chew, Derek P; Welsh, Robert C; Huynh, Thao; DeYoung, J Paul; Baer, Carolyn; Gyenes, Gabor T; Udell, Jacob A; Fox, Keith A A; Yan, Andrew T

2017-10-01

Although there are sex differences in management and outcome of acute coronary syndromes (ACS), sex is not a component of Global Registry of Acute Coronary Events (GRACE) risk score (RS) for in-hospital mortality prediction. We sought to determine the prognostic utility of GRACE RS in men and women, and whether its predictive accuracy would be augmented through sex-based modification of its components. Canadian men and women enrolled in GRACE and Canadian Registry of Acute Coronary Events were stratified as ST-segment elevation myocardial infarction (STEMI) or non-ST-segment elevation ACS (NSTE-ACS). GRACE RS was calculated as per original model. Discrimination and calibration were evaluated using the c-statistic and Hosmer-Lemeshow goodness-of-fit test, respectively. Multivariable logistic regression was undertaken to assess potential interactions of sex with GRACE RS components. For the overall cohort (n=14,422), unadjusted in-hospital mortality rate was higher in women than men (4.5% vs. 3.0%, p<0.001). Overall, GRACE RS c-statistic and goodness-of-fit test p-value were 0.85 (95% CI 0.83-0.87) and 0.11, respectively. While the RS had excellent discrimination for all subgroups (c-statistics >0.80), discrimination was lower for women compared to men with STEMI [0.80 (0.75-0.84) vs. 0.86 (0.82-0.89), respectively, p<0.05]. The goodness-of-fit test showed good calibration for women (p=0.86), but suboptimal for men (p=0.031). No significant interaction was evident between sex and RS components (all p>0.25). The GRACE RS is a valid predictor of in-hospital mortality for both men and women with ACS. The lack of interaction between sex and RS components suggests that sex-based modification is not required. Copyright © 2017 Elsevier B.V. All rights reserved.

PIV-measured versus CFD-predicted flow dynamics in anatomically realistic cerebral aneurysm models.

PubMed

Ford, Matthew D; Nikolov, Hristo N; Milner, Jaques S; Lownie, Stephen P; Demont, Edwin M; Kalata, Wojciech; Loth, Francis; Holdsworth, David W; Steinman, David A

2008-04-01

Computational fluid dynamics (CFD) modeling of nominally patient-specific cerebral aneurysms is increasingly being used as a research tool to further understand the development, prognosis, and treatment of brain aneurysms. We have previously developed virtual angiography to indirectly validate CFD-predicted gross flow dynamics against the routinely acquired digital subtraction angiograms. Toward a more direct validation, here we compare detailed, CFD-predicted velocity fields against those measured using particle imaging velocimetry (PIV). Two anatomically realistic flow-through phantoms, one a giant internal carotid artery (ICA) aneurysm and the other a basilar artery (BA) tip aneurysm, were constructed of a clear silicone elastomer. The phantoms were placed within a computer-controlled flow loop, programed with representative flow rate waveforms. PIV images were collected on several anterior-posterior (AP) and lateral (LAT) planes. CFD simulations were then carried out using a well-validated, in-house solver, based on micro-CT reconstructions of the geometries of the flow-through phantoms and inlet/outlet boundary conditions derived from flow rates measured during the PIV experiments. PIV and CFD results from the central AP plane of the ICA aneurysm showed a large stable vortex throughout the cardiac cycle. Complex vortex dynamics, captured by PIV and CFD, persisted throughout the cardiac cycle on the central LAT plane. Velocity vector fields showed good overall agreement. For the BA, aneurysm agreement was more compelling, with both PIV and CFD similarly resolving the dynamics of counter-rotating vortices on both AP and LAT planes. Despite the imposition of periodic flow boundary conditions for the CFD simulations, cycle-to-cycle fluctuations were evident in the BA aneurysm simulations, which agreed well, in terms of both amplitudes and spatial distributions, with cycle-to-cycle fluctuations measured by PIV in the same geometry. The overall good agreement between PIV and CFD suggests that CFD can reliably predict the details of the intra-aneurysmal flow dynamics observed in anatomically realistic in vitro models. Nevertheless, given the various modeling assumptions, this does not prove that they are mimicking the actual in vivo hemodynamics, and so validations against in vivo data are encouraged whenever possible.

Population Pharmacokinetics of Topiramate in Japanese Pediatric and Adult Patients With Epilepsy Using Routinely Monitored Data.

PubMed

Takeuchi, Masato; Yano, Ikuko; Ito, Satoko; Sugimoto, Mitsuhiro; Yamamoto, Shota; Yonezawa, Atsushi; Ikeda, Akio; Matsubara, Kazuo

2017-04-01

Topiramate is a second-generation antiepileptic drug used as monotherapy and adjunctive therapy in adults and children with partial seizures. A population pharmacokinetic (PPK) analysis was performed to improve the topiramate dosage adjustment for individualized treatment. Patients whose steady-state serum concentration of topiramate was routinely monitored at Kyoto University Hospital from April 2012 to March 2013 were included in the model-building data. A nonlinear mixed effects modeling program was used to evaluate the influence of covariates on topiramate pharmacokinetics. The obtained PPK model was evaluated by internal model validations, including goodness-of-fit plots and prediction-corrected visual predictive checks, and was externally confirmed using the validation data from January 2015 to December 2015. A total of 177 steady-state serum concentrations from 93 patients were used for the model-building analysis. The patients' age ranged from 2 to 68 years, and body weight ranged from 8.6 to 105 kg. The median serum concentration of topiramate was 1.7 mcg/mL, and half of the patients received carbamazepine coadministration. Based on a one-compartment model with first order absorption and elimination, the apparent volume of distribution was 105 L/70 kg, and the apparent clearance was allometrically related to the body weight as 2.25 L·h·70 kg without carbamazepine or phenytoin. Combination treatment with carbamazepine or phenytoin increased the apparent clearance to 3.51 L·h·70 kg. Goodness-of-fit plots, prediction-corrected visual predictive check, and external validation using the validation data from 43 patients confirmed an appropriateness of the final model. Simulations based on the final model showed that dosage adjustments allometrically scaling to body weight can equalize the serum concentrations in children of various ages and adults. The PPK model, using the power scaling of body weight, effectively elucidated the topiramate serum concentration profile ranging from pediatric to adult patients. Dosage adjustments based on body weight and concomitant antiepileptic drug help obtain the dosage of topiramate necessary to reach an effective concentration in each individual.

Screen Twice, Cut Once: Assessing the Predictive Validity of Teacher Selection Tools. Working Paper 120

ERIC Educational Resources Information Center

Goldhaber, Dan; Grout, Cyrus; Huntington-Klein, Nick

2014-01-01

Evidence suggests that teacher hiring in public schools is ad hoc and often fails to result in good selection among applicants. Some districts use structured selection instruments in the hiring process, but we know little about the efficacy of such tools. In this paper, we evaluate the ability of applicant selection tools used by the Spokane…

Design and validation of a Cannabis Use Intention Questionnaire (CUIQ) for adolescents.

PubMed

Lloret Irles, Daniel; Morell-Gomis, Ramón; Laguía, Ana; Moriano, Juan A

2018-01-01

In Spain, one in four 14 to 18-year-old adolescents has used cannabis during the last twelve months. Demand for treatment has increased in European countries. These facts have prompted the development of preventive interventions that require screening tools in order to identify the vulnerable population and to properly asses the efficacy of such interventions. The Theory of Planned Behaviour (TPB), widely used to forecast behavioural intention, has also demonstrated a good predictive capacity in addictions. The aim of this study is to design and validate a Cannabis Use Intention Questionnaire (CUIQ) based on TPB. 1,011 teenagers answered a set of tests to assess attitude towards use, subjective norms, self-efficacy towards non-use, and intention to use cannabis. CUIQ had good psychometric properties. Structural Equation Modelling results confirm the predictive model on intention to use cannabis in the Spanish adolescent sample, classified as users and non-users, explaining 40% of variance of intention to consume. CUIQ is aimed at providing a better understanding of the psychological processes that lead to cannabis use and allowing the evaluation of programmes. This can be particularly useful for improving the design and implementation of selective prevention programmes.

Predicting field-scale dispersion under realistic conditions with the polar Markovian velocity process model

NASA Astrophysics Data System (ADS)

Dünser, Simon; Meyer, Daniel W.

2016-06-01

In most groundwater aquifers, dispersion of tracers is dominated by flow-field inhomogeneities resulting from the underlying heterogeneous conductivity or transmissivity field. This effect is referred to as macrodispersion. Since in practice, besides a few point measurements the complete conductivity field is virtually never available, a probabilistic treatment is needed. To quantify the uncertainty in tracer concentrations from a given geostatistical model for the conductivity, Monte Carlo (MC) simulation is typically used. To avoid the excessive computational costs of MC, the polar Markovian velocity process (PMVP) model was recently introduced delivering predictions at about three orders of magnitude smaller computing times. In artificial test cases, the PMVP model has provided good results in comparison with MC. In this study, we further validate the model in a more challenging and realistic setup. The setup considered is derived from the well-known benchmark macrodispersion experiment (MADE), which is highly heterogeneous and non-stationary with a large number of unevenly scattered conductivity measurements. Validations were done against reference MC and good overall agreement was found. Moreover, simulations of a simplified setup with a single measurement were conducted in order to reassess the model's most fundamental assumptions and to provide guidance for model improvements.

Implementation and validation of a wake model for vortex-surface interactions in low speed forward flight

NASA Technical Reports Server (NTRS)

Komerath, Narayanan M.; Schreiber, Olivier A.

1987-01-01

The wake model was implemented using a VAX 750 and a Microvax II workstation. Online graphics capability using a DISSPLA graphics package. The rotor model used by Beddoes was significantly extended to include azimuthal variations due to forward flight and a simplified scheme for locating critical points where vortex elements are placed. A test case was obtained for validation of the predictions of induced velocity. Comparison of the results indicates that the code requires some more features before satisfactory predictions can be made over the whole rotor disk. Specifically, shed vorticity due to the azimuthal variation of blade loading must be incorporated into the model. Interactions between vortices shed from the four blades of the model rotor must be included. The Scully code for calculating the velocity field is being modified in parallel with these efforts to enable comparison with experimental data. To date, some comparisons with flow visualization data obtained at Georgia Tech were performed and show good agreement for the isolated rotor case. Comparison of time-resolved velocity data obtained at Georgia Tech also shows good agreement. Modifications are being implemented to enable generation of time-averaged results for comparison with NASA data.

Development of the Galaxy Chronic Obstructive Pulmonary Disease (COPD) Model Using Data from ECLIPSE: Internal Validation of a Linked-Equations Cohort Model.

PubMed

Briggs, Andrew H; Baker, Timothy; Risebrough, Nancy A; Chambers, Mike; Gonzalez-McQuire, Sebastian; Ismaila, Afisi S; Exuzides, Alex; Colby, Chris; Tabberer, Maggie; Muellerova, Hana; Locantore, Nicholas; Rutten van Mölken, Maureen P M H; Lomas, David A

2017-05-01

The recent joint International Society for Pharmacoeconomics and Outcomes Research / Society for Medical Decision Making Modeling Good Research Practices Task Force emphasized the importance of conceptualizing and validating models. We report a new model of chronic obstructive pulmonary disease (COPD) (part of the Galaxy project) founded on a conceptual model, implemented using a novel linked-equation approach, and internally validated. An expert panel developed a conceptual model including causal relationships between disease attributes, progression, and final outcomes. Risk equations describing these relationships were estimated using data from the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) study, with costs estimated from the TOwards a Revolution in COPD Health (TORCH) study. Implementation as a linked-equation model enabled direct estimation of health service costs and quality-adjusted life years (QALYs) for COPD patients over their lifetimes. Internal validation compared 3 years of predicted cohort experience with ECLIPSE results. At 3 years, the Galaxy COPD model predictions of annual exacerbation rate and annual decline in forced expiratory volume in 1 second fell within the ECLIPSE data confidence limits, although 3-year overall survival was outside the observed confidence limits. Projections of the risk equations over time permitted extrapolation to patient lifetimes. Averaging the predicted cost/QALY outcomes for the different patients within the ECLIPSE cohort gives an estimated lifetime cost of £25,214 (undiscounted)/£20,318 (discounted) and lifetime QALYs of 6.45 (undiscounted/5.24 [discounted]) per ECLIPSE patient. A new form of model for COPD was conceptualized, implemented, and internally validated, based on a series of linked equations using epidemiological data (ECLIPSE) and cost data (TORCH). This Galaxy model predicts COPD outcomes from treatment effects on disease attributes such as lung function, exacerbations, symptoms, or exercise capacity; further external validation is required.

Preoperative Prediction of Node-Negative Disease After Neoadjuvant Chemotherapy in Patients Presenting with Node-Negative or Node-Positive Breast Cancer.

PubMed

Murphy, Brittany L; L Hoskin, Tanya; Heins, Courtney Day N; Habermann, Elizabeth B; Boughey, Judy C

2017-09-01

Axillary node status after neoadjuvant chemotherapy (NAC) influences the axillary surgical staging procedure as well as recommendations regarding reconstruction and radiation. Our aim was to construct a clinical preoperative prediction model to identify the likelihood of patients being node negative after NAC. Using the National Cancer Database (NCDB) from January 2010 to December 2012, we identified cT1-T4c, N0-N3 breast cancer patients treated with NAC. The effects of patient and tumor factors on pathologic node status were assessed by multivariable logistic regression separately for clinically node negative (cN0) and clinically node positive (cN+) disease, and two models were constructed. Model performance was validated in a cohort of NAC patients treated at our institution (January 2013-July 2016), and model discrimination was assessed by estimating the area under the curve (AUC). Of 16,153 NCDB patients, 6659 (41%) were cN0 and 9494 (59%) were cN+. Factors associated with pathologic nodal status and included in the models were patient age, tumor grade, biologic subtype, histology, clinical tumor category, and, in cN+ patients only, clinical nodal category. The validation dataset included 194 cN0 and 180 cN+ patients. The cN0 model demonstrated good discrimination, with an AUC of 0.73 (95% confidence interval [CI] 0.72-0.74) in the NCDB and 0.77 (95% CI 0.68-0.85) in the external validation, while the cN+ patient model AUC was 0.71 (95% CI 0.70-0.72) in the NCDB and 0.74 (95% CI 0.67-0.82) in the external validation. We constructed two models that showed good discrimination for predicting ypN0 status following NAC in cN0 and cN+ patients. These clinically useful models can guide surgical planning after NAC.

Development of a questionnaire to measure heart disease risk knowledge in people with diabetes: the Heart Disease Fact Questionnaire.

PubMed

Wagner, Julie; Lacey, Kimberly; Chyun, Deborah; Abbott, Gina

2005-07-01

This paper describes a paper and pencil questionnaire that measures heart disease risk knowledge in people with diabetes. The Heart Disease Fact Questionnaire (HDFQ) is a 25-item questionnaire that was developed to tap into respondents' knowledge of major risk factors for the development of CHD. Approximately half of these items specifically address diabetes-related CHD risk factors. Based on extensive pilot data, the current study analyzed responses from 524 people with diabetes to assess the psychometric properties. The HDFQ is readable to an average 13-year old and imposes little burden. It shows good content and face validity. It demonstrates adequate internal consistency, with Kuder-Richardson-20 formula = 0.77 and good item-total correlations. Item analysis showed a desirable range in P-values. In discriminant function analyses, HDFQ scores differentiated respondents by knowledge of their own cardiovascular health, use of lipid lowering medications, health insurance status, and educational attainment, thus indicating good criterion related validity. This measure of heart disease risk knowledge is brief, understandable to respondents, and easy to administer and score. Its potential for use in research and practice is discussed. Future research should establish norms as well as investigate its test-retest reliability and predictive validity.

A proteinuria cut-off level of 0.7 g/day after 12 months of treatment best predicts long-term renal outcome in lupus nephritis: data from the MAINTAIN Nephritis Trial

PubMed Central

Tamirou, Farah; Lauwerys, Bernard R; Dall'Era, Maria; Mackay, Meggan; Rovin, Brad; Cervera, Ricard; Houssiau, Frédéric A

2015-01-01

Background Although an early decrease in proteinuria has been correlated with good long-term renal outcome in lupus nephritis (LN), studies aimed at defining a cut-off proteinuria value are missing, except a recent analysis performed on patients randomised in the Euro-Lupus Nephritis Trial, demonstrating that a target value of 0.8 g/day at month 12 optimised sensitivity and specificity for the prediction of good renal outcome. The objective of the current work is to validate this target in another LN study, namely the MAINTAIN Nephritis Trial (MNT). Methods Long-term (at least 7 years) renal function data were available for 90 patients randomised in the MNT. Receiver operating characteristic curves were built to test the performance of proteinuria measured within the 1st year as short-term predictor of long-term renal outcome. We calculated the positive and negative predictive values (PPV, NPV). Results After 12 months of treatment, achievement of a proteinuria <0.7 g/day best predicted good renal outcome, with a sensitivity and a specificity of 71% and 75%, respectively. The PPV was high (94%) but the NPV low (29%). Addition of the requirement of urine red blood cells ≤5/hpf as response criteria at month 12 reduced sensitivity from 71% to 41%. Conclusions In this cohort of mainly Caucasian patients suffering from a first episode of LN in most cases, achievement of a proteinuria <0.7 g/day at month 12 best predicts good outcome at 7 years and inclusion of haematuria in the set of criteria at month 12 undermines the sensitivity of early proteinuria decrease for the prediction of good outcome. The robustness of these conclusions stems from the very similar results obtained in two distinct LN cohorts. Trial registration number: NCT00204022. PMID:26629352

Effectiveness of Cooperative Learning Instructional Tools With Predict-Observe-Explain Strategy on the Topic of Cuboid and Cube Volume

NASA Astrophysics Data System (ADS)

Nurhuda; Lukito, A.; Masriyah

2018-01-01

This study aims to develop instructional tools and implement it to see the effectiveness. The method used in this research referred to Designing Effective Instruction. Experimental research with two-group pretest-posttest design method was conducted. The instructional tools have been developed is cooperative learning model with predict-observe-explain strategy on the topic of cuboid and cube volume which consist of lesson plans, POE tasks, and Tests. Instructional tools were of good quality by criteria of validity, practicality, and effectiveness. These instructional tools was very effective for teaching the volume of cuboid and cube. Cooperative instructional tool with predict-observe-explain (POE) strategy was good of quality because the teacher was easy to implement the steps of learning, students easy to understand the material and students’ learning outcomes completed classically. Learning by using this instructional tool was effective because learning activities were appropriate and students were very active. Students’ learning outcomes were completed classically and better than conventional learning. This study produced a good instructional tool and effectively used in learning. Therefore, these instructional tools can be used as an alternative to teach volume of cuboid and cube topics.

Validation of the LOD score compared with APACHE II score in prediction of the hospital outcome in critically ill patients.

PubMed

Khwannimit, Bodin

2008-01-01

The Logistic Organ Dysfunction score (LOD) is an organ dysfunction score that can predict hospital mortality. The aim of this study was to validate the performance of the LOD score compared with the Acute Physiology and Chronic Health Evaluation II (APACHE II) score in a mixed intensive care unit (ICU) at a tertiary referral university hospital in Thailand. The data were collected prospectively on consecutive ICU admissions over a 24 month period from July1, 2004 until June 30, 2006. Discrimination was evaluated by the area under the receiver operating characteristic curve (AUROC). The calibration was assessed by the Hosmer-Lemeshow goodness-of-fit H statistic. The overall fit of the model was evaluated by the Brier's score. Overall, 1,429 patients were enrolled during the study period. The mortality in the ICU was 20.9% and in the hospital was 27.9%. The median ICU and hospital lengths of stay were 3 and 18 days, respectively, for all patients. Both models showed excellent discrimination. The AUROC for the LOD and APACHE II were 0.860 [95% confidence interval (CI) = 0.838-0.882] and 0.898 (95% Cl = 0.879-0.917), respectively. The LOD score had perfect calibration with the Hosmer-Lemeshow goodness-of-fit H chi-2 = 10 (p = 0.44). However, the APACHE II had poor calibration with the Hosmer-Lemeshow goodness-of-fit H chi-2 = 75.69 (p < 0.001). Brier's score showed the overall fit for both models were 0.123 (95%Cl = 0.107-0.141) and 0.114 (0.098-0.132) for the LOD and APACHE II, respectively. Thus, the LOD score was found to be accurate for predicting hospital mortality for general critically ill patients in Thailand.

Validation of Ten Noninvasive Diagnostic Models for Prediction of Liver Fibrosis in Patients with Chronic Hepatitis B

PubMed Central

Cheng, Jieyao; Hou, Jinlin; Ding, Huiguo; Chen, Guofeng; Xie, Qing; Wang, Yuming; Zeng, Minde; Ou, Xiaojuan; Ma, Hong; Jia, Jidong

2015-01-01

Background and Aims Noninvasive models have been developed for fibrosis assessment in patients with chronic hepatitis B. However, the sensitivity, specificity and diagnostic accuracy in evaluating liver fibrosis of these methods have not been validated and compared in the same group of patients. The aim of this study was to verify the diagnostic performance and reproducibility of ten reported noninvasive models in a large cohort of Asian CHB patients. Methods The diagnostic performance of ten noninvasive models (HALF index, FibroScan, S index, Zeng model, Youyi model, Hui model, APAG, APRI, FIB-4 and FibroTest) was assessed against the liver histology by ROC curve analysis in CHB patients. The reproducibility of the ten models were evaluated by recalculating the diagnostic values at the given cut-off values defined by the original studies. Results Six models (HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest) had AUROCs higher than 0.70 in predicting any fibrosis stage and 2 of them had best diagnostic performance with AUROCs to predict F≥2, F≥3 and F4 being 0.83, 0.89 and 0.89 for HALF index, 0.82, 0.87 and 0.87 for FibroScan, respectively. Four models (HALF index, FibroScan, Zeng model and Youyi model) showed good diagnostic values at given cut-offs. Conclusions HALF index, FibroScan, Zeng model, Youyi model, S index and FibroTest show a good diagnostic performance and all of them, except S index and FibroTest, have good reproducibility for evaluating liver fibrosis in CHB patients. Registration Number ChiCTR-DCS-07000039. PMID:26709706

Cooperativeness and competitiveness as two distinct constructs: validating the Cooperative and Competitive Personality Scale in a social dilemma context.

PubMed

Lu, Su; Au, Wing-Tung; Jiang, Feng; Xie, Xiaofei; Yam, Paton

2013-01-01

The present research validated the construct and criterion validities of the Cooperative and Competitive Personality Scale (CCPS) in a social dilemma context. The results from three studies supported the notion that cooperativeness and competitiveness are two independent dimensions, challenging the traditional view that they are two ends of a single continuum. First, confirmatory factor analyses revealed that a two-factor structure fit the data significantly better than a one-factor structure. Moreover, cooperativeness and competitiveness were either not significantly correlated (Studies 1 and 3) or only moderately positively correlated (Study 2). Second, cooperativeness and competitiveness were differentially associated with Schwartz's Personal Values. These results further supported the idea that cooperativeness and competitiveness are two distinct constructs. Specifically, the individuals who were highly cooperative emphasized self-transcendent values (i.e., universalism and benevolence) more, whereas the individuals who were highly competitive emphasized self-enhancement values (i.e., power and achievement) more. Finally, the CCPS, which adheres to the trait perspective of personality, was found to be a useful supplement to more prevalent social motive measures (i.e., social value orientation) in predicting cooperative behaviors. Specifically, in Study 2, when social value orientation was controlled for, the CCPS significantly predicted cooperative behaviors in a public goods dilemma (individuals who score higher on cooperativeness scale contributed more to the public goods). In Study 3, when social value orientation was controlled for, the CCPS significantly predicted cooperative behaviors in commons dilemmas (individuals who score higher on cooperativeness scale requested fewer resources from the common resource pool). The practical implications of the CCPS in conflict resolution, as well as in recruitment and selection settings, are discussed.

A clinical score to obviate the need for cardiac stress testing in patients with acute chest pain and negative troponins.

PubMed

Bouzas-Mosquera, Alberto; Peteiro, Jesús; Broullón, Francisco J; Álvarez-García, Nemesio; Maneiro-Melón, Nicolás; Pardo-Martinez, Patricia; Sagastagoitia-Fornie, Marta; Martínez, Dolores; Yáñez, Juan C; Vázquez-Rodríguez, José Manuel

2016-08-01

Although cardiac stress testing may help establish the safety of early discharge in patients with suspected acute coronary syndromes and negative troponins, more cost-effective strategies are necessary. We aimed to develop a clinical prediction rule to safely obviate the need for cardiac stress testing in this setting. A decision rule was derived in a prospective cohort of 3001 patients with acute chest pain and negative troponins, and validated in a set of 1473 subjects. The primary end point was a composite of positive cardiac stress testing (in the absence of a subsequent negative coronary angiogram), positive coronary angiography, or any major coronary events within 3 months. A score chart was built based on 7 variables: male sex (+2), age (+1 per decade from the fifth decade), diabetes mellitus (+2), hypercholesterolemia (+1), prior coronary revascularization (+2), type of chest pain (typical angina, +5; non-specific chest pain, -3), and non-diagnostic repolarization abnormalities (+2). In the validation set, the model showed good discrimination (c statistic = 0.84; 95% confidence interval, 0.82-0.87) and calibration (Hosmer-Lemeshow goodness-of-fit test, P= .34). If stress tests were avoided in patients in the validation sample with a sum score of 0 or lower, the number of referrals would be reduced by 23.4%, yielding a negative predictive value of 98.8% (95% confidence interval, 97.0%-99.7%). This novel prediction rule based on a combination of readily available clinical characteristics may be a valuable tool to decide whether stress testing can be reliably avoided in patients with acute chest pain and negative troponins. Copyright © 2016 Elsevier Inc. All rights reserved.

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

PubMed

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

2018-01-01

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

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

PubMed

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

2015-03-01

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

Selecting the optimum number of partial least squares components for the calibration of attenuated total reflectance-mid-infrared spectra of undesigned kerosene samples.

PubMed

Gómez-Carracedo, M P; Andrade, J M; Rutledge, D N; Faber, N M

2007-03-07

Selecting the correct dimensionality is critical for obtaining partial least squares (PLS) regression models with good predictive ability. Although calibration and validation sets are best established using experimental designs, industrial laboratories cannot afford such an approach. Typically, samples are collected in an (formally) undesigned way, spread over time and their measurements are included in routine measurement processes. This makes it hard to evaluate PLS model dimensionality. In this paper, classical criteria (leave-one-out cross-validation and adjusted Wold's criterion) are compared to recently proposed alternatives (smoothed PLS-PoLiSh and a randomization test) to seek out the optimum dimensionality of PLS models. Kerosene (jet fuel) samples were measured by attenuated total reflectance-mid-IR spectrometry and their spectra where used to predict eight important properties determined using reference methods that are time-consuming and prone to analytical errors. The alternative methods were shown to give reliable dimensionality predictions when compared to external validation. By contrast, the simpler methods seemed to be largely affected by the largest changes in the modeling capabilities of the first components.

Implementation and Validation of the Viscoelastic Continuum Damage Theory for Asphalt Mixture and Pavement Analysis in Brazil

NASA Astrophysics Data System (ADS)

Nascimento, Luis Alberto Herrmann do

This dissertation presents the implementation and validation of the viscoelastic continuum damage (VECD) model for asphalt mixture and pavement analysis in Brazil. It proposes a simulated damage-to-fatigue cracked area transfer function for the layered viscoelastic continuum damage (LVECD) program framework and defines the model framework's fatigue cracking prediction error for asphalt pavement reliability-based design solutions in Brazil. The research is divided into three main steps: (i) implementation of the simplified viscoelastic continuum damage (S-VECD) model in Brazil (Petrobras) for asphalt mixture characterization, (ii) validation of the LVECD model approach for pavement analysis based on field performance observations, and defining a local simulated damage-to-cracked area transfer function for the Fundao Project's pavement test sections in Rio de Janeiro, RJ, and (iii) validation of the Fundao project local transfer function to be used throughout Brazil for asphalt pavement fatigue cracking predictions, based on field performance observations of the National MEPDG Project's pavement test sections, thereby validating the proposed framework's prediction capability. For the first step, the S-VECD test protocol, which uses controlled-on-specimen strain mode-of-loading, was successfully implemented at the Petrobras and used to characterize Brazilian asphalt mixtures that are composed of a wide range of asphalt binders. This research verified that the S-VECD model coupled with the GR failure criterion is accurate for fatigue life predictions of Brazilian asphalt mixtures, even when very different asphalt binders are used. Also, the applicability of the load amplitude sweep (LAS) test for the fatigue characterization of the asphalt binders was checked, and the effects of different asphalt binders on the fatigue damage properties of the asphalt mixtures was investigated. The LAS test results, modeled according to VECD theory, presented a strong correlation with the asphalt mixtures' fatigue performance. In the second step, the S-VECD test protocol was used to characterize the asphalt mixtures used in the 27 selected Fundao project test sections and subjected to real traffic loading. Thus, the asphalt mixture properties, pavement structure data, traffic loading, and climate were input into the LVECD program for pavement fatigue cracking performance simulations. The simulation results showed good agreement with the field-observed distresses. Then, a damage shift approach, based on the initial simulated damage growth rate, was introduced in order to obtain a unique relationship between the LVECD-simulated shifted damage and the pavement-observed fatigue cracked areas. This correlation was fitted to a power form function and defined as the averaged reduced damage-to-cracked area transfer function. The last step consisted of using the averaged reduced damage-to-cracked area transfer function that was developed in the Fundao project to predict pavement fatigue cracking in 17 National MEPDG project test sections. The procedures for the material characterization and pavement data gathering adopted in this step are similar to those used for the Fundao project simulations. This research verified that the transfer function defined for the Fundao project sections can be used for the fatigue performance predictions of a wide range of pavements all over Brazil, as the predicted and observed cracked areas for the National MEPDG pavements presented good agreement, following the same trends found for the Fundao project pavement sites. Based on the prediction errors determined for all 44 pavement test sections (Fundao and National MEPDG test sections), the proposed framework's prediction capability was determined so that reliability-based solutions can be applied for flexible pavement design. It was concluded that the proposed LVECD program framework has very good fatigue cracking prediction capability.

Rule extraction from minimal neural networks for credit card screening.

PubMed

Setiono, Rudy; Baesens, Bart; Mues, Christophe

2011-08-01

While feedforward neural networks have been widely accepted as effective tools for solving classification problems, the issue of finding the best network architecture remains unresolved, particularly so in real-world problem settings. We address this issue in the context of credit card screening, where it is important to not only find a neural network with good predictive performance but also one that facilitates a clear explanation of how it produces its predictions. We show that minimal neural networks with as few as one hidden unit provide good predictive accuracy, while having the added advantage of making it easier to generate concise and comprehensible classification rules for the user. To further reduce model size, a novel approach is suggested in which network connections from the input units to this hidden unit are removed by a very straightaway pruning procedure. In terms of predictive accuracy, both the minimized neural networks and the rule sets generated from them are shown to compare favorably with other neural network based classifiers. The rules generated from the minimized neural networks are concise and thus easier to validate in a real-life setting.

Development of rotorcraft interior noise control concepts. Phase 2: Full scale testing, revision 1

NASA Technical Reports Server (NTRS)

Yoerkie, C. A.; Gintoli, P. J.; Moore, J. A.

1986-01-01

The phase 2 effort consisted of a series of ground and flight test measurements to obtain data for validation of the Statistical Energy Analysis (SEA) model. Included in the gound tests were various transfer function measurements between vibratory and acoustic subsystems, vibration and acoustic decay rate measurements, and coherent source measurements. The bulk of these, the vibration transfer functions, were used for SEA model validation, while the others provided information for characterization of damping and reverberation time of the subsystems. The flight test program included measurements of cabin and cockpit sound pressure level, frame and panel vibration level, and vibration levels at the main transmission attachment locations. Comparisons between measured and predicted subsystem excitation levels from both ground and flight testing were evaluated. The ground test data show good correlation with predictions of vibration levels throughout the cabin overhead for all excitations. The flight test results also indicate excellent correlation of inflight sound pressure measurements to sound pressure levels predicted by the SEA model, where the average aircraft speech interference level is predicted within 0.2 dB.

Ability of preoperative 3.0-Tesla magnetic resonance imaging to predict the absence of side-specific extracapsular extension of prostate cancer.

PubMed

Hara, Tomohiko; Nakanishi, Hiroyuki; Nakagawa, Tohru; Komiyama, Motokiyo; Kawahara, Takashi; Manabe, Tomoko; Miyake, Mototaka; Arai, Eri; Kanai, Yae; Fujimoto, Hiroyuki

2013-10-01

Recent studies have shown an improvement in prostate cancer diagnosis with the use of 3.0-Tesla magnetic resonance imaging. We retrospectively assessed the ability of this imaging technique to predict side-specific extracapsular extension of prostate cancer. From October 2007 to August 2011, prostatectomy was carried out in 396 patients after preoperative 3.0-Tesla magnetic resonance imaging. Among these, 132 (primary sample) and 134 patients (validation sample) underwent 12-core prostate biopsy at the National Cancer Center Hospital of Tokyo, Japan, and at other institutions, respectively. In the primary dataset, univariate and multivariate analyses were carried out to predict side-specific extracapsular extension using variables determined preoperatively, including 3.0-Tesla magnetic resonance imaging findings (T2-weighted and diffusion-weighted imaging). A prediction model was then constructed and applied to the validation study sample. Multivariate analysis identified four significant independent predictors (P < 0.05), including a biopsy Gleason score of ≥8, positive 3.0-Tesla diffusion-weighted magnetic resonance imaging findings, ≥2 positive biopsy cores on each side and a maximum percentage of positive cores ≥31% on each side. The negative predictive value was 93.9% in the combination model with these four predictors, meanwhile the positive predictive value was 33.8%. Good reproducibility of these four significant predictors and the combination model was observed in the validation study sample. The side-specific extracapsular extension prediction by the biopsy Gleason score and factors associated with tumor location, including a positive 3.0-Tesla diffusion-weighted magnetic resonance imaging finding, have a high negative predictive value, but a low positive predictive value. © 2013 The Japanese Urological Association.

[Prediction of soil adsorption coefficients of organic compounds in a wide range of soil types by soil column liquid chromatography].

PubMed

Guo, Rongbo; Chen, Jiping; Zhang, Qing; Wu, Wenzhong; Liang, Xinmiao

2004-01-01

Using the methanol-water mixtures as mobile phases of soil column liquid chromatography (SCLC), prediction of soil adsorption coefficients (K(d)) by SCLC was validated in a wide range of soil types. The correlations between the retention factors measured by SCLC and soil adsorption coefficients measured by batch experiments were studied for five soils with different properties, i.e., Eurosoil 1#, 2#, 3#, 4# and 5#. The results show that good correlations existed between the retention factors and soil adsorption coefficients for Eurosoil 1#, 2#, 3# and 4#. For Eurosoil 5# which has a pH value of near 3, the correlation between retention factors and soil adsorption coefficients was unsatisfactory using methanol-water as mobile phase of SCLC. However, a good correlation was obtained using a methanol-buffer mixture with pH 3 as the mobile phase. This study proved that the SCLC is suitable for the prediction of soil adsorption coefficients.

Derivation and validation of simple anthropometric equations to predict adipose tissue mass and total fat mass with MRI as the reference method

PubMed Central

Al-Gindan, Yasmin Y.; Hankey, Catherine R.; Govan, Lindsay; Gallagher, Dympna; Heymsfield, Steven B.; Lean, Michael E. J.

2017-01-01

The reference organ-level body composition measurement method is MRI. Practical estimations of total adipose tissue mass (TATM), total adipose tissue fat mass (TATFM) and total body fat are valuable for epidemiology, but validated prediction equations based on MRI are not currently available. We aimed to derive and validate new anthropometric equations to estimate MRI-measured TATM/TATFM/total body fat and compare them with existing prediction equations using older methods. The derivation sample included 416 participants (222 women), aged between 18 and 88 years with BMI between 15·9 and 40·8 (kg/m2). The validation sample included 204 participants (110 women), aged between 18 and 86 years with BMI between 15·7 and 36·4 (kg/m2). Both samples included mixed ethnic/racial groups. All the participants underwent whole-body MRI to quantify TATM (dependent variable) and anthropometry (independent variables). Prediction equations developed using stepwise multiple regression were further investigated for agreement and bias before validation in separate data sets. Simplest equations with optimal R2 and Bland–Altman plots demonstrated good agreement without bias in the validation analyses: men: TATM (kg) = 0·198 weight (kg) + 0·478 waist (cm) − 0·147 height (cm) − 12·8 (validation: R2 0·79, CV = 20 %, standard error of the estimate (SEE)=3·8 kg) and women: TATM (kg)=0·789 weight (kg) + 0·0786 age (years) − 0·342 height (cm) + 24·5 (validation: R2 0·84, CV = 13 %, SEE = 3·0 kg). Published anthropometric prediction equations, based on MRI and computed tomographic scans, correlated strongly with MRI-measured TATM: (R2 0·70 – 0·82). Estimated TATFM correlated well with published prediction equations for total body fat based on underwater weighing (R2 0·70–0·80), with mean bias of 2·5–4·9 kg, correctable with log-transformation in most equations. In conclusion, new equations, using simple anthropometric measurements, estimated MRI-measured TATM with correlations and agreements suitable for use in groups and populations across a wide range of fatness. PMID:26435103

A novel method to estimate the affinity of HLA-A∗0201 restricted CTL epitope

NASA Astrophysics Data System (ADS)

Xu, Yun-sheng; Lin, Yong; Zhu, Bo; Lin, Zhi-hua

2009-02-01

A set of 70 peptides with affinity for the class I MHC HLA-A∗0201 molecule was subjected to quantitative structure-affinity relationship studies based on the SCORE function with good results ( r2 = 0.6982, RMS = 0.280). Then the 'leave-one-out' cross-validation (LOO-CV) and an outer test set including 18 outer samples were used to validate the QSAR model. The results of the LOO-CV were q2 = 0.6188, RMS = 0.315, and the results of outer test set were r2 = 0.5633, RMS = 0.2292. All these show that the QSAR model has good predictability. Statistical analysis showed that the hydrophobic and hydrogen bond interaction played a significant role in peptide-MHC molecule binding. The study also provided useful information for structure modification of CTL epitope, and laid theoretical base for molecular design of therapeutic vaccine.

Parasitic Parameters Extraction for InP DHBT Based on EM Method and Validation up to H-Band

NASA Astrophysics Data System (ADS)

Li, Oupeng; Zhang, Yong; Wang, Lei; Xu, Ruimin; Cheng, Wei; Wang, Yuan; Lu, Haiyan

2017-05-01

This paper presents a small-signal model for InGaAs/InP double heterojunction bipolar transistor (DHBT). Parasitic parameters of access via and electrode finger are extracted by 3-D electromagnetic (EM) simulation. By analyzing the equivalent circuit of seven special structures and using the EM simulation results, the parasitic parameters are extracted systematically. Compared with multi-port s-parameter EM model, the equivalent circuit model has clear physical intension and avoids the complex internal ports setting. The model is validated on a 0.5 × 7 μm2 InP DHBT up to 325 GHz. The model provides a good fitting result between measured and simulated multi-bias s-parameters in full band. At last, an H-band amplifier is designed and fabricated for further verification. The measured amplifier performance is highly agreed with the model prediction, which indicates the model has good accuracy in submillimeterwave band.

Estimation of the intelligence quotient using Wechsler Intelligence Scales in children and adolescents with Asperger syndrome.

PubMed

Merchán-Naranjo, Jessica; Mayoral, María; Rapado-Castro, Marta; Llorente, Cloe; Boada, Leticia; Arango, Celso; Parellada, Mara

2012-01-01

Asperger syndrome (AS) patients show heterogeneous intelligence profiles and the validity of short forms for estimating intelligence has rarely been studied in this population. We analyzed the validity of Wechsler Intelligence Scale (WIS) short forms for estimating full-scale intelligence quotient (FSIQ) and assessing intelligence profiles in 29 AS patients. Only the Information and Block Design dyad meets the study criteria. No statistically significant differences were found between dyad scores and FSIQ scores (t(28) = 1.757; p = 0.09). The dyad has a high correlation with FSIQ, good percentage of variance explained (R(2) = 0.591; p < 0.001), and high consistency with the FSIQ classification (χ(2)(36) = 45.202; p = 0.14). Short forms with good predictive accuracy may not be accurate in clinical groups with atypical cognitive profiles such as AS patients.

Spanish validation of the Person-centered Care Assessment Tool (P-CAT).

PubMed

Martínez, Teresa; Suárez-Álvarez, Javier; Yanguas, Javier; Muñiz, José

2016-01-01

Person-centered Care (PCC) is an innovative approach which seeks to improve the quality of care services given to the care-dependent elderly. At present there are no Spanish language instruments for the evaluation of PCC delivered by elderly care services. The aim of this work is the adaptation and validation of the Person-centered Care Assessment Tool (P-CAT) for a Spanish population. The P-CAT was translated and adapted into Spanish, then given to a sample of 1339 front-line care professionals from 56 residential elderly care homes. The reliability and validity of the P-CAT were analyzed, within the frameworks of Classical Test Theory and Item Response Theory models. The Spanish P-CAT demonstrated good reliability, with an alpha coefficient of .88 and a test-retest reliability coefficient of .79. The P-CAT information function indicates that the test measures with good precision for the majority of levels of the measured variables (θ values between -2 and +1). The factorial structure of the test is essentially one-dimensional and the item discrimination indices are high, with values between .26 and .61. In terms of predictive validity, the correlations which stand out are between the P-CAT and organizational climate (r = .689), and the burnout factors; personal accomplishment (r = .382), and emotional exhaustion (r = - .510). The Spanish version of the P-CAT demonstrates good psychometric properties for its use in the evaluation of elderly care homes both professionally and in research.

Classification and regression tree (CART) model to predict pulmonary tuberculosis in hospitalized patients.

PubMed

Aguiar, Fabio S; Almeida, Luciana L; Ruffino-Netto, Antonio; Kritski, Afranio Lineu; Mello, Fernanda Cq; Werneck, Guilherme L

2012-08-07

Tuberculosis (TB) remains a public health issue worldwide. The lack of specific clinical symptoms to diagnose TB makes the correct decision to admit patients to respiratory isolation a difficult task for the clinician. Isolation of patients without the disease is common and increases health costs. Decision models for the diagnosis of TB in patients attending hospitals can increase the quality of care and decrease costs, without the risk of hospital transmission. We present a predictive model for predicting pulmonary TB in hospitalized patients in a high prevalence area in order to contribute to a more rational use of isolation rooms without increasing the risk of transmission. Cross sectional study of patients admitted to CFFH from March 2003 to December 2004. A classification and regression tree (CART) model was generated and validated. The area under the ROC curve (AUC), sensitivity, specificity, positive and negative predictive values were used to evaluate the performance of model. Validation of the model was performed with a different sample of patients admitted to the same hospital from January to December 2005. We studied 290 patients admitted with clinical suspicion of TB. Diagnosis was confirmed in 26.5% of them. Pulmonary TB was present in 83.7% of the patients with TB (62.3% with positive sputum smear) and HIV/AIDS was present in 56.9% of patients. The validated CART model showed sensitivity, specificity, positive predictive value and negative predictive value of 60.00%, 76.16%, 33.33%, and 90.55%, respectively. The AUC was 79.70%. The CART model developed for these hospitalized patients with clinical suspicion of TB had fair to good predictive performance for pulmonary TB. The most important variable for prediction of TB diagnosis was chest radiograph results. Prospective validation is still necessary, but our model offer an alternative for decision making in whether to isolate patients with clinical suspicion of TB in tertiary health facilities in countries with limited resources.

Development and validation of the coping with terror scale.

PubMed

Stein, Nathan R; Schorr, Yonit; Litz, Brett T; King, Lynda A; King, Daniel W; Solomon, Zahava; Horesh, Danny

2013-10-01

Terrorism creates lingering anxiety about future attacks. In prior terror research, the conceptualization and measurement of coping behaviors were constrained by the use of existing coping scales that index reactions to daily hassles and demands. The authors created and validated the Coping with Terror Scale to fill the measurement gap. The authors emphasized content validity, leveraging the knowledge of terror experts and groups of Israelis. A multistep approach involved construct definition and item generation, trimming and refining the measure, exploring the factor structure underlying item responses, and garnering evidence for reliability and validity. The final scale comprised six factors that were generally consistent with the authors' original construct specifications. Scores on items linked to these factors demonstrate good reliability and validity. Future studies using the Coping with Terror Scale with other populations facing terrorist threats are needed to test its ability to predict resilience, functional impairment, and psychological distress.

Development and Validation of the Food Liking Questionnaire in a French-Canadian Population

PubMed Central

Carbonneau, Elise; Bradette-Laplante, Maude; Lamarche, Benoît; Provencher, Véronique; Bégin, Catherine; Robitaille, Julie; Desroches, Sophie; Corneau, Louise; Lemieux, Simone

2017-01-01

The purpose of this study was to develop and validate a questionnaire assessing food liking in a French-Canadian population. A questionnaire was developed, in which participants were asked to rate their degree of liking of 50 food items. An expert panel evaluated the content validity. For the validation study, 150 men and women completed the questionnaire twice. An Exploratory Factor Analysis (EFA) was performed to assess the number of subscales of the questionnaire. Internal consistency and test-retest reliability of the subscales were evaluated. Concurrent validity was assessed through correlations between liking scores and self-reported frequencies of consumption. Comments from the experts led to changes in the list of foods included in the questionnaire. The EFA revealed a two-factor structure for the questionnaire (i.e., savory and sweet foods) and led to the removal of nine items, resulting in a 32-item questionnaire. The two subscales revealed good internal consistency (Cronbach alphas: 0.85 and 0.89) and test-retest reliability (p = 0.84 and 0.86). The questionnaire demonstrated adequate concurrent validity, with moderate correlations between food liking and self-reported frequency of consumption (r = 0.19–0.39, ps < 0.05). This new Food Liking Questionnaire assessing liking of a variety of savory and sweet foods demonstrated good psychometric properties in every validation step. This questionnaire will be useful to explore the role of food liking and its interactions with other factors in predicting eating behaviors and energy intake. PMID:29292754

Development and Validation of the Food Liking Questionnaire in a French-Canadian Population.

PubMed

Carbonneau, Elise; Bradette-Laplante, Maude; Lamarche, Benoît; Provencher, Véronique; Bégin, Catherine; Robitaille, Julie; Desroches, Sophie; Vohl, Marie-Claude; Corneau, Louise; Lemieux, Simone

2017-12-08

The purpose of this study was to develop and validate a questionnaire assessing food liking in a French-Canadian population. A questionnaire was developed, in which participants were asked to rate their degree of liking of 50 food items. An expert panel evaluated the content validity. For the validation study, 150 men and women completed the questionnaire twice. An Exploratory Factor Analysis (EFA) was performed to assess the number of subscales of the questionnaire. Internal consistency and test-retest reliability of the subscales were evaluated. Concurrent validity was assessed through correlations between liking scores and self-reported frequencies of consumption. Comments from the experts led to changes in the list of foods included in the questionnaire. The EFA revealed a two-factor structure for the questionnaire (i.e., savory and sweet foods) and led to the removal of nine items, resulting in a 32-item questionnaire. The two subscales revealed good internal consistency (Cronbach alphas: 0.85 and 0.89) and test-retest reliability ( p = 0.84 and 0.86). The questionnaire demonstrated adequate concurrent validity, with moderate correlations between food liking and self-reported frequency of consumption ( r = 0.19-0.39, p s < 0.05). This new Food Liking Questionnaire assessing liking of a variety of savory and sweet foods demonstrated good psychometric properties in every validation step. This questionnaire will be useful to explore the role of food liking and its interactions with other factors in predicting eating behaviors and energy intake.

Decision curve analysis and external validation of the postoperative Karakiewicz nomogram for renal cell carcinoma based on a large single-center study cohort.

PubMed

Zastrow, Stefan; Brookman-May, Sabine; Cong, Thi Anh Phuong; Jurk, Stanislaw; von Bar, Immanuel; Novotny, Vladimir; Wirth, Manfred

2015-03-01

To predict outcome of patients with renal cell carcinoma (RCC) who undergo surgical therapy, risk models and nomograms are valuable tools. External validation on independent datasets is crucial for evaluating accuracy and generalizability of these models. The objective of the present study was to externally validate the postoperative nomogram developed by Karakiewicz et al. for prediction of cancer-specific survival. A total of 1,480 consecutive patients with a median follow-up of 82 months (IQR 46-128) were included into this analysis with 268 RCC-specific deaths. Nomogram-estimated survival probabilities were compared with survival probabilities of the actual cohort, and concordance indices were calculated. Calibration plots and decision curve analyses were used for evaluating calibration and clinical net benefit of the nomogram. Concordance between predictions of the nomogram and survival rates of the cohort was 0.911 after 12, 0.909 after 24 months and 0.896 after 60 months. Comparison of predicted probabilities and actual survival estimates with calibration plots showed an overestimation of tumor-specific survival based on nomogram predictions of high-risk patients, although calibration plots showed a reasonable calibration for probability ranges of interest. Decision curve analysis showed a positive net benefit of nomogram predictions for our patient cohort. The postoperative Karakiewicz nomogram provides a good concordance in this external cohort and is reasonably calibrated. It may overestimate tumor-specific survival in high-risk patients, which should be kept in mind when counseling patients. A positive net benefit of nomogram predictions was proven.

Predicting the risk for hospital-onset Clostridium difficile infection (HO-CDI) at the time of inpatient admission: HO-CDI risk score.

PubMed

Tabak, Ying P; Johannes, Richard S; Sun, Xiaowu; Nunez, Carlos M; McDonald, L Clifford

2015-06-01

To predict the likelihood of hospital-onset Clostridium difficile infection (HO-CDI) based on patient clinical presentations at admission Retrospective data analysis Six US acute care hospitals Adult inpatients We used clinical data collected at the time of admission in electronic health record (EHR) systems to develop and validate a HO-CDI predictive model. The outcome measure was HO-CDI cases identified by a nonduplicate positive C. difficile toxin assay result with stool specimens collected >48 hours after inpatient admission. We fit a logistic regression model to predict the risk of HO-CDI. We validated the model using 1,000 bootstrap simulations. Among 78,080 adult admissions, 323 HO-CDI cases were identified (ie, a rate of 4.1 per 1,000 admissions). The logistic regression model yielded 14 independent predictors, including hospital community onset CDI pressure, patient age ≥65, previous healthcare exposures, CDI in previous admission, admission to the intensive care unit, albumin ≤3 g/dL, creatinine >2.0 mg/dL, bands >32%, platelets ≤150 or >420 109/L, and white blood cell count >11,000 mm3. The model had a c-statistic of 0.78 (95% confidence interval [CI], 0.76-0.81) with good calibration. Among 79% of patients with risk scores of 0-7, 19 HO-CDIs occurred per 10,000 admissions; for patients with risk scores >20, 623 HO-CDIs occurred per 10,000 admissions (P<.0001). Using clinical parameters available at the time of admission, this HO-CDI model demonstrated good predictive ability, and it may have utility as an early risk identification tool for HO-CDI preventive interventions and outcome comparisons.

A Risk Prediction Model for Sporadic CRC Based on Routine Lab Results.

PubMed

Boursi, Ben; Mamtani, Ronac; Hwang, Wei-Ting; Haynes, Kevin; Yang, Yu-Xiao

2016-07-01

Current risk scores for colorectal cancer (CRC) are based on demographic and behavioral factors and have limited predictive values. To develop a novel risk prediction model for sporadic CRC using clinical and laboratory data in electronic medical records. We conducted a nested case-control study in a UK primary care database. Cases included those with a diagnostic code of CRC, aged 50-85. Each case was matched with four controls using incidence density sampling. CRC predictors were examined using univariate conditional logistic regression. Variables with p value <0.25 in the univariate analysis were further evaluated in multivariate models using backward elimination. Discrimination was assessed using receiver operating curve. Calibration was evaluated using the McFadden's R2. Net reclassification index (NRI) associated with incorporation of laboratory results was calculated. Results were internally validated. A model similar to existing CRC prediction models which included age, sex, height, obesity, ever smoking, alcohol dependence, and previous screening colonoscopy had an AUC of 0.58 (0.57-0.59) with poor goodness of fit. A laboratory-based model including hematocrit, MCV, lymphocytes, and neutrophil-lymphocyte ratio (NLR) had an AUC of 0.76 (0.76-0.77) and a McFadden's R2 of 0.21 with a NRI of 47.6 %. A combined model including sex, hemoglobin, MCV, white blood cells, platelets, NLR, and oral hypoglycemic use had an AUC of 0.80 (0.79-0.81) with a McFadden's R2 of 0.27 and a NRI of 60.7 %. Similar results were shown in an internal validation set. A laboratory-based risk model had good predictive power for sporadic CRC risk.

QSAR Analysis of 2-Amino or 2-Methyl-1-Substituted Benzimidazoles Against Pseudomonas aeruginosa

PubMed Central

Podunavac-Kuzmanović, Sanja O.; Cvetković, Dragoljub D.; Barna, Dijana J.

2009-01-01

A set of benzimidazole derivatives were tested for their inhibitory activities against the Gram-negative bacterium Pseudomonas aeruginosa and minimum inhibitory concentrations were determined for all the compounds. Quantitative structure activity relationship (QSAR) analysis was applied to fourteen of the abovementioned derivatives using a combination of various physicochemical, steric, electronic, and structural molecular descriptors. A multiple linear regression (MLR) procedure was used to model the relationships between molecular descriptors and the antibacterial activity of the benzimidazole derivatives. The stepwise regression method was used to derive the most significant models as a calibration model for predicting the inhibitory activity of this class of molecules. The best QSAR models were further validated by a leave one out technique as well as by the calculation of statistical parameters for the established theoretical models. To confirm the predictive power of the models, an external set of molecules was used. High agreement between experimental and predicted inhibitory values, obtained in the validation procedure, indicated the good quality of the derived QSAR models. PMID:19468332

The East London glaucoma prediction score: web-based validation of glaucoma risk screening tool

PubMed Central

Stephen, Cook; Benjamin, Longo-Mbenza

2013-01-01

AIM It is difficult for Optometrists and General Practitioners to know which patients are at risk. The East London glaucoma prediction score (ELGPS) is a web based risk calculator that has been developed to determine Glaucoma risk at the time of screening. Multiple risk factors that are available in a low tech environment are assessed to provide a risk assessment. This is extremely useful in settings where access to specialist care is difficult. Use of the calculator is educational. It is a free web based service. Data capture is user specific. METHOD The scoring system is a web based questionnaire that captures and subsequently calculates the relative risk for the presence of Glaucoma at the time of screening. Three categories of patient are described: Unlikely to have Glaucoma; Glaucoma Suspect and Glaucoma. A case review methodology of patients with known diagnosis is employed to validate the calculator risk assessment. RESULTS Data from the patient records of 400 patients with an established diagnosis has been captured and used to validate the screening tool. The website reports that the calculated diagnosis correlates with the actual diagnosis 82% of the time. Biostatistics analysis showed: Sensitivity = 88%; Positive predictive value = 97%; Specificity = 75%. CONCLUSION Analysis of the first 400 patients validates the web based screening tool as being a good method of screening for the at risk population. The validation is ongoing. The web based format will allow a more widespread recruitment for different geographic, population and personnel variables. PMID:23550097

Identification of patients at high risk for Clostridium difficile infection: development and validation of a risk prediction model in hospitalized patients treated with antibiotics.

PubMed

van Werkhoven, C H; van der Tempel, J; Jajou, R; Thijsen, S F T; Diepersloot, R J A; Bonten, M J M; Postma, D F; Oosterheert, J J

2015-08-01

To develop and validate a prediction model for Clostridium difficile infection (CDI) in hospitalized patients treated with systemic antibiotics, we performed a case-cohort study in a tertiary (derivation) and secondary care hospital (validation). Cases had a positive Clostridium test and were treated with systemic antibiotics before suspicion of CDI. Controls were randomly selected from hospitalized patients treated with systemic antibiotics. Potential predictors were selected from the literature. Logistic regression was used to derive the model. Discrimination and calibration of the model were tested in internal and external validation. A total of 180 cases and 330 controls were included for derivation. Age >65 years, recent hospitalization, CDI history, malignancy, chronic renal failure, use of immunosuppressants, receipt of antibiotics before admission, nonsurgical admission, admission to the intensive care unit, gastric tube feeding, treatment with cephalosporins and presence of an underlying infection were independent predictors of CDI. The area under the receiver operating characteristic curve of the model in the derivation cohort was 0.84 (95% confidence interval 0.80-0.87), and was reduced to 0.81 after internal validation. In external validation, consisting of 97 cases and 417 controls, the model area under the curve was 0.81 (95% confidence interval 0.77-0.85) and model calibration was adequate (Brier score 0.004). A simplified risk score was derived. Using a cutoff of 7 points, the positive predictive value, sensitivity and specificity were 1.0%, 72% and 73%, respectively. In conclusion, a risk prediction model was developed and validated, with good discrimination and calibration, that can be used to target preventive interventions in patients with increased risk of CDI. Copyright © 2015 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.

Predicting umbilical artery pH during labour: Development and validation of a nomogram using fetal heart rate patterns.

PubMed

Ramanah, Rajeev; Omar, Sikiyah; Guillien, Alicia; Pugin, Aurore; Martin, Alain; Riethmuller, Didier; Mottet, Nicolas

2018-06-01

Nomograms are statistical models that combine variables to obtain the most accurate and reliable prediction for a particular risk. Fetal heart rate (FHR) interpretation alone has been found to be poorly predictive for fetal acidosis while other clinical risk factors exist. The aim of this study was to create and validate a nomogram based on FHR patterns and relevant clinical parameters to provide a non-invasive individualized prediction of umbilical artery pH during labour. A retrospective observational study was conducted on 4071 patients in labour presenting singleton pregnancies at >34 gestational weeks and delivering vaginally. Clinical characteristics, FHR patterns and umbilical cord gas of 1913 patients were used to construct a nomogram predicting an umbilical artery (Ua) pH <7.18 (10th centile of the study population) after an univariate and multivariate stepwise logistic regression analysis. External validation was obtained from an independent cohort of 2158 patients. Area under the receiver operating characteristics (ROC) curve, sensitivity, specificity, positive and negative predictive values of the nomogram were determined. Upon multivariate analysis, parity (p < 0.01), induction of labour (p = 0.01), a prior uterine scar (p = 0.02), maternal fever (p = 0.02) and the type of FHR (p < 0.01) were significantly associated with an Ua pH <7.18 (p < 0.05). Apgar score at 1, 5 and 10 min were significantly lower in the group with an Ua pH <7.18 (p < 0.01). The nomogram constructed had a Concordance Index of 0.75 (area under the curve) with a sensitivity of 57%, a specificity of 91%, a negative predictive value of 5% and a positive predictive value of 99%. Calibration found no difference between the predicted probabilities and the observed rate of Ua pH <7.18 (p = 0.63). The validation set had a Concordance Index of 0.72 and calibration with a p < 0.77. We successfully developed and validated a nomogram to predict Ua pH by combining easily available clinical variables and FHR. Discrimination and calibration of the model were statistically good. This mathematical tool can help clinicians in the management of labour by predicting umbilical artery pH based on FHR tracings. Copyright © 2018 Elsevier B.V. All rights reserved.

Prediction of overall survival for metastatic pancreatic cancer: Development and validation of a prognostic nomogram with data from open clinical trial and real-world study.

PubMed

Hang, Junjie; Wu, Lixia; Zhu, Lina; Sun, Zhiqiang; Wang, Ge; Pan, Jingjing; Zheng, Suhua; Xu, Kequn; Du, Jiadi; Jiang, Hua

2018-06-01

It is necessary to develop prognostic tools of metastatic pancreatic cancer (MPC) for optimizing therapeutic strategies. Thus, we tried to develop and validate a prognostic nomogram of MPC. Data from 3 clinical trials (NCT00844649, NCT01124786, and NCT00574275) and 133 Chinese MPC patients were used for analysis. The former 2 trials were taken as the training cohort while NCT00574275 was used as the validation cohort. In addition, 133 MPC patients treated in China were taken as the testing cohort. Cox regression model was used to investigate prognostic factors in the training cohort. With these factors, we established a nomogram and verified it by Harrell's concordance index (C-index) and calibration plots. Furthermore, the nomogram was externally validated in the validation cohort and testing cohort. In the training cohort (n = 445), performance status, liver metastasis, Carbohydrate antigen 19-9 (CA19-9) log-value, absolute neutrophil count (ANC), and albumin were independent prognostic factors for overall survival (OS). A nomogram was established with these factors to predict OS and survival probabilities. The nomogram showed an acceptable discrimination ability (C-index: .683) and good calibration, and was further externally validated in the validation cohort (n = 273, C-index: .699) and testing cohort (n = 133, C-index: .653).The nomogram total points (NTP) had the potential to stratify patients into 3-risk groups with median OS of 11.7, 7.0 and 3.7 months (P < .001), respectively. In conclusion, the prognostic nomogram with NTP can predict OS for patients with MPC with considerable accuracy. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Fatigue life prediction of rotor blade composites: Validation of constant amplitude formulations with variable amplitude experiments

NASA Astrophysics Data System (ADS)

Westphal, T.; Nijssen, R. P. L.

2014-12-01

The effect of Constant Life Diagram (CLD) formulation on the fatigue life prediction under variable amplitude (VA) loading was investigated based on variable amplitude tests using three different load spectra representative for wind turbine loading. Next to the Wisper and WisperX spectra, the recently developed NewWisper2 spectrum was used. Based on these variable amplitude fatigue results the prediction accuracy of 4 CLD formulations is investigated. In the study a piecewise linear CLD based on the S-N curves for 9 load ratios compares favourably in terms of prediction accuracy and conservativeness. For the specific laminate used in this study Boerstra's Multislope model provides a good alternative at reduced test effort.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS.

PubMed

Regenbogen, Sam; Wilkins, Angela D; Lichtarge, Olivier

2016-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses.

COMPUTING THERAPY FOR PRECISION MEDICINE: COLLABORATIVE FILTERING INTEGRATES AND PREDICTS MULTI-ENTITY INTERACTIONS

PubMed Central

REGENBOGEN, SAM; WILKINS, ANGELA D.; LICHTARGE, OLIVIER

2015-01-01

Biomedicine produces copious information it cannot fully exploit. Specifically, there is considerable need to integrate knowledge from disparate studies to discover connections across domains. Here, we used a Collaborative Filtering approach, inspired by online recommendation algorithms, in which non-negative matrix factorization (NMF) predicts interactions among chemicals, genes, and diseases only from pairwise information about their interactions. Our approach, applied to matrices derived from the Comparative Toxicogenomics Database, successfully recovered Chemical-Disease, Chemical-Gene, and Disease-Gene networks in 10-fold cross-validation experiments. Additionally, we could predict each of these interaction matrices from the other two. Integrating all three CTD interaction matrices with NMF led to good predictions of STRING, an independent, external network of protein-protein interactions. Finally, this approach could integrate the CTD and STRING interaction data to improve Chemical-Gene cross-validation performance significantly, and, in a time-stamped study, it predicted information added to CTD after a given date, using only data prior to that date. We conclude that collaborative filtering can integrate information across multiple types of biological entities, and that as a first step towards precision medicine it can compute drug repurposing hypotheses. PMID:26776170

Assessing Participation in Community-Based Physical Activity Programs in Brazil

PubMed Central

REIS, RODRIGO S.; YAN, YAN; PARRA, DIANA C.; BROWNSON, ROSS C.

2015-01-01

Purpose This study aimed to develop and validate a risk prediction model to examine the characteristics that are associated with participation in community-based physical activity programs in Brazil. Methods We used pooled data from three surveys conducted from 2007 to 2009 in state capitals of Brazil with 6166 adults. A risk prediction model was built considering program participation as an outcome. The predictive accuracy of the model was quantified through discrimination (C statistic) and calibration (Brier score) properties. Bootstrapping methods were used to validate the predictive accuracy of the final model. Results The final model showed sex (women: odds ratio [OR] = 3.18, 95% confidence interval [CI] = 2.14–4.71), having less than high school degree (OR = 1.71, 95% CI = 1.16–2.53), reporting a good health (OR = 1.58, 95% CI = 1.02–2.24) or very good/excellent health (OR = 1.62, 95% CI = 1.05–2.51), having any comorbidity (OR = 1.74, 95% CI = 1.26–2.39), and perceiving the environment as safe to walk at night (OR = 1.59, 95% CI = 1.18–2.15) as predictors of participation in physical activity programs. Accuracy indices were adequate (C index = 0.778, Brier score = 0.031) and similar to those obtained from bootstrapping (C index = 0.792, Brier score = 0.030). Conclusions Sociodemographic and health characteristics as well as perceptions of the environment are strong predictors of participation in community-based programs in selected cities of Brazil. PMID:23846162

Cross-cultural validity of the theory of planned behavior for predicting healthy food choice in secondary school students of Inner Mongolia.

PubMed

Shimazaki, Takashi; Bao, Hugejiletu; Deli, Geer; Uechi, Hiroaki; Lee, Ying-Hua; Miura, Kayo; Takenaka, Koji

2017-11-01

Unhealthy eating behavior is a serious health concern among secondary school students in Inner Mongolia. To predict their healthy food choices and devise methods of correcting unhealthy choices, we sought to confirm the cross-cultural validity of the theory of planned behavior among Inner Mongolian students. A cross-sectional study, conducted between November and December 2014. Overall, 3047 students were enrolled. We devised a questionnaire based on the theory of planned behavior to measure its components (intentions, attitudes, subjective norms, and perceived behavioral control) in relation to healthy food choices; we also assessed their current engagement in healthy food choices. A principal component analysis revealed high contribution rates for the components (69.32%-88.77%). A confirmatory factor analysis indicated that the components of the questionnaire had adequate model fit (goodness of fit index=0.997, adjusted goodness of fit index=0.984, comparative fit index=0.998, and root mean square error of approximation=0.049). Notably, data from participants within the suburbs did not support the theory of planned behavior construction. Several paths did not predict the hypothesis variables. However, attitudes toward healthy food choices strongly predicted behavioral intention (path coefficients 0.49-0.77, p<0.01), regardless of demographic characteristics. Our results support that the theory of planned behavior can apply to secondary school students in urban areas. Furthermore, attitudes towards healthy food choices were the best predictor of behavioral intentions to engage in such choices in Inner Mongolian students. Copyright © 2017 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Predicting survival of men with recurrent prostate cancer after radical prostatectomy.

PubMed

Dell'Oglio, Paolo; Suardi, Nazareno; Boorjian, Stephen A; Fossati, Nicola; Gandaglia, Giorgio; Tian, Zhe; Moschini, Marco; Capitanio, Umberto; Karakiewicz, Pierre I; Montorsi, Francesco; Karnes, R Jeffrey; Briganti, Alberto

2016-02-01

To develop and externally validate a novel nomogram aimed at predicting cancer-specific mortality (CSM) after biochemical recurrence (BCR) among prostate cancer (PCa) patients treated with radical prostatectomy (RP) with or without adjuvant external beam radiotherapy (aRT) and/or hormonal therapy (aHT). The development cohort included 689 consecutive PCa patients treated with RP between 1987 and 2011 with subsequent BCR, defined as two subsequent prostate-specific antigen values >0.2 ng/ml. Multivariable competing-risks regression analyses tested the predictors of CSM after BCR for the purpose of 5-year CSM nomogram development. Validation (2000 bootstrap resamples) was internally tested. External validation was performed into a population of 6734 PCa patients with BCR after treatment with RP at the Mayo Clinic from 1987 to 2011. The predictive accuracy (PA) was quantified using the receiver operating characteristic-derived area under the curve and the calibration plot method. The 5-year CSM-free survival rate was 83.6% (confidence interval [CI]: 79.6-87.2). In multivariable analyses, pathologic stage T3b or more (hazard ratio [HR]: 7.42; p = 0.008), pathologic Gleason score 8-10 (HR: 2.19; p = 0.003), lymph node invasion (HR: 3.57; p = 0.001), time to BCR (HR: 0.99; p = 0.03) and age at BCR (HR: 1.04; p = 0.04), were each significantly associated with the risk of CSM after BCR. The bootstrap-corrected PA was 87.4% (bootstrap 95% CI: 82.0-91.7%). External validation of our nomogram showed a good PA at 83.2%. We developed and externally validated the first nomogram predicting 5-year CSM applicable to contemporary patients with BCR after RP with or without adjuvant treatment. Copyright © 2015 Elsevier Ltd. All rights reserved.

Individual differences in situation awareness: Validation of the Situationism Scale

PubMed Central

Roberts, Megan E.; Gibbons, Frederick X.; Gerrard, Meg; Klein, William M. P.

2015-01-01

This paper concerns the construct of lay situationism—an individual’s belief in the importance of a behavior’s context. Study 1 identified a 13-item Situationism Scale, which demonstrated good reliability and validity. In particular, higher situationism was associated with greater situation-control (strategies to manipulate the environment in order to avoid temptation). Subsequent laboratory studies indicated that people higher on the situationism subscales used greater situation-control by sitting farther from junk food (Study 2) and choosing to drink non-alcoholic beverages before a cognitive task (Study 3). Overall, findings provide preliminary support for the psychometric validity and predictive utility of the Situationism Scale and offer this individual difference construct as a means to expand self-regulation theory. PMID:25329242

[Validation of the nutritional index in Mexican pre-teens with the sensitivity and specificity method].

PubMed

Saucedo-Molina, T J; Gómez-Peresmitré, G

1998-01-01

To determine the diagnostic validity of the nutritional index (NI) in a sample of Mexican preadolescents. A total of 256 preadolescents, between 10 and 12 years old, male and female, students from Mexico City, were used to establish the diagnostic validity of NI using the sensitivity and specificity method. The findings show that the conventional NI cut-off points showed good sensitivity and specificity for the diagnosis of low weight, normality and obesity but not for overweight. When the cut-off points of NI were normalized, the sensitivity, specificity and prediction potency values were more suitable in all categories. When working with preadolescents, it is better to use the new cut-off points of NI, to obtain more reliable diagnosis.

Development and Initial Validation of the Multicultural Personality Inventory (MPI).

PubMed

Ponterotto, Joseph G; Fietzer, Alexander W; Fingerhut, Esther C; Woerner, Scott; Stack, Lauren; Magaldi-Dopman, Danielle; Rust, Jonathan; Nakao, Gen; Tsai, Yu-Ting; Black, Natasha; Alba, Renaldo; Desai, Miraj; Frazier, Chantel; LaRue, Alyse; Liao, Pei-Wen

2014-01-01

Two studies summarize the development and initial validation of the Multicultural Personality Inventory (MPI). In Study 1, the 115-item prototype MPI was administered to 415 university students where exploratory factor analysis resulted in a 70-item, 7-factor model. In Study 2, the 70-item MPI and theoretically related companion instruments were administered to a multisite sample of 576 university students. Confirmatory factory analysis found the 7-factor structure to be a relatively good fit to the data (Comparative Fit Index =.954; root mean square error of approximation =.057), and MPI factors predicted variance in criterion variables above and beyond the variance accounted for by broad personality traits (i.e., Big Five). Study limitations and directions for further validation research are specified.

Predicting the 10-year risk of hip and major osteoporotic fracture in rheumatoid arthritis and in the general population: an independent validation and update of UK FRAX without bone mineral density

PubMed Central

Klop, Corinne; de Vries, Frank; Bijlsma, Johannes W J; Leufkens, Hubert G M; Welsing, Paco M J

2016-01-01

Objectives FRAX incorporates rheumatoid arthritis (RA) as a dichotomous predictor for predicting the 10-year risk of hip and major osteoporotic fracture (MOF). However, fracture risk may deviate with disease severity, duration or treatment. Aims were to validate, and if needed to update, UK FRAX for patients with RA and to compare predictive performance with the general population (GP). Methods Cohort study within UK Clinical Practice Research Datalink (CPRD) (RA: n=11 582, GP: n=38 755), also linked to hospital admissions for hip fracture (CPRD-Hospital Episode Statistics, HES) (RA: n=7221, GP: n=24 227). Predictive performance of UK FRAX without bone mineral density was assessed by discrimination and calibration. Updating methods included recalibration and extension. Differences in predictive performance were assessed by the C-statistic and Net Reclassification Improvement (NRI) using the UK National Osteoporosis Guideline Group intervention thresholds. Results UK FRAX significantly overestimated fracture risk in patients with RA, both for MOF (mean predicted vs observed 10-year risk: 13.3% vs 8.4%) and hip fracture (CPRD: 5.5% vs 3.1%, CPRD-HES: 5.5% vs 4.1%). Calibration was good for hip fracture in the GP (CPRD-HES: 2.7% vs 2.4%). Discrimination was good for hip fracture (RA: 0.78, GP: 0.83) and moderate for MOF (RA: 0.69, GP: 0.71). Extension of the recalibrated UK FRAX using CPRD-HES with duration of RA disease, glucocorticoids (>7.5 mg/day) and secondary osteoporosis did not improve the NRI (0.01, 95% CI −0.04 to 0.05) or C-statistic (0.78). Conclusions UK FRAX overestimated fracture risk in RA, but performed well for hip fracture in the GP after linkage to hospitalisations. Extension of the recalibrated UK FRAX did not improve predictive performance. PMID:26984006

A first European scale multimedia fate modelling of BDE-209 from 1970 to 2020.

PubMed

Earnshaw, Mark R; Jones, Kevin C; Sweetman, Andy J

2015-01-01

The European Variant Berkeley Trent (EVn-BETR) multimedia fugacity model is used to test the validity of previously derived emission estimates and predict environmental concentrations of the main decabromodiphenyl ether congener, BDE-209. The results are presented here and compared with measured environmental data from the literature. Future multimedia concentration trends are predicted using three emission scenarios (Low, Realistic and High) in the dynamic unsteady state mode covering the period 1970-2020. The spatial and temporal distributions of emissions are evaluated. It is predicted that BDE-209 atmospheric concentrations peaked in 2004 and will decline to negligible levels by 2025. Freshwater concentrations should have peaked in 2011, one year after the emissions peak with sediment concentrations peaking in 2013. Predicted atmospheric concentrations are in good agreement with measured data for the Realistic (best estimate of emissions) and High (worst case scenario) emission scenarios. The Low emission scenario consistently underestimates measured data. The German unilateral ban on the use of DecaBDE in the textile industry is simulated in an additional scenario, the effects of which are mainly observed within Germany with only a small effect on the surrounding areas. Overall, the EVn-BTER model predicts atmospheric concentrations reasonably well, within a factor of 5 and 1.2 for the Realistic and High emission scenarios respectively, providing partial validation for the original emission estimate. Total mean MEC:PEC shows the High emission scenario predicts the best fit between air, freshwater and sediment data. An alternative spatial distribution of emissions is tested, based on higher consumption in EBFRIP member states, resulting in improved agreement between MECs and PECs in comparison with the Uniform spatial distribution based on population density. Despite good agreement between modelled and measured point data, more long-term monitoring datasets are needed to compare predicted trends in concentration to determine the rate of change of POPs within the environment. Copyright © 2014 Elsevier Ltd. All rights reserved.

Independent validation of a new reirradiation risk score (RRRS) for glioma patients predicting post-recurrence survival: A multicenter DKTK/ROG analysis.

PubMed

Niyazi, Maximilian; Adeberg, Sebastian; Kaul, David; Boulesteix, Anne-Laure; Bougatf, Nina; Fleischmann, Daniel F; Grün, Arne; Krämer, Anna; Rödel, Claus; Eckert, Franziska; Paulsen, Frank; Kessel, Kerstin A; Combs, Stephanie E; Oehlke, Oliver; Grosu, Anca-Ligia; Seidlitz, Annekatrin; Lattermann, Annika; Krause, Mechthild; Baumann, Michael; Guberina, Maja; Stuschke, Martin; Budach, Volker; Belka, Claus; Debus, Jürgen

2018-04-01

Reirradiation (reRT) is a valid option with considerable efficacy in patients with recurrent high-grade glioma, but it is still not known which patients might be optimal candidates for a second course of irradiation. This study validated a newly developed prognostic score independently in an external patient cohort. The reRT risk score (RRRS) is based on a linear combination of initial histology, clinical performance status, and age derived from a multivariable model of 353 patients. This score can predict post-recurrence survival (PRS) after reRT. The validation dataset consisted of 212 patients. The RRRS differentiates three prognostic groups. Discrimination and calibration were maintained in the validation group. Median PRS times in the development cohort for the good/intermediate/poor risk categories were 14.2, 9.1, and 5.3 months, respectively. The respective groups within the validation cohort displayed median PRS times of 13.8, 8.8, and 3.8 months, respectively. Uno's C for development data was 0.64 (CI: 0.60-0.69) and for validation data 0.63 (CI: 0.58-0.68). The RRRS has been successfully validated in an independent patient cohort. This linear combination of three easily determined clinicopathological factors allows for a reliable classification of patients and may be used as stratification factor for future trials. Copyright © 2018 Elsevier B.V. All rights reserved.

[The Basel Screening Instrument for Psychosis (BSIP): development, structure, reliability and validity].

PubMed

Riecher-Rössler, A; Aston, J; Ventura, J; Merlo, M; Borgwardt, S; Gschwandtner, U; Stieglitz, R-D

2008-04-01

Early detection of psychosis is of growing clinical importance. So far there is, however, no screening instrument for detecting individuals with beginning psychosis in the atypical early stages of the disease with sufficient validity. We have therefore developed the Basel Screening Instrument for Psychosis (BSIP) and tested its feasibility, interrater-reliability and validity. Aim of this paper is to describe the development and structure of the instrument, as well as to report the results of the studies on reliability and validity. The instrument was developed based on a comprehensive search of literature on the most important risk factors and early signs of schizophrenic psychoses. The interraterreliability study was conducted on 24 psychiatric cases. Validity was tested based on 206 individuals referred to our early detection clinic from 3/1/2000 until 2/28/2003. We identified seven categories of relevance for early detection of psychosis and used them to construct a semistructured interview. Interrater-reliability for high risk individuals was high (Kappa .87). Predictive validity was comparable to other, more comprehensive instruments: 16 (32 %) of 50 individuals classified as being at risk for psychosis by the BSIP have in fact developed frank psychosis within an follow-up period of two to five years. The BSIP is the first screening instrument for the early detection of psychosis which has been validated based on transition to psychosis. The BSIP is easy to use by experienced psychiatrists and has a very good interrater-reliability and predictive validity.

Development and validation of QMortality risk prediction algorithm to estimate short term risk of death and assess frailty: cohort study.

PubMed

Hippisley-Cox, Julia; Coupland, Carol

2017-09-20

Objectives  To derive and validate a risk prediction equation to estimate the short term risk of death, and to develop a classification method for frailty based on risk of death and risk of unplanned hospital admission. Design  Prospective open cohort study. Participants  Routinely collected data from 1436 general practices contributing data to QResearch in England between 2012 and 2016. 1079 practices were used to develop the scores and a separate set of 357 practices to validate the scores. 1.47 million patients aged 65-100 years were in the derivation cohort and 0.50 million patients in the validation cohort. Methods  Cox proportional hazards models in the derivation cohort were used to derive separate risk equations in men and women for evaluation of the risk of death at one year. Risk factors considered were age, sex, ethnicity, deprivation, smoking status, alcohol intake, body mass index, medical conditions, specific drugs, social factors, and results of recent investigations. Measures of calibration and discrimination were determined in the validation cohort for men and women separately and for each age and ethnic group. The new mortality equation was used in conjunction with the existing QAdmissions equation (which predicts risk of unplanned hospital admission) to classify patients into frailty groups. Main outcome measure  The primary outcome was all cause mortality. Results  During follow-up 180 132 deaths were identified in the derivation cohort arising from 4.39 million person years of observation. The final model included terms for age, body mass index, Townsend score, ethnic group, smoking status, alcohol intake, unplanned hospital admissions in the past 12 months, atrial fibrillation, antipsychotics, cancer, asthma or chronic obstructive pulmonary disease, living in a care home, congestive heart failure, corticosteroids, cardiovascular disease, dementia, epilepsy, learning disability, leg ulcer, chronic liver disease or pancreatitis, Parkinson's disease, poor mobility, rheumatoid arthritis, chronic kidney disease, type 1 diabetes, type 2 diabetes, venous thromboembolism, anaemia, abnormal liver function test result, high platelet count, visited doctor in the past year with either appetite loss, unexpected weight loss, or breathlessness. The model had good calibration and high levels of explained variation and discrimination. In women, the equation explained 55.6% of the variation in time to death (R 2 ), and had very good discrimination-the D statistic was 2.29, and Harrell's C statistic value was 0.85. The corresponding values for men were 53.1%, 2.18, and 0.84. By combining predicted risks of mortality and unplanned hospital admissions, 2.7% of patients (n=13 665) were classified as severely frail, 9.4% (n=46 770) as moderately frail, 43.1% (n=215 253) as mildly frail, and 44.8% (n=223 790) as fit. Conclusions  We have developed new equations to predict the short term risk of death in men and women aged 65 or more, taking account of demographic, social, and clinical variables. The equations had good performance on a separate validation cohort. The QMortality equations can be used in conjunction with the QAdmissions equations, to classify patients into four frailty groups (known as QFrailty categories) to enable patients to be identified for further assessment or interventions. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

INCLEN Diagnostic Tool for Autism Spectrum Disorder (INDT-ASD): development and validation.

PubMed

Juneja, Monica; Mishra, Devendra; Russell, Paul S S; Gulati, Sheffali; Deshmukh, Vaishali; Tudu, Poma; Sagar, Rajesh; Silberberg, Donald; Bhutani, Vinod K; Pinto, Jennifer M; Durkin, Maureen; Pandey, Ravindra M; Nair, M K C; Arora, Narendra K

2014-05-01

To develop and validate INCLEN Diagnostic Tool for Autism Spectrum Disorder (INDT-ASD). Diagnostic test evaluation by cross sectional design. Four tertiary pediatric neurology centers in Delhi and Thiruvanthapuram, India. Children aged 2-9 years were enrolled in the study. INDT-ASD and Childhood Autism Rating Scale (CARS) were administered in a randomly decided sequence by trained psychologist, followed by an expert evaluation by DSM-IV TR diagnostic criteria (gold standard). Psychometric parameters of diagnostic accuracy, validity (construct, criterion and convergent) and internal consistency. 154 children (110 boys, mean age 64.2 mo) were enrolled. The overall diagnostic accuracy (AUC=0.97, 95% CI 0.93, 0.99; P<0.001) and validity (sensitivity 98%, specificity 95%, positive predictive value 91%, negative predictive value 99%) of INDT-ASD for Autism spectrum disorder were high, taking expert diagnosis using DSM-IV-TR as gold standard. The concordance rate between the INDT-ASD and expert diagnosis for 'ASD group' was 82.52% [Cohen's k=0.89; 95% CI (0.82, 0.97); P=0.001]. The internal consistency of INDT-ASD was 0.96. The convergent validity with CARS (r = 0.73, P= 0.001) and divergent validity with Binet-Kamat Test of intelligence (r = -0.37; P=0.004) were significantly high. INDT-ASD has a 4-factor structure explaining 85.3% of the variance. INDT-ASD has high diagnostic accuracy, adequate content validity, good internal consistency high criterion validity and high to moderate convergent validity and 4-factor construct validity for diagnosis of Autistm spectrum disorder.

The work role functioning questionnaire 2.0 (Dutch version): examination of its reliability, validity and responsiveness in the general working population.

PubMed

Abma, Femke I; van der Klink, Jac J L; Bültmann, Ute

2013-03-01

The promotion of a sustainable, healthy and productive working life attracts more and more attention. Recently the Work Role Functioning Questionnaire (WRFQ) has been cross-culturally translated and adapted to Dutch. This questionnaire aims to measure the health-related work functioning of workers with health problems. The aim of this study is to evaluate the reliability, validity (including five new items) and responsiveness of the WRFQ 2.0 in the working population. A longitudinal study was conducted among workers. The reliability (internal consistency, test-retest reliability, measurement error), validity (structural validity-factor analysis, construct validity by means of hypotheses testing) and responsiveness of the WRFQ 2.0 were evaluated. A total of N = 553 workers completed the survey. The final WRFQ 2.0 has four subscales and showed very good internal consistency, moderate test-retest reliability, good construct validity and moderate responsiveness in the working population. The WRFQ was able to distinguish between groups with different levels of mental health, physical health, fatigue and need for recovery. A moderate correlation was found between WRFQ and related constructs respectively work ability and work productivity. A weak relationship was found with general self-rated health, work engagement and work involvement. The WRFQ 2.0 is a reliable and valid instrument to measure health-related work functioning in the working population. Further validation in larger samples is recommended, especially for test-retest reliability, responsiveness and the questionnaire's ability to predict the future course of health-related work functioning.

Predicting the Onset of Anxiety Syndromes at 12 Months in Primary Care Attendees. The PredictA-Spain Study

PubMed Central

Moreno-Peral, Patricia; Luna, Juan de Dios; Marston, Louise; King, Michael; Nazareth, Irwin; Motrico, Emma; GildeGómez-Barragán, María Josefa; Torres-González, Francisco; Montón-Franco, Carmen; Sánchez-Celaya, Marta; Díaz-Barreiros, Miguel Ángel; Vicens, Catalina; Muñoz-Bravo, Carlos; Bellón, Juan Ángel

2014-01-01

Background There are no risk algorithms for the onset of anxiety syndromes at 12 months in primary care. We aimed to develop and validate internally a risk algorithm to predict the onset of anxiety syndromes at 12 months. Methods A prospective cohort study with evaluations at baseline, 6 and 12 months. We measured 39 known risk factors and used multilevel logistic regression and inverse probability weighting to build the risk algorithm. Our main outcome was generalized anxiety, panic and other non-specific anxiety syndromes as measured by the Primary Care Evaluation of Mental Disorders, Patient Health Questionnaire (PRIME-MD-PHQ). We recruited 3,564 adult primary care attendees without anxiety syndromes from 174 family physicians and 32 health centers in 6 Spanish provinces. Results The cumulative 12-month incidence of anxiety syndromes was 12.2%. The predictA-Spain risk algorithm included the following predictors of anxiety syndromes: province; sex (female); younger age; taking medicines for anxiety, depression or stress; worse physical and mental quality of life (SF-12); dissatisfaction with paid and unpaid work; perception of financial strain; and the interactions sex*age, sex*perception of financial strain, and age*dissatisfaction with paid work. The C-index was 0.80 (95% confidence interval = 0.78–0.83) and the Hedges' g = 1.17 (95% confidence interval = 1.04–1.29). The Copas shrinkage factor was 0.98 and calibration plots showed an accurate goodness of fit. Conclusions The predictA-Spain risk algorithm is valid to predict anxiety syndromes at 12 months. Although external validation is required, the predictA-Spain is available for use as a predictive tool in the prevention of anxiety syndromes in primary care. PMID:25184313

Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.

PubMed

Singh, Kunwar P; Gupta, Shikha; Rai, Premanjali

2013-09-01

The research aims to develop global modeling tools capable of categorizing structurally diverse chemicals in various toxicity classes according to the EEC and European Community directives, and to predict their acute toxicity in fathead minnow using set of selected molecular descriptors. Accordingly, artificial intelligence approach based classification and regression models, such as probabilistic neural networks (PNN), generalized regression neural networks (GRNN), multilayer perceptron neural network (MLPN), radial basis function neural network (RBFN), support vector machines (SVM), gene expression programming (GEP), and decision tree (DT) were constructed using the experimental toxicity data. Diversity and non-linearity in the chemicals' data were tested using the Tanimoto similarity index and Brock-Dechert-Scheinkman statistics. Predictive and generalization abilities of various models constructed here were compared using several statistical parameters. PNN and GRNN models performed relatively better than MLPN, RBFN, SVM, GEP, and DT. Both in two and four category classifications, PNN yielded a considerably high accuracy of classification in training (95.85 percent and 90.07 percent) and validation data (91.30 percent and 86.96 percent), respectively. GRNN rendered a high correlation between the measured and model predicted -log LC50 values both for the training (0.929) and validation (0.910) data and low prediction errors (RMSE) of 0.52 and 0.49 for two sets. Efficiency of the selected PNN and GRNN models in predicting acute toxicity of new chemicals was adequately validated using external datasets of different fish species (fathead minnow, bluegill, trout, and guppy). The PNN and GRNN models showed good predictive and generalization abilities and can be used as tools for predicting toxicities of structurally diverse chemical compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

Which Patients Require Extended Thromboprophylaxis After Colectomy? Modeling Risk and Assessing Indications for Post-discharge Pharmacoprophylaxis.

PubMed

Beal, Eliza W; Tumin, Dmitry; Chakedis, Jeffery; Porter, Erica; Moris, Dimitrios; Zhang, Xu-Feng; Arnold, Mark; Harzman, Alan; Husain, Syed; Schmidt, Carl R; Pawlik, Timothy M

2018-07-01

Given the conflicting nature of reported risk factors for post-discharge venous thromboembolism (VTE) and unclear guidelines for post-discharge pharmacoprophylaxis, we sought to determine risk factors for 30-day post-discharge VTE after colectomy to predict which patients will benefit from post-discharge pharmacoprophylaxis. Patients who underwent colectomy in the American College of Surgeons National Surgical Quality Improvement Project Participant Use Files from 2011 to 2015 were identified. Logistic regression modeling was used. Receiver-operating characteristic curves were used and the best cut-points were determined using Youden's J index (sensitivity + specificity - 1). Hosmer-Lemeshow goodness-of-fit test was used to test model calibration. A random sample of 30% of the cohort was used as a validation set. Among 77,823 cases, the overall incidence of VTE after colectomy was 1.9%, with 0.7% of VTE events occurring in the post-discharge setting. Factors associated with post-discharge VTE risk including body mass index, preoperative albumin, operation time, hospital length of stay, race, smoking status, inflammatory bowel disease, return to the operating room and postoperative ileus were included in logistic regression equation model. The model demonstrated good calibration (goodness of fit P = 0.7137) and good discrimination (area under the curve (AUC) = 0.68; validation set, AUC = 0.70). A score of ≥-5.00 had the maxim sensitivity and specificity, resulting in 36.63% of patients being treated with prophylaxis for an overall VTE risk of 0.67%. Approximately one-third of post-colectomy VTE events occurred after discharge. Patients with predicted post-discharge VTE risk of ≥-5.00 should be recommended for extended post-discharge VTE prophylaxis.

Update of the German Diabetes Risk Score and external validation in the German MONICA/KORA study.

PubMed

Mühlenbruch, Kristin; Ludwig, Tonia; Jeppesen, Charlotte; Joost, Hans-Georg; Rathmann, Wolfgang; Meisinger, Christine; Peters, Annette; Boeing, Heiner; Thorand, Barbara; Schulze, Matthias B

2014-06-01

Several published diabetes prediction models include information about family history of diabetes. The aim of this study was to extend the previously developed German Diabetes Risk Score (GDRS) with family history of diabetes and to validate the updated GDRS in the Multinational MONItoring of trends and determinants in CArdiovascular Diseases (MONICA)/German Cooperative Health Research in the Region of Augsburg (KORA) study. We used data from the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam study for extending the GDRS, including 21,846 participants. Within 5 years of follow-up 492 participants developed diabetes. The definition of family history included information about the father, the mother and/or sibling/s. Model extension was evaluated by discrimination and reclassification. We updated the calculation of the score and absolute risks. External validation was performed in the MONICA/KORA study comprising 11,940 participants with 315 incident cases after 5 years of follow-up. The basic ROC-AUC of 0.856 (95%-CI: 0.842-0.870) was improved by 0.007 (0.003-0.011) when parent and sibling history was included in the GDRS. The net reclassification improvement was 0.110 (0.072-0.149), respectively. For the updated score we demonstrated good calibration across all tenths of risk. In MONICA/KORA, the ROC-AUC was 0.837 (0.819-0.855); regarding calibration we saw slight overestimation of absolute risks. Inclusion of the number of diabetes-affected parents and sibling history improved the prediction of type 2 diabetes. Therefore, we updated the GDRS algorithm accordingly. Validation in another German cohort study showed good discrimination and acceptable calibration for the vast majority of individuals. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Experimental validation of finite element modelling of a modular metal-on-polyethylene total hip replacement.

PubMed

Hua, Xijin; Wang, Ling; Al-Hajjar, Mazen; Jin, Zhongmin; Wilcox, Ruth K; Fisher, John

2014-07-01

Finite element models are becoming increasingly useful tools to conduct parametric analysis, design optimisation and pre-clinical testing for hip joint replacements. However, the verification of the finite element model is critically important. The purposes of this study were to develop a three-dimensional anatomic finite element model for a modular metal-on-polyethylene total hip replacement for predicting its contact mechanics and to conduct experimental validation for a simple finite element model which was simplified from the anatomic finite element model. An anatomic modular metal-on-polyethylene total hip replacement model (anatomic model) was first developed and then simplified with reasonable accuracy to a simple modular total hip replacement model (simplified model) for validation. The contact areas on the articulating surface of three polyethylene liners of modular metal-on-polyethylene total hip replacement bearings with different clearances were measured experimentally in the Leeds ProSim hip joint simulator under a series of loading conditions and different cup inclination angles. The contact areas predicted from the simplified model were then compared with that measured experimentally under the same conditions. The results showed that the simplification made for the anatomic model did not change the predictions of contact mechanics of the modular metal-on-polyethylene total hip replacement substantially (less than 12% for contact stresses and contact areas). Good agreements of contact areas between the finite element predictions from the simplified model and experimental measurements were obtained, with maximum difference of 14% across all conditions considered. This indicated that the simplification and assumptions made in the anatomic model were reasonable and the finite element predictions from the simplified model were valid. © IMechE 2014.

Development and validation of a prediction algorithm for the onset of common mental disorders in a working population.

PubMed

Fernandez, Ana; Salvador-Carulla, Luis; Choi, Isabella; Calvo, Rafael; Harvey, Samuel B; Glozier, Nicholas

2018-01-01

Common mental disorders are the most common reason for long-term sickness absence in most developed countries. Prediction algorithms for the onset of common mental disorders may help target indicated work-based prevention interventions. We aimed to develop and validate a risk algorithm to predict the onset of common mental disorders at 12 months in a working population. We conducted a secondary analysis of the Household, Income and Labour Dynamics in Australia Survey, a longitudinal, nationally representative household panel in Australia. Data from the 6189 working participants who did not meet the criteria for a common mental disorders at baseline were non-randomly split into training and validation databases, based on state of residence. Common mental disorders were assessed with the mental component score of 36-Item Short Form Health Survey questionnaire (score ⩽45). Risk algorithms were constructed following recommendations made by the Transparent Reporting of a multivariable prediction model for Prevention Or Diagnosis statement. Different risk factors were identified among women and men for the final risk algorithms. In the training data, the model for women had a C-index of 0.73 and effect size (Hedges' g) of 0.91. In men, the C-index was 0.76 and the effect size was 1.06. In the validation data, the C-index was 0.66 for women and 0.73 for men, with positive predictive values of 0.28 and 0.26, respectively Conclusion: It is possible to develop an algorithm with good discrimination for the onset identifying overall and modifiable risks of common mental disorders among working men. Such models have the potential to change the way that prevention of common mental disorders at the workplace is conducted, but different models may be required for women.

Validation and uncertainty analysis of a pre-treatment 2D dose prediction model

NASA Astrophysics Data System (ADS)

Baeza, Jose A.; Wolfs, Cecile J. A.; Nijsten, Sebastiaan M. J. J. G.; Verhaegen, Frank

2018-02-01

Independent verification of complex treatment delivery with megavolt photon beam radiotherapy (RT) has been effectively used to detect and prevent errors. This work presents the validation and uncertainty analysis of a model that predicts 2D portal dose images (PDIs) without a patient or phantom in the beam. The prediction model is based on an exponential point dose model with separable primary and secondary photon fluence components. The model includes a scatter kernel, off-axis ratio map, transmission values and penumbra kernels for beam-delimiting components. These parameters were derived through a model fitting procedure supplied with point dose and dose profile measurements of radiation fields. The model was validated against a treatment planning system (TPS; Eclipse) and radiochromic film measurements for complex clinical scenarios, including volumetric modulated arc therapy (VMAT). Confidence limits on fitted model parameters were calculated based on simulated measurements. A sensitivity analysis was performed to evaluate the effect of the parameter uncertainties on the model output. For the maximum uncertainty, the maximum deviating measurement sets were propagated through the fitting procedure and the model. The overall uncertainty was assessed using all simulated measurements. The validation of the prediction model against the TPS and the film showed a good agreement, with on average 90.8% and 90.5% of pixels passing a (2%,2 mm) global gamma analysis respectively, with a low dose threshold of 10%. The maximum and overall uncertainty of the model is dependent on the type of clinical plan used as input. The results can be used to study the robustness of the model. A model for predicting accurate 2D pre-treatment PDIs in complex RT scenarios can be used clinically and its uncertainties can be taken into account.

Measurement versus prediction in the construction of patient-reported outcome questionnaires: can we have our cake and eat it?

PubMed

Smits, Niels; van der Ark, L Andries; Conijn, Judith M

2017-11-02

Two important goals when using questionnaires are (a) measurement: the questionnaire is constructed to assign numerical values that accurately represent the test taker's attribute, and (b) prediction: the questionnaire is constructed to give an accurate forecast of an external criterion. Construction methods aimed at measurement prescribe that items should be reliable. In practice, this leads to questionnaires with high inter-item correlations. By contrast, construction methods aimed at prediction typically prescribe that items have a high correlation with the criterion and low inter-item correlations. The latter approach has often been said to produce a paradox concerning the relation between reliability and validity [1-3], because it is often assumed that good measurement is a prerequisite of good prediction. To answer four questions: (1) Why are measurement-based methods suboptimal for questionnaires that are used for prediction? (2) How should one construct a questionnaire that is used for prediction? (3) Do questionnaire-construction methods that optimize measurement and prediction lead to the selection of different items in the questionnaire? (4) Is it possible to construct a questionnaire that can be used for both measurement and prediction? An empirical data set consisting of scores of 242 respondents on questionnaire items measuring mental health is used to select items by means of two methods: a method that optimizes the predictive value of the scale (i.e., forecast a clinical diagnosis), and a method that optimizes the reliability of the scale. We show that for the two scales different sets of items are selected and that a scale constructed to meet the one goal does not show optimal performance with reference to the other goal. The answers are as follows: (1) Because measurement-based methods tend to maximize inter-item correlations by which predictive validity reduces. (2) Through selecting items that correlate highly with the criterion and lowly with the remaining items. (3) Yes, these methods may lead to different item selections. (4) For a single questionnaire: Yes, but it is problematic because reliability cannot be estimated accurately. For a test battery: Yes, but it is very costly. Implications for the construction of patient-reported outcome questionnaires are discussed.

Predicting the risk of toxic blooms of golden alga from cell abundance and environmental covariates

USGS Publications Warehouse

Patino, Reynaldo; VanLandeghem, Matthew M.; Denny, Shawn

2016-01-01

Golden alga (Prymnesium parvum) is a toxic haptophyte that has caused considerable ecological damage to marine and inland aquatic ecosystems worldwide. Studies focused primarily on laboratory cultures have indicated that toxicity is poorly correlated with the abundance of golden alga cells. This relationship, however, has not been rigorously evaluated in the field where environmental conditions are much different. The ability to predict toxicity using readily measured environmental variables and golden alga abundance would allow managers rapid assessments of ichthyotoxicity potential without laboratory bioassay confirmation, which requires additional resources to accomplish. To assess the potential utility of these relationships, several a priori models relating lethal levels of golden alga ichthyotoxicity to golden alga abundance and environmental covariates were constructed. Model parameters were estimated using archived data from four river basins in Texas and New Mexico (Colorado, Brazos, Red, Pecos). Model predictive ability was quantified using cross-validation, sensitivity, and specificity, and the relative ranking of environmental covariate models was determined by Akaike Information Criterion values and Akaike weights. Overall, abundance was a generally good predictor of ichthyotoxicity as cross validation of golden alga abundance-only models ranged from ∼ 80% to ∼ 90% (leave-one-out cross-validation). Environmental covariates improved predictions, especially the ability to predict lethally toxic events (i.e., increased sensitivity), and top-ranked environmental covariate models differed among the four basins. These associations may be useful for monitoring as well as understanding the abiotic factors that influence toxicity during blooms.

Development of a model for predicting reaction rate constants of organic chemicals with ozone at different temperatures.

PubMed

Li, Xuehua; Zhao, Wenxing; Li, Jing; Jiang, Jingqiu; Chen, Jianji; Chen, Jingwen

2013-08-01

To assess the persistence and fate of volatile organic compounds in the troposphere, the rate constants for the reaction with ozone (kO3) are needed. As kO3 values are only available for hundreds of compounds, and experimental determination of kO3 is costly and time-consuming, it is of importance to develop predictive models on kO3. In this study, a total of 379 logkO3 values at different temperatures were used to develop and validate a model for the prediction of kO3, based on quantum chemical descriptors, Dragon descriptors and structural fragments. Molecular descriptors were screened by stepwise multiple linear regression, and the model was constructed by partial least-squares regression. The cross validation coefficient QCUM(2) of the model is 0.836, and the external validation coefficient Qext(2) is 0.811, indicating that the model has high robustness and good predictive performance. The most significant descriptor explaining logkO3 is the BELm2 descriptor with connectivity information weighted atomic masses. kO3 increases with increasing BELm2, and decreases with increasing ionization potential. The applicability domain of the proposed model was visualized by the Williams plot. The developed model can be used to predict kO3 at different temperatures for a wide range of organic chemicals, including alkenes, cycloalkenes, haloalkenes, alkynes, oxygen-containing compounds, nitrogen-containing compounds (except primary amines) and aromatic compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.

Anticancer drug sensitivity prediction in cell lines from baseline gene expression through recursive feature selection.

PubMed

Dong, Zuoli; Zhang, Naiqian; Li, Chun; Wang, Haiyun; Fang, Yun; Wang, Jun; Zheng, Xiaoqi

2015-06-30

An enduring challenge in personalized medicine is to select right drug for individual patients. Testing drugs on patients in large clinical trials is one way to assess their efficacy and toxicity, but it is impractical to test hundreds of drugs currently under development. Therefore the preclinical prediction model is highly expected as it enables prediction of drug response to hundreds of cell lines in parallel. Recently, two large-scale pharmacogenomic studies screened multiple anticancer drugs on over 1000 cell lines in an effort to elucidate the response mechanism of anticancer drugs. To this aim, we here used gene expression features and drug sensitivity data in Cancer Cell Line Encyclopedia (CCLE) to build a predictor based on Support Vector Machine (SVM) and a recursive feature selection tool. Robustness of our model was validated by cross-validation and an independent dataset, the Cancer Genome Project (CGP). Our model achieved good cross validation performance for most drugs in the Cancer Cell Line Encyclopedia (≥80% accuracy for 10 drugs, ≥75% accuracy for 19 drugs). Independent tests on eleven common drugs between CCLE and CGP achieved satisfactory performance for three of them, i.e., AZD6244, Erlotinib and PD-0325901, using expression levels of only twelve, six and seven genes, respectively. These results suggest that drug response could be effectively predicted from genomic features. Our model could be applied to predict drug response for some certain drugs and potentially play a complementary role in personalized medicine.

The Transition Readiness Assessment Questionnaire (TRAQ): its factor structure, reliability, and validity.

PubMed

Wood, David L; Sawicki, Gregory S; Miller, M David; Smotherman, Carmen; Lukens-Bull, Katryne; Livingood, William C; Ferris, Maria; Kraemer, Dale F

2014-01-01

National consensus statements recommend that providers regularly assess the transition readiness skills of adolescent and young adults (AYA). In 2010 we developed a 29-item version of Transition Readiness Assessment Questionnaire (TRAQ). We reevaluated item performance and factor structure, and reassessed the TRAQ's reliability and validity. We surveyed youth from 3 academic clinics in Jacksonville, Florida; Chapel Hill, North Carolina; and Boston, Massachusetts. Participants were AYA with special health care needs aged 14 to 21 years. From a convenience sample of 306 patients, we conducted item reduction strategies and exploratory factor analysis (EFA). On a second convenience sample of 221 patients, we conducted confirmatory factor analysis (CFA). Internal reliability was assessed by Cronbach's alpha and criterion validity. Analyses were conducted by the Wilcoxon rank sum test and mixed linear models. The item reduction and EFA resulted in a 20-item scale with 5 identified subscales. The CFA conducted on a second sample provided a good fit to the data. The overall scale has high reliability overall (Cronbach's alpha = .94) and good reliability for 4 of the 5 subscales (Cronbach's alpha ranging from .90 to .77 in the pooled sample). Each of the 5 subscale scores were significantly higher for adolescents aged 18 years and older versus those younger than 18 (P < .0001) in both univariate and multivariate analyses. The 20-item, 5-factor structure for the TRAQ is supported by EFA and CFA on independent samples and has good internal reliability and criterion validity. Additional work is needed to expand or revise the TRAQ subscales and test their predictive validity. Copyright © 2014 Academic Pediatric Association. Published by Elsevier Inc. All rights reserved.

Functional Status Score for the Intensive Care Unit (FSS-ICU): An International Clinimetric Analysis of Validity, Responsiveness, and Minimal Important Difference

PubMed Central

Huang, Minxuan; Chan, Kitty S.; Zanni, Jennifer M.; Parry, Selina M.; Neto, Saint-Clair G. B.; Neto, Jose A. A.; da Silva, Vinicius Z. M.; Kho, Michelle E.; Needham, Dale M.

2017-01-01

Objective To evaluate the internal consistency, validity, responsiveness, and minimal important difference of the Functional Status Score for the Intensive Care Unit (FSS-ICU), a physical function measure designed for the intensive care unit (ICU). Design Clinimetric analysis. Settings Five international data sets from the United States, Australia, and Brazil. Patients 819 ICU patients. Intervention None. Measurements and Main Results Clinimetric analyses were initially conducted separately for each data source and time point to examine generalizability of findings, with pooled analyses performed thereafter to increase power of analyses. The FSS-ICU demonstrated good to excellent internal consistency. There was good convergent and discriminant validity, with significant and positive correlations (r = 0.30 to 0.95) between FSS-ICU and other physical function measures, and generally weaker correlations with non-physical measures (|r| = 0.01 to 0.70). Known group validity was demonstrated by significantly higher FSS-ICU scores among patients without ICU-acquired weakness (Medical Research Council sumscore ≥48 versus <48) and with hospital discharge to home (versus healthcare facility). FSS-ICU at ICU discharge predicted post-ICU hospital length of stay and discharge location. Responsiveness was supported via increased FSS-ICU scores with improvements in muscle strength. Distribution-based methods indicated a minimal important difference of 2.0 to 5.0. Conclusions The FSS-ICU has good internal consistency and is a valid and responsive measure of physical function for ICU patients. The estimated minimal important difference can be used in sample size calculations and in interpreting studies comparing the physical function of groups of ICU patients. PMID:27488220

Validation of a Spanish-language version of the ADHD Rating Scale IV in a Spanish sample.

PubMed

Vallejo-Valdivielso, M; Soutullo, C A; de Castro-Manglano, P; Marín-Méndez, J J; Díez-Suárez, A

2017-07-14

The purpose of this study is to validate a Spanish-language version of the 18-item ADHD Rating Scale-IV (ADHD-RS-IV.es) in a Spanish sample. From a total sample of 652 children and adolescents aged 6 to 17 years (mean age was 11.14±3.27), we included 518 who met the DSM-IV-TR criteria for ADHD and 134 healthy controls. To evaluate the factorial structure, validity, and reliability of the scale, we performed a confirmatory factor analysis (CFA) using structural equation modelling on a polychoric correlation matrix and maximum likelihood estimation. The scale's discriminant validity and predictive value were estimated using ROC (receiver operating characteristics) curve analysis. Both the full scale and the subscales of the Spanish-language version of the ADHD-RS-IV showed good internal consistency. Cronbach's alpha was 0.94 for the full scale and ≥ 0.90 for the subscales, and ordinal alpha was 0.95 and ≥ 0.90, respectively. CFA showed that a two-factor model (inattention and hyperactivity/impulsivity) provided the best fit for the data. ADHD-RS-IV.es offered good discriminant ability to distinguish between patients with ADHD and controls (AUC=0.97). The two-factor structure of the Spanish-language version of the ADHD-RS-IV (ADHD-RS-IV.es) is consistent with those of the DSM-IV-TR and DSM-5 as well as with the model proposed by the author of the original scale. Furthermore, it has good discriminant ability. ADHD-RS-IV.es is therefore a valid and reliable tool for determining presence and severity of ADHD symptoms in the Spanish population. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Development and validation of Prediction models for Risks of complications in Early-onset Pre-eclampsia (PREP): a prospective cohort study.

PubMed

Thangaratinam, Shakila; Allotey, John; Marlin, Nadine; Mol, Ben W; Von Dadelszen, Peter; Ganzevoort, Wessel; Akkermans, Joost; Ahmed, Asif; Daniels, Jane; Deeks, Jon; Ismail, Khaled; Barnard, Ann Marie; Dodds, Julie; Kerry, Sally; Moons, Carl; Riley, Richard D; Khan, Khalid S

2017-04-01

The prognosis of early-onset pre-eclampsia (before 34 weeks' gestation) is variable. Accurate prediction of complications is required to plan appropriate management in high-risk women. To develop and validate prediction models for outcomes in early-onset pre-eclampsia. Prospective cohort for model development, with validation in two external data sets. Model development: 53 obstetric units in the UK. Model transportability: PIERS (Pre-eclampsia Integrated Estimate of RiSk for mothers) and PETRA (Pre-Eclampsia TRial Amsterdam) studies. Pregnant women with early-onset pre-eclampsia. Nine hundred and forty-six women in the model development data set and 850 women (634 in PIERS, 216 in PETRA) in the transportability (external validation) data sets. The predictors were identified from systematic reviews of tests to predict complications in pre-eclampsia and were prioritised by Delphi survey. The primary outcome was the composite of adverse maternal outcomes established using Delphi surveys. The secondary outcome was the composite of fetal and neonatal complications. We developed two prediction models: a logistic regression model (PREP-L) to assess the overall risk of any maternal outcome until postnatal discharge and a survival analysis model (PREP-S) to obtain individual risk estimates at daily intervals from diagnosis until 34 weeks. Shrinkage was used to adjust for overoptimism of predictor effects. For internal validation (of the full models in the development data) and external validation (of the reduced models in the transportability data), we computed the ability of the models to discriminate between those with and without poor outcomes ( c -statistic), and the agreement between predicted and observed risk (calibration slope). The PREP-L model included maternal age, gestational age at diagnosis, medical history, systolic blood pressure, urine protein-to-creatinine ratio, platelet count, serum urea concentration, oxygen saturation, baseline treatment with antihypertensive drugs and administration of magnesium sulphate. The PREP-S model additionally included exaggerated tendon reflexes and serum alanine aminotransaminase and creatinine concentration. Both models showed good discrimination for maternal complications, with anoptimism-adjusted c -statistic of 0.82 [95% confidence interval (CI) 0.80 to 0.84] for PREP-L and 0.75 (95% CI 0.73 to 0.78) for the PREP-S model in the internal validation. External validation of the reduced PREP-L model showed good performance with a c -statistic of 0.81 (95% CI 0.77 to 0.85) in PIERS and 0.75 (95% CI 0.64 to 0.86) in PETRA cohorts for maternal complications, and calibrated well with slopes of 0.93 (95% CI 0.72 to 1.10) and 0.90 (95% CI 0.48 to 1.32), respectively. In the PIERS data set, the reduced PREP-S model had a c -statistic of 0.71 (95% CI 0.67 to 0.75) and a calibration slope of 0.67 (95% CI 0.56 to 0.79). Low gestational age at diagnosis, high urine protein-to-creatinine ratio, increased serum urea concentration, treatment with antihypertensive drugs, magnesium sulphate, abnormal uterine artery Doppler scan findings and estimated fetal weight below the 10th centile were associated with fetal complications. The PREP-L model provided individualised risk estimates in early-onset pre-eclampsia to plan management of high- or low-risk individuals. The PREP-S model has the potential to be used as a triage tool for risk assessment. The impacts of the model use on outcomes need further evaluation. Current Controlled Trials ISRCTN40384046. The National Institute for Health Research Health Technology Assessment programme.

Predicting plant uptake of cadmium: validated with long-term contaminated soils.

PubMed

Lamb, Dane T; Kader, Mohammed; Ming, Hui; Wang, Liang; Abbasi, Sedigheh; Megharaj, Mallavarapu; Naidu, Ravi

2016-10-01

Cadmium accumulates in plant tissues at low soil loadings and is a concern for human health. Yet at higher levels it is also of concern for ecological receptors. We determined Cd partitioning constants for 41 soils to examine the role of soil properties controlling Cd partitioning and plant uptake. From a series of sorption and dose response studies, transfer functions were developed for predicting Cd uptake in Cucumis sativa L. (cucumber). The parameter log K f was predicted with soil pH ca , logCEC and log OC. Transfer of soil pore-water Cd 2+ to shoots was described with a power function (R 2  = 0.73). The dataset was validated with 13 long-term contaminated soils (plus 2 control soils) ranging in Cd concentration from 0.2 to 300 mg kg -1 . The series of equations predicting Cd shoot from pore-water Cd 2+ were able to predict the measured data in the independent dataset (root mean square error = 2.2). The good relationship indicated that Cd uptake to cucumber shoots could be predicted with Cd pore and Cd 2+ without other pore-water parameters such as pH or Ca 2+ . The approach may be adapted to a range of plant species.

Nomogram Prediction of Overall Survival After Curative Irradiation for Uterine Cervical Cancer

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

Seo, YoungSeok; Yoo, Seong Yul; Kim, Mi-Sook

Purpose: The purpose of this study was to develop a nomogram capable of predicting the probability of 5-year survival after radical radiotherapy (RT) without chemotherapy for uterine cervical cancer. Methods and Materials: We retrospectively analyzed 549 patients that underwent radical RT for uterine cervical cancer between March 1994 and April 2002 at our institution. Multivariate analysis using Cox proportional hazards regression was performed and this Cox model was used as the basis for the devised nomogram. The model was internally validated for discrimination and calibration by bootstrap resampling. Results: By multivariate regression analysis, the model showed that age, hemoglobin levelmore » before RT, Federation Internationale de Gynecologie Obstetrique (FIGO) stage, maximal tumor diameter, lymph node status, and RT dose at Point A significantly predicted overall survival. The survival prediction model demonstrated good calibration and discrimination. The bootstrap-corrected concordance index was 0.67. The predictive ability of the nomogram proved to be superior to FIGO stage (p = 0.01). Conclusions: The devised nomogram offers a significantly better level of discrimination than the FIGO staging system. In particular, it improves predictions of survival probability and could be useful for counseling patients, choosing treatment modalities and schedules, and designing clinical trials. However, before this nomogram is used clinically, it should be externally validated.« less

How to quantify exposure to traumatic stress? Reliability and predictive validity of measures for cumulative trauma exposure in a post-conflict population.

PubMed

Wilker, Sarah; Pfeiffer, Anett; Kolassa, Stephan; Koslowski, Daniela; Elbert, Thomas; Kolassa, Iris-Tatjana

2015-01-01

While studies with survivors of single traumatic experiences highlight individual response variation following trauma, research from conflict regions shows that almost everyone develops posttraumatic stress disorder (PTSD) if trauma exposure reaches extreme levels. Therefore, evaluating the effects of cumulative trauma exposure is of utmost importance in studies investigating risk factors for PTSD. Yet, little research has been devoted to evaluate how this important environmental risk factor can be best quantified. We investigated the retest reliability and predictive validity of different trauma measures in a sample of 227 Ugandan rebel war survivors. Trauma exposure was modeled as the number of traumatic event types experienced or as a score considering traumatic event frequencies. In addition, we investigated whether age at trauma exposure can be reliably measured and improves PTSD risk prediction. All trauma measures showed good reliability. While prediction of lifetime PTSD was most accurate from the number of different traumatic event types experienced, inclusion of event frequencies slightly improved the prediction of current PTSD. As assessing the number of traumatic events experienced is the least stressful and time-consuming assessment and leads to the best prediction of lifetime PTSD, we recommend this measure for research on PTSD etiology.

A quantitative property-property relationship for the internal diffusion coefficients of organic compounds in solid materials.

PubMed

Huang, L; Fantke, P; Ernstoff, A; Jolliet, O

2017-11-01

Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32 consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R 2 of .93). The internal validations showed the model to be robust, stable and not a result of chance correlation. The external validation against two separate prediction datasets demonstrated the model has good predicting ability within its applicability domain (Rext2>.8), namely MW between 30 and 1178 g/mol and temperature between 4 and 180°C. By covering a much wider range of organic chemicals and materials, this QPPR facilitates high-throughput estimates of human exposures for chemicals encapsulated in solid materials. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Assessment of heart rate, acidosis, consciousness, oxygenation, and respiratory rate to predict noninvasive ventilation failure in hypoxemic patients.

PubMed

Duan, Jun; Han, Xiaoli; Bai, Linfu; Zhou, Lintong; Huang, Shicong

2017-02-01

To develop and validate a scale using variables easily obtained at the bedside for prediction of failure of noninvasive ventilation (NIV) in hypoxemic patients. The test cohort comprised 449 patients with hypoxemia who were receiving NIV. This cohort was used to develop a scale that considers heart rate, acidosis, consciousness, oxygenation, and respiratory rate (referred to as the HACOR scale) to predict NIV failure, defined as need for intubation after NIV intervention. The highest possible score was 25 points. To validate the scale, a separate group of 358 hypoxemic patients were enrolled in the validation cohort. The failure rate of NIV was 47.8 and 39.4% in the test and validation cohorts, respectively. In the test cohort, patients with NIV failure had higher HACOR scores at initiation and after 1, 12, 24, and 48 h of NIV than those with successful NIV. At 1 h of NIV the area under the receiver operating characteristic curve was 0.88, showing good predictive power for NIV failure. Using 5 points as the cutoff value, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy for NIV failure were 72.6, 90.2, 87.2, 78.1, and 81.8%, respectively. These results were confirmed in the validation cohort. Moreover, the diagnostic accuracy for NIV failure exceeded 80% in subgroups classified by diagnosis, age, or disease severity and also at 1, 12, 24, and 48 h of NIV. Among patients with NIV failure with a HACOR score of >5 at 1 h of NIV, hospital mortality was lower in those who received intubation at ≤12 h of NIV than in those intubated later [58/88 (66%) vs. 138/175 (79%); p = 0.03). The HACOR scale variables are easily obtained at the bedside. The scale appears to be an effective way of predicting NIV failure in hypoxemic patients. Early intubation in high-risk patients may reduce hospital mortality.

Performance of PRISM III and PELOD-2 scores in a pediatric intensive care unit.

PubMed

Gonçalves, Jean-Pierre; Severo, Milton; Rocha, Carla; Jardim, Joana; Mota, Teresa; Ribeiro, Augusto

2015-10-01

The study aims were to compare two models (The Pediatric Risk of Mortality III (PRISM III) and Pediatric Logistic Organ Dysfunction (PELOD-2)) for prediction of mortality in a pediatric intensive care unit (PICU) and recalibrate PELOD-2 in a Portuguese population. To achieve the previous goal, a prospective cohort study to evaluate score performance (standardized mortality ratio, discrimination, and calibration) for both models was performed. A total of 556 patients consecutively admitted to our PICU between January 2011 and December 2012 were included in the analysis. The median age was 65 months, with an interquartile range of 1 month to 17 years. The male-to-female ratio was 1.5. The median length of PICU stay was 3 days. The overall predicted number of deaths using PRISM III score was 30.8 patients whereas that by PELOD-2 was 22.1 patients. The observed mortality was 29 patients. The area under the receiver operating characteristics curve for the two models was 0.92 and 0.94, respectively. The Hosmer and Lemeshow goodness-of-fit test showed a good calibration only for PRISM III (PRISM III: χ (2) = 3.820, p = 0.282; PELOD-2: χ (2) = 9.576, p = 0.022). Both scores had good discrimination. PELOD-2 needs recalibration to be a better reliable prediction tool. • PRISM III (Pediatric Risk of Mortality III) and PELOD (Pediatric Logistic Organ Dysfunction) scores are frequently used to assess the performance of intensive care units and also for mortality prediction in the pediatric population. • Pediatric Logistic Organ Dysfunction 2 is the newer version of PELOD and has recently been validated with good discrimination and calibration. What is New: • In our population, both scores had good discrimination. • PELOD-2 needs recalibration to be a better reliable prediction tool.

Derivation and external validation of a case mix model for the standardized reporting of 30-day stroke mortality rates.

PubMed

Bray, Benjamin D; Campbell, James; Cloud, Geoffrey C; Hoffman, Alex; James, Martin; Tyrrell, Pippa J; Wolfe, Charles D A; Rudd, Anthony G

2014-11-01

Case mix adjustment is required to allow valid comparison of outcomes across care providers. However, there is a lack of externally validated models suitable for use in unselected stroke admissions. We therefore aimed to develop and externally validate prediction models to enable comparison of 30-day post-stroke mortality outcomes using routine clinical data. Models were derived (n=9000 patients) and internally validated (n=18 169 patients) using data from the Sentinel Stroke National Audit Program, the national register of acute stroke in England and Wales. External validation (n=1470 patients) was performed in the South London Stroke Register, a population-based longitudinal study. Models were fitted using general estimating equations. Discrimination and calibration were assessed using receiver operating characteristic curve analysis and correlation plots. Two final models were derived. Model A included age (<60, 60-69, 70-79, 80-89, and ≥90 years), National Institutes of Health Stroke Severity Score (NIHSS) on admission, presence of atrial fibrillation on admission, and stroke type (ischemic versus primary intracerebral hemorrhage). Model B was similar but included only the consciousness component of the NIHSS in place of the full NIHSS. Both models showed excellent discrimination and calibration in internal and external validation. The c-statistics in external validation were 0.87 (95% confidence interval, 0.84-0.89) and 0.86 (95% confidence interval, 0.83-0.89) for models A and B, respectively. We have derived and externally validated 2 models to predict mortality in unselected patients with acute stroke using commonly collected clinical variables. In settings where the ability to record the full NIHSS on admission is limited, the level of consciousness component of the NIHSS provides a good approximation of the full NIHSS for mortality prediction. © 2014 American Heart Association, Inc.

Development and validation of the Dimensional Anhedonia Rating Scale (DARS) in a community sample and individuals with major depression.

PubMed

Rizvi, Sakina J; Quilty, Lena C; Sproule, Beth A; Cyriac, Anna; Michael Bagby, R; Kennedy, Sidney H

2015-09-30

Anhedonia, a core symptom of Major Depressive Disorder (MDD), is predictive of antidepressant non-response. In contrast to the definition of anhedonia as a "loss of pleasure", neuropsychological studies provide evidence for multiple facets of hedonic function. The aim of the current study was to develop and validate the Dimensional Anhedonia Rating Scale (DARS), a dynamic scale that measures desire, motivation, effort and consummatory pleasure across hedonic domains. Following item selection procedures and reliability testing using data from community participants (N=229) (Study 1), the 17-item scale was validated in an online study with community participants (N=150) (Study 2). The DARS was also validated in unipolar or bipolar depressed patients (n=52) and controls (n=50) (Study 3). Principal components analysis of the 17-item DARS revealed a 4-component structure mapping onto the domains of anhedonia: hobbies, food/drink, social activities, and sensory experience. Reliability of the DARS subscales was high across studies (Cronbach's α=0.75-0.92). The DARS also demonstrated good convergent and divergent validity. Hierarchical regression analysis revealed the DARS showed additional utility over the Snaith-Hamilton Pleasure Scale (SHAPS) in predicting reward function and distinguishing MDD subgroups. These studies provide support for the reliability and validity of the DARS. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2016-11-01

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

Reliability and validity of the parent efficacy for child healthy weight behaviour (PECHWB) scale.

PubMed

Palmer, F; Davis, M C

2014-05-01

Interventions for childhood overweight and obesity that target parents as the agents of change by increasing parent self-efficacy for facilitating their child's healthy weight behaviours require a reliable and valid tool to measure parent self-efficacy before and after interventions. Nelson and Davis developed the Parent Efficacy for Child Healthy Weight Behaviour (PECHWB) scale with good preliminary evidence of reliability and validity. The aim of this research was to provide further psychometric evidence from an independent Australian sample. Data were provided by a convenience sample of 261 primary caregivers of children aged 4-17 years via an online survey. PECHWB scores were correlated with scores on other self-report measures of parenting efficacy and 2- to 4-week test-retest reliability of the PECHWB was assessed. The results of the study confirmed the four-factor structure of the PECHWB (Fat and Sugar, Sedentary Behaviours, Physical Activity, and Fruit and Vegetables) and provided strong evidence of internal consistency and test-retest reliability, as well as good evidence of convergent validity. Future research should investigate the properties of the PECHWB in a sample of parents of overweight or obese children, including measures of child weight and actual child healthy weight behaviours to provide evidence of the concurrent and predictive validity of PECHWB scores. © 2013 John Wiley & Sons Ltd.

Identifying and classifying hyperostosis frontalis interna via computerized tomography.

PubMed

May, Hila; Peled, Nathan; Dar, Gali; Hay, Ori; Abbas, Janan; Masharawi, Youssef; Hershkovitz, Israel

2010-12-01

The aim of this study was to recognize the radiological characteristics of hyperostosis frontalis interna (HFI) and to establish a valid and reliable method for its identification and classification. A reliability test was carried out on 27 individuals who had undergone a head computerized tomography (CT) scan. Intra-observer reliability was obtained by examining the images three times, by the same researcher, with a 2-week interval between each sample ranking. The inter-observer test was performed by three independent researchers. A validity test was carried out using two methods for identifying and classifying HFI: 46 cadaver skullcaps were ranked twice via computerized tomography scans and then by direct observation. Reliability and validity were calculated using Kappa test (SPSS 15.0). Reliability tests of ranking HFI via CT scans demonstrated good results (K > 0.7). As for validity, a very good consensus was obtained between the CT and direct observation, when moderate and advanced types of HFI were present (K = 0.82). The suggested classification method for HFI, using CT, demonstrated a sensitivity of 84%, specificity of 90.5%, and positive predictive value of 91.3%. In conclusion, volume rendering is a reliable and valid tool for identifying HFI. The suggested three-scale classification is most suitable for radiological diagnosis of the phenomena. Considering the increasing awareness of HFI as an early indicator of a developing malady, this study may assist radiologists in identifying and classifying the phenomena.

The Dutch motor skills assessment as tool for talent development in table tennis: a reproducibility and validity study.

PubMed

Faber, Irene R; Nijhuis-Van Der Sanden, Maria W G; Elferink-Gemser, Marije T; Oosterveld, Frits G J

2015-01-01

A motor skills assessment could be helpful in talent development by estimating essential perceptuo-motor skills of young players, which are considered requisite to develop excellent technical and tactical qualities. The Netherlands Table Tennis Association uses a motor skills assessment in their talent development programme consisting of eight items measuring perceptuo-motor skills specific to table tennis under varying conditions. This study aimed to investigate this assessment regarding its reproducibility, internal consistency, underlying dimensions and concurrent validity in 113 young table tennis players (6-10 years). Intraclass correlation coefficients of six test items met the criteria of 0.7 with coefficients of variation between 3% and 8%. Cronbach's alpha valued 0.853 for internal consistency. The principal components analysis distinguished two conceptually meaningful factors: "ball control" and "gross motor function." Concurrent validity analyses demonstrated moderate associations between the motor skills assessment's results and national ranking; boys r = -0.53 (P < 0.001) and girls r = -0.45 (P = 0.015). In conclusion, this evaluation demonstrated six test items with acceptable reproducibility, good internal consistency and good prospects for validity. Two test items need revision to upgrade reproducibility. Since the motor skills assessment seems to be a reproducible, objective part of a talent development programme, more longitudinal studies are required to investigate its predictive validity.

Validity of the stroke rehabilitation assessment of movement scale in acute rehabilitation: a comparison with the functional independence measure and stroke impact scale-16.

PubMed

Ward, Irene; Pivko, Susan; Brooks, Gary; Parkin, Kate

2011-11-01

To demonstrate sensitivity to change of the Stroke Rehabilitation Assessment of Movement (STREAM) as well as the concurrent and predictive validity of the STREAM in an acute rehabilitation setting. Prospective cohort study. Acute, in-patient rehabilitation department within a tertiary-care teaching hospital in the United States. Thirty adults with a newly diagnosed, first ischemic stroke. Clinical assessments were conducted on admission and then again on discharge from the rehabilitation hospital with the STREAM (total STREAM and upper extremity, lower extremity, and mobility subscales), Functional Independence Measure (FIM), and Stroke Impact Scale-16 (SIS-16). Sensitivity to change was determined with the Wilcoxon signed rank test and by the calculation of standardized response means. Spearman correlations were used to assess concurrent validity of the total STREAM and STREAM subscales with the FIM and SIS-16 on admission and discharge. We determined predictive validity for all instruments by correlating admission scores with actual and predicted length of stay and by testing associations between admission scores and discharge destination (home vs subacute facility). Not applicable. For all instruments, there was statistically significant improvement from admission to discharge. The standardized response means for the total STREAM and STREAM subscales were large. Spearman correlations between the total STREAM and STREAM subscales and the FIM and SIS-16 were moderate to excellent, both on admission and discharge. Among change scores, only the SIS-16 correlated with the total STREAM. All 3 instruments were significantly associated with discharge destination; however, the associations were strongest for the total STREAM and STREAM subscales. All instruments showed moderate-to-excellent correlations with predicted and actual length of stay. The STREAM is sensitive to change and demonstrates good concurrent and predictive validity as compared with the FIM and SIS-16 in the acute inpatient rehabilitation population. Copyright © 2011 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.

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

Developing a Suitable Model for Water Uptake for Biodegradable Polymers Using Small Training Sets.

PubMed

Valenzuela, Loreto M; Knight, Doyle D; Kohn, Joachim

2016-01-01

Prediction of the dynamic properties of water uptake across polymer libraries can accelerate polymer selection for a specific application. We first built semiempirical models using Artificial Neural Networks and all water uptake data, as individual input. These models give very good correlations (R (2) > 0.78 for test set) but very low accuracy on cross-validation sets (less than 19% of experimental points within experimental error). Instead, using consolidated parameters like equilibrium water uptake a good model is obtained (R (2) = 0.78 for test set), with accurate predictions for 50% of tested polymers. The semiempirical model was applied to the 56-polymer library of L-tyrosine-derived polyarylates, identifying groups of polymers that are likely to satisfy design criteria for water uptake. This research demonstrates that a surrogate modeling effort can reduce the number of polymers that must be synthesized and characterized to identify an appropriate polymer that meets certain performance criteria.

Assessing Anxiety in Youth with the Multidimensional Anxiety Scale for Children (MASC)

PubMed Central

Wei, Chiaying; Hoff, Alexandra; Villabø, Marianne A.; Peterman, Jeremy; Kendall, Philip C.; Piacentini, John; McCracken, James; Walkup, John T.; Albano, Anne Marie; Rynn, Moira; Sherrill, Joel; Sakolsky, Dara; Birmaher, Boris; Ginsburg, Golda; Keaton, Courtney; Gosch, Elizabeth; Compton, Scott N.; March, John

2013-01-01

The present study examined the psychometric properties, including discriminant validity and clinical utility, of the youth self-report and parent-report forms of the Multidimensional Anxiety Scale for Children (MASC) among youth with anxiety disorders. The sample included parents and youth (N= 488, 49.6% male) ages 7 – 17 who participated in the Child/Adolescent Anxiety Multimodal Study (CAMS). Although the typical low agreement between parent and youth self-reports was found, the MASC evidenced good internal reliability across MASC subscales and informants. The main MASC subscales (i.e., Physical Symptoms, Harm Avoidance, Social Anxiety, and Separation/Panic) were examined. The Social Anxiety and Separation/Panic subscales were found to be significantly predictive of the presence and severity of social phobia and separation anxiety disorder, respectively. Using multiple informants improved the accuracy of prediction. The MASC subscales demonstrated good psychometric properties and clinical utilities in identifying youth with anxiety disorders. PMID:23845036

Reliability and validity of the assessment of neurological soft-signs in children with and without attention-deficit-hyperactivity disorder.

PubMed

Gustafsson, Peik; Svedin, Carl Göran; Ericsson, Ingegerd; Lindén, Christian; Karlsson, Magnus K; Thernlund, Gunilla

2010-04-01

To study the value and reliability of an examination of neurological soft-signs, often used in Sweden, in the assessment of children with attention-deficit-hyperactivity disorder (ADHD), by examining children with and without ADHD, as diagnosed by an experienced clinician using the DSM-III-R. We have examined interrater reliability (26 males, nine females; age range 5y 6mo-11y), internal consistency (94 males, 43 females; age range 5y 6mo-11y), test-retest reliability (12 males, eight females; age range 6-9y), and validity (79 males, 33 females; age range 5y 6mo-9y). The sum of the scores for the items on the examination had good interrater reliability (intraclass correlation [ICC] 0.95) and acceptable internal consistency (Cronbach's alpha 0.76). The test-retest study also showed good reliability (ICC 0.91). There were modest associations between the examination and the assessment of motor function made by the physical education teacher (ICC 0.37) as well as from the parents' description (ICC 0.39). The examination of neurological soft-signs had a sensitivity of 0.80 and a specificity of 0.76 in predicting motor problems as evaluated by the physical education teacher. The reliability and validity of this examination seem to be good and can be recommended for clinical practice and research.

Reliability and validity of current physical examination techniques of the foot and ankle.

PubMed

Wrobel, James S; Armstrong, David G

2008-01-01

This literature review was undertaken to evaluate the reliability and validity of the orthopedic, neurologic, and vascular examination of the foot and ankle. We searched PubMed-the US National Library of Medicine's database of biomedical citations-and abstracts for relevant publications from 1966 to 2006. We also searched the bibliographies of the retrieved articles. We identified 35 articles to review. For discussion purposes, we used reliability interpretation guidelines proposed by others. For the kappa statistic that calculates reliability for dichotomous (eg, yes or no) measures, reliability was defined as moderate (0.4-0.6), substantial (0.6-0.8), and outstanding (> 0.8). For the intraclass correlation coefficient that calculates reliability for continuous (eg, degrees of motion) measures, reliability was defined as good (> 0.75), moderate (0.5-0.75), and poor (< 0.5). Intraclass correlations, based on the various examinations performed, varied widely. The range was from 0.08 to 0.98, depending on the examination performed. Concurrent and predictive validity ranged from poor to good. Although hundreds of articles exist describing various methods of lower-extremity assessment, few rigorously assess the measurement properties. This information can be used both by the discerning clinician in the art of clinical examination and by the scientist in the measurement properties of reproducibility and validity.

Three-dimensional localized coherent structures of surface turbulence: Model validation with experiments and further computations.

PubMed

Demekhin, E A; Kalaidin, E N; Kalliadasis, S; Vlaskin, S Yu

2010-09-01

We validate experimentally the Kapitsa-Shkadov model utilized in the theoretical studies by Demekhin [Phys. Fluids 19, 114103 (2007)10.1063/1.2793148; Phys. Fluids 19, 114104 (2007)]10.1063/1.2793149 of surface turbulence on a thin liquid film flowing down a vertical planar wall. For water at 15° , surface turbulence typically occurs at an inlet Reynolds number of ≃40 . Of particular interest is to assess experimentally the predictions of the model for three-dimensional nonlinear localized coherent structures, which represent elementary processes of surface turbulence. For this purpose we devise simple experiments to investigate the instabilities and transitions leading to such structures. Our experimental results are in good agreement with the theoretical predictions of the model. We also perform time-dependent computations for the formation of coherent structures and their interaction with localized structures of smaller amplitude on the surface of the film.

Classification of cardiac rhythm using heart rate dynamical measures: validation in MIT-BIH databases.

PubMed

Carrara, Marta; Carozzi, Luca; Moss, Travis J; de Pasquale, Marco; Cerutti, Sergio; Lake, Douglas E; Moorman, J Randall; Ferrario, Manuela

2015-01-01

Identification of atrial fibrillation (AF) is a clinical imperative. Heartbeat interval time series are increasingly available from personal monitors, allowing new opportunity for AF diagnosis. Previously, we devised numerical algorithms for identification of normal sinus rhythm (NSR), AF, and SR with frequent ectopy using dynamical measures of heart rate. Here, we wished to validate them in the canonical MIT-BIH ECG databases. We tested algorithms on the NSR, AF and arrhythmia databases. When the databases were combined, the positive predictive value of the new algorithms exceeded 95% for NSR and AF, and was 40% for SR with ectopy. Further, dynamical measures did not distinguish atrial from ventricular ectopy. Inspection of individual 24hour records showed good correlation of observed and predicted rhythms. Heart rate dynamical measures are effective ingredients in numerical algorithms to classify cardiac rhythm from the heartbeat intervals time series alone. Copyright © 2015 Elsevier Inc. All rights reserved.

A kinetic model of municipal sludge degradation during non-catalytic wet oxidation.

PubMed

Prince-Pike, Arrian; Wilson, David I; Baroutian, Saeid; Andrews, John; Gapes, Daniel J

2015-12-15

Wet oxidation is a successful process for the treatment of municipal sludge. In addition, the resulting effluent from wet oxidation is a useful carbon source for subsequent biological nutrient removal processes in wastewater treatment. Owing to limitations with current kinetic models, this study produced a kinetic model which predicts the concentrations of key intermediate components during wet oxidation. The model was regressed from lab-scale experiments and then subsequently validated using data from a wet oxidation pilot plant. The model was shown to be accurate in predicting the concentrations of each component, and produced good results when applied to a plant 500 times larger in size. A statistical study was undertaken to investigate the validity of the regressed model parameters. Finally the usefulness of the model was demonstrated by suggesting optimum operating conditions such that volatile fatty acids were maximised. Copyright © 2015 Elsevier Ltd. All rights reserved.

Validation of the solar heating and cooling high speed performance (HISPER) computer code

NASA Technical Reports Server (NTRS)

Wallace, D. B.

1980-01-01

Developed to give a quick and accurate predictions HISPER, a simplification of the TRNSYS program, achieves its computational speed by not simulating detailed system operations or performing detailed load computations. In order to validate the HISPER computer for air systems the simulation was compared to the actual performance of an operational test site. Solar insolation, ambient temperature, water usage rate, and water main temperatures from the data tapes for an office building in Huntsville, Alabama were used as input. The HISPER program was found to predict the heating loads and solar fraction of the loads with errors of less than ten percent. Good correlation was found on both a seasonal basis and a monthly basis. Several parameters (such as infiltration rate and the outside ambient temperature above which heating is not required) were found to require careful selection for accurate simulation.

Performance of the score systems Acute Physiology and Chronic Health Evaluation II and III at an interdisciplinary intensive care unit, after customization

PubMed Central

Markgraf, Rainer; Deutschinoff, Gerd; Pientka, Ludger; Scholten, Theo; Lorenz, Cristoph

2001-01-01

Background: Mortality predictions calculated using scoring scales are often not accurate in populations other than those in which the scales were developed because of differences in case-mix. The present study investigates the effect of first-level customization, using a logistic regression technique, on discrimination and calibration of the Acute Physiology and Chronic Health Evaluation (APACHE) II and III scales. Method: Probabilities of hospital death for patients were estimated by applying APACHE II and III and comparing these with observed outcomes. Using the split sample technique, a customized model to predict outcome was developed by logistic regression. The overall goodness-of-fit of the original and the customized models was assessed. Results: Of 3383 consecutive intensive care unit (ICU) admissions over 3 years, 2795 patients could be analyzed, and were split randomly into development and validation samples. The discriminative powers of APACHE II and III were unchanged by customization (areas under the receiver operating characteristic [ROC] curve 0.82 and 0.85, respectively). Hosmer-Lemeshow goodness-of-fit tests showed good calibration for APACHE II, but insufficient calibration for APACHE III. Customization improved calibration for both models, with a good fit for APACHE III as well. However, fit was different for various subgroups. Conclusions: The overall goodness-of-fit of APACHE III mortality prediction was improved significantly by customization, but uniformity of fit in different subgroups was not achieved. Therefore, application of the customized model provides no advantage, because differences in case-mix still limit comparisons of quality of care. PMID:11178223

Comparison of the predictive validity of diagnosis-based risk adjusters for clinical outcomes.

PubMed

Petersen, Laura A; Pietz, Kenneth; Woodard, LeChauncy D; Byrne, Margaret

2005-01-01

Many possible methods of risk adjustment exist, but there is a dearth of comparative data on their performance. We compared the predictive validity of 2 widely used methods (Diagnostic Cost Groups [DCGs] and Adjusted Clinical Groups [ACGs]) for 2 clinical outcomes using a large national sample of patients. We studied all patients who used Veterans Health Administration (VA) medical services in fiscal year (FY) 2001 (n = 3,069,168) and assigned both a DCG and an ACG to each. We used logistic regression analyses to compare predictive ability for death or long-term care (LTC) hospitalization for age/gender models, DCG models, and ACG models. We also assessed the effect of adding age to the DCG and ACG models. Patients in the highest DCG categories, indicating higher severity of illness, were more likely to die or to require LTC hospitalization. Surprisingly, the age/gender model predicted death slightly more accurately than the ACG model (c-statistic of 0.710 versus 0.700, respectively). The addition of age to the ACG model improved the c-statistic to 0.768. The highest c-statistic for prediction of death was obtained with a DCG/age model (0.830). The lowest c-statistics were obtained for age/gender models for LTC hospitalization (c-statistic 0.593). The c-statistic for use of ACGs to predict LTC hospitalization was 0.783, and improved to 0.792 with the addition of age. The c-statistics for use of DCGs and DCG/age to predict LTC hospitalization were 0.885 and 0.890, respectively, indicating the best prediction. We found that risk adjusters based upon diagnoses predicted an increased likelihood of death or LTC hospitalization, exhibiting good predictive validity. In this comparative analysis using VA data, DCG models were generally superior to ACG models in predicting clinical outcomes, although ACG model performance was enhanced by the addition of age.

Predictive Validation of an Influenza Spread Model

PubMed Central

Hyder, Ayaz; Buckeridge, David L.; Leung, Brian

2013-01-01

Background Modeling plays a critical role in mitigating impacts of seasonal influenza epidemics. Complex simulation models are currently at the forefront of evaluating optimal mitigation strategies at multiple scales and levels of organization. Given their evaluative role, these models remain limited in their ability to predict and forecast future epidemics leading some researchers and public-health practitioners to question their usefulness. The objective of this study is to evaluate the predictive ability of an existing complex simulation model of influenza spread. Methods and Findings We used extensive data on past epidemics to demonstrate the process of predictive validation. This involved generalizing an individual-based model for influenza spread and fitting it to laboratory-confirmed influenza infection data from a single observed epidemic (1998–1999). Next, we used the fitted model and modified two of its parameters based on data on real-world perturbations (vaccination coverage by age group and strain type). Simulating epidemics under these changes allowed us to estimate the deviation/error between the expected epidemic curve under perturbation and observed epidemics taking place from 1999 to 2006. Our model was able to forecast absolute intensity and epidemic peak week several weeks earlier with reasonable reliability and depended on the method of forecasting-static or dynamic. Conclusions Good predictive ability of influenza epidemics is critical for implementing mitigation strategies in an effective and timely manner. Through the process of predictive validation applied to a current complex simulation model of influenza spread, we provided users of the model (e.g. public-health officials and policy-makers) with quantitative metrics and practical recommendations on mitigating impacts of seasonal influenza epidemics. This methodology may be applied to other models of communicable infectious diseases to test and potentially improve their predictive ability. PMID:23755236

Assessment of Biopsychosocial Complexity and Health Care Needs: Measurement Properties of the INTERMED Self-Assessment Version.

PubMed

van Reedt Dortland, Arianne K B; Peters, Lilian L; Boenink, Annette D; Smit, Jan H; Slaets, Joris P J; Hoogendoorn, Adriaan W; Joos, Andreas; Latour, Corine H M; Stiefel, Friedrich; Burrus, Cyrille; Guitteny-Collas, Marie; Ferrari, Silvia

2017-05-01

The INTERMED Self-Assessment questionnaire (IMSA) was developed as an alternative to the observer-rated INTERMED (IM) to assess biopsychosocial complexity and health care needs. We studied feasibility, reliability, and validity of the IMSA within a large and heterogeneous international sample of adult hospital inpatients and outpatients as well as its predictive value for health care use (HCU) and quality of life (QoL). A total of 850 participants aged 17 to 90 years from five countries completed the IMSA and were evaluated with the IM. The following measurement properties were determined: feasibility by percentages of missing values; reliability by Cronbach α; interrater agreement by intraclass correlation coefficients; convergent validity of IMSA scores with mental health (Short Form 36 emotional well-being subscale and Hospital Anxiety and Depression Scale), medical health (Cumulative Illness Rating Scale) and QoL (Euroqol-5D) by Spearman rank correlations; and predictive validity of IMSA scores with HCU and QoL by (generalized) linear mixed models. Feasibility, face validity, and reliability (Cronbach α = 0.80) were satisfactory. Intraclass correlation coefficient between IMSA and IM total scores was .78 (95% CI = .75-.81). Correlations of the IMSA with the Short Form 36, Hospital Anxiety and Depression Scale, Cumulative Illness Rating Scale, and Euroqol-5D (convergent validity) were -.65, .15, .28, and -.59, respectively. The IMSA significantly predicted QoL and also HCU (emergency department visits, hospitalization, outpatient visits, and diagnostic examinations) after 3- and 6-month follow-up. Results were comparable between hospital sites, inpatients and outpatients, as well as age groups. The IMSA is a generic and time-efficient method to assess biopsychosocial complexity and to provide guidance for multidisciplinary care trajectories in adult patients, with good reliability and validity across different cultures.

Improved modeling of GaN HEMTs for predicting thermal and trapping-induced-kink effects

NASA Astrophysics Data System (ADS)

Jarndal, Anwar; Ghannouchi, Fadhel M.

2016-09-01

In this paper, an improved modeling approach has been developed and validated for GaN high electron mobility transistors (HEMTs). The proposed analytical model accurately simulates the drain current and its inherent trapping and thermal effects. Genetic-algorithm-based procedure is developed to automatically find the fitting parameters of the model. The developed modeling technique is implemented on a packaged GaN-on-Si HEMT and validated by DC and small-/large-signal RF measurements. The model is also employed for designing and realizing a switch-mode inverse class-F power amplifier. The amplifier simulations showed a very good agreement with RF large-signal measurements.

Design, Fabrication, and Validation of an Ultra-Lightweight Membrane Mirror (Conference Proceedings)

DTIC Science & Technology

2005-08-01

Membrane Mirror Active boundary control is very promising and studies predict good control over astigmatism and coma aberrations. However, the primary...design analysis. The mount has a split lenticular setup, allowing one canopy and many membrane mirrors that can be interchanged. The mount has a...spherical aberration, which is as expected. Results from finite element modeling showed that astigmatism can be corrected with the normal actuators

It's Selective, but Is It Effective? Exploring the Predictive Validity of Teacher Selection Tools. CEDR Brief. Policy Brief No. 2014-­9

ERIC Educational Resources Information Center

Goldhaber, Dan; Grout, Cyrus; Huntington-Klein, Nick

2014-01-01

Evidence suggests teacher hiring in public schools is ad-hoc and often does not result in good selection amongst applicants. Some districts use structured selection instruments in the hiring process, but we know little about the efficacy of such tools. In this paper we evaluate the ability of applicant selection tools used by the Spokane Public…

Prioritization of candidate disease genes by combining topological similarity and semantic similarity.

PubMed

Liu, Bin; Jin, Min; Zeng, Pan

2015-10-01

The identification of gene-phenotype relationships is very important for the treatment of human diseases. Studies have shown that genes causing the same or similar phenotypes tend to interact with each other in a protein-protein interaction (PPI) network. Thus, many identification methods based on the PPI network model have achieved good results. However, in the PPI network, some interactions between the proteins encoded by candidate gene and the proteins encoded by known disease genes are very weak. Therefore, some studies have combined the PPI network with other genomic information and reported good predictive performances. However, we believe that the results could be further improved. In this paper, we propose a new method that uses the semantic similarity between the candidate gene and known disease genes to set the initial probability vector of a random walk with a restart algorithm in a human PPI network. The effectiveness of our method was demonstrated by leave-one-out cross-validation, and the experimental results indicated that our method outperformed other methods. Additionally, our method can predict new causative genes of multifactor diseases, including Parkinson's disease, breast cancer and obesity. The top predictions were good and consistent with the findings in the literature, which further illustrates the effectiveness of our method. Copyright © 2015 Elsevier Inc. All rights reserved.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

NASA Astrophysics Data System (ADS)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-05-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

Statistical prediction of dynamic distortion of inlet flow using minimum dynamic measurement. An application to the Melick statistical method and inlet flow dynamic distortion prediction without RMS measurements

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Chen, Y. S.

1986-01-01

The Melick method of inlet flow dynamic distortion prediction by statistical means is outlined. A hypothetic vortex model is used as the basis for the mathematical formulations. The main variables are identified by matching the theoretical total pressure rms ratio with the measured total pressure rms ratio. Data comparisons, using the HiMAT inlet test data set, indicate satisfactory prediction of the dynamic peak distortion for cases with boundary layer control device vortex generators. A method for the dynamic probe selection was developed. Validity of the probe selection criteria is demonstrated by comparing the reduced-probe predictions with the 40-probe predictions. It is indicated that the the number of dynamic probes can be reduced to as few as two and still retain good accuracy.

Predictive modeling capabilities from incident powder and laser to mechanical properties for laser directed energy deposition

NASA Astrophysics Data System (ADS)

Shin, Yung C.; Bailey, Neil; Katinas, Christopher; Tan, Wenda

2018-01-01

This paper presents an overview of vertically integrated comprehensive predictive modeling capabilities for directed energy deposition processes, which have been developed at Purdue University. The overall predictive models consist of vertically integrated several modules, including powder flow model, molten pool model, microstructure prediction model and residual stress model, which can be used for predicting mechanical properties of additively manufactured parts by directed energy deposition processes with blown powder as well as other additive manufacturing processes. Critical governing equations of each model and how various modules are connected are illustrated. Various illustrative results along with corresponding experimental validation results are presented to illustrate the capabilities and fidelity of the models. The good correlations with experimental results prove the integrated models can be used to design the metal additive manufacturing processes and predict the resultant microstructure and mechanical properties.

SPR Hydrostatic Column Model Verification and Validation.

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

Bettin, Giorgia; Lord, David; Rudeen, David Keith

2015-10-01

A Hydrostatic Column Model (HCM) was developed to help differentiate between normal "tight" well behavior and small-leak behavior under nitrogen for testing the pressure integrity of crude oil storage wells at the U.S. Strategic Petroleum Reserve. This effort was motivated by steady, yet distinct, pressure behavior of a series of Big Hill caverns that have been placed under nitrogen for extended period of time. This report describes the HCM model, its functional requirements, the model structure and the verification and validation process. Different modes of operation are also described, which illustrate how the software can be used to model extendedmore » nitrogen monitoring and Mechanical Integrity Tests by predicting wellhead pressures along with nitrogen interface movements. Model verification has shown that the program runs correctly and it is implemented as intended. The cavern BH101 long term nitrogen test was used to validate the model which showed very good agreement with measured data. This supports the claim that the model is, in fact, capturing the relevant physical phenomena and can be used to make accurate predictions of both wellhead pressure and interface movements.« less

Dyadic Short Forms of the Wechsler Adult Intelligence Scale-IV.

PubMed

Denney, David A; Ringe, Wendy K; Lacritz, Laura H

2015-08-01

Full Wechsler Adult Intelligence Scale-Fourth Edition (WAIS-IV) administration can be time-consuming and may not be necessary when intelligence quotient estimates will suffice. Estimated Full Scale Intelligence Quotient (FSIQ) and General Ability Index (GAI) scores were derived from nine dyadic short forms using individual regression equations based on data from a clinical sample (n = 113) that was then cross validated in a separate clinical sample (n = 50). Derived scores accounted for 70%-83% of the variance in FSIQ and 77%-88% of the variance in GAI. Predicted FSIQs were strongly associated with actual FSIQ (rs = .73-.88), as were predicted and actual GAIs (rs = .80-.93). Each of the nine dyadic short forms of the WAIS-IV was a good predictor of FSIQ and GAI in the validation sample. These data support the validity of WAIS-IV short forms when time is limited or lengthier batteries cannot be tolerated by patients. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

When Significant Others Suffer: German Validation of the Burden Assessment Scale (BAS)

PubMed Central

Hunger, Christina; Krause, Lena; Hilzinger, Rebecca; Ditzen, Beate; Schweitzer, Jochen

2016-01-01

There is a need of an economical, reliable, and valid instrument in the German-speaking countries to measure the burden of relatives who care for mentally ill persons. We translated the Burden Assessment Scale (BAS) and conducted a study investigating factor structure, psychometric quality and predictive validity. We used confirmative factor analyses (CFA, maximum-likelihood method) to examine the dimensionality of the German BAS in a sample of 215 relatives (72% women; M = 32 years, SD = 14, range: 18 to 77; 39% employed) of mentally ill persons (50% (ex-)partner or (best) friend; M = 32 years, SD = 13, range 8 to 64; main complaints were depression and/or anxiety). Cronbach’s α determined the internal consistency. We examined predictive validity using regression analyses including the BAS and validated scales of social systems functioning (Experience In Social Systems Questionnaire, EXIS.pers, EXIS.org) and psychopathology (Brief Symptom Inventory, BSI). Variables that might have influenced the dependent variables (e.g. age, gender, education, employment and civil status) were controlled by their introduction in the first step, and the BAS in the second step of the regression analyses. A model with four correlated factors (Disrupted Activities, Personal Distress, Time Perspective, Guilt) showed the best fit. With respect to the number of items included, the internal consistency was very good. The modified German BAS predicted relatives’ social systems functioning and psychopathology. The economical design makes the 19-item BAS promising for practice-oriented research, and for studies under time constraints. Strength, limitations and future directions are discussed. PMID:27764109

Thyroid-specific questions on work ability showed known-groups validity among Danes with thyroid diseases.

PubMed

Nexo, Mette Andersen; Watt, Torquil; Bonnema, Steen Joop; Hegedüs, Laszlo; Rasmussen, Åse Krogh; Feldt-Rasmussen, Ulla; Bjorner, Jakob Bue

2015-07-01

We aimed to identify the best approach to work ability assessment in patients with thyroid disease by evaluating the factor structure, measurement equivalence, known-groups validity, and predictive validity of a broad set of work ability items. Based on the literature and interviews with thyroid patients, 24 work ability items were selected from previous questionnaires, revised, or developed anew. Items were tested among 632 patients with thyroid disease (non-toxic goiter, toxic nodular goiter, Graves' disease (with or without orbitopathy), autoimmune hypothyroidism, and other thyroid diseases), 391 of which had participated in a study 5 years previously. Responses to select items were compared to general population data. We used confirmatory factor analyses for categorical data, logistic regression analyses and tests of differential item function, and head-to-head comparisons of relative validity in distinguishing known groups. Although all work ability items loaded on a common factor, the optimal factor solution included five factors: role physical, role emotional, thyroid-specific limitations, work limitations (without disease attribution), and work performance. The scale on thyroid-specific limitations showed the most power in distinguishing clinical groups and time since diagnosis. A global single item proved useful for comparisons with the general population, and a thyroid-specific item predicted labor market exclusion within the next 5 years (OR 5.0, 95 % CI 2.7-9.1). Items on work limitations with attribution to thyroid disease were most effective in detecting impact on work ability and showed good predictive validity. Generic work ability items remain useful for general population comparisons.

External validation of the MRI-DRAGON score: early prediction of stroke outcome after intravenous thrombolysis.

PubMed

Turc, Guillaume; Aguettaz, Pierre; Ponchelle-Dequatre, Nelly; Hénon, Hilde; Naggara, Olivier; Leclerc, Xavier; Cordonnier, Charlotte; Leys, Didier; Mas, Jean-Louis; Oppenheim, Catherine

2014-01-01

The aim of our study was to validate in an independent cohort the MRI-DRAGON score, an adaptation of the (CT-) DRAGON score to predict 3-month outcome in acute ischemic stroke patients undergoing MRI before intravenous thrombolysis (IV-tPA). We reviewed consecutive (2009-2013) anterior circulation stroke patients treated within 4.5 hours by IV-tPA in the Lille stroke unit (France), where MRI is the first-line pretherapeutic work-up. We assessed the discrimination and calibration of the MRI-DRAGON score to predict poor 3-month outcome, defined as modified Rankin Score >2, using c-statistic and the Hosmer-Lemeshow test, respectively. We included 230 patients (mean ±SD age 70.4±16.0 years, median [IQR] baseline NIHSS 8 [5]-[14]; poor outcome in 78(34%) patients). The c-statistic was 0.81 (95%CI 0.75-0.87), and the Hosmer-Lemeshow test was not significant (p = 0.54). The MRI-DRAGON score showed good prognostic performance in the external validation cohort. It could therefore be used to inform the patient's relatives about long-term prognosis and help to identify poor responders to IV-tPA alone, who may be candidates for additional therapeutic strategies, if they are otherwise eligible for such procedures based on the institutional criteria.

Validation of the post-delivery perceived stress inventory.

PubMed

Razurel, Chantal; Kaiser, Barbara; Dupuis, Marc; Antonietti, Jean-Philippe; Sellenet, Catherine; Epiney, Manuela

2014-01-01

This article presents the post-delivery perceived stress inventory (PDPSI) and its psychometric properties. This inventory is unique in that it links the measurement of perceived stress to events experienced during and after delivery. A total of 235 French-speaking, primiparous mothers completed the PDPSI two days after their delivery. To evaluate the predictive validity of the PDPSI on anxiety and depression, participants also completed the EPDS and the STAI two days and six weeks postpartum. The exploratory analysis revealed a 16-item structure divided into five factors: F1: relationship with the child; F2: delivery; F3: fatigue after delivery; F4: breastfeeding; and F5: relationship with the caregivers. The PDPSI demonstrated good internal consistency. Moreover, confirmatory factor analysis produced excellent indices, indicating that the complexity of the PDPSI was taken into account and its fit to the sample. The discriminant analysis showed that the PDPSI was not sensitive to specific changes in the sample making the inventory generalizable to other populations. Predictive validity showed that the scale significantly predicted depression and anxiety in the early postpartum period as well as anxiety six weeks postpartum. Overall, the PDPSI showed excellent psychometric qualities, making it a useful tool for future research-evaluating interventions related to perceived stress during the postpartum period.

The validation of pharmacogenetics for the identification of Fabry patients to be treated with migalastat.

PubMed

Benjamin, Elfrida R; Della Valle, Maria Cecilia; Wu, Xiaoyang; Katz, Evan; Pruthi, Farhana; Bond, Sarah; Bronfin, Benjamin; Williams, Hadis; Yu, Julie; Bichet, Daniel G; Germain, Dominique P; Giugliani, Roberto; Hughes, Derralynn; Schiffmann, Raphael; Wilcox, William R; Desnick, Robert J; Kirk, John; Barth, Jay; Barlow, Carrolee; Valenzano, Kenneth J; Castelli, Jeff; Lockhart, David J

2017-04-01

Fabry disease is an X-linked lysosomal storage disorder caused by mutations in the α-galactosidase A gene. Migalastat, a pharmacological chaperone, binds to specific mutant forms of α-galactosidase A to restore lysosomal activity. A pharmacogenetic assay was used to identify the α-galactosidase A mutant forms amenable to migalastat. Six hundred Fabry disease-causing mutations were expressed in HEK-293 (HEK) cells; increases in α-galactosidase A activity were measured by a good laboratory practice (GLP)-validated assay (GLP HEK/Migalastat Amenability Assay). The predictive value of the assay was assessed based on pharmacodynamic responses to migalastat in phase II and III clinical studies. Comparison of the GLP HEK assay results in in vivo white blood cell α-galactosidase A responses to migalastat in male patients showed high sensitivity, specificity, and positive and negative predictive values (≥0.875). GLP HEK assay results were also predictive of decreases in kidney globotriaosylceramide in males and plasma globotriaosylsphingosine in males and females. The clinical study subset of amenable mutations (n = 51) was representative of all 268 amenable mutations identified by the GLP HEK assay. The GLP HEK assay is a clinically validated method of identifying male and female Fabry patients for treatment with migalastat.Genet Med 19 4, 430-438.

Predicting arsenic concentrations in groundwater of San Luis Valley, Colorado: implications for individual-level lifetime exposure assessment.

PubMed

James, Katherine A; Meliker, Jaymie R; Buttenfield, Barbara E; Byers, Tim; Zerbe, Gary O; Hokanson, John E; Marshall, Julie A

2014-08-01

Consumption of inorganic arsenic in drinking water at high levels has been associated with chronic diseases. Risk is less clear at lower levels of arsenic, in part due to difficulties in estimating exposure. Herein we characterize spatial and temporal variability of arsenic concentrations and develop models for predicting aquifer arsenic concentrations in the San Luis Valley, Colorado, an area of moderately elevated arsenic in groundwater. This study included historical water samples with total arsenic concentrations from 595 unique well locations. A longitudinal analysis established temporal stability in arsenic levels in individual wells. The mean arsenic levels for a random sample of 535 wells were incorporated into five kriging models to predict groundwater arsenic concentrations at any point in time. A separate validation dataset (n = 60 wells) was used to identify the model with strongest predictability. Findings indicate that arsenic concentrations are temporally stable (r = 0.88; 95 % CI 0.83-0.92 for samples collected from the same well 15-25 years apart) and the spatial model created using ordinary kriging best predicted arsenic concentrations (ρ = 0.72 between predicted and observed validation data). These findings illustrate the value of geostatistical modeling of arsenic and suggest the San Luis Valley is a good region for conducting epidemiologic studies of groundwater metals because of the ability to accurately predict variation in groundwater arsenic concentrations.

The DoE method as an efficient tool for modeling the behavior of monocrystalline Si-PV module

NASA Astrophysics Data System (ADS)

Kessaissia, Fatma Zohra; Zegaoui, Abdallah; Boutoubat, Mohamed; Allouache, Hadj; Aillerie, Michel; Charles, Jean-Pierre

2018-05-01

The objective of this paper is to apply the Design of Experiments (DoE) method to study and to obtain a predictive model of any marketed monocrystalline photovoltaic (mc-PV) module. This technique allows us to have a mathematical model that represents the predicted responses depending upon input factors and experimental data. Therefore, the DoE model for characterization and modeling of mc-PV module behavior can be obtained by just performing a set of experimental trials. The DoE model of the mc-PV panel evaluates the predictive maximum power, as a function of irradiation and temperature in a bounded domain of study for inputs. For the mc-PV panel, the predictive model for both one level and two levels were developed taking into account both influences of the main effect and the interactive effects on the considered factors. The DoE method is then implemented by developing a code under Matlab software. The code allows us to simulate, characterize, and validate the predictive model of the mc-PV panel. The calculated results were compared to the experimental data, errors were estimated, and an accurate validation of the predictive models was evaluated by the surface response. Finally, we conclude that the predictive models reproduce the experimental trials and are defined within a good accuracy.

The Dirty Dozen Scale: Validation of a Polish Version and Extension of the Nomological Net.

PubMed

Czarna, Anna Z; Jonason, Peter K; Dufner, Michael; Kossowska, Małgorzata

2016-01-01

In five studies (total N = 1300) we developed and validated a Polish version of the Dirty Dozen measure (DTDD-P) that measures the three traits of the Dark Triad, Machiavellianism, psychopathy, and narcissism. We detail the presence and stability of a bifactor structure of the 12 items and present evidence for good internal consistency and test-retest reliability. We examine the nomological network surrounding the Dark Triad and show that both the Dark Triad total score and the subscales have acceptable validity. We also present evidence on the Dark Triad and moral behavior. Dark Triad predicts utilitarian moral choice (e.g., approval for sacrificing somebody's life for the sake of saving others) and this link is mediated by low empathic concern. In total, our results suggest that the Polish Dirty Dozen-Parszywa Dwunastka-is valid, stable, and useful for the study of lingering puzzles in the literature.

Animal models of binge drinking, current challenges to improve face validity.

PubMed

Jeanblanc, Jérôme; Rolland, Benjamin; Gierski, Fabien; Martinetti, Margaret P; Naassila, Mickael

2018-05-05

Binge drinking (BD), i.e., consuming a large amount of alcohol in a short period of time, is an increasing public health issue. Though no clear definition has been adopted worldwide the speed of drinking seems to be a keystone of this behavior. Developing relevant animal models of BD is a priority for gaining a better characterization of the neurobiological and psychobiological mechanisms underlying this dangerous and harmful behavior. Until recently, preclinical research on BD has been conducted mostly using forced administration of alcohol, but more recent studies used scheduled access to alcohol, to model more voluntary excessive intakes, and to achieve signs of intoxications that mimic the human behavior. The main challenges for future research are discussed regarding the need of good face validity, construct validity and predictive validity of animal models of BD. Copyright © 2018 Elsevier Ltd. All rights reserved.

Orthorexia nervosa: validation of a diagnosis questionnaire.

PubMed

Donini, L M; Marsili, D; Graziani, M P; Imbriale, M; Cannella, C

2005-06-01

To validate a questionnaire for the diagnosis of orhorexia oervosa, an eating disorder defined as "maniacal obsession for healthy food". 525 subjects were enrolled. Then they were randomized into two samples (sample of 404 subjects for the construction of the test for the diagnosis of orthorexia ORTO-15; sample of 121 subjects for the validation of the test). The ORTO-15 questionnaire, validated for the diagnosis of orthorexia, is made-up of 15 multiple-choice items. The test we proposed for the diagnosis of orthorexia (ORTO 15) showed a good predictive capability at a threshold value of 40 (efficacy 73.8%, sensitivity 55.6% and specificity 75.8%) also on verification with a control sample. However, it has a limit in identifying the obsessive disorder. For this reason we maintain that further investigation is necessary and that new questions useful for the evaluation of the obsessive-compulsive behavior should be added to the ORTO-15 questionnaire.

RankProd Combined with Genetic Algorithm Optimized Artificial Neural Network Establishes a Diagnostic and Prognostic Prediction Model that Revealed C1QTNF3 as a Biomarker for Prostate Cancer.

PubMed

Hou, Qi; Bing, Zhi-Tong; Hu, Cheng; Li, Mao-Yin; Yang, Ke-Hu; Mo, Zu; Xie, Xiang-Wei; Liao, Ji-Lin; Lu, Yan; Horie, Shigeo; Lou, Ming-Wu

2018-06-01

Prostate cancer (PCa) is the most commonly diagnosed cancer in males in the Western world. Although prostate-specific antigen (PSA) has been widely used as a biomarker for PCa diagnosis, its results can be controversial. Therefore, new biomarkers are needed to enhance the clinical management of PCa. From publicly available microarray data, differentially expressed genes (DEGs) were identified by meta-analysis with RankProd. Genetic algorithm optimized artificial neural network (GA-ANN) was introduced to establish a diagnostic prediction model and to filter candidate genes. The diagnostic and prognostic capability of the prediction model and candidate genes were investigated in both GEO and TCGA datasets. Candidate genes were further validated by qPCR, Western Blot and Tissue microarray. By RankProd meta-analyses, 2306 significantly up- and 1311 down-regulated probes were found in 133 cases and 30 controls microarray data. The overall accuracy rate of the PCa diagnostic prediction model, consisting of a 15-gene signature, reached up to 100% in both the training and test dataset. The prediction model also showed good results for the diagnosis (AUC = 0.953) and prognosis (AUC of 5 years overall survival time = 0.808) of PCa in the TCGA database. The expression levels of three genes, FABP5, C1QTNF3 and LPHN3, were validated by qPCR. C1QTNF3 high expression was further validated in PCa tissue by Western Blot and Tissue microarray. In the GEO datasets, C1QTNF3 was a good predictor for the diagnosis of PCa (GSE6956: AUC = 0.791; GSE8218: AUC = 0.868; GSE26910: AUC = 0.972). In the TCGA database, C1QTNF3 was significantly associated with PCa patient recurrence free survival (P < .001, AUC = 0.57). In this study, we have developed a diagnostic and prognostic prediction model for PCa. C1QTNF3 was revealed as a promising biomarker for PCa. This approach can be applied to other high-throughput data from different platforms for the discovery of oncogenes or biomarkers in different kinds of diseases. Copyright © 2018. Published by Elsevier B.V.

Development and validation of the FRAGIRE tool for assessment an older person's risk for frailty.

PubMed

Vernerey, Dewi; Anota, Amelie; Vandel, Pierre; Paget-Bailly, Sophie; Dion, Michele; Bailly, Vanessa; Bonin, Marie; Pozet, Astrid; Foubert, Audrey; Benetkiewicz, Magdalena; Manckoundia, Patrick; Bonnetain, Franck

2016-11-17

Frailty is highly prevalent in elderly people. While significant progress has been made to understand its pathogenesis process, few validated questionnaire exist to assess the multidimensional concept of frailty and to detect people frail or at risk to become frail. The objectives of this study were to construct and validate a new frailty-screening instrument named Frailty Groupe Iso-Ressource Evaluation (FRAGIRE) that accurately predicts the risk for frailty in older adults. A prospective multicenter recruitment of the elderly patients was undertaken in France. The subjects were classified into financially-helped group (FH, with financial assistance) and non-financially helped group (NFH, without any financial assistance), considering FH subjects are more frail than the NFH group and thus representing an acceptable surrogate population for frailty. Psychometric properties of the FRAGIRE grid were assessed including discrimination between the FH and NFH groups. Items reduction was made according to statistical analyses and experts' point of view. The association between items response and tests with "help requested status" was assessed in univariate and multivariate unconditional logistic regression analyses and a prognostic score to become frail was finally proposed for each subject. Between May 2013 and July 2013, 385 subjects were included: 338 (88%) in the FH group and 47 (12%) in the NFH group. The initial FRAGIRE grid included 65 items. After conducting the item selection, the final grid of the FRAGIRE was reduced to 19 items. The final grid showed fair discrimination ability to predict frailty (area under the curve (AUC) = 0.85) and good calibration (Hosmer-Lemeshow P-value = 0.580), reflecting a good agreement between the prediction by the final model and actual observation. The Cronbach's alpha for the developed tool scored as high as 0.69 (95% Confidence Interval: 0.64 to 0.74). The final prognostic score was excellent, with an AUC of 0.756. Moreover, it facilitated significant separation of patients into individuals requesting for help from others (P-value < 0.0001), with sensitivity of 81%, specificity of 61%, positive predictive value of 93%, negative predictive value of 34%, and a global predictive value of 78%. The FRAGIRE seems to have considerable potential as a reliable and effective tool for identifying frail elderly individuals by a public health social worker without medical training.

Construct Validity of the Relationship Profile Test: Links with measures of psychopathology and adult attachment

PubMed Central

Haggerty, Greg; Bornstein, Robert F.; Khalid, Mohammad; Sharma, Vishal; Riaz, Usman; Blanchard, Mark; Siefert, Caleb J; Sinclair, Samuel J.

2015-01-01

This study assessed the construct validity of the Relationship Profile Test (RPT; Bornstein & Languirand, 2003) with a substance abuse sample. One hundred-eight substance abuse patients completed the RPT, Experiences in Close Relationships Scale (ECR-SF; Wei, Russell, Mallinckrodt, & Vogel, 2007), Personality Assessment Inventory (PAI; Morey, 1991), and Symptom Checklist-90-Revised (SCL-90-R: Derogatis 1983). Results suggest that the RPT has good construct validity when compared against theoretically related broadband measures of personality, psychopathology and adult attachment. Overall, health hependency was negatively related to measures of psychopathology and insecure attachment, and overdependence was positively related to measures of psychopathology and attachment anxiety. Many of the predictions regarding RPT detachment and the criterion measures were not supported. Implications of these findings are discussed. PMID:26620463

Influences on emergency department length of stay for older people.

PubMed

Street, Maryann; Mohebbi, Mohammadreza; Berry, Debra; Cross, Anthony; Considine, Julie

2018-02-14

The aim of this study was to examine the influences on emergency department (ED) length of stay (LOS) for older people and develop a predictive model for an ED LOS more than 4 h. This retrospective cohort study used organizational data linkage at the patient level from a major Australian health service. The study population was aged 65 years or older, attending an ED during the 2013/2014 financial year. We developed and internally validated a clinical prediction rule. Discriminatory performance of the model was evaluated by receiver operating characteristic (ROC) curve analysis. An integer-based risk score was developed using multivariate logistic regression. The risk score was evaluated using ROC analysis. There were 33 926 ED attendances: 57.5% (n=19 517) had an ED LOS more than 4 h. The area under ROC for age, usual accommodation, triage category, arrival by ambulance, arrival overnight, imaging, laboratory investigations, overcrowding, time to be seen by doctor, ED visits with admission and access block relating to ED LOS more than 4 h was 0.796, indicating good performance. In the validation set, area under ROC was 0.80, P-value was 0.36 and prediction mean square error was 0.18, indicating good calibration. The risk score value attributed to each risk factor ranged from 2 to 68 points. The clinical prediction rule stratified patients into five levels of risk on the basis of the total risk score. Objective identification of older people at intermediate and high risk of an ED LOS more than 4 h early in ED care enables targeted approaches to streamline the patient journey, decrease ED LOS and optimize emergency care for older people.

First versus second trimester mean platelet volume and uric acid for prediction of preeclampsia in women at moderate and low risk.

PubMed

Rezk, Mohamed; Gaber, Wael; Shaheen, Abdelhamid; Nofal, Ahmed; Emara, Mahmoud; Gamal, Awni; Badr, Hassan

2018-06-12

To determine if second trimester mean platelet volume (MPV) and serum uric acid are reasonable predictors of preeclampsia (PE) or not, in patients at moderate and low risk. This prospective study was conducted on 9522 women at low or moderate risk for developing PE who underwent dual measurements of MPV and serum uric acid at late first trimester (10-12 weeks) and at second trimester (18-20 weeks) and subsequently divided into two groups; PE group (n = 286) who later developed PE and non-PE group (n = 9236). Test validity of MPV and serum uric acid was the primary outcome measure. Data were collected and analyzed. Second trimester MPV is a good predictor for development of PE at a cutoff value of 9.55 fL with area under the curve (AUC) of 0.86, sensitivity of 95.2%, specificity of 66.7%, positive predictive value (PPV) of 87%, negative predictive value (NPV) of 85.7%, and accuracy of 86.7%. Second trimester serum uric acid is a good predictor for development of PE at a cutoff value of 7.35 mg/dL, with AUC of 0.85, sensitivity of 95.2%, specificity of 55.6%, PPV of 83.3%, NPV of 83.3%, and accuracy of 83.3%. Combination of both tests has a sensitivity of 100%, specificity of 22.2%, PPV of 75%, NPV of 100%, and accuracy of 76.7%. Second trimester MPV and serum uric acid alone or in combination could be used as a useful biochemical markers for prediction of PE based on their validity, simplicity, and availability.

Fatigue Life Prediction Based on Crack Closure and Equivalent Initial Flaw Size

PubMed Central

Wang, Qiang; Zhang, Wei; Jiang, Shan

2015-01-01

Failure analysis and fatigue life prediction are necessary and critical for engineering structural materials. In this paper, a general methodology is proposed to predict fatigue life of smooth and circular-hole specimens, in which the crack closure model and equivalent initial flaw size (EIFS) concept are employed. Different effects of crack closure on small crack growth region and long crack growth region are considered in the proposed method. The EIFS is determined by the fatigue limit and fatigue threshold stress intensity factor △Kth. Fatigue limit is directly obtained from experimental data, and △Kth is calculated by using a back-extrapolation method. Experimental data for smooth and circular-hole specimens in three different alloys (Al2024-T3, Al7075-T6 and Ti-6Al-4V) under multiple stress ratios are used to validate the method. In the validation section, Semi-circular surface crack and quarter-circular corner crack are assumed to be the initial crack shapes for the smooth and circular-hole specimens, respectively. A good agreement is observed between model predictions and experimental data. The detailed analysis and discussion are performed on the proposed model. Some conclusions and future work are given. PMID:28793625

CFD-RANS prediction of individual exposure from continuous release of hazardous airborne materials in complex urban environments

NASA Astrophysics Data System (ADS)

Efthimiou, G. C.; Andronopoulos, S.; Bartzis, J. G.; Berbekar, E.; Harms, F.; Leitl, B.

2017-02-01

One of the key issues of recent research on the dispersion inside complex urban environments is the ability to predict individual exposure (maximum dosages) of an airborne material which is released continuously from a point source. The present work addresses the question whether the computational fluid dynamics (CFD)-Reynolds-averaged Navier-Stokes (RANS) methodology can be used to predict individual exposure for various exposure times. This is feasible by providing the two RANS concentration moments (mean and variance) and a turbulent time scale to a deterministic model. The whole effort is focused on the prediction of individual exposure inside a complex real urban area. The capabilities of the proposed methodology are validated against wind-tunnel data (CUTE experiment). The present simulations were performed 'blindly', i.e. the modeller had limited information for the inlet boundary conditions and the results were kept unknown until the end of the COST Action ES1006. Thus, a high uncertainty of the results was expected. The general performance of the methodology due to this 'blind' strategy is good. The validation metrics fulfil the acceptance criteria. The effect of the grid and the turbulence model on the model performance is examined.

Shock tube and chemical kinetic modeling study of the oxidation of 2,5-dimethylfuran.

PubMed

Sirjean, Baptiste; Fournet, René; Glaude, Pierre-Alexandre; Battin-Leclerc, Frédérique; Wang, Weijing; Oehlschlaeger, Matthew A

2013-02-21

A detailed kinetic model describing the oxidation of 2,5-dimethylfuran (DMF), a potential second-generation biofuel, is proposed. The kinetic model is based upon quantum chemical calculations for the initial DMF consumption reactions and important reactions of intermediates. The model is validated by comparison to new DMF shock tube ignition delay time measurements (over the temperature range 1300-1831 K and at nominal pressures of 1 and 4 bar) and the DMF pyrolysis speciation measurements of Lifshitz et al. [ J. Phys. Chem. A 1998 , 102 ( 52 ), 10655 - 10670 ]. Globally, modeling predictions are in good agreement with the considered experimental targets. In particular, ignition delay times are predicted well by the new model, with model-experiment deviations of at most a factor of 2, and DMF pyrolysis conversion is predicted well, to within experimental scatter of the Lifshitz et al. data. Additionally, comparisons of measured and model predicted pyrolysis speciation provides validation of theoretically calculated channels for the oxidation of DMF. Sensitivity and reaction flux analyses highlight important reactions as well as the primary reaction pathways responsible for the decomposition of DMF and formation and destruction of key intermediate and product species.

Dengue score as a diagnostic predictor for pleural effusion and/or ascites: external validation and clinical application.

PubMed

Suwarto, Suhendro; Hidayat, Mohammad Jauharsyah; Widjaya, Bing

2018-02-23

The Dengue Score is a model for predicting pleural effusion and/or ascites and uses the hematocrit (Hct), albumin concentration, platelet count and aspartate aminotransferase (AST) ratio as independent variables. As this metric has not been validated, we conducted a study to validate the Dengue Score and assess its clinical application. A retrospective study was performed at a private hospital in Jakarta, Indonesia. Patients with dengue infection hospitalized from January 2011 through March 2016 were included. The Dengue Score was calculated using four parameters: Hct increase≥15.1%, serum albumin≤3.49 mg/dL, platelet count≤49,500/μL and AST ratio ≥ 2.51. Each parameter was scored as 1 if present and 0 if absent. To validate the Dengue Score, goodness-of-fit was used to assess calibration, and the area under the receiver operating characteristic curve (AROC) was used to assess discrimination. Associations between clinical parameters and Dengue Score groups were determined by bivariate analysis. A total of 207 patients were included in this study. The calibration of the Dengue Score was acceptable (Hosmer-Lemeshow test, p = 0.11), and the score's discriminative ability was good (AROC = 0.88 (95% CI: 0.83-0.92)). At a cutoff of ≥2, the Dengue Score had a positive predictive value (PPV) of 79.03% and a negative predictive value (NPV) of 90.36% for the diagnostic prediction of pleural effusion and/or ascites. Compared with the Dengue Score ≤ 1 group, the Dengue Score = 2 group was significantly associated with hemoconcentration> 20% (p = 0.029), severe thrombocytopenia (p = 0.029), and increased length of hospital stay (p = 0.003). Compared with the Dengue Score = 2 group, the Dengue Score ≥ 3 group was significantly associated with hemoconcentration> 20% (p = 0.001), severe thrombocytopenia (p = 0.024), severe dengue (p = 0.039), and increased length of hospital stay (p = 0.011). The Dengue Score performed well and can be used in daily practice to help clinicians identify patients who have plasma leakage associated with severe dengue.

SU-E-T-516: Dosimetric Validation of AcurosXB Algorithm in Comparison with AAA & CCC Algorithms for VMAT Technique.

PubMed

Kathirvel, M; Subramanian, V Sai; Arun, G; Thirumalaiswamy, S; Ramalingam, K; Kumar, S Ashok; Jagadeesh, K

2012-06-01

To dosimetrically validate AcurosXB algorithm for Volumetric Modulated Arc Therapy (VMAT) in comparison with standard clinical Anisotropic Analytic Algorithm(AAA) and Collapsed Cone Convolution(CCC) dose calculation algorithms. AcurosXB dose calculation algorithm is available with Varian Eclipse treatment planning system (V10). It uses grid-based Boltzmann equation solver to predict dose precisely in lesser time. This study was made to realize algorithms ability to predict dose accurately as its delivery for which five clinical cases each of Brain, Head&Neck, Thoracic, Pelvic and SBRT were taken. Verification plans were created on multicube phantom with iMatrixx-2D detector array and then dose prediction was done with AcurosXB, AAA & CCC (COMPASS System) algorithm and the same were delivered onto CLINAC-iX treatment machine. Delivered dose was captured in iMatrixx plane for all 25 plans. Measured dose was taken as reference to quantify the agreement between AcurosXB calculation algorithm against previously validated AAA and CCC algorithm. Gamma evaluation was performed with clinical criteria distance-to-agreement 3&2mm and dose difference 3&2% in omnipro-I'MRT software. Plans were evaluated in terms of correlation coefficient, quantitative area gamma and average gamma. Study shows good agreement between mean correlation 0.9979±0.0012, 0.9984±0.0009 & 0.9979±0.0011 for AAA, CCC & Acuros respectively. Mean area gamma for criteria 3mm/3% was found to be 98.80±1.04, 98.14±2.31, 98.08±2.01 and 2mm/2% was found to be 93.94±3.83, 87.17±10.54 & 92.36±5.46 for AAA, CCC & Acuros respectively. Mean average gamma for 3mm/3% was 0.26±0.07, 0.42±0.08, 0.28±0.09 and 2mm/2% was found to be 0.39±0.10, 0.64±0.11, 0.42±0.13 for AAA, CCC & Acuros respectively. This study demonstrated that the AcurosXB algorithm had a good agreement with the AAA & CCC in terms of dose prediction. In conclusion AcurosXB algorithm provides a valid, accurate and speedy alternative to AAA and CCC algorithms in a busy clinical environment. © 2012 American Association of Physicists in Medicine.

Braden scale (ALB) for assessing pressure ulcer risk in hospital patients: A validity and reliability study.

PubMed

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

2017-02-01

The inter-rater reliability of Braden Scale is not so good. We modified the Braden(ALB) scale by defining nutrition subscale based on serum albumin, then assessed it's the validity and reliability in hospital patients. We designed a retrospective study for validity analysis, and a prospective study for reliability analysis. Receiver operating curve (ROC) and area under the curve (AUC) were used to evaluate the predictive validity. Intra-class correlation coefficient (ICC) was used to investigate the inter-rater reliability. Two thousand five hundred twenty-five patients were included for validity analysis, 76 patients (3.0%) developed pressure ulcer. Positive correlation was found between serum albumin and nutrition score in Braden scale (Spearman's coefficient 0.2203, P<0.0001). The AUCs for Braden scale and Braden(ALB) scale predicting pressure ulcer risk were 0.813 (95% CI 0.797-0.828; P<0.0001), and 0.859 (95% CI 0.845-0.872; P<0.0001), respectively. The Braden(ALB) scale was even more valid than the Braden scale (z=1.860, P=0.0628). In different age subgroups, the Braden(ALB) scale seems also more valid than the original Braden scale, but no statistically significant differences were found (P>0.05). The inter-rater reliability study showed the ICC-value for nutrition increased 45.9%, and increased 4.3% for total score. The Braden(ALB) scale has similar validity compared with the original Braden scale for in hospital patients. However, the inter-rater reliability was significantly increased. Copyright © 2016 Elsevier Inc. All rights reserved.

Predicting the Individual Risk of Acute Severe Colitis at Diagnosis.

PubMed

Cesarini, Monica; Collins, Gary S; Rönnblom, Anders; Santos, Antonieta; Wang, Lai Mun; Sjöberg, Daniel; Parkes, Miles; Keshav, Satish; Travis, Simon P L

2017-03-01

Acute severe colitis [ASC] is associated with major morbidity. We aimed to develop and externally validate an index that predicted ASC within 3 years of diagnosis. The development cohort included patients aged 16-89 years, diagnosed with ulcerative colitis [UC] in Oxford and followed for 3 years. Primary outcome was hospitalization for ASC, excluding patients admitted within 1 month of diagnosis. Multivariable logistic regression examined the adjusted association of seven risk factors with ASC. Backwards elimination produced a parsimonious model that was simplified to create an easy-to-use index. External validation occurred in separate cohorts from Cambridge, UK, and Uppsala, Sweden. The development cohort [Oxford] included 34/111 patients who developed ASC within a median 14 months [range 1-29]. The final model applied the sum of 1 point each for extensive disease, C-reactive protein [CRP] > 10mg/l, or haemoglobin < 12g/dl F or < 14g/dl M at diagnosis, to give a score from 0/3 to 3/3. This predicted a 70% risk of developing ASC within 3 years [score 3/3]. Validation cohorts included different proportions with ASC [Cambridge = 25/96; Uppsala = 18/298]. Of those scoring 3/3 at diagnosis, 18/18 [Cambridge] and 12/13 [Uppsala] subsequently developed ASC. Discriminant ability [c-index, where 1.0 = perfect discrimination] was 0.81 [Oxford], 0.95 [Cambridge], 0.97 [Uppsala]. Internal validation using bootstrapping showed good calibration, with similar predicted risk across all cohorts. A nomogram predicted individual risk. An index applied at diagnosis reliably predicts the risk of ASC within 3 years in different populations. Patients with a score 3/3 at diagnosis may merit early immunomodulator therapy. Copyright © 2016 European Crohn’s and Colitis Organisation (ECCO). Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com

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 I, Development of the Formula and its Internal Validation.

PubMed

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

2017-04-01

As the elderly population increases, a growing number of patients have lower urinary tract symptom (LUTS)/benign prostatic hyperplasia (BPH). The aim of this study was to develop decision support formulas and nomograms for the prediction of bladder outlet obstruction (BOO) and for BOO-related surgical decision-making, and to validate them in patients with LUTS/BPH. Patient with LUTS/BPH between October 2004 and May 2014 were enrolled as a development cohort. The available variables included age, International Prostate Symptom Score, free uroflowmetry, postvoid residual volume, total prostate volume, and the results of a pressure-flow study. A causal Bayesian network analysis was used to identify relevant parameters. Using multivariate logistic regression analysis, formulas were developed to calculate the probabilities of having BOO and requiring prostatic surgery. Patients between June 2014 and December 2015 were prospectively enrolled for internal validation. Receiver operating characteristic curve analysis, calibration plots, and decision curve analysis were performed. A total of 1,179 male patients with LUTS/BPH, with a mean age of 66.1 years, were included as a development cohort. Another 253 patients were enrolled as an internal validation cohort. Using multivariate logistic regression analysis, 2 and 4 formulas were established to estimate the probabilities of having BOO and requiring prostatic surgery, respectively. Our analysis of the predictive accuracy of the model revealed area under the curve values of 0.82 for BOO and 0.87 for prostatic surgery. The sensitivity and specificity were 53.6% and 87.0% for BOO, and 91.6% and 50.0% for prostatic surgery, respectively. The calibration plot indicated that these prediction models showed a good correspondence. In addition, the decision curve analysis showed a high net benefit across the entire spectrum of probability thresholds. We established nomograms for the prediction of BOO and BOO-related prostatic surgery in patients with LUTS/BPH. Internal validation of the nomograms demonstrated that they predicted both having BOO and requiring prostatic surgery very well.

Predictive validity and reliability of the Braden scale for risk assessment of pressure ulcers in an intensive care unit.

PubMed

Lima-Serrano, M; González-Méndez, M I; Martín-Castaño, C; Alonso-Araujo, I; Lima-Rodríguez, J S

2018-03-01

Contribution to validation of the Braden scale in patients admitted to the ICU, based on an analysis of its reliability and predictive validity. An analytical, observational, longitudinal prospective study was carried out. Intensive Care Unit, Hospital Virgen del Rocío, Seville (Spain). Patients aged 18years or older and admitted for over 24hours to the ICU were included. Patients with pressure ulcers upon admission were excluded. A total of 335 patients were enrolled in two study periods of one month each. None. The presence of gradei-iv pressure ulcers was regarded as the main or dependent variable. Three categories were considered (demographic, clinical and prognostic) for the remaining variables. The incidence of patients who developed pressure ulcers was 8.1%. The proportion of gradei andii pressure ulcer was 40.6% and 59.4% respectively, highlighting the sacrum as the most frequently affected location. Cronbach's alpha coefficient in the assessments considered indicated good to moderate reliability. In the three evaluations made, a cutoff point of 12 was presented as optimal in the assessment of the first and second days of admission. In relation to the assessment of the day with minimum score, the optimal cutoff point was 10. The Braden scale shows insufficient predictive validity and poor precision for cutoff points of both 18 and 16, which are those accepted in the different clinical scenarios. Copyright © 2017 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Novel Risk Engine for Diabetes Progression and Mortality in USA: Building, Relating, Assessing, and Validating Outcomes (BRAVO).

PubMed

Shao, Hui; Fonseca, Vivian; Stoecker, Charles; Liu, Shuqian; Shi, Lizheng

2018-05-03

There is an urgent need to update diabetes prediction, which has relied on the United Kingdom Prospective Diabetes Study (UKPDS) that dates back to 1970 s' European populations. The objective of this study was to develop a risk engine with multiple risk equations using a recent patient cohort with type 2 diabetes mellitus reflective of the US population. A total of 17 risk equations for predicting diabetes-related microvascular and macrovascular events, hypoglycemia, mortality, and progression of diabetes risk factors were estimated using the data from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (n = 10,251). Internal and external validation processes were used to assess performance of the Building, Relating, Assessing, and Validating Outcomes (BRAVO) risk engine. One-way sensitivity analysis was conducted to examine the impact of risk factors on mortality at the population level. The BRAVO risk engine added several risk factors including severe hypoglycemia and common US racial/ethnicity categories compared with the UKPDS risk engine. The BRAVO risk engine also modeled mortality escalation associated with intensive glycemic control (i.e., glycosylated hemoglobin < 6.5%). External validation showed a good prediction power on 28 endpoints observed from other clinical trials (slope = 1.071, R 2  = 0.86). The BRAVO risk engine for the US diabetes cohort provides an alternative to the UKPDS risk engine. It can be applied to assist clinical and policy decision making such as cost-effective resource allocation in USA.

Development and Validation of the Narrative Quality Assessment Tool.

PubMed

Kim, Wonsun Sunny; Shin, Cha-Nam; Kathryn Larkey, Linda; Roe, Denise J

2017-04-01

The use of storytelling in health promotion has grown over the past 2 decades, showing promise for moving people to initiate healthy behavior change. Given the increasingly prevalent role of storytelling in health promotion research and the need to more clearly identify what storytelling elements and mediators may better predict behavior change, there is a need to develop measures to specifically assess these factors in a cultural community context. The purpose of this study is to develop and preliminarily validate a narrative quality assessment tool for measuring elements of storytelling that are predicted to affect attitude and behavior change (i.e., narrative characteristics, identification, and transportation) within a cultural community setting using a culture-centric model. Reliability and validity of these scales were assessed with repeated administrations among 74 Latino men and women with a mean age of 39.6 years (SD = 11.47 years). The confirmatory factor analysis in addition to internal consistency tests revealed preliminary evidence for reliability and validity of the narrative characteristics, identification, and transportation scales. Cronbach's alpha ranged from .92 to .94. Items revealed adequate factor loadings (.85-.98) and good model fit. The new scales provide the first step in moving the assessment of narrative quality into a culturally relevant context for evaluation of story use in health promotion. The results present valuable information for nurse researchers to guide the development and testing of culturally grounded storytelling interventions' potential to predict attitude and behavior change for patients.

Prediction of blood-brain partitioning: a model based on molecular electronegativity distance vector descriptors.

PubMed

Zhang, Yong-Hong; Xia, Zhi-Ning; Qin, Li-Tang; Liu, Shu-Shen

2010-09-01

The objective of this paper is to build a reliable model based on the molecular electronegativity distance vector (MEDV) descriptors for predicting the blood-brain barrier (BBB) permeability and to reveal the effects of the molecular structural segments on the BBB permeability. Using 70 structurally diverse compounds, the partial least squares regression (PLSR) models between the BBB permeability and the MEDV descriptors were developed and validated by the variable selection and modeling based on prediction (VSMP) technique. The estimation ability, stability, and predictive power of a model are evaluated by the estimated correlation coefficient (r), leave-one-out (LOO) cross-validation correlation coefficient (q), and predictive correlation coefficient (R(p)). It has been found that PLSR model has good quality, r=0.9202, q=0.7956, and R(p)=0.6649 for M1 model based on the training set of 57 samples. To search the most important structural factors affecting the BBB permeability of compounds, we performed the values of the variable importance in projection (VIP) analysis for MEDV descriptors. It was found that some structural fragments in compounds, such as -CH(3), -CH(2)-, =CH-, =C, triple bond C-, -CH<, =C<, =N-, -NH-, =O, and -OH, are the most important factors affecting the BBB permeability. (c) 2010. Published by Elsevier Inc.

A new real-time visual assessment method for faulty movement patterns during a jump-landing task.

PubMed

Rabin, Alon; Levi, Ran; Abramowitz, Shai; Kozol, Zvi

2016-07-01

Determine the interrater reliability of a new real-time assessment of faulty movement patterns during a jump-landing task. Interrater reliability study. Human movement laboratory. 50 healthy females. Assessment included 6 items which were evaluated from a front and a side view. Two Physical Therapy students used a 9-point scale (0-8) to independently rate the quality of movement as good (0-2), moderate (3-5), or poor (6-8). Interrater reliability was expressed by percent agreement and weighted kappa. One examiner rated the quality of movement of 6 subjects as good, 34 subjects as moderate, and 10 subjects as poor. The second examiner rated the quality of movement of 12 subjects as good, 23 subjects as moderate, and 15 subjects as poor. Percent agreement and weighted kappa (95% confidence interval) were 78% and 0.68 (0.51, 0.85), respectively. A new real-time assessment of faulty movement patterns during jump-landing demonstrated adequate interrater reliability. Further study is warranted to validate this method against a motion analysis system, as well as to establish its predictive validity for injury. Copyright © 2015 Elsevier Ltd. All rights reserved.

The Work-Family Conflict Scale (WAFCS): development and initial validation of a self-report measure of work-family conflict for use with parents.

PubMed

Haslam, Divna; Filus, Ania; Morawska, Alina; Sanders, Matthew R; Fletcher, Renee

2015-06-01

This paper outlines the development and validation of the Work-Family Conflict Scale (WAFCS) designed to measure work-to-family conflict (WFC) and family-to-work conflict (FWC) for use with parents of young children. An expert informant and consumer feedback approach was utilised to develop and refine 20 items, which were subjected to a rigorous validation process using two separate samples of parents of 2-12 year old children (n = 305 and n = 264). As a result of statistical analyses several items were dropped resulting in a brief 10-item scale comprising two subscales assessing theoretically distinct but related constructs: FWC (five items) and WFC (five items). Analyses revealed both subscales have good internal consistency, construct validity as well as concurrent and predictive validity. The results indicate the WAFCS is a promising brief measure for the assessment of work-family conflict in parents. Benefits of the measure as well as potential uses are discussed.

Development and Validation of Triarchic Construct Scales from the Psychopathic Personality Inventory

PubMed Central

Hall, Jason R.; Drislane, Laura E.; Patrick, Christopher J.; Morano, Mario; Lilienfeld, Scott O.; Poythress, Norman G.

2014-01-01

The Triarchic model of psychopathy describes this complex condition in terms of distinct phenotypic components of boldness, meanness, and disinhibition. Brief self-report scales designed specifically to index these psychopathy facets have thus far demonstrated promising construct validity. The present study sought to develop and validate scales for assessing facets of the Triarchic model using items from a well-validated existing measure of psychopathy—the Psychopathic Personality Inventory (PPI). A consensus rating approach was used to identify PPI items relevant to each Triarchic facet, and the convergent and discriminant validity of the resulting PPI-based Triarchic scales were evaluated in relation to multiple criterion variables (i.e., other psychopathy inventories, antisocial personality disorder features, personality traits, psychosocial functioning) in offender and non-offender samples. The PPI-based Triarchic scales showed good internal consistency and related to criterion variables in ways consistent with predictions based on the Triarchic model. Findings are discussed in terms of implications for conceptualization and assessment of psychopathy. PMID:24447280

Development and validation of Triarchic construct scales from the psychopathic personality inventory.

PubMed

Hall, Jason R; Drislane, Laura E; Patrick, Christopher J; Morano, Mario; Lilienfeld, Scott O; Poythress, Norman G

2014-06-01

The Triarchic model of psychopathy describes this complex condition in terms of distinct phenotypic components of boldness, meanness, and disinhibition. Brief self-report scales designed specifically to index these psychopathy facets have thus far demonstrated promising construct validity. The present study sought to develop and validate scales for assessing facets of the Triarchic model using items from a well-validated existing measure of psychopathy-the Psychopathic Personality Inventory (PPI). A consensus-rating approach was used to identify PPI items relevant to each Triarchic facet, and the convergent and discriminant validity of the resulting PPI-based Triarchic scales were evaluated in relation to multiple criterion variables (i.e., other psychopathy inventories, antisocial personality disorder features, personality traits, psychosocial functioning) in offender and nonoffender samples. The PPI-based Triarchic scales showed good internal consistency and related to criterion variables in ways consistent with predictions based on the Triarchic model. Findings are discussed in terms of implications for conceptualization and assessment of psychopathy.

To develop a regional ICU mortality prediction model during the first 24 h of ICU admission utilizing MODS and NEMS with six other independent variables from the Critical Care Information System (CCIS) Ontario, Canada.

PubMed

Kao, Raymond; Priestap, Fran; Donner, Allan

2016-01-01

Intensive care unit (ICU) scoring systems or prediction models evolved to meet the desire of clinical and administrative leaders to assess the quality of care provided by their ICUs. The Critical Care Information System (CCIS) is province-wide data information for all Ontario, Canada level 3 and level 2 ICUs collected for this purpose. With the dataset, we developed a multivariable logistic regression ICU mortality prediction model during the first 24 h of ICU admission utilizing the explanatory variables including the two validated scores, Multiple Organs Dysfunctional Score (MODS) and Nine Equivalents Nursing Manpower Use Score (NEMS) followed by the variables age, sex, readmission to the ICU during the same hospital stay, admission diagnosis, source of admission, and the modified Charlson Co-morbidity Index (CCI) collected through the hospital health records. This study is a single-center retrospective cohort review of 8822 records from the Critical Care Trauma Centre (CCTC) and Medical-Surgical Intensive Care Unit (MSICU) of London Health Sciences Centre (LHSC), Ontario, Canada between 1 Jan 2009 to 30 Nov 2012. Multivariable logistic regression on training dataset (n = 4321) was used to develop the model and validate by bootstrapping method on the testing dataset (n = 4501). Discrimination, calibration, and overall model performance were also assessed. The predictors significantly associated with ICU mortality included: age (p < 0.001), source of admission (p < 0.0001), ICU admitting diagnosis (p < 0.0001), MODS (p < 0.0001), and NEMS (p < 0.0001). The variables sex and modified CCI were not significantly associated with ICU mortality. The training dataset for the developed model has good discriminating ability between patients with high risk and those with low risk of mortality (c-statistic 0.787). The Hosmer and Lemeshow goodness-of-fit test has a strong correlation between the observed and expected ICU mortality (χ (2) = 5.48; p > 0.31). The overall optimism of the estimation between the training and testing data set ΔAUC = 0.003, indicating a stable prediction model. This study demonstrates that CCIS data available after the first 24 h of ICU admission at LHSC can be used to create a robust mortality prediction model with acceptable fit statistic and internal validity for valid benchmarking and monitoring ICU performance.

CoMFA and CoMSIA 3D-QSAR studies on S(6)-(4-nitrobenzyl)mercaptopurine riboside (NBMPR) analogs as inhibitors of human equilibrative nucleoside transporter 1 (hENT1).

PubMed

Gupte, Amol; Buolamwini, John K

2009-01-15

3D-QSAR (CoMFA and CoMSIA) studies were performed on human equlibrative nucleoside transporter (hENT1) inhibitors displaying K(i) values ranging from 10,000 to 0.7nM. Both CoMFA and CoMSIA analysis gave reliable models with q2 values >0.50 and r2 values >0.92. The models have been validated for their stability and robustness using group validation and bootstrapping techniques and for their predictive abilities using an external test set of nine compounds. The high predictive r2 values of the test set (0.72 for CoMFA model and 0.74 for CoMSIA model) reveals that the models can prove to be a useful tool for activity prediction of newly designed nucleoside transporter inhibitors. The CoMFA and CoMSIA contour maps identify features important for exhibiting good binding affinities at the transporter, and can thus serve as a useful guide for the design of potential equilibrative nucleoside transporter inhibitors.

The Metacognitions about Gambling Questionnaire: Development and psychometric properties.

PubMed

Caselli, Gabriele; Fernie, Bruce; Canfora, Flaviano; Mascolo, Cristina; Ferrari, Andrea; Antonioni, Maria; Giustina, Lucia; Donato, Gilda; Marcotriggiani, Antonella; Bertani, Andrea; Altieri, Antonella; Pellegrini, Eliana; Spada, Marcantonio M

2018-03-01

Recent research has suggested that metacognitions may play a role across the spectrum of addictive behaviours. The goal of our studies was to develop the first self-report scale of metacognitions about gambling. We conducted three studies with one community (n = 165) and two clinical (n = 110; n = 87) samples to test the structure and psychometric properties of the Metacognitions about Gambling Questionnaire and examined its capacity to prospectively predict severity of gambling. Findings supported a two factor solution consisting of positive and negative metacognitions about gambling. Internal consistency, predictive and divergent validity were acceptable. All the factors of the Metacognitions about Gambling Questionnaire correlated positively with gambling severity. Regression analyses showed that negative metacognitions about gambling were significantly associated to gambling severity over and above negative affect and gambling-specific cognitive distortions. Finally only gambling severity and negative metacognitions about gambling were significant prospective predictors of gambling severity as measured three months later. The Metacognitions about Gambling Questionnaire was shown to possess good psychometric properties, as well as predictive and divergent validity within the populations that were tested. Copyright © 2018 Elsevier B.V. All rights reserved.

Modeling ready biodegradability of fragrance materials.

PubMed

Ceriani, Lidia; Papa, Ester; Kovarich, Simona; Boethling, Robert; Gramatica, Paola

2015-06-01

In the present study, quantitative structure activity relationships were developed for predicting ready biodegradability of approximately 200 heterogeneous fragrance materials. Two classification methods, classification and regression tree (CART) and k-nearest neighbors (kNN), were applied to perform the modeling. The models were validated with multiple external prediction sets, and the structural applicability domain was verified by the leverage approach. The best models had good sensitivity (internal ≥80%; external ≥68%), specificity (internal ≥80%; external 73%), and overall accuracy (≥75%). Results from the comparison with BIOWIN global models, based on group contribution method, show that specific models developed in the present study perform better in prediction than BIOWIN6, in particular for the correct classification of not readily biodegradable fragrance materials. © 2015 SETAC.

Reliability and Validity of Prototype Diagnosis for Adolescent Psychopathology.

PubMed

Haggerty, Greg; Zodan, Jennifer; Mehra, Ashwin; Zubair, Ayyan; Ghosh, Krishnendu; Siefert, Caleb J; Sinclair, Samuel J; DeFife, Jared

2016-04-01

The current study investigated the interrater reliability and validity of prototype ratings of 5 common adolescent psychiatric disorders: attention-deficit/hyperactivity disorder, conduct disorder, major depressive disorder, generalized anxiety disorder, and posttraumatic stress disorder. One hundred fifty-seven adolescent inpatient participants consented to participate in this study. We compared ratings from 2 inpatient clinicians, blinded to each other's ratings and patient measures, after their separate initial diagnostic interview to assess interrater reliability. Prototype ratings completed by clinicians after their initial diagnostic interview with adolescent inpatients and outpatients were compared with patient-reported behavior problems and parents' report of their child's behavioral problems. Prototype ratings demonstrated good interrater reliability. Clinicians' prototype ratings showed predicted relationships with patient-reported behavior problems and parent-reported behavior problems. Prototype matching seems to be a possible alternative for psychiatric diagnosis. Prototype ratings showed good interrater reliability based on clinicians unique experiences with the patient (as opposed to video-/audio-recorded material) with no training.

Computational Modelling of Patella Femoral Kinematics During Gait Cycle and Experimental Validation

NASA Astrophysics Data System (ADS)

Maiti, Raman

2016-06-01

The effect of loading and boundary conditions on patellar mechanics is significant due to the complications arising in patella femoral joints during total knee replacements. To understand the patellar mechanics with respect to loading and motion, a computational model representing the patella femoral joint was developed and validated against experimental results. The computational model was created in IDEAS NX and simulated in MSC ADAMS/VIEW software. The results obtained in the form of internal external rotations and anterior posterior displacements for a new and experimentally simulated specimen for patella femoral joint under standard gait condition were compared with experimental measurements performed on the Leeds ProSim knee simulator. A good overall agreement between the computational prediction and the experimental data was obtained for patella femoral kinematics. Good agreement between the model and the past studies was observed when the ligament load was removed and the medial lateral displacement was constrained. The model is sensitive to ±5 % change in kinematics, frictional, force and stiffness coefficients and insensitive to time step.

Computational Modelling of Patella Femoral Kinematics During Gait Cycle and Experimental Validation

NASA Astrophysics Data System (ADS)

Maiti, Raman

2018-06-01

The effect of loading and boundary conditions on patellar mechanics is significant due to the complications arising in patella femoral joints during total knee replacements. To understand the patellar mechanics with respect to loading and motion, a computational model representing the patella femoral joint was developed and validated against experimental results. The computational model was created in IDEAS NX and simulated in MSC ADAMS/VIEW software. The results obtained in the form of internal external rotations and anterior posterior displacements for a new and experimentally simulated specimen for patella femoral joint under standard gait condition were compared with experimental measurements performed on the Leeds ProSim knee simulator. A good overall agreement between the computational prediction and the experimental data was obtained for patella femoral kinematics. Good agreement between the model and the past studies was observed when the ligament load was removed and the medial lateral displacement was constrained. The model is sensitive to ±5 % change in kinematics, frictional, force and stiffness coefficients and insensitive to time step.

The theoretical and psychometric properties of the Subjective Traumatic Outlook (STO) questionnaire.

PubMed

Palgi, Yuval; Shrira, Amit; Ben-Ezra, Menachem

2017-07-01

The present study aimed to develop the theoretical construct and examine the psychometric properties of a new scale for measuring subjective traumatic outlook (STO) among individuals exposed to traumatic events. The main idea behind this construct is to assess individual differences in the way people exposed to traumatic experiences subjectively perceive their trauma. Using four samples, we conducted five studies that examine the new questionnaire's exploratory/confirmatory factor analysis (EFA/CFA), test-retest reliability, and construct validity. The STO was best captured by a five-item factor construct. This construct was found to have good convergent validity with similar, related subjective evaluations of PTSD and PTSD-related constructs. Yet, the STO also has unique and divergent properties compared to other questionnaires. The STO is a new, short questionnaire with excellent psychometric properties. It may provide practitioners with a good screening tool for attaining first impression about one's inner traumatic world, and predicting future risk for developing PTSD. Copyright © 2017. Published by Elsevier B.V.

Nutritional evaluation of commercial dry dog foods by near infrared reflectance spectroscopy.

PubMed

Alomar, D; Hodgkinson, S; Abarzúa, D; Fuchslocher, R; Alvarado, C; Rosales, E

2006-06-01

Near infrared reflectance spectroscopy (NIRS) was used to predict the nutritional value of dog foods sold in Chile. Fifty-nine dry foods for adult and growing dogs were collected, ground and scanned across the visible/NIR range and subsequently analysed for dry matter (DM), crude protein (CP), crude fibre (CF), total fat, linoleic acid, gross energy (GE), estimated metabolizable energy (ME) and several amino acids and minerals. Calibration equations were developed by modified partial least squares regression, and tested by cross-validation. Standard error of cross validation (SE(CV)) and coefficient of determination of cross validation (SE(CV)) were used to select best equations. Equations with good predicting accuracy were obtained for DM, CF, CP, GE and fat. Corresponding values for and SE(CV) were 0.96 and 1.7 g/kg, 0.91 and 3.1 g/kg, 0.99 and 5.0 g/kg, 0.93 and 0.26 MJ/kg, 0.89 and 12.4 g/kg. Several amino acids were also well predicted, such as arginine, leucine, isoleucine, phenylalanine-tyrosine (combined), threonine and valine, with values for and SE(CV) (g/kg) of 0.89 and 0.9, 0.94 and 1.3, 0.91 and 0.5, 0.95 and 0.9, 0.91 and 0.5, 0.93 and 0.5. Intermediate values, appropriate for ranking purposes, were obtained for ME, histidine, lysine and methionine-cysteine. Tryptophan, minerals or linoleic acid were not acceptably predicted, irrespective of the mathematical treatment applied. It is concluded that NIR can be successfully used to predict important nutritional characteristics of commercial dog foods.

Clinical prediction model to aid emergency doctors managing febrile children at risk of serious bacterial infections: diagnostic study

PubMed Central

Nijman, Ruud G; Vergouwe, Yvonne; Thompson, Matthew; van Veen, Mirjam; van Meurs, Alfred H J; van der Lei, Johan; Steyerberg, Ewout W; Moll, Henriette A

2013-01-01

Objective To derive, cross validate, and externally validate a clinical prediction model that assesses the risks of different serious bacterial infections in children with fever at the emergency department. Design Prospective observational diagnostic study. Setting Three paediatric emergency care units: two in the Netherlands and one in the United Kingdom. Participants Children with fever, aged 1 month to 15 years, at three paediatric emergency care units: Rotterdam (n=1750) and the Hague (n=967), the Netherlands, and Coventry (n=487), United Kingdom. A prediction model was constructed using multivariable polytomous logistic regression analysis and included the predefined predictor variables age, duration of fever, tachycardia, temperature, tachypnoea, ill appearance, chest wall retractions, prolonged capillary refill time (>3 seconds), oxygen saturation <94%, and C reactive protein. Main outcome measures Pneumonia, other serious bacterial infections (SBIs, including septicaemia/meningitis, urinary tract infections, and others), and no SBIs. Results Oxygen saturation <94% and presence of tachypnoea were important predictors of pneumonia. A raised C reactive protein level predicted the presence of both pneumonia and other SBIs, whereas chest wall retractions and oxygen saturation <94% were useful to rule out the presence of other SBIs. Discriminative ability (C statistic) to predict pneumonia was 0.81 (95% confidence interval 0.73 to 0.88); for other SBIs this was even better: 0.86 (0.79 to 0.92). Risk thresholds of 10% or more were useful to identify children with serious bacterial infections; risk thresholds less than 2.5% were useful to rule out the presence of serious bacterial infections. External validation showed good discrimination for the prediction of pneumonia (0.81, 0.69 to 0.93); discriminative ability for the prediction of other SBIs was lower (0.69, 0.53 to 0.86). Conclusion A validated prediction model, including clinical signs, symptoms, and C reactive protein level, was useful for estimating the likelihood of pneumonia and other SBIs in children with fever, such as septicaemia/meningitis and urinary tract infections. PMID:23550046

Criterion and concurrent validity of Conners Adult ADHD Diagnostic Interview for DSM-IV (CAADID) Spanish version.

PubMed

Ramos-Quiroga, Josep Antoni; Bosch, Rosa; Richarte, Vanesa; Valero, Sergi; Gómez-Barros, Nuria; Nogueira, Mariana; Palomar, Gloria; Corrales, Montse; Sáez-Francàs, Naia; Corominas, Margarida; Real, Alberto; Vidal, Raquel; Chalita, Pablo J; Casas, Miguel

2012-01-01

Attention deficit hyperactivity disorder (ADHD) is a common neuropsychiatric disorder in adulthood. Its diagnosis requires a retrospective evaluation of ADHD symptoms in childhood, the continuity of these symptoms in adulthood, and a differential diagnosis. For these reasons, diagnosis of ADHD in adults is a complex process which needs effective diagnostic tools. To analyse the criterion validity of the CAADID semi-structured interview, Spanish version, and the concurrent validity compared with other ADHD severity scales. An observational case-control study was conducted on 691 patients with ADHD. They were out-patients treated in a program for adults with ADHD in a hospital. A sensitivity of 98.86%, specificity 67.68%, positive predictive value 90.77% and a negative predictive value 94.87% were observed. Diagnostic precision was 91.46%. The kappa index concordance between the clinical diagnostic interview and the CAADID was 0.88. Good concurrent validity was obtained, the CAADID correlated significantly with WURS scale (r=0.522, P<.01), ADHD Rating Scale (r=0.670, P<.0.1) and CAARS (self-rating version; r=0.656, P<.01 and observer-report r=0.514, P<.01). CAADID is a valid and useful tool for the diagnosis of ADHD in adults for clinical, as well as for research purposes. Copyright © 2012 SEP y SEPB. Published by Elsevier España, S.L. All rights reserved.

Reliability, validity and minimal detectable change of computerized respiratory sounds in patients with chronic obstructive pulmonary disease.

PubMed

Oliveira, Ana; Lage, Susan; Rodrigues, João; Marques, Alda

2017-11-17

Computerized respiratory sounds (CRS) are closely related to the movement of air within the tracheobronchial tree and are promising outcome measures in patients with chronic obstructive pulmonary disease (COPD). However, CRS measurement properties have been poorly tested. The aim of this study was to assess the reliability, validity and the minimal detectable changes (MDC) of CRS in patients with stable COPD. Fifty patients (36♂, 67.26 ± 9.31y, FEV 1 49.52 ± 19.67%predicted) were enrolled. CRS were recorded simultaneously at seven anatomic locations (trachea; right and left anterior, lateral and posterior chest). The number of crackles, wheeze occupation rate, median frequency (F50) and maximum intensity (Imax) were processed using validated algorithms. Within-day and between-days reliability, criterion and construct validity, validity to predict exacerbations and MDC were established. CRS presented moderate-to-excellent within-day reliability (ICC 1,3  ≥ 0.51; P < .05) and moderate-to-good between-days reliability (ICC 1,2  ≥ 0.47; P < .05) for most locations. Negligible-to-moderate correlations with FEV 1 %predicted were found (-0.53 < r s  < -0.28; P < .05), and the inspiratory number of crackles were the best discriminator between mild-to-moderate and severe-to-very severe airflow limitations (area under the curve >0.78). CRS correlated poorly with patient-reported outcomes (r s  < 0.48; P < .05) and did not predict exacerbations. Inspiratory number of crackles at posterior right chest, inspiratory F50 at trachea and anterior left chest and expiratory Imax at anterior right chest were simultaneously reliable and valid, and their MDC were 2.41, 55.27, 29.55 and 3.98, respectively. CRS are reliable and valid. Their use, integrated with other clinical and patient-reported measures, may fill the gap of assessing small airways and contribute toward a patient's comprehensive evaluation. © 2017 John Wiley & Sons Ltd.

Development and validation of a risk-prediction nomogram for in-hospital mortality in adults poisoned with drugs and nonpharmaceutical agents

PubMed Central

Lionte, Catalina; Sorodoc, Victorita; Jaba, Elisabeta; Botezat, Alina

2017-01-01

Abstract Acute poisoning with drugs and nonpharmaceutical agents represents an important challenge in the emergency department (ED). The objective is to create and validate a risk-prediction nomogram for use in the ED to predict the risk of in-hospital mortality in adults from acute poisoning with drugs and nonpharmaceutical agents. This was a prospective cohort study involving adults with acute poisoning from drugs and nonpharmaceutical agents admitted to a tertiary referral center for toxicology between January and December 2015 (derivation cohort) and between January and June 2016 (validation cohort). We used a program to generate nomograms based on binary logistic regression predictive models. We included variables that had significant associations with death. Using regression coefficients, we calculated scores for each variable, and estimated the event probability. Model validation was performed using bootstrap to quantify our modeling strategy and using receiver operator characteristic (ROC) analysis. The nomogram was tested on a separate validation cohort using ROC analysis and goodness-of-fit tests. Data from 315 patients aged 18 to 91 years were analyzed (n = 180 in the derivation cohort; n = 135 in the validation cohort). In the final model, the following variables were significantly associated with mortality: age, laboratory test results (lactate, potassium, MB isoenzyme of creatine kinase), electrocardiogram parameters (QTc interval), and echocardiography findings (E wave velocity deceleration time). Sex was also included to use the same model for men and women. The resulting nomogram showed excellent survival/mortality discrimination (area under the curve [AUC] 0.976, 95% confidence interval [CI] 0.954–0.998, P < 0.0001 for the derivation cohort; AUC 0.957, 95% CI 0.892–1, P < 0.0001 for the validation cohort). This nomogram provides more precise, rapid, and simple risk-analysis information for individual patients acutely exposed to drugs and nonpharmaceutical agents, and accurately estimates the probability of in-hospital death, exclusively using the results of objective tests available in the ED. PMID:28328838

A novel risk score model for prediction of contrast-induced nephropathy after emergent percutaneous coronary intervention.

PubMed

Lin, Kai-Yang; Zheng, Wei-Ping; Bei, Wei-Jie; Chen, Shi-Qun; Islam, Sheikh Mohammed Shariful; Liu, Yong; Xue, Lin; Tan, Ning; Chen, Ji-Yan

2017-03-01

A few studies developed simple risk model for predicting CIN with poor prognosis after emergent PCI. The study aimed to develop and validate a novel tool for predicting the risk of contrast-induced nephropathy (CIN) in patients undergoing emergent percutaneous coronary intervention (PCI). 692 consecutive patients undergoing emergent PCI between January 2010 and December 2013 were randomly (2:1) assigned to a development dataset (n=461) and a validation dataset (n=231). Multivariate logistic regression was applied to identify independent predictors of CIN, and established CIN predicting model, whose prognostic accuracy was assessed using the c-statistic for discrimination and the Hosmere Lemeshow test for calibration. The overall incidence of CIN was 55(7.9%). A total of 11 variables were analyzed, including age >75years old, baseline serum creatinine (SCr)>1.5mg/dl, hypotension and the use of intra-aortic balloon pump(IABP), which were identified to enter risk score model (Chen). The incidence of CIN was 32(6.9%) in the development dataset (in low risk (score=0), 1.0%, moderate risk (score:1-2), 13.4%, high risk (score≥3), 90.0%). Compared to the classical Mehran's and ACEF CIN risk score models, the risk score (Chen) across the subgroup of the study population exhibited similar discrimination and predictive ability on CIN (c-statistic:0.828, 0.776, 0.853, respectively), in-hospital mortality, 2, 3-years mortality (c-statistic:0.738.0.750, 0.845, respectively) in the validation population. Our data showed that this simple risk model exhibited good discrimination and predictive ability on CIN, similar to Mehran's and ACEF score, and even on long-term mortality after emergent PCI. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

PREDICT: a new UK prognostic model that predicts survival following surgery for invasive breast cancer.

PubMed

Wishart, Gordon C; Azzato, Elizabeth M; Greenberg, David C; Rashbass, Jem; Kearins, Olive; Lawrence, Gill; Caldas, Carlos; Pharoah, Paul D P

2010-01-01

The aim of this study was to develop and validate a prognostication model to predict overall and breast cancer specific survival for women treated for early breast cancer in the UK. Using the Eastern Cancer Registration and Information Centre (ECRIC) dataset, information was collated for 5,694 women who had surgery for invasive breast cancer in East Anglia from 1999 to 2003. Breast cancer mortality models for oestrogen receptor (ER) positive and ER negative tumours were derived from these data using Cox proportional hazards, adjusting for prognostic factors and mode of cancer detection (symptomatic versus screen-detected). An external dataset of 5,468 patients from the West Midlands Cancer Intelligence Unit (WMCIU) was used for validation. Differences in overall actual and predicted mortality were <1% at eight years for ECRIC (18.9% vs. 19.0%) and WMCIU (17.5% vs. 18.3%) with area under receiver-operator-characteristic curves (AUC) of 0.81 and 0.79 respectively. Differences in breast cancer specific actual and predicted mortality were <1% at eight years for ECRIC (12.9% vs. 13.5%) and <1.5% at eight years for WMCIU (12.2% vs. 13.6%) with AUC of 0.84 and 0.82 respectively. Model calibration was good for both ER positive and negative models although the ER positive model provided better discrimination (AUC 0.82) than ER negative (AUC 0.75). We have developed a prognostication model for early breast cancer based on UK cancer registry data that predicts breast cancer survival following surgery for invasive breast cancer and includes mode of detection for the first time. The model is well calibrated, provides a high degree of discrimination and has been validated in a second UK patient cohort.

Configuration and validation of a novel prostate disease nomogram predicting prostate biopsy outcome: A prospective study correlating clinical indicators among Filipino adult males with elevated PSA level.

PubMed

Chua, Michael E; Tanseco, Patrick P; Mendoza, Jonathan S; Castillo, Josefino C; Morales, Marcelino L; Luna, Saturnino L

2015-04-01

To configure and validate a novel prostate disease nomogram providing prostate biopsy outcome probabilities from a prospective study correlating clinical indicators and diagnostic parameters among Filipino adult male with elevated serum total prostate specific antigen (PSA) level. All men with an elevated serum total PSA underwent initial prostate biopsy at our institution from January 2011 to August 2014 were included. Clinical indicators, diagnostic parameters, which include PSA level and PSA-derivatives, were collected as predictive factors for biopsy outcome. Multiple logistic-regression analysis involving a backward elimination selection procedure was used to select independent predictors. A nomogram was developed to calculate the probability of the biopsy outcomes. External validation of the nomogram was performed using separate data set from another center for determination of sensitivity and specificity. A receiver-operating characteristic (ROC) curve was used to assess the accuracy in predicting differential biopsy outcome. Total of 552 patients was included. One hundred and ninety-one (34.6%) patients had benign prostatic hyperplasia, and 165 (29.9%) had chronic prostatitis. The remaining 196 (35.5%) patients had prostate adenocarcinoma. The significant independent variables used to predict biopsy outcome were age, family history of prostate cancer, prior antibiotic intake, PSA level, PSA-density, PSA-velocity, echogenic findings on ultrasound, and DRE status. The areas under the receiver-operating characteristic curve for prostate cancer using PSA alone and the nomogram were 0.688 and 0.804, respectively. The nomogram configured based on routinely available clinical parameters, provides high predictive accuracy with good performance characteristics in predicting the prostate biopsy outcome such as presence of prostate cancer, high Gleason prostate cancer, benign prostatic hyperplasia, and chronic prostatitis.

Predicting microbiologically defined infection in febrile neutropenic episodes in children: global individual participant data multivariable meta-analysis

PubMed Central

Phillips, Robert S; Sung, Lillian; Amman, Roland A; Riley, Richard D; Castagnola, Elio; Haeusler, Gabrielle M; Klaassen, Robert; Tissing, Wim J E; Lehrnbecher, Thomas; Chisholm, Julia; Hakim, Hana; Ranasinghe, Neil; Paesmans, Marianne; Hann, Ian M; Stewart, Lesley A

2016-01-01

Background: Risk-stratified management of fever with neutropenia (FN), allows intensive management of high-risk cases and early discharge of low-risk cases. No single, internationally validated, prediction model of the risk of adverse outcomes exists for children and young people. An individual patient data (IPD) meta-analysis was undertaken to devise one. Methods: The ‘Predicting Infectious Complications in Children with Cancer' (PICNICC) collaboration was formed by parent representatives, international clinical and methodological experts. Univariable and multivariable analyses, using random effects logistic regression, were undertaken to derive and internally validate a risk-prediction model for outcomes of episodes of FN based on clinical and laboratory data at presentation. Results: Data came from 22 different study groups from 15 countries, of 5127 episodes of FN in 3504 patients. There were 1070 episodes in 616 patients from seven studies available for multivariable analysis. Univariable analyses showed associations with microbiologically defined infection (MDI) in many items, including higher temperature, lower white cell counts and acute myeloid leukaemia, but not age. Patients with osteosarcoma/Ewings sarcoma and those with more severe mucositis were associated with a decreased risk of MDI. The predictive model included: malignancy type, temperature, clinically ‘severely unwell', haemoglobin, white cell count and absolute monocyte count. It showed moderate discrimination (AUROC 0.723, 95% confidence interval 0.711–0.759) and good calibration (calibration slope 0.95). The model was robust to bootstrap and cross-validation sensitivity analyses. Conclusions: This new prediction model for risk of MDI appears accurate. It requires prospective studies assessing implementation to assist clinicians and parents/patients in individualised decision making. PMID:26954719

Predicting fitness-to-drive following stroke using the Occupational Therapy - Driver Off Road Assessment Battery.

PubMed

Unsworth, Carolyn A; Baker, Anne; Lannin, Natasha; Harries, Priscilla; Strahan, Janene; Browne, Matthew

2018-02-28

It is difficult to determine if, or when, individuals with stroke are ready to undergo on-road fitness-to-drive assessment. The Occupational Therapy - Driver Off Road Assessment Battery was developed to determine client suitability to resume driving. The predictive validity of the Battery needs to be verified for people with stroke. Examine the predictive validity of the Occupational Therapy - Driver Off Road Assessment Battery for on-road performance among people with stroke. Off-road data were collected from 148 people post stroke on the Battery and the outcome of their on-road assessment was recorded as: fit-to-drive or not fit-to-drive. The majority of participants (76%) were able to resume driving. A classification and regression tree (CART) analysis using four subtests (three cognitive and one physical) from the Battery demonstrated an area under the curve (AUC) of 0.8311. Using a threshold of 0.5, the model correctly predicted 98/112 fit-to-drive (87.5%) and 26/36 people not fit-to-drive (72.2%). The three cognitive subtests from the Occupational Therapy - Driver Off Road Assessment Battery and potentially one of the physical tests have good predictive validity for client fitness-to-drive. These tests can be used to screen client suitability for proceeding to an on-road test following stroke. Implications for Rehabilitation: Following stroke, drivers should be counseled (including consideration of local legislation) concerning return to driving. The Occupational Therapy - Driver Off Road Assessment Battery can be used in the clinic to screen people for suitability to undertake on road assessment. Scores on four of the Occupational Therapy - Driver Off Road Assessment Battery subtests are predictive of resumption of driving following stroke.

Validation of High Frequency (HF) Propagation Prediction Models in the Arctic region

NASA Astrophysics Data System (ADS)

Athieno, R.; Jayachandran, P. T.

2014-12-01

Despite the emergence of modern techniques for long distance communication, Ionospheric communication in the high frequency (HF) band (3-30 MHz) remains significant to both civilian and military users. However, the efficient use of the ever-varying ionosphere as a propagation medium is dependent on the reliability of ionospheric and HF propagation prediction models. Most available models are empirical implying that data collection has to be sufficiently large to provide good intended results. The models we present were developed with little data from the high latitudes which necessitates their validation. This paper presents the validation of three long term High Frequency (HF) propagation prediction models over a path within the Arctic region. Measurements of the Maximum Usable Frequency for a 3000 km range (MUF (3000) F2) for Resolute, Canada (74.75° N, 265.00° E), are obtained from hand-scaled ionograms generated by the Canadian Advanced Digital Ionosonde (CADI). The observations have been compared with predictions obtained from the Ionospheric Communication Enhanced Profile Analysis Program (ICEPAC), Voice of America Coverage Analysis Program (VOACAP) and International Telecommunication Union Recommendation 533 (ITU-REC533) for 2009, 2011, 2012 and 2013. A statistical analysis shows that the monthly predictions seem to reproduce the general features of the observations throughout the year though it is more evident in the winter and equinox months. Both predictions and observations show a diurnal and seasonal variation. The analysed models did not show large differences in their performances. However, there are noticeable differences across seasons for the entire period analysed: REC533 gives a better performance in winter months while VOACAP has a better performance for both equinox and summer months. VOACAP gives a better performance in the daily predictions compared to ICEPAC though, in general, the monthly predictions seem to agree more with the observations compared to the daily predictions.

Theoretical and experimental studies of the deposition of Na2So4 from seeded combustion gases

NASA Technical Reports Server (NTRS)

Kohl, F. J.; Santoro, G. J.; Stearns, C. A.; Fryburg, G. C.; Rosner, D. E.

1977-01-01

Flames in a Mach 0.3 atmospheric pressure laboratory burner rig were doped with sea salt, NaS04, and NaCl, respectively, in an effort to validate theoretical dew point predictions made by a local thermochemical equilibrium (LTCE) method of predicting condensation temperatures of sodium sulfate in flame environments. Deposits were collected on cylindrical platinum targets placed in the combustion products, and the deposition was studied as a function of collector temperature. Experimental deposition onset temperatures checked within experimental error with LTCE-predicted temperatures. A multicomponent mass transfer equation was developed to predict the rate of deposition of Na2SO4(c) via vapor transport at temperatures below the deposition onset temperature. Agreement between maximum deposition rates predicted by this chemically frozen boundary layer (CFBL) theory and those obtained in the seeded laboratory burner experiments is good.

KNT-artificial neural network model for flux prediction of ultrafiltration membrane producing drinking water.

PubMed

Oh, H K; Yu, M J; Gwon, E M; Koo, J Y; Kim, S G; Koizumi, A

2004-01-01

This paper describes the prediction of flux behavior in an ultrafiltration (UF) membrane system using a Kalman neuro training (KNT) network model. The experimental data was obtained from operating a pilot plant of hollow fiber UF membrane with groundwater for 7 months. The network was trained using operating conditions such as inlet pressure, filtration duration, and feed water quality parameters including turbidity, temperature and UV254. Pre-processing of raw data allowed the normalized input data to be used in sigmoid activation functions. A neural network architecture was structured by modifying the number of hidden layers, neurons and learning iterations. The structure of KNT-neural network with 3 layers and 5 neurons allowed a good prediction of permeate flux by 0.997 of correlation coefficient during the learning phase. Also the validity of the designed model was evaluated with other experimental data not used during the training phase and nonlinear flux behavior was accurately estimated with 0.999 of correlation coefficient and a lower error of prediction in the testing phase. This good flux prediction can provide preliminary criteria in membrane design and set up the proper cleaning cycle in membrane operation. The KNT-artificial neural network is also expected to predict the variation of transmembrane pressure during filtration cycles and can be applied to automation and control of full scale treatment plants.

Predictive power of the grace score in population with diabetes.

PubMed

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

2017-12-01

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

The Social Meaning in Life Events Scale (SMILES): A preliminary psychometric evaluation in a bereaved sample.

PubMed

Bellet, Benjamin W; Holland, Jason M; Neimeyer, Robert A

2018-06-05

A mourner's success in making meaning of a loss has proven key in predicting a wide array of bereavement outcomes. However, much of this meaning-making process takes place in an interpersonal framework that is hypothesized to either aid or obstruct this process. To date, a psychometrically validated measure of the degree to which a mourner successfully makes meaning of a loss in a social context has yet to be developed. The present study examines the factor structure, reliability, and validity of a new measure called the Social Meaning in Life Events Scale (SMILES) in a sample of bereaved college students (N = 590). The SMILES displayed a two-factor structure, with one factor assessing the extent to which a mourner's efforts at making meaning were invalidated (Social Invalidation subscale), and the other assessing the extent to which a mourner's meaning-making process was validated (Social Validation subscale). The subscales displayed good reliability and construct validity in reference to several outcome variables of interest (complicated grief, general health, and post-loss growth), as well as related but different variables (social support and meaning made). The subscales also demonstrated group differences according to two demographic variables associated with complications in the mourning process (age and mode of loss), as well as incremental validity in predicting adverse bereavement outcomes over and above general social support. Clinical and research implications involving the use of this new measure are discussed.

A Diagnostic Calculator for Detecting Glaucoma on the Basis of Retinal Nerve Fiber Layer, Optic Disc, and Retinal Ganglion Cell Analysis by Optical Coherence Tomography.

PubMed

Larrosa, José Manuel; Moreno-Montañés, Javier; Martinez-de-la-Casa, José María; Polo, Vicente; Velázquez-Villoria, Álvaro; Berrozpe, Clara; García-Granero, Marta

2015-10-01

The purpose of this study was to develop and validate a multivariate predictive model to detect glaucoma by using a combination of retinal nerve fiber layer (RNFL), retinal ganglion cell-inner plexiform (GCIPL), and optic disc parameters measured using spectral-domain optical coherence tomography (OCT). Five hundred eyes from 500 participants and 187 eyes of another 187 participants were included in the study and validation groups, respectively. Patients with glaucoma were classified in five groups based on visual field damage. Sensitivity and specificity of all glaucoma OCT parameters were analyzed. Receiver operating characteristic curves (ROC) and areas under the ROC (AUC) were compared. Three predictive multivariate models (quantitative, qualitative, and combined) that used a combination of the best OCT parameters were constructed. A diagnostic calculator was created using the combined multivariate model. The best AUC parameters were: inferior RNFL, average RNFL, vertical cup/disc ratio, minimal GCIPL, and inferior-temporal GCIPL. Comparisons among the parameters did not show that the GCIPL parameters were better than those of the RNFL in early and advanced glaucoma. The highest AUC was in the combined predictive model (0.937; 95% confidence interval, 0.911-0.957) and was significantly (P = 0.0001) higher than the other isolated parameters considered in early and advanced glaucoma. The validation group displayed similar results to those of the study group. Best GCIPL, RNFL, and optic disc parameters showed a similar ability to detect glaucoma. The combined predictive formula improved the glaucoma detection compared to the best isolated parameters evaluated. The diagnostic calculator obtained good classification from participants in both the study and validation groups.

A Mathematical Model on Water Redistribution Mechanism of the Seismonastic Movement of Mimosa Pudica

PubMed Central

Kwan, K.W.; Ye, Z.W.; Chye, M.L.; Ngan, A.H.W.

2013-01-01

A theoretical model based on the water redistribution mechanism is proposed to predict the volumetric strain of motor cells in Mimosa pudica during the seismonastic movement. The model describes the water and ion movements following the opening of ion channels triggered by stimulation. The cellular strain is related to the angular velocity of the plant movement, and both their predictions are in good agreement with experimental data, thus validating the water redistribution mechanism. The results reveal that an increase in ion diffusivity across the cell membrane of <15-fold is sufficient to produce the observed seismonastic movement. PMID:23823246

Brownian systems with spatially inhomogeneous activity

NASA Astrophysics Data System (ADS)

Sharma, A.; Brader, J. M.

2017-09-01

We generalize the Green-Kubo approach, previously applied to bulk systems of spherically symmetric active particles [J. Chem. Phys. 145, 161101 (2016), 10.1063/1.4966153], to include spatially inhomogeneous activity. The method is applied to predict the spatial dependence of the average orientation per particle and the density. The average orientation is given by an integral over the self part of the Van Hove function and a simple Gaussian approximation to this quantity yields an accurate analytical expression. Taking this analytical result as input to a dynamic density functional theory approximates the spatial dependence of the density in good agreement with simulation data. All theoretical predictions are validated using Brownian dynamics simulations.

Homogenization kinetics of a nickel-based superalloy produced by powder bed fusion laser sintering

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

Zhang, Fan; Levine, Lyle E.; Allen, Andrew J.

2017-04-01

Additively manufactured (AM) metal components often exhibit fine dendritic microstructures and elemental segregation due to the initial rapid solidification and subsequent melting and cooling during the build process, which without homogenization would adversely affect materials performance. In this letter, we report in situ observation of the homogenization kinetics of an AM nickel-based superalloy using synchrotron small angle X-ray scattering. The identified kinetic time scale is in good agreement with thermodynamic diffusion simulation predictions using microstructural dimensions acquired by ex situ scanning electron microscopy. These findings could serve as a recipe for predicting, observing, and validating homogenization treatments in AM materials.

Homogenization Kinetics of a Nickel-based Superalloy Produced by Powder Bed Fusion Laser Sintering.

PubMed

Zhang, Fan; Levine, Lyle E; Allen, Andrew J; Campbell, Carelyn E; Lass, Eric A; Cheruvathur, Sudha; Stoudt, Mark R; Williams, Maureen E; Idell, Yaakov

2017-04-01

Additively manufactured (AM) metal components often exhibit fine dendritic microstructures and elemental segregation due to the initial rapid solidification and subsequent melting and cooling during the build process, which without homogenization would adversely affect materials performance. In this letter, we report in situ observation of the homogenization kinetics of an AM nickel-based superalloy using synchrotron small angle X-ray scattering. The identified kinetic time scale is in good agreement with thermodynamic diffusion simulation predictions using microstructural dimensions acquired by ex situ scanning electron microscopy. These findings could serve as a recipe for predicting, observing, and validating homogenization treatments in AM materials.

Prediction of facial cooling while walking in cold wind.

PubMed

Tikuisis, Peter; Ducharme, Michel B; Brajkovic, Dragan

2007-09-01

A dynamic model of cheek cooling has been modified to account for increased skin blood circulation of individuals walking in cold wind. This was achieved by modelling the cold-induced vasodilation response to cold as a varying blood perfusion term, which provided a source of convective heat to the skin tissues of the model. Physiologically-valid blood perfusion was fitted to replicate the cheek skin temperature responses of 12 individuals experimentally exposed to air temperatures from -10 to 10 degrees C at wind speeds from 2 to 8 ms(-1). Resultant cheek skin temperatures met goodness-of-fit criteria and implications on wind chill predictions are discussed.

Blade loss transient dynamic analysis of turbomachinery

NASA Technical Reports Server (NTRS)

Stallone, M. J.; Gallardo, V.; Storace, A. F.; Bach, L. J.; Black, G.; Gaffney, E. F.

1982-01-01

This paper reports on work completed to develop an analytical method for predicting the transient non-linear response of a complete aircraft engine system due to the loss of a fan blade, and to validate the analysis by comparing the results against actual blade loss test data. The solution, which is based on the component element method, accounts for rotor-to-casing rubs, high damping and rapid deceleration rates associated with the blade loss event. A comparison of test results and predicted response show good agreement except for an initial overshoot spike not observed in test. The method is effective for analysis of large systems.

Optimization of Nd: YAG Laser Marking of Alumina Ceramic Using RSM And ANN

NASA Astrophysics Data System (ADS)

Peter, Josephine; Doloi, B.; Bhattacharyya, B.

2011-01-01

The present research papers deals with the artificial neural network (ANN) and the response surface methodology (RSM) based mathematical modeling and also an optimization analysis on marking characteristics on alumina ceramic. The experiments have been planned and carried out based on Design of Experiment (DOE). It also analyses the influence of the major laser marking process parameters and the optimal combination of laser marking process parametric setting has been obtained. The output of the RSM optimal data is validated through experimentation and ANN predictive model. A good agreement is observed between the results based on ANN predictive model and actual experimental observations.

External validation of the DRAGON score in an elderly Spanish population: prediction of stroke prognosis after IV thrombolysis.

PubMed

Giralt-Steinhauer, Eva; Rodríguez-Campello, Ana; Cuadrado-Godia, Elisa; Ois, Ángel; Jiménez-Conde, Jordi; Soriano-Tárraga, Carolina; Roquer, Jaume

2013-01-01

Intravenous (i.v.) thrombolysis within 4.5 h of symptom onset has proven efficacy in acute ischemic stroke treatment, although half of all outcomes are unfavorable. The recently published DRAGON score aims to predict the 3-month outcome in stroke patients who have received i.v. alteplase. The purpose of this study was an external validation of the results of the DRAGON score in a Spanish cohort. Patients with acute stroke treated with alteplase were prospectively registered in our BasicMar database. We collected demographic characteristics, vascular risk factors, the time from stroke onset to treatment, baseline serum glucose levels and stroke severity for this population. We then reviewed hyperdense cerebral artery signs and signs of early infarct on the admission CT scan. We calculated the DRAGON score and used the developers' 3-month prognosis categories: good [modified Rankin Scale score (mRS) 0-2], poor (mRS 3-6) and miserable (mRS 5-6) outcome. Discrimination was tested using the area under the receiver operator curve (AUC-ROC). Calibration was assessed by the Hosmer-Lemeshow test. Our final cohort of 297 patients was older (median age 74 years, IQR 65-80) and had more risk factors and severe strokes [median National Institutes of Health Stroke Scale (NIHSS) points 13, IQR 7-19] than the original study population. Poor prognosis was observed in 143 (48.1%) patients. Higher DRAGON scores were associated with a higher risk of poor prognosis. None of our treated stroke patients with a DRAGON score ≥8 at admission experienced a favorable outcome after 3 months. All DRAGON variables were significantly associated with a worse outcome in the multivariate analysis except for onset-to-treatment time (p = 0.334). Discrimination to predict poor prognosis was very good (AUC-ROC 0.84) and the score had good Hosmer-Lemeshow calibration (p = 0.84). The DRAGON score is easy to perform and offers a rapid, reliable prediction of poor prognosis in acute-stroke patients treated with alteplase. This study replicates the original results in a different population. Copyright © 2013 S. Karger AG, Basel.

Intelligent processing for thick composites

NASA Astrophysics Data System (ADS)

Shin, Daniel Dong-Ok

2000-10-01

Manufacturing thick composite parts are associated with adverse curing conditions such as large in-plane temperature gradient and exotherms. The condition is further aggravated because the manufacturer's cycle and the existing cure control systems do not adequately counter such affects. In response, the forecast-based thermal control system is developed to have better cure control for thick composites. Accurate cure kinetic model is crucial for correctly identifying the amount of heat generated for composite process simulation. A new technique for identifying cure parameters for Hercules AS4/3502 prepreg is presented by normalizing the DSC data. The cure kinetics is based on an autocatalytic model for the proposed method, which uses dynamic and isothermal DSC data to determine its parameters. Existing models are also used to determine kinetic parameters but rendered inadequate because of the material's temperature dependent final degree of cure. The model predictions determined from the new technique showed good agreement to both isothermal and dynamic DSC data. The final degree of cure was also in good agreement with experimental data. A realistic cure simulation model including bleeder ply analysis and compaction is validated with Hercules AS4/3501-6 based laminates. The nonsymmetrical temperature distribution resulting from the presence of bleeder plies agreed well to the model prediction. Some of the discrepancies in the predicted compaction behavior were attributed to inaccurate viscosity and permeability models. The temperature prediction was quite good for the 3cm laminate. The validated process simulation model along with cure kinetics model for AS4/3502 prepreg were integrated into the thermal control system. The 3cm Hercules AS4/3501-6 and AS4/3502 laminate were fabricated. The resulting cure cycles satisfied all imposed requirements by minimizing exotherms and temperature gradient. Although the duration of the cure cycles increased, such phenomena was inevitable since longer time was required to maintain acceptable temperature gradient. The derived cure cycles were slightly different than what was anticipated by the offline simulation. Nevertheless, the system adapted to unanticipated events to satisfy the cure requirements.

A novel measure of compulsive food restriction in anorexia nervosa: validation of the Self-Starvation Scale (SS).

PubMed

Godier, Lauren R; Park, Rebecca J

2015-04-01

The characteristic relentless self-starvation behaviour seen in Anorexia Nervosa (AN) has been described as evidence of compulsivity, with increasing suggestion of transdiagnostic parallels with addictive behaviour. There is a paucity of standardised self-report measures of compulsive behaviour in eating disorders (EDs). Measures that index the concept of compulsive self-starvation in AN are needed to explore the suggested parallels with addictions. With this aim a novel measure of self-starvation was developed (the Self-Starvation Scale, SS). 126 healthy participants, and 78 individuals with experience of AN, completed the new measure along with existing measures of eating disorder symptoms, anxiety and depression. Initial validation in the healthy sample indicated good reliability and construct validity, and incremental validity in predicting eating disorder symptoms. The psychometric properties of the SS scale were replicated in the AN sample. The ability of this scale to predict ED symptoms was particularly strong in individuals currently suffering from AN. These results suggest the SS may be a useful index of compulsive food restriction in AN. The concept of 'starvation dependence' in those with eating disorders, as a parallel with addiction, may be of clinical and theoretical importance. Copyright © 2014 Elsevier Ltd. All rights reserved.

[Reliability and validity of a Mexican version of the Pro Children Project questionnaire].

PubMed

Ochoa-Meza, Gerardo; Sierra, Juan Carlos; Pérez-Rodrigo, Carmen; Aranceta Bartrina, Javier; Esparza-Del Villar, Óscar A

2014-08-01

To determine the test-retest reliability, the internal consistency, and the predictive validity of the constructs of the Mexican version of the Pro Children Project questionnaire (PCHP) for assessing personal and environmental factors related to fruit and vegetable intake in 10-12 year-old schoolchildren. Test-retest design with a 14 days interval. A sample of 957 children completed the questionnaire with 82 items. The study was conducted at eight primary schools in 2012 in Ciudad Juarez, Chihuahua, Mexico. For all fruit constructs and vegetable constructs, the test-retest reliability was moderate (intraclass correlation coefficient (ICC) > 0.60). Cronbach s alpha values were from moderate to high (range of 0.54 to 0.92) similar to those in the original study. Values for predictive validity ranged from moderate to good with Spearman correlations between 0.23 and 0.60 for personal factors and between 0.14 and 0.40 for environmental factors. The results of the Mexican version of the PCHP questionnaire provide a sufficient reliability and validity for assessing personal and environmental factors of fruit and vegetable intake in 10-12 year old schoolchildren. Finally, implications to administer this instrument in scholar settings and guidelines for futures studies are discussed. Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.

Analysis of expert validation on developing integrated science worksheet to improve problem solving skills of natural science prospective teachers

NASA Astrophysics Data System (ADS)

Widodo, W.; Sudibyo, E.; Sari, D. A. P.

2018-04-01

This study aims to develop student worksheets for higher education that apply integrated science learning in discussing issues about motion in humans. These worksheets will guide students to solve the problem about human movement. They must integrate their knowledge about biology, physics, and chemistry to solve the problem. The worksheet was validated by three experts in Natural Science Integrated Science, especially in Human Movement topic. The aspects of the validation were feasibility of the content, the construction, and the language. This research used the Likert scale to measure the validity of each aspect, which is 4.00 for very good validity criteria, 3.00 for good validity criteria, 2.00 for more or less validity criteria, and 1.00 for not good validity criteria. Data showed that the validity for each aspect were in the range of good validity and very good validity criteria (3.33 to 3.67 for the content aspect, 2.33 to 4.00 for the construction aspect, and 3.33 to 4.00 for language aspect). However, there was a part of construction aspect that needed to improve. Overall, this students’ worksheet can be applied in classroom after some revisions based on suggestions from the validators.

Evaluation of ride quality prediction methods for operational military helicopters

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Clevenson, S. A.; Hollenbaugh, D. D.

1984-01-01

The results of a simulator study conducted to compare and validate various ride quality prediction methods for use in assessing passenger/crew ride comfort within helicopters are presented. Included are results quantifying 35 helicopter pilots' discomfort responses to helicopter interior noise and vibration typical of routine flights, assessment of various ride quality metrics including the NASA ride comfort model, and examination of possible criteria approaches. Results of the study indicated that crew discomfort results from a complex interaction between vibration and interior noise. Overall measures such as weighted or unweighted root-mean-square acceleration level and A-weighted noise level were not good predictors of discomfort. Accurate prediction required a metric incorporating the interactive effects of both noise and vibration. The best metric for predicting crew comfort to the combined noise and vibration environment was the NASA discomfort index.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks.

PubMed

Khan, Taimoor; De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results.

Prediction of Slot Shape and Slot Size for Improving the Performance of Microstrip Antennas Using Knowledge-Based Neural Networks

PubMed Central

De, Asok

2014-01-01

In the last decade, artificial neural networks have become very popular techniques for computing different performance parameters of microstrip antennas. The proposed work illustrates a knowledge-based neural networks model for predicting the appropriate shape and accurate size of the slot introduced on the radiating patch for achieving desired level of resonance, gain, directivity, antenna efficiency, and radiation efficiency for dual-frequency operation. By incorporating prior knowledge in neural model, the number of required training patterns is drastically reduced. Further, the neural model incorporated with prior knowledge can be used for predicting response in extrapolation region beyond the training patterns region. For validation, a prototype is also fabricated and its performance parameters are measured. A very good agreement is attained between measured, simulated, and predicted results. PMID:27382616

An Integrative Model of Physiological Traits Can be Used to Predict Obstructive Sleep Apnea and Response to Non Positive Airway Pressure Therapy.

PubMed

Owens, Robert L; Edwards, Bradley A; Eckert, Danny J; Jordan, Amy S; Sands, Scott A; Malhotra, Atul; White, David P; Loring, Stephen H; Butler, James P; Wellman, Andrew

2015-06-01

Both anatomical and nonanatomical traits are important in obstructive sleep apnea (OSA) pathogenesis. We have previously described a model combining these traits, but have not determined its diagnostic accuracy to predict OSA. A valid model, and knowledge of the published effect sizes of trait manipulation, would also allow us to predict the number of patients with OSA who might be effectively treated without using positive airway pressure (PAP). Fifty-seven subjects with and without OSA underwent standard clinical and research sleep studies to measure OSA severity and the physiological traits important for OSA pathogenesis, respectively. The traits were incorporated into a physiological model to predict OSA. The model validity was determined by comparing the model prediction of OSA to the clinical diagnosis of OSA. The effect of various trait manipulations was then simulated to predict the proportion of patients treated by each intervention. The model had good sensitivity (80%) and specificity (100%) for predicting OSA. A single intervention on one trait would be predicted to treat OSA in approximately one quarter of all patients. Combination therapy with two interventions was predicted to treat OSA in ∼50% of patients. An integrative model of physiological traits can be used to predict population-wide and individual responses to non-PAP therapy. Many patients with OSA would be expected to be treated based on known trait manipulations, making a strong case for the importance of non-anatomical traits in OSA pathogenesis and the effectiveness of non-PAP therapies. © 2015 Associated Professional Sleep Societies, LLC.

Measuring disability: a systematic review of the validity and reliability of the Global Activity Limitations Indicator (GALI).

PubMed

Van Oyen, Herman; Bogaert, Petronille; Yokota, Renata T C; Berger, Nicolas

2018-01-01

GALI or Global Activity Limitation Indicator is a global survey instrument measuring participation restriction. GALI is the measure underlying the European indicator Healthy Life Years (HLY). Gali has a substantial policy use within the EU and its Member States. The objective of current paper is to bring together what is known from published manuscripts on the validity and the reliability of GALI. Following the PRISMA guidelines, two search strategies (PUBMED, Google Scholar) were combined to identify manuscripts published in English with publication date 2000 or beyond. Articles were classified as reliability studies, concurrent or predictive validity studies, in national or international populations. Four cross-sectional studies (of which 2 international) studied how GALI relates to other health measures (concurrent validity). A dose-response effect by GALI severity level on the association with the other health status measures was observed in the national studies. The 2 international studies (SHARE, EHIS) concluded that the odds of reporting participation restriction was higher in subjects with self-reported or observed functional limitations. In SHARE, the size of the Odds Ratio's (ORs) in the different countries was homogeneous, while in EHIS the size of the ORs varied more strongly. For the predictive validity, subjects were followed over time (4 studies of which one international). GALI proved, both in national and international data, to be a consistent predictor of future health outcomes both in terms of mortality and health care expenditure. As predictors of mortality, the two distinct health concepts, self-rated health and GALI, acted independently and complementary of each other. The one reliability study identified reported a sufficient reliability of GALI. GALI as inclusive one question instrument fits all conceptual characteristics specified for a global measure on participation restriction. In none of the studies, included in the review, there was evidence of a failing validity. The review shows that GALI has a good and sufficient concurrent and predictive validity, and reliability.

Development and validation of a clinical prediction rule to identify suspected breast cancer: a prospective cohort study.

PubMed

Galvin, Rose; Joyce, Doireann; Downey, Eithne; Boland, Fiona; Fahey, Tom; Hill, Arnold K

2014-10-03

The number of primary care referrals of women with breast symptoms to symptomatic breast units (SBUs) has increased exponentially in the past decade in Ireland. The aim of this study is to develop and validate a clinical prediction rule (CPR) to identify women with breast cancer so that a more evidence based approach to referral from primary care to these SBUs can be developed. We analysed routine data from a prospective cohort of consecutive women reviewed at a SBU with breast symptoms. The dataset was split into a derivation and validation cohort. Regression analysis was used to derive a CPR from the patient's history and clinical findings. Validation of the CPR consisted of estimating the number of breast cancers predicted to occur compared with the actual number of observed breast cancers across deciles of risk. A total of 6,590 patients were included in the derivation study and 4.9% were diagnosed with breast cancer. Independent clinical predictors for breast cancer were: increasing age by year (adjusted odds ratio 1.08, 95% CI 1.07-1.09); presence of a lump (5.63, 95% CI 4.2-7.56); nipple change (2.77, 95% CI 1.68-4.58) and nipple discharge (2.09, 95% CI 1.1-3.97). Validation of the rule (n = 911) demonstrated that the probability of breast cancer was higher with an increasing number of these independent variables. The Hosmer-Lemeshow goodness of fit showed no overall significant difference between the expected and the observed numbers of breast cancer (χ(2)HL: 6.74, p-value: 0.56). This study derived and validated a CPR for breast cancer in women attending an Irish national SBU. We found that increasing age, presence of a lump, nipple discharge and nipple change are all associated with increased risk of breast cancer. Further validation of the rule is necessary as well as an assessment of its impact on referral practice.

Prediction of Process-Induced Distortions in L-Shaped Composite Profiles Using Path-Dependent Constitutive Law

NASA Astrophysics Data System (ADS)

Ding, Anxin; Li, Shuxin; Wang, Jihui; Ni, Aiqing; Sun, Liangliang; Chang, Lei

2016-10-01

In this paper, the corner spring-in angles of AS4/8552 L-shaped composite profiles with different thicknesses are predicted using path-dependent constitutive law with the consideration of material properties variation due to phase change during curing. The prediction accuracy mainly depends on the properties in the rubbery and glassy states obtained by homogenization method rather than experimental measurements. Both analytical and finite element (FE) homogenization methods are applied to predict the overall properties of AS4/8552 composite. The effect of fiber volume fraction on the properties is investigated for both rubbery and glassy states using both methods. And the predicted results are compared with experimental measurements for the glassy state. Good agreement is achieved between the predicted results and available experimental data, showing the reliability of the homogenization method. Furthermore, the corner spring-in angles of L-shaped composite profiles are measured experimentally and the reliability of path-dependent constitutive law is validated as well as the properties prediction by FE homogenization method.

Reliability, validity, sensitivity and specificity of Guajarati version of the Roland-Morris Disability Questionnaire.

PubMed

Nambi, S Gopal

2013-01-01

The most common instruments developed to assess the functional status of patients with Non specific low back pain is the Roland-Morris Disability Questionnaire (RMDQ). Clinical and epidemiological research related to low back pain in the Gujarati population would be facilitated by the availability of well-established outcome measures. To find the reliability, validity, sensitivity and specificity of the Gujarati version of the RMDQ for use in Non Specific Chronic low back pain. A reliability, validity, sensitivity and specificity study of Gujarati version of the Roland-Morris Disability Questionnaire (RMDQ). Thirty out patients with Non Specific Chronic low back pain were assessed by the RMDQ. Reliability is assessed by using internal consistency and the intra-class correlation coefficient (ICC). Internal construct validity is assessed by RASCH Analysis and external construct validity is assessed by association with pain and spinal movement. Clinical calculator was used to determine the sensitivity and specificity. Internal consistency of the RMDQ is found to be adequate (> 0.65) at both times, with high ICC's also at both time points. Internal construct validity of the scale is good, indicating a single underlying construct. Expected associations with pain and spinal movement confirm external construct validity. The Sensitivity and Specificity at cut off point of 0.5 was 80% and 84% with respectively positive predictive value (PPV) of 83.33% and negative predictive value (NPV) of 80.76%. The Questionnaire is at the ordinal level. The RMDQ is a one-dimensional, ordinal measure, which works well in the Gujarati population.

Derivation of a 3D pharmacophore model for the angiotensin-II site one receptor

NASA Astrophysics Data System (ADS)

Prendergast, Kristine; Adams, Kym; Greenlee, William J.; Nachbar, Robert B.; Patchett, Arthur A.; Underwood, Dennis J.

1994-10-01

A systematic search has been used to derive a hypothesis for the receptor-bound conformation of A-II antagonists at the AT1 receptor. The validity of the pharmacophore hypothesis has been tested using CoMFA, which included 50 diverse A-II antagonists, spanning four orders of magnitude in activity. The resulting cross-validated R2 of 0.64 (conventional R2 of 0.76) is indicative of a good predictive model of activity, and has been used to estimate potency for a variety of non-peptidyl antagonists. The structural model for the non-peptide has been compared with respect to the natural substrate, A-II, by generating peptide to non-peptide overlays.

Sulfonamide-containing PTP 1B inhibitors: Docking studies, synthesis and model validation

NASA Astrophysics Data System (ADS)

Niu, Enli; Gan, Qiang; Chen, Xi; Feng, Changgen

2017-01-01

PTP 1B plays an important role in regulating insulin signaling pathway and is regarded as a valid target for curing diabetes and obesity. In this paper, two novel sulfonamide-containing PTP 1B inhibitors were designed, synthesized in mild condition, and characterized by FT-IR, 1H NMR, 13C NMR and elemental analysis. The single crystal of compounds 7 and 8 were obtained and their structures were determined by X-ray single crystal diffraction analysis. In addition, their inhibitory activity were predicted by genetic algorithm, and carried on in vitro enzyme activity test. Of which compound 8 showed good inhibitory activity, in consistent with docking studies.

Validation of the Physician Teaching Motivation Questionnaire (PTMQ).

PubMed

Dybowski, Christoph; Harendza, Sigrid

2015-10-02

Physicians play a major role as teachers in undergraduate medical education. Studies indicate that different forms and degrees of motivation can influence work performance in general and that teachers' motivation to teach can influence students' academic achievements in particular. Therefore, the aim of this study was to develop and to validate an instrument measuring teaching motivations in hospital-based physicians. We chose self-determination theory as a theoretical framework for item and scale development. It distinguishes between different dimensions of motivation depending on the amount of self-regulation and autonomy involved and its empirical evidence has been demonstrated in other areas of research. To validate the new instrument (PTMQ = Physician Teaching Motivation Questionnaire), we used data from a sample of 247 physicians from internal medicine and surgery at six German medical faculties. Structural equation modelling was conducted to confirm the factorial structure, correlation analyses and linear regressions were performed to examine concurrent and incremental validity. Structural equation modelling confirmed a good global fit for the factorial structure of the final instrument (RMSEA = .050, TLI = .957, SRMR = .055, CFI = .966). Cronbach's alphas indicated good internal consistencies for all scales (α = .75 - .89) except for the identified teaching motivation subscale with an acceptable internal consistency (α = .65). Tests of concurrent validity with global work motivation, perceived teaching competence, perceived teaching involvement and voluntariness of lesson allocation delivered theory-consistent results with slight deviations for some scales. Incremental validity over global work motivation in predicting perceived teaching involvement was also confirmed. Our results indicate that the PTMQ is a reliable, valid and therefore suitable instrument for assessing physicians' teaching motivation.

Measuring attitudes, self-efficacy, and social and environmental influences on fruit and vegetable consumption of 11- and 12-year-old children: reliability and validity.

PubMed

Vereecken, Carine Anna; Van Damme, Wendy; Maes, Lea

2005-02-01

This article examines the reliability and construct validity of questions assessing mediating factors of fruit and vegetable consumption among 11- and 12-year-old children (N=207). Internal consistencies were good for most scales, ranging from 0.56 to 0.94. Intraclass correlation coefficients between test and retest were acceptable, ranging from 0.39 to 0.90. Concerning predictive validity, preferences and perceived parental and peer behavior were significantly associated with fruit and vegetable consumption. Self-efficacy in difficult situations and a variety of available fruit were significantly correlated with fruit consumption, while permissive eating practices and obligation rules were significantly correlated with vegetable consumption. General attitudes, outcome expectations, selection efficacy, and encouraging practices were not associated with fruit or vegetable consumption.

The MOVES (Motor tic, Obsessions and compulsions, Vocal tic Evaluation Survey): cross-cultural evaluation of the French version and additional psychometric assessment.

PubMed

Jalenques, Isabelle; Guiguet-Auclair, Candy; Derost, Philippe; Joubert, Pauline; Foures, Louis; Hartmann, Andreas; Muellner, Julia; Rondepierre, Fabien

2018-03-01

The Motor tic, Obsessions and compulsions, Vocal tic Evaluation Survey (MOVES) is a self-report scale suggested as a severity scale for tics and related sensory phenomena observed in Gilles de la Tourette syndrome (GTS) and recommended as a screening instrument by the Committee on Rating Scale Development of the International Parkinson's Disease and Movement Disorder Society. To cross-culturally adapt a French version of the MOVES and to evaluate its psychometric properties. After the cross-cultural adaptation of the MOVES, we assessed its psychometric properties in 53 patients aged 12-16 years and in 54 patients aged 16 years and above: reliability and construct validity (relationships between items and scales), internal consistency and concurrent validity with the Yale Global Tic Severity Scale (YGTSS) and the Children's Yale-Brown Obsessive-Compulsive Scale (CY-BOCS) or the auto-Yale-Brown scale. The results showed very good acceptability with response rates greater than 92%, good internal consistency (Cronbach's alpha ranging from 0.62 and 0.89) and good test-retest reliability (ICCs ranging from 0.59 to 0.91). Concurrent validity with the YGTSS, CY-BOCS and auto-Yale-Brown scales showed strong expected correlations. The cut-off points tested for diagnostic performance gave satisfactory values of sensitivity, specificity, and positive and negative predictive values. Our study provides evidence of the good psychometric properties of the French version of the MOVES. The cross-cultural adaptation of this specific instrument will allow investigators to include French-speaking persons with GTS aged 12 years and over in national and international collaboration research projects.

Clinical and Psychometric Evaluations of the Cerebral Vision Screening Questionnaire in 461 Nonaphasic Individuals Poststroke.

PubMed

Neumann, Guenter; Schaadt, Anna-Katharina; Reinhart, Stefan; Kerkhoff, Georg

2016-03-01

Cerebral vision disorders (CVDs) are frequent after brain damage and impair the patient's outcome. Yet clinically and psychometrically validated procedures for the anamnesis of CVD are lacking. To evaluate the clinical validity and psychometric qualities of the Cerebral Vision Screening Questionnaire (CVSQ) for the anamnesis of CVD in individuals poststroke. Analysis of the patients' subjective visual complaints in the 10-item CVSQ in relation to objective visual perimetry, tests of reading, visual scanning, visual acuity, spatial contrast sensitivity, light/dark adaptation, and visual depth judgments. Psychometric analyses of concurrent validity, specificity, sensitivity, positive/negative predictive value, and interrater reliability were also done. Four hundred sixty-one patients with unilateral (39.5% left, 47.5% right) or bilateral stroke (13.0%) were included. Most patients were assessed in the chronic stage, on average 36.7 (range = 1-620) weeks poststroke. The majority of all patients (96.4%) recognized their visual symptoms within 1 week poststroke when asked for specifically. Mean concurrent validity of the CVSQ with objective tests was 0.64 (0.54-0.79, P < .05). The mean positive predictive value was 80.1%, mean negative predictive value 82.9%, mean specificity 81.7%, and mean sensitivity 79.8%. The mean interrater reliability was 0.76 for a 1-week interval between both assessments (all P < .05). The CVSQ is suitable for the anamnesis of CVD poststroke because of its brevity (10 minute), clinical validity, and good psychometric qualities. It, thus, improves neurovisual diagnosis and guides the clinician in the selection of necessary assessments and appropriate neurovisual therapies for the patient. © The Author(s) 2015.

A simple test of choice stepping reaction time for assessing fall risk in people with multiple sclerosis.

PubMed

Tijsma, Mylou; Vister, Eva; Hoang, Phu; Lord, Stephen R

2017-03-01

Purpose To determine (a) the discriminant validity for established fall risk factors and (b) the predictive validity for falls of a simple test of choice stepping reaction time (CSRT) in people with multiple sclerosis (MS). Method People with MS (n = 210, 21-74y) performed the CSRT, sensorimotor, balance and neuropsychological tests in a single session. They were then followed up for falls using monthly fall diaries for 6 months. Results The CSRT test had excellent discriminant validity with respect to established fall risk factors. Frequent fallers (≥3 falls) performed significantly worse in the CSRT test than non-frequent fallers (0-2 falls). With the odds of suffering frequent falls increasing 69% with each SD increase in CSRT (OR = 1.69, 95% CI: 1.27-2.26, p = <0.001). In regression analysis, CSRT was best explained by sway, time to complete the 9-Hole Peg test, knee extension strength of the weaker leg, proprioception and the time to complete the Trails B test (multiple R 2   =   0.449, p < 0.001). Conclusions A simple low tech CSRT test has excellent discriminative and predictive validity in relation to falls in people with MS. This test may prove useful in documenting longitudinal changes in fall risk in relation to MS disease progression and effects of interventions. Implications for rehabilitation Good choice stepping reaction time (CSRT) is required for maintaining balance. A simple low-tech CSRT test has excellent discriminative and predictive validity in relation to falls in people with MS. This test may prove useful documenting longitudinal changes in fall risk in relation to MS disease progression and effects of interventions.

Fundamental Movement Skills Are More than Run, Throw and Catch: The Role of Stability Skills.

PubMed

Rudd, James R; Barnett, Lisa M; Butson, Michael L; Farrow, Damian; Berry, Jason; Polman, Remco C J

2015-01-01

In motor development literature fundamental movement skills are divided into three constructs: locomotive, object control and stability skills. Most fundamental movement skills research has focused on children's competency in locomotor and object control skills. The first aim of this study was to validate a test battery to assess the construct of stability skills, in children aged 6 to 10 (M age = 8.2, SD = 1.2). Secondly we assessed how the stability skills construct fitted into a model of fundamental movement skill. The Delphi method was used to select the stability skill battery. Confirmatory factor analysis (CFA) was used to assess if the skills loaded onto the same construct and a new model of FMS was developed using structural equation modelling. Three postural control tasks were selected (the log roll, rock and back support) because they had good face and content validity. These skills also demonstrated good predictive validity with gymnasts scoring significantly better than children without gymnastic training and children from a high SES school performing better than those from a mid and low SES schools and the mid SES children scored better than the low SES children (all p < .05). Inter rater reliability tests were excellent for all three skills (ICC = 0.81, 0.87, 0.87) as was test re-test reliability (ICC 0.87-0.95). CFA provided good construct validity, and structural equation modelling revealed stability skills to be an independent factor in an overall FMS model which included locomotor (r = .88), object control (r = .76) and stability skills (r = .81). This study provides a rationale for the inclusion of stability skills in FMS assessment. The stability skills could be used alongside other FMS assessment tools to provide a holistic assessment of children's fundamental movement skills.

Infant Feeding Attitudes and Practices of Spanish Low-Risk Expectant Women Using the IIFAS (Iowa Infant Feeding Attitude Scale)

PubMed Central

Cotelo, María del Carmen Suárez; Pita-García, Paula

2018-01-01

The Iowa Infant Feeding Attitude Scale (IIFAS) has been shown to have good psychometric properties for English-speaking populations, but it has not been validated among low-risk pregnant women in Spain. The aim of this study was to assess the reliability and validity of the translated version of the IIFAS in order to examine infant feeding attitudes in Spanish women with an uncomplicated pregnancy. Low-risk expectant women (n = 297) were recruited from eight primary public health care centres in Galicia (Spain). Questionnaires including both socio-demographic and breastfeeding characteristics and items about infant feeding were administered during the third trimester. Participants were contacted by telephone during the postpartum period to obtain information regarding their infant feeding status. Prediction validity and internal consistency were assessed. The translated IIFAS (69.76 ± 7.75), which had good psychometric properties (Cronbach’s alpha = 0.785; area under the curve (AUC) of the receiver operating characteristic (ROC) curve = 0.841, CI95% = 0.735–0.948), showed more positive attitudes towards breastfeeding than towards formula feeding, especially among mothers who intended to exclusively breastfeed. This scale was also useful for inferring the intent to breastfeed and duration of breastfeeding. This study provides evidence that the IIFAS is a reliable and valid tool for assessing infant feeding attitudes in Spanish women with an uncomplicated pregnancy. PMID:29690542

Infant Feeding Attitudes and Practices of Spanish Low-Risk Expectant Women Using the IIFAS (Iowa Infant Feeding Attitude Scale).

PubMed

Cotelo, María Del Carmen Suárez; Movilla-Fernández, María Jesús; Pita-García, Paula; Novío, Silvia

2018-04-22

The Iowa Infant Feeding Attitude Scale (IIFAS) has been shown to have good psychometric properties for English-speaking populations, but it has not been validated among low-risk pregnant women in Spain. The aim of this study was to assess the reliability and validity of the translated version of the IIFAS in order to examine infant feeding attitudes in Spanish women with an uncomplicated pregnancy. Low-risk expectant women ( n = 297) were recruited from eight primary public health care centres in Galicia (Spain). Questionnaires including both socio-demographic and breastfeeding characteristics and items about infant feeding were administered during the third trimester. Participants were contacted by telephone during the postpartum period to obtain information regarding their infant feeding status. Prediction validity and internal consistency were assessed. The translated IIFAS (69.76 ± 7.75), which had good psychometric properties (Cronbach's alpha = 0.785; area under the curve (AUC) of the receiver operating characteristic (ROC) curve = 0.841, CI 95% = 0.735⁻0.948), showed more positive attitudes towards breastfeeding than towards formula feeding, especially among mothers who intended to exclusively breastfeed. This scale was also useful for inferring the intent to breastfeed and duration of breastfeeding. This study provides evidence that the IIFAS is a reliable and valid tool for assessing infant feeding attitudes in Spanish women with an uncomplicated pregnancy.

Predicting the 10-year risk of hip and major osteoporotic fracture in rheumatoid arthritis and in the general population: an independent validation and update of UK FRAX without bone mineral density.

PubMed

Klop, Corinne; de Vries, Frank; Bijlsma, Johannes W J; Leufkens, Hubert G M; Welsing, Paco M J

2016-12-01

FRAX incorporates rheumatoid arthritis (RA) as a dichotomous predictor for predicting the 10-year risk of hip and major osteoporotic fracture (MOF). However, fracture risk may deviate with disease severity, duration or treatment. Aims were to validate, and if needed to update, UK FRAX for patients with RA and to compare predictive performance with the general population (GP). Cohort study within UK Clinical Practice Research Datalink (CPRD) (RA: n=11 582, GP: n=38 755), also linked to hospital admissions for hip fracture (CPRD-Hospital Episode Statistics, HES) (RA: n=7221, GP: n=24 227). Predictive performance of UK FRAX without bone mineral density was assessed by discrimination and calibration. Updating methods included recalibration and extension. Differences in predictive performance were assessed by the C-statistic and Net Reclassification Improvement (NRI) using the UK National Osteoporosis Guideline Group intervention thresholds. UK FRAX significantly overestimated fracture risk in patients with RA, both for MOF (mean predicted vs observed 10-year risk: 13.3% vs 8.4%) and hip fracture (CPRD: 5.5% vs 3.1%, CPRD-HES: 5.5% vs 4.1%). Calibration was good for hip fracture in the GP (CPRD-HES: 2.7% vs 2.4%). Discrimination was good for hip fracture (RA: 0.78, GP: 0.83) and moderate for MOF (RA: 0.69, GP: 0.71). Extension of the recalibrated UK FRAX using CPRD-HES with duration of RA disease, glucocorticoids (>7.5 mg/day) and secondary osteoporosis did not improve the NRI (0.01, 95% CI -0.04 to 0.05) or C-statistic (0.78). UK FRAX overestimated fracture risk in RA, but performed well for hip fracture in the GP after linkage to hospitalisations. Extension of the recalibrated UK FRAX did not improve predictive performance. 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/.

Development and Validation of a Novel Scoring System for Predicting Technical Success of Chronic Total Occlusion Percutaneous Coronary Interventions: The PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) Score.

PubMed

Christopoulos, Georgios; Kandzari, David E; Yeh, Robert W; Jaffer, Farouc A; Karmpaliotis, Dimitri; Wyman, Michael R; Alaswad, Khaldoon; Lombardi, William; Grantham, J Aaron; Moses, Jeffrey; Christakopoulos, Georgios; Tarar, Muhammad Nauman J; Rangan, Bavana V; Lembo, Nicholas; Garcia, Santiago; Cipher, Daisha; Thompson, Craig A; Banerjee, Subhash; Brilakis, Emmanouil S

2016-01-11

This study sought to develop a novel parsimonious score for predicting technical success of chronic total occlusion (CTO) percutaneous coronary intervention (PCI) performed using the hybrid approach. Predicting technical success of CTO PCI can facilitate clinical decision making and procedural planning. We analyzed clinical and angiographic parameters from 781 CTO PCIs included in PROGRESS CTO (Prospective Global Registry for the Study of Chronic Total Occlusion Intervention) using a derivation and validation cohort (2:1 sampling ratio). Variables with strong association with technical success in multivariable analysis were assigned 1 point, and a 4-point score was developed from summing all points. The PROGRESS CTO score was subsequently compared with the J-CTO (Multicenter Chronic Total Occlusion Registry in Japan) score in the validation cohort. Technical success was 92.9%. On multivariable analysis, factors associated with technical success included proximal cap ambiguity (beta coefficient [b] = 0.88), moderate/severe tortuosity (b = 1.18), circumflex artery CTO (b = 0.99), and absence of "interventional" collaterals (b = 0.88). The resulting score demonstrated good calibration and discriminatory capacity in the derivation (Hosmer-Lemeshow chi-square = 2.633; p = 0.268, and receiver-operator characteristic [ROC] area = 0.778) and validation (Hosmer-Lemeshow chi-square = 5.333; p = 0.070, and ROC area = 0.720) subset. In the validation cohort, the PROGRESS CTO and J-CTO scores performed similarly in predicting technical success (ROC area 0.720 vs. 0.746, area under the curve difference = 0.026, 95% confidence interval = -0.093 to 0.144). The PROGRESS CTO score is a novel useful tool for estimating technical success in CTO PCI performed using the hybrid approach. Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

Lack of Early Improvement Predicts Poor Outcome Following Acute Intracerebral Hemorrhage.

PubMed

Yogendrakumar, Vignan; Smith, Eric E; Demchuk, Andrew M; Aviv, Richard I; Rodriguez-Luna, David; Molina, Carlos A; Silva Blas, Yolanda; Dzialowski, Imanuel; Kobayashi, Adam; Boulanger, Jean-Martin; Lum, Cheemun; Gubitz, Gord; Padma, Vasantha; Roy, Jayanta; Kase, Carlos S; Bhatia, Rohit; Ali, Myzoon; Lyden, Patrick; Hill, Michael D; Dowlatshahi, Dar

2018-04-01

There are limited data as to what degree of early neurologic change best relates to outcome in acute intracerebral hemorrhage. We aimed to derive and validate a threshold for early postintracerebral hemorrhage change that best predicts 90-day outcomes. Derivation: retrospective analysis of collated clinical stroke trial data (Virtual International Stroke Trials Archive). retrospective analysis of a prospective multicenter cohort study (Prediction of haematoma growth and outcome in patients with intracerebral haemorrhage using the CT-angiography spot sign [PREDICT]). Neurocritical and ICUs. Patients with acute intracerebral hemorrhage presenting less than 6 hours. Derivation: 552 patients; validation: 275 patients. None. We generated a receiver operating characteristic curve for the association between 24-hour National Institutes of Health Stroke Scale change and clinical outcome. The primary outcome was a modified Rankin Scale score of 4-6 at 90 days; secondary outcomes were other modified Rankin Scale score ranges (modified Rankin Scale, 2-6, 3-6, 5-6, 6). We employed Youden's J Index to select optimal cut points and calculated sensitivity, specificity, and predictive values. We determined independent predictors via multivariable logistic regression. The derived definitions were validated in the PREDICT cohort. Twenty-four-hour National Institutes of Health Stroke Scale change was strongly associated with 90-day outcome with an area under the receiver operating characteristic curve of 0.75. Youden's method showed an optimum cut point at -0.5, corresponding to National Institutes of Health Stroke Scale change of greater than or equal to 0 (a lack of clinical improvement), which was seen in 46%. Early neurologic change accurately predicted poor outcome when defined as greater than or equal to 0 (sensitivity, 65%; specificity, 73%; positive predictive value, 70%; adjusted odds ratio, 5.05 [CI, 3.25-7.85]) or greater than or equal to 4 (sensitivity, 19%; specificity, 98%; positive predictive value, 91%; adjusted odds ratio, 12.24 [CI, 4.08-36.66]). All definitions reproduced well in the validation cohort. Lack of clinical improvement at 24 hours robustly predicted poor outcome and showed good discrimination for individual patients who would do poorly. These findings are useful for prognostication and may also present as a potential early surrogate outcome for future intracerebral hemorrhage treatment trials.

Development of demi-span equations for predicting height among the Malaysian elderly.

PubMed

Ngoh, H J; Sakinah, H; Harsa Amylia, M S

2012-08-01

This study aimed to develop demi-span equations for predicting height in the Malaysian elderly and to explore the applicability of previous published demi-span equations derived from adult populations to the elderly. A cross-sectional study was conducted on Malaysian elderly aged 60 years and older. Subjects were residents of eight shelter homes in Peninsular Malaysia; 204 men and 124 women of Malay, Chinese and Indian ethnicity were included. Measurements of weight, height and demi-span were obtained using standard procedures. Statistical analyses were performed using SPSS version 18.0. The demi-span equations obtained were as follows: Men: Height (cm) = 67.51 + (1.29 x demi-span) - (0.12 x age) + 4.13; Women: Height (cm) = 67.51 + (1.29 x demi-span) - (0.12 x age). Height predicted from these new equations demonstrated good agreement with measured height and no significant differences were found between the mean values of predicted and measured heights in either gender (p>0.05). However, the heights predicted from previous published adult-derived demi-span equations failed to yield good agreement with the measured height of the elderly; significant over-estimation and underestimation of heights tended to occur (p>0.05). The new demi-span equations allow prediction of height with sufficient accuracy in the Malaysian elderly. However, further validation on other elderly samples is needed. Also, we recommend caution when using adult-derived demi-span equations to predict height in elderly people.

Numerical simulation and validation of helicopter blade-vortex interaction using coupled CFD/CSD and three levels of aerodynamic modeling

NASA Astrophysics Data System (ADS)

Amiraux, Mathieu

Rotorcraft Blade-Vortex Interaction (BVI) remains one of the most challenging flow phenomenon to simulate numerically. Over the past decade, the HART-II rotor test and its extensive experimental dataset has been a major database for validation of CFD codes. Its strong BVI signature, with high levels of intrusive noise and vibrations, makes it a difficult test for computational methods. The main challenge is to accurately capture and preserve the vortices which interact with the rotor, while predicting correct blade deformations and loading. This doctoral dissertation presents the application of a coupled CFD/CSD methodology to the problem of helicopter BVI and compares three levels of fidelity for aerodynamic modeling: a hybrid lifting-line/free-wake (wake coupling) method, with modified compressible unsteady model; a hybrid URANS/free-wake method; and a URANS-based wake capturing method, using multiple overset meshes to capture the entire flow field. To further increase numerical correlation, three helicopter fuselage models are implemented in the framework. The first is a high resolution 3D GPU panel code; the second is an immersed boundary based method, with 3D elliptic grid adaption; the last one uses a body-fitted, curvilinear fuselage mesh. The main contribution of this work is the implementation and systematic comparison of multiple numerical methods to perform BVI modeling. The trade-offs between solution accuracy and computational cost are highlighted for the different approaches. Various improvements have been made to each code to enhance physical fidelity, while advanced technologies, such as GPU computing, have been employed to increase efficiency. The resulting numerical setup covers all aspects of the simulation creating a truly multi-fidelity and multi-physics framework. Overall, the wake capturing approach showed the best BVI phasing correlation and good blade deflection predictions, with slightly under-predicted aerodynamic loading magnitudes. However, it proved to be much more expensive than the other two methods. Wake coupling with RANS solver had very good loading magnitude predictions, and therefore good acoustic intensities, with acceptable computational cost. The lifting-line based technique often had over-predicted aerodynamic levels, due to the degree of empiricism of the model, but its very short run-times, thanks to GPU technology, makes it a very attractive approach.

Coupling of EIT with computational lung modeling for predicting patient-specific ventilatory responses.

PubMed

Roth, Christian J; Becher, Tobias; Frerichs, Inéz; Weiler, Norbert; Wall, Wolfgang A

2017-04-01

Providing optimal personalized mechanical ventilation for patients with acute or chronic respiratory failure is still a challenge within a clinical setting for each case anew. In this article, we integrate electrical impedance tomography (EIT) monitoring into a powerful patient-specific computational lung model to create an approach for personalizing protective ventilatory treatment. The underlying computational lung model is based on a single computed tomography scan and able to predict global airflow quantities, as well as local tissue aeration and strains for any ventilation maneuver. For validation, a novel "virtual EIT" module is added to our computational lung model, allowing to simulate EIT images based on the patient's thorax geometry and the results of our numerically predicted tissue aeration. Clinically measured EIT images are not used to calibrate the computational model. Thus they provide an independent method to validate the computational predictions at high temporal resolution. The performance of this coupling approach has been tested in an example patient with acute respiratory distress syndrome. The method shows good agreement between computationally predicted and clinically measured airflow data and EIT images. These results imply that the proposed framework can be used for numerical prediction of patient-specific responses to certain therapeutic measures before applying them to an actual patient. In the long run, definition of patient-specific optimal ventilation protocols might be assisted by computational modeling. NEW & NOTEWORTHY In this work, we present a patient-specific computational lung model that is able to predict global and local ventilatory quantities for a given patient and any selected ventilation protocol. For the first time, such a predictive lung model is equipped with a virtual electrical impedance tomography module allowing real-time validation of the computed results with the patient measurements. First promising results obtained in an acute respiratory distress syndrome patient show the potential of this approach for personalized computationally guided optimization of mechanical ventilation in future. Copyright © 2017 the American Physiological Society.

Prediction of Response to Preoperative Chemoradiotherapy in Rectal Cancer by Multiplex Kinase Activity Profiling

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

Folkvord, Sigurd; Flatmark, Kjersti; Department of Cancer and Surgery, Norwegian Radium Hospital, Oslo University Hospital

2010-10-01

Purpose: Tumor response of rectal cancer to preoperative chemoradiotherapy (CRT) varies considerably. In experimental tumor models and clinical radiotherapy, activity of particular subsets of kinase signaling pathways seems to predict radiation response. This study aimed to determine whether tumor kinase activity profiles might predict tumor response to preoperative CRT in locally advanced rectal cancer (LARC). Methods and Materials: Sixty-seven LARC patients were treated with a CRT regimen consisting of radiotherapy, fluorouracil, and, where possible, oxaliplatin. Pretreatment tumor biopsy specimens were analyzed using microarrays with kinase substrates, and the resulting substrate phosphorylation patterns were correlated with tumor response to preoperative treatmentmore » as assessed by histomorphologic tumor regression grade (TRG). A predictive model for TRG scores from phosphosubstrate signatures was obtained by partial-least-squares discriminant analysis. Prediction performance was evaluated by leave-one-out cross-validation and use of an independent test set. Results: In the patient population, 73% and 15% were scored as good responders (TRG 1-2) or intermediate responders (TRG 3), whereas 12% were assessed as poor responders (TRG 4-5). In a subset of 7 poor responders and 12 good responders, treatment outcome was correctly predicted for 95%. Application of the prediction model on the remaining patient samples resulted in correct prediction for 85%. Phosphosubstrate signatures generated by poor-responding tumors indicated high kinase activity, which was inhibited by the kinase inhibitor sunitinib, and several discriminating phosphosubstrates represented proteins derived from signaling pathways implicated in radioresistance. Conclusions: Multiplex kinase activity profiling may identify functional biomarkers predictive of tumor response to preoperative CRT in LARC.« less

Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

NASA Technical Reports Server (NTRS)

Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

1999-01-01

Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

USGS Publications Warehouse

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

Evaluating the complementary roles of an SJT and academic assessment for entry into clinical practice.

PubMed

Cousans, Fran; Patterson, Fiona; Edwards, Helena; Walker, Kim; McLachlan, John C; Good, David

2017-05-01

Although there is extensive evidence confirming the predictive validity of situational judgement tests (SJTs) in medical education, there remains a shortage of evidence for their predictive validity for performance of postgraduate trainees in their first role in clinical practice. Moreover, to date few researchers have empirically examined the complementary roles of academic and non-academic selection methods in predicting in-role performance. This is an important area of enquiry as despite it being common practice to use both types of methods within a selection system, there is currently no evidence that this approach translates into increased predictive validity of the selection system as a whole, over that achieved by the use of a single selection method. In this preliminary study, the majority of the range of scores achieved by successful applicants to the UK Foundation Programme provided a unique opportunity to address both of these areas of enquiry. Sampling targeted high (>80th percentile) and low (<20th percentile) scorers on the SJT. Supervisors rated 391 trainees' in-role performance, and incidence of remedial action was collected. SJT and academic performance scores correlated with supervisor ratings (r = .31 and .28, respectively). The relationship was stronger between the SJT and in-role performance for the low scoring group (r = .33, high scoring group r = .11), and between academic performance and in-role performance for the high scoring group (r = .29, low scoring group r = .11). Trainees with low SJT scores were almost five times more likely to receive remedial action. Results indicate that an SJT for entry into trainee physicians' first role in clinical practice has good predictive validity of supervisor-rated performance and incidence of remedial action. In addition, an SJT and a measure of academic performance appeared to be complementary to each other. These initial findings suggest that SJTs may be more predictive at the lower end of a scoring distribution, and academic attainment more predictive at the higher end.

Validation of published Stirling engine design methods using engine characteristics from the literature

NASA Technical Reports Server (NTRS)

Martini, W. R.

1980-01-01

Four fully disclosed reference engines and five design methods are discussed. So far, the agreement between theory and experiment is about as good for the simpler calculation methods as it is for the more complicated methods, that is, within 20%. For the simpler methods, a one number adjustable constant can be used to reduce the error in predicting power output and efficiency over the entire operating map to less than 10%.

Linear and nonlinear methods in modeling the aqueous solubility of organic compounds.

PubMed

Catana, Cornel; Gao, Hua; Orrenius, Christian; Stouten, Pieter F W

2005-01-01

Solubility data for 930 diverse compounds have been analyzed using linear Partial Least Square (PLS) and nonlinear PLS methods, Continuum Regression (CR), and Neural Networks (NN). 1D and 2D descriptors from MOE package in combination with E-state or ISIS keys have been used. The best model was obtained using linear PLS for a combination between 22 MOE descriptors and 65 ISIS keys. It has a correlation coefficient (r2) of 0.935 and a root-mean-square error (RMSE) of 0.468 log molar solubility (log S(w)). The model validated on a test set of 177 compounds not included in the training set has r2 0.911 and RMSE 0.475 log S(w). The descriptors were ranked according to their importance, and at the top of the list have been found the 22 MOE descriptors. The CR model produced results as good as PLS, and because of the way in which cross-validation has been done it is expected to be a valuable tool in prediction besides PLS model. The statistics obtained using nonlinear methods did not surpass those got with linear ones. The good statistic obtained for linear PLS and CR recommends these models to be used in prediction when it is difficult or impossible to make experimental measurements, for virtual screening, combinatorial library design, and efficient leads optimization.

The validity of the potential model in predicting the structural, dynamical, thermodynamic properties of the unary and binary mixture of water-alcohol: Methanol-water case

NASA Astrophysics Data System (ADS)

Obeidat, Abdalla; Abu-Ghazleh, Hind

2018-06-01

Two intermolecular potential models of methanol (TraPPE-UA and OPLS-AA) have been used in order to examine their validity in reproducing the selected structural, dynamical, and thermodynamic properties in the unary and binary systems. These two models are combined with two water models (SPC/E and TIP4P). The temperature dependence of density, surface tension, diffusion and structural properties for the unary system has been computed over specific range of temperatures (200-300K). The very good performance of the TraPPE-UA potential model in predicting surface tension, diffusion, structure, and density of the unary system led us to examine its accuracy and performance in its aqueous solution. In the binary system the same properties were examined, using different mole fractions of methanol. The TraPPE-UA model combined with TIP4P-water shows a very good agreement with the experimental results for density and surface tension properties; whereas the OPLS-AA combined with SPCE-water shows a very agreement with experimental results regarding the diffusion coefficients. Two different approaches have been used in calculating the diffusion coefficient in the mixture, namely the Einstein equation (EE) and Green-Kubo (GK) method. Our results show the advantageous of applying GK over EE in reproducing the experimental results and in saving computer time.

Neuro-genetic non-invasive temperature estimation: intensity and spatial prediction.

PubMed

Teixeira, César A; Ruano, M Graça; Ruano, António E; Pereira, Wagner C A

2008-06-01

The existence of proper non-invasive temperature estimators is an essential aspect when thermal therapy applications are envisaged. These estimators must be good predictors to enable temperature estimation at different operational situations, providing better control of the therapeutic instrumentation. In this work, radial basis functions artificial neural networks were constructed to access temperature evolution on an ultrasound insonated medium. The employed models were radial basis functions neural networks with external dynamics induced by their inputs. Both the most suited set of model inputs and number of neurons in the network were found using the multi-objective genetic algorithm. The neural models were validated in two situations: the operating ones, as used in the construction of the network; and in 11 unseen situations. The new data addressed two new spatial locations and a new intensity level, assessing the intensity and space prediction capacity of the proposed model. Good performance was obtained during the validation process both in terms of the spatial points considered and whenever the new intensity level was within the range of applied intensities. A maximum absolute error of 0.5 degrees C+/-10% (0.5 degrees C is the gold-standard threshold in hyperthermia/diathermia) was attained with low computationally complex models. The results confirm that the proposed neuro-genetic approach enables foreseeing temperature propagation, in connection to intensity and space parameters, thus enabling the assessment of different operating situations with proper temperature resolution.

Simultaneous Determination of Metamizole, Thiamin and Pyridoxin Using UV-Spectroscopy in Combination with Multivariate Calibration

PubMed Central

Chotimah, Chusnul; Sudjadi; Riyanto, Sugeng; Rohman, Abdul

2015-01-01

Purpose: Analysis of drugs in multicomponent system officially is carried out using chromatographic technique, however, this technique is too laborious and involving sophisticated instrument. Therefore, UV-VIS spectrophotometry coupled with multivariate calibration of partial least square (PLS) for quantitative analysis of metamizole, thiamin and pyridoxin is developed in the presence of cyanocobalamine without any separation step. Methods: The calibration and validation samples are prepared. The calibration model is prepared by developing a series of sample mixture consisting these drugs in certain proportion. Cross validation of calibration sample using leave one out technique is used to identify the smaller set of components that provide the greatest predictive ability. The evaluation of calibration model was based on the coefficient of determination (R2) and root mean square error of calibration (RMSEC). Results: The results showed that the coefficient of determination (R2) for the relationship between actual values and predicted values for all studied drugs was higher than 0.99 indicating good accuracy. The RMSEC values obtained were relatively low, indicating good precision. The accuracy and presision results of developed method showed no significant difference compared to those obtained by official method of HPLC. Conclusion: The developed method (UV-VIS spectrophotometry in combination with PLS) was succesfully used for analysis of metamizole, thiamin and pyridoxin in tablet dosage form. PMID:26819934

Validation of a predictive model for identifying febrile young infants with altered urinalysis at low risk of invasive bacterial infection.

PubMed

Velasco, R; Gómez, B; Hernández-Bou, S; Olaciregui, I; de la Torre, M; González, A; Rivas, A; Durán, I; Rubio, A

2017-02-01

In 2015, a predictive model for invasive bacterial infection (IBI) in febrile young infants with altered urine dipstick was published. The aim of this study was to externally validate a previously published set of low risk criteria for invasive bacterial infection in febrile young infants with altered urine dipstick. Retrospective multicenter study including nine Spanish hospitals. Febrile infants ≤90 days old with altered urinalysis (presence of leukocyturia and/or nitrituria) were included. According to our predictive model, an infant is classified as low-risk for IBI when meeting all the following: appearing well at arrival to the emergency department, being >21 days old, having a procalcitonin value <0.5 ng/mL and a C-reactive protein value <20 mg/L. IBI was considered as secondary to urinary tract infection if the same pathogen was isolated in the urine culture and in the blood or cerebrospinal fluid culture. A total of 391 patients with altered urine dipstick were included. Thirty (7.7 %) of them developed an IBI, with 26 (86.7 %) of them secondary to UTI. Prevalence of IBI was 2/104 (1.9 %; CI 95% 0.5-6.7) among low-risk patients vs 28/287 (9.7 %; CI 95% 6.8-13.7) among high-risk patients (p < 0.05). Sensitivity of the model was 93.3 % (CI 95% 78.7-98.2) and negative predictive value was 98.1 % (93.3-99.4). Although our predictive model was shown to be less accurate in the validation cohort, it still showed a good discriminatory ability to detect IBI. Larger prospective external validation studies, taking into account fever duration as well as the role of ED observation, should be undertaken before its implementation into clinical practice.

Estimated glomerular filtration rate is an early biomarker of cardiac surgery-associated acute kidney injury.

PubMed

Candela-Toha, Ángel; Pardo, María Carmen; Pérez, Teresa; Muriel, Alfonso; Zamora, Javier

2018-04-20

and objective Acute kidney injury (AKI) diagnosis is still based on serum creatinine and diuresis. However, increases in creatinine are typically delayed 48h or longer after injury. Our aim was to determine the utility of routine postoperative renal function blood tests, to predict AKI one or 2days in advance in a cohort of cardiac surgery patients. Using a prospective database, we selected a sample of patients who had undergone major cardiac surgery between January 2002 and December 2013. The ability of the parameters to predict AKI was based on Acute Kidney Injury Network serum creatinine criteria. A cohort of 3,962 cases was divided into 2groups of similar size, one being exploratory and the other a validation sample. The exploratory group was used to show primary objectives and the validation group to confirm results. The ability to predict AKI of several kidney function parameters measured in routine postoperative blood tests, was measured with time-dependent ROC curves. The primary endpoint was time from measurement to AKI diagnosis. AKI developed in 610 (30.8%) and 623 (31.4%) patients in the exploratory and validation samples, respectively. Estimated glomerular filtration rate using the MDRD-4 equation showed the best AKI prediction capacity, with values for the AUC ROC curves between 0.700 and 0.946. We obtained different cut-off values for estimated glomerular filtration rate depending on the degree of AKI severity and on the time elapsed between surgery and parameter measurement. Results were confirmed in the validation sample. Postoperative estimated glomerular filtration rate using the MDRD-4 equation showed good ability to predict AKI following cardiac surgery one or 2days in advance. Copyright © 2018 Sociedad Española de Nefrología. Published by Elsevier España, S.L.U. All rights reserved.

Simple Scoring System and Artificial Neural Network for Knee Osteoarthritis Risk Prediction: A Cross-Sectional Study

PubMed Central

Yoo, Tae Keun; Kim, Deok Won; Choi, Soo Beom; Oh, Ein; Park, Jee Soo

2016-01-01

Background Knee osteoarthritis (OA) is the most common joint disease of adults worldwide. Since the treatments for advanced radiographic knee OA are limited, clinicians face a significant challenge of identifying patients who are at high risk of OA in a timely and appropriate way. Therefore, we developed a simple self-assessment scoring system and an improved artificial neural network (ANN) model for knee OA. Methods The Fifth Korea National Health and Nutrition Examination Surveys (KNHANES V-1) data were used to develop a scoring system and ANN for radiographic knee OA. A logistic regression analysis was used to determine the predictors of the scoring system. The ANN was constructed using 1777 participants and validated internally on 888 participants in the KNHANES V-1. The predictors of the scoring system were selected as the inputs of the ANN. External validation was performed using 4731 participants in the Osteoarthritis Initiative (OAI). Area under the curve (AUC) of the receiver operating characteristic was calculated to compare the prediction models. Results The scoring system and ANN were built using the independent predictors including sex, age, body mass index, educational status, hypertension, moderate physical activity, and knee pain. In the internal validation, both scoring system and ANN predicted radiographic knee OA (AUC 0.73 versus 0.81, p<0.001) and symptomatic knee OA (AUC 0.88 versus 0.94, p<0.001) with good discriminative ability. In the external validation, both scoring system and ANN showed lower discriminative ability in predicting radiographic knee OA (AUC 0.62 versus 0.67, p<0.001) and symptomatic knee OA (AUC 0.70 versus 0.76, p<0.001). Conclusions The self-assessment scoring system may be useful for identifying the adults at high risk for knee OA. The performance of the scoring system is improved significantly by the ANN. We provided an ANN calculator to simply predict the knee OA risk. PMID:26859664

Why Do I Feel More Confident? Bandura's Sources Predict Preservice Teachers' Latent Changes in Teacher Self-Efficacy

PubMed Central

Pfitzner-Eden, Franziska

2016-01-01

Teacher self-efficacy (TSE) is associated with a multitude of positive outcomes for teachers and students. However, the development of TSE is an under-researched area. Bandura (1997) proposed four sources of self-efficacy: mastery experiences, vicarious experiences, verbal persuasion, and physiological and affective states. This study introduces a first instrument to assess the four sources for TSE in line with Bandura's conception. Gathering evidence of convergent validity, the contribution that each source made to the development of TSE during a practicum at a school was explored for two samples of German preservice teachers. The first sample (N = 359) were beginning preservice teachers who completed an observation practicum. The second sample (N = 395) were advanced preservice teachers who completed a teaching practicum. The source measure showed good reliability, construct validity, and convergent validity. Latent true change modeling was applied to explore how the sources predicted changes in TSE. Three different models were compared. As expected, results showed that TSE changes in both groups were significantly predicted by mastery experiences, with a stronger relationship in the advanced group. Further, the results indicated that mastery experiences were largely informed by the other three sources to varying degrees depending on the type of practicum. Implications for the practice of teacher education are discussed in light of the results. PMID:27807422

Why Do I Feel More Confident? Bandura's Sources Predict Preservice Teachers' Latent Changes in Teacher Self-Efficacy.

PubMed

Pfitzner-Eden, Franziska

2016-01-01

Teacher self-efficacy (TSE) is associated with a multitude of positive outcomes for teachers and students. However, the development of TSE is an under-researched area. Bandura (1997) proposed four sources of self-efficacy: mastery experiences, vicarious experiences, verbal persuasion, and physiological and affective states. This study introduces a first instrument to assess the four sources for TSE in line with Bandura's conception. Gathering evidence of convergent validity, the contribution that each source made to the development of TSE during a practicum at a school was explored for two samples of German preservice teachers. The first sample ( N = 359) were beginning preservice teachers who completed an observation practicum. The second sample ( N = 395) were advanced preservice teachers who completed a teaching practicum. The source measure showed good reliability, construct validity, and convergent validity. Latent true change modeling was applied to explore how the sources predicted changes in TSE. Three different models were compared. As expected, results showed that TSE changes in both groups were significantly predicted by mastery experiences, with a stronger relationship in the advanced group. Further, the results indicated that mastery experiences were largely informed by the other three sources to varying degrees depending on the type of practicum. Implications for the practice of teacher education are discussed in light of the results.

Effective equations for matter-wave gap solitons in higher-order transversal states.

PubMed

Mateo, A Muñoz; Delgado, V

2013-10-01

We demonstrate that an important class of nonlinear stationary solutions of the three-dimensional (3D) Gross-Pitaevskii equation (GPE) exhibiting nontrivial transversal configurations can be found and characterized in terms of an effective one-dimensional (1D) model. Using a variational approach we derive effective equations of lower dimensionality for BECs in (m,n(r)) transversal states (states featuring a central vortex of charge m as well as n(r) concentric zero-density rings at every z plane) which provides us with a good approximate solution of the original 3D problem. Since the specifics of the transversal dynamics can be absorbed in the renormalization of a couple of parameters, the functional form of the equations obtained is universal. The model proposed finds its principal application in the study of the existence and classification of 3D gap solitons supported by 1D optical lattices, where in addition to providing a good estimate for the 3D wave functions it is able to make very good predictions for the μ(N) curves characterizing the different fundamental families. We have corroborated the validity of our model by comparing its predictions with those from the exact numerical solution of the full 3D GPE.

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.

Measurement of academic entitlement.

PubMed

Miller, Brian K

2013-10-01

Members of Generation Y, or Millennials, have been accused of being lazy, whiny, pampered, and entitled, particularly in the college classroom. Using an equity theory framework, eight items from a measure of work entitlement were adapted to measure academic entitlement in a university setting in three independent samples. In Study 1 (n = 229), confirmatory factor analyses indicated good model fit to a unidimensional structure for the data. In Study 2 (n = 200), the questionnaire predicted unique variance in university satisfaction beyond two more general measures of dispositional entitlement. In Study 3 (n = 161), the measure predicted unique variance in perceptions of grade fairness beyond that which was predicted by another measure of academic entitlement. This analysis provides evidence of discriminant, convergent, incremental, concurrent criterion-related, and construct validity for the Academic Equity Preference Questionnaire.

The relationship between maternal attitudes and symptoms of depression and anxiety among pregnant and postpartum first-time mothers.

PubMed

Sockol, Laura E; Epperson, C Neill; Barber, Jacques P

2014-06-01

Two studies examined the relationship between maternal attitudes and symptoms of depression and anxiety during pregnancy and the early postpartum period. In the first study, a measure of maternal attitudes, the Attitudes Toward Motherhood Scale (AToM), was developed and validated in a sample of first-time mothers. The AToM was found to have good internal reliability and convergent validity with cognitive biases and an existing measure of maternal attitudes. Exploratory and confirmatory factor analyses determined that the measure comprises three correlated factors: beliefs about others' judgments, beliefs about maternal responsibility, and maternal role idealization. In the second study, we used the AToM to assess the relationship between maternal attitudes and other psychological variables. The factor structure of the measure was confirmed. Maternal attitudes predicted symptoms of depression and anxiety, and these attitudes had incremental predictive validity over general cognitive biases and interpersonal risk factors. Overall, the results of these studies suggest that maternal attitudes are related to psychological distress among first-time mothers during the transition to parenthood and may provide a useful means of identifying women who may benefit from intervention during the perinatal period.

Thermogravimetric analysis for rapid assessment of moisture diffusivity in polydisperse powder and thin film matrices.

PubMed

Thirunathan, Praveena; Arnz, Patrik; Husny, Joeska; Gianfrancesco, Alessandro; Perdana, Jimmy

2018-03-01

Accurate description of moisture diffusivity is key to precisely understand and predict moisture transfer behaviour in a matrix. Unfortunately, measuring moisture diffusivity is not trivial, especially at low moisture values and/or elevated temperatures. This paper presents a novel experimental procedure to accurately measure moisture diffusivity based on thermogravimetric approach. The procedure is capable to measure diffusivity even at elevated temperatures (>70°C) and low moisture values (>1%). Diffusivity was extracted from experimental data based on "regular regime approach". The approach was tailored to determine diffusivity from thin film and from poly-dispersed powdered samples. Subsequently, measured diffusivity was validated by comparing to available literature data, showing good agreement. Ability of this approach to accurately measure diffusivity at a wider range of temperatures provides better insight on temperature dependency of diffusivity. Thus, this approach can be crucial to ensure good accuracy of moisture transfer description/prediction especially when involving elevated temperatures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Development of a modified independent parallel reactions kinetic model and comparison with the distributed activation energy model for the pyrolysis of a wide variety of biomass fuels.

PubMed

Sfakiotakis, Stelios; Vamvuka, Despina

2015-12-01

The pyrolysis of six waste biomass samples was studied and the fuels were kinetically evaluated. A modified independent parallel reactions scheme (IPR) and a distributed activation energy model (DAEM) were developed and their validity was assessed and compared by checking their accuracy of fitting the experimental results, as well as their prediction capability in different experimental conditions. The pyrolysis experiments were carried out in a thermogravimetric analyzer and a fitting procedure, based on least squares minimization, was performed simultaneously at different experimental conditions. A modification of the IPR model, considering dependence of the pre-exponential factor on heating rate, was proved to give better fit results for the same number of tuned kinetic parameters, comparing to the known IPR model and very good prediction results for stepwise experiments. Fit of calculated data to the experimental ones using the developed DAEM model was also proved to be very good. Copyright © 2015 Elsevier Ltd. All rights reserved.

[Design and validation of a brief questionnaire to assess young´s sexual knowledge].

PubMed

Leon-Larios, Fátima; Gómez-Baya, Diego

2018-06-01

Only very few instruments have been developed to assess sexual knowledge and practices. Most of the research to date has been carried out with adolescent samples, but not with university students, who are also at a particularly risky stage. The aim of this study was to design and validate a brief questionnaire to assess young´s sexual knowledge, practices and behaviors to design health education programs in the university context. We created a specific questionnaire about sexual pattern in university adolescents and a brief questionnaire consisted of 9 items (true/false) about contraception, sexuality and sexual transmission diseases. We carried out a pilot study, reliability (KR-20) and validity analyses using factorial analysis and examining the association with other variables. 566 students from University of Seville participated during 2015/16. One item was eliminated because of comprehension (only 13.9% of correct answers) and weak or non significant associations (p more than 0.05). Finally, the scale was formed by 8 items and had good internal consistency reliability (KR-20 = 0.57), and both factorial and external validity reliability. A three-factor model showed good data fit, χ2 (14, N=566)=17.48, p= 0.232, Comparative Fit Index CFI = 0.97, root mean squared error of prediction RMSEA = 0.02. Participants with less knowledge about sexuality were whose did not receive any information (M=6.82, SD=1.41), without partner (M=6.87, SD=1.35), had an abortion (M=6.43, SD=1.95) and did not use any contraceptive method (M=6.66, SD=0.58) or coitus interruptus (M=6.55, SD=1.39), and had less sexual relationships, e.g., once or twice a year (M=6.49, SD=1.70). This questionnaire is a short instrument to assess students´ practices and knowledge about sexuality and contraception. The analyses of reliability and validity have shown the good psychometric properties of this instrument.

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.

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.

Prediction of sound transmission loss through multilayered panels by using Gaussian distribution of directional incident energy

PubMed

Kang; Ih; Kim; Kim

2000-03-01

In this study, a new prediction method is suggested for sound transmission loss (STL) of multilayered panels of infinite extent. Conventional methods such as random or field incidence approach often given significant discrepancies in predicting STL of multilayered panels when compared with the experiments. In this paper, appropriate directional distributions of incident energy to predict the STL of multilayered panels are proposed. In order to find a weighting function to represent the directional distribution of incident energy on the wall in a reverberation chamber, numerical simulations by using a ray-tracing technique are carried out. Simulation results reveal that the directional distribution can be approximately expressed by the Gaussian distribution function in terms of the angle of incidence. The Gaussian function is applied to predict the STL of various multilayered panel configurations as well as single panels. The compared results between the measurement and the prediction show good agreements, which validate the proposed Gaussian function approach.

Strain intensity factor approach for predicting the strength of continuously reinforced metal matrix composites

NASA Technical Reports Server (NTRS)

Poe, C. C., Jr.

1988-01-01

A method was previously developed to predict the fracture toughness (stress intensity factor at failure) of composites in terms of the elastic constants and the tensile failing strain of the fibers. The method was applied to boron/aluminum composites made with various proportions of 0 to + or - 45 deg plies. Predicted values of fracture toughness were in gross error because widespread yielding of the aluminum matrix made the compliance very nonlinear. An alternate method was developed to predict the strain intensity factor at failure rather than the stress intensity factor because the singular strain field was not affected by yielding as much as the stress field. Strengths of specimens containing crack-like slits were calculated from predicted failing strains using uniaxial stress-strain curves. Predicted strengths were in good agreement with experimental values, even for the very nonlinear laminates that contained only + or - 45 deg plies. This approach should be valid for other metal matrix composites that have continuous fibers.

Evaluation of modified Dennis parasitological technique for diagnosis of bovine fascioliasis.

PubMed

Correa, Stefanya; Martínez, Yudy Liceth; López, Jessika Lissethe; Velásquez, Luz Elena

2016-02-23

Bovine fascioliasis causes important economic losses, estimated at COP$ 12,483 billion per year; its prevalence is 25% in dairy cattle. Parasitological techniques are required for it diagnosis. The Dennis technique, modified in 2002, is the one used in Colombia, but its sensitivity, specificity and validity are not known.  To evaluate the validity and performance of the modified Dennis technique for diagnosis of bovine fascioliasis using as reference test the observation of parasites in the liver.  We conducted a diagnostic evaluation study. We selected a convenience sample of discarded bovines sacrificed between March and June, 2013, in Frigocolanta for the study. We collected 25 g of feces from each animal and their liver and bile ducts were examined for Fasciola hepatica. The sensitivity, specificity, predictive positive value, predictive negative value, and validity index were calculated with 95% confidence intervals. The post-mortem evaluation was used as the gold standard.  We analyzed 180 bovines. The sensitivity and specificity of the modified Dennis technique were 73.2% (95% CI=58.4% - 87.9%) and 84.2% (95% CI= 77.7% - 90.6%), respectively. The positive predictive value was 57.7% (95% CI= 43.3% - 72.1%) and the negative one 91.4% (95% CI= 86.2% - 96.6%). The prevalence of bovine fascioliasis was 22.8% (95% CI= 16.4% - 29.2%).  The validity and the performance of the modified Dennis technique were higher than those of the traditional one, which makes it a good screening test for diagnosing fascioliasis for population and prevalence studies and during animal health campaigns.

External validation of a PCA-3-based nomogram for predicting prostate cancer and high-grade cancer on initial prostate biopsy.

PubMed

Greene, Daniel J; Elshafei, Ahmed; Nyame, Yaw A; Kara, Onder; Malkoc, Ercan; Gao, Tianming; Jones, J Stephen

2016-08-01

The aim of this study was to externally validate a previously developed PCA3-based nomogram for the prediction of prostate cancer (PCa) and high-grade (intermediate and/or high-grade) prostate cancer (HGPCa) at the time of initial prostate biopsy. A retrospective review was performed on a cohort of 336 men from a large urban academic medical center. All men had serum PSA <20 ng/ml and underwent initial transrectal ultrasound-guided prostate biopsy with at least 10 cores sampling for suspicious exam and/or elevated PSA. Covariates were collected for the nomogram and included age, ethnicity, family history (FH) of PCa, PSA at diagnosis, PCA3, total prostate volume (TPV), and abnormal finding on digital rectal exam (DRE). These variables were used to test the accuracy (concordance index) and calibration of a previously published PCA3 nomogram. Biopsy confirms PCa and HGPCa in 51.0% and 30.4% of validation patients, respectively. This differed from the original cohort in that it had significantly more PCa and HGPCA (51% vs. 44%, P = 0.019; and 30.4% vs. 19.1%, P < 0.001). Despite the differences in PCa detection the concordance index was 75% and 77% for overall PCa and HGPCa, respectively. Calibration for overall PCa was good. This represents the first external validation of a PCA3-based prostate cancer predictive nomogram in a North American population. Prostate 76:1019-1023, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Seasonal prediction of winter haze days in the north central North China Plain

NASA Astrophysics Data System (ADS)

Yin, Zhicong; Wang, Huijun

2016-11-01

Recently, the winter (December-February) haze pollution over the north central North China Plain (NCP) has become severe. By treating the year-to-year increment as the predictand, two new statistical schemes were established using the multiple linear regression (MLR) and the generalized additive model (GAM). By analyzing the associated increment of atmospheric circulation, seven leading predictors were selected to predict the upcoming winter haze days over the NCP (WHDNCP). After cross validation, the root mean square error and explained variance of the MLR (GAM) prediction model was 3.39 (3.38) and 53 % (54 %), respectively. For the final predicted WHDNCP, both of these models could capture the interannual and interdecadal trends and the extremums successfully. Independent prediction tests for 2014 and 2015 also confirmed the good predictive skill of the new schemes. The predicted bias of the MLR (GAM) prediction model in 2014 and 2015 was 0.09 (-0.07) and -3.33 (-1.01), respectively. Compared to the MLR model, the GAM model had a higher predictive skill in reproducing the rapid and continuous increase of WHDNCP after 2010.

Validation of the GRACE Risk score for hospital mortality in patients with acute coronary syndrome in the Arab Middle East.

PubMed

Yusufali, Afzalhussein; Zubaid, Mohammad; Al-Zakwani, Ibrahim; Alsheikh-Ali, Alawi A; Al-Mallah, Mouaz H; Al Suwaidi, Jassim; AlMahmeed, Wael; Rashed, Wafa; Sulaiman, Kadhim; Amin, Haitham

2011-07-01

Our objective was to validate the Global Registry of Acute Coronary Events (GRACE) risk score for in-hospital mortality in a Middle Eastern acute coronary syndrome (ACS) population enrolled in the Gulf Registry of Acute Coronary Events (Gulf RACE). Out of 8176, unselected, consecutive patients with ACS, during 6 months in 2006 and 2007 from 63 hospitals in 6 Arab countries in the Middle East Gulf region, 7709 (94.3%) with available data were included. The main outcome measures were discriminatory performance (using C-index) and calibration of the GRACE risk score (in-hospital mortality predicted by GRACE risk score versus the actual mortality). In-hospital mortality in the Gulf RACE was 3.09% (n = 238). The discriminatory performance of the GRACE risk scores in the Gulf RACE was good overall (C-index = 0.86). Observed and predicted risk corresponded well in each stratum of risk of in-hospital mortality. This suggests its suitability for clinical use in this patient population.

Damping in Space Constructions

NASA Astrophysics Data System (ADS)

de Vreugd, Jan; de Lange, Dorus; Winters, Jasper; Human, Jet; Kamphues, Fred; Tabak, Erik

2014-06-01

Monolithic structures are often used in optomechanical designs for space applications to achieve high dimensional stability and to prevent possible backlash and friction phenomena. The capacity of monolithic structures to dissipate mechanical energy is however limited due to the high Q-factor, which might result in high stresses during dynamic launch loads like random vibration, sine sweeps and shock. To reduce the Q-factor in space applications, the effect of constrained layer damping (CLD) is investigated in this work. To predict the damping increase, the CLD effect is implemented locally at the supporting struts in an existing FE model of an optical instrument. Numerical simulations show that the effect of local damping treatment in this instrument could reduce the vibrational stresses with 30-50%. Validation experiments on a simple structure showed good agreement between measured and predicted damping properties. This paper presents material characterization, material modeling, numerical implementation of damping models in finite element code, numerical results on space hardware and the results of validation experiments.

Psychometric properties of the "sport satisfaction instrument (SSI)" in female athletes: predictive model of sport commitment.

PubMed

Granero-Gallegos, A; Baena-Extremera, A; Gómez-López, M; Abraldes, J A

2014-08-01

The objective of this research was to assess the psychometric properties of the Sport Satisfaction Instrument (SSI) in a Spanish sample of female athletes in team sports federations, to decide whether it constitutes a valid and reliable instrument to be used in the context of female competitive sport in future research. The SSI was administered to a total of 615 athletes from 12 to 38 yr. of age. Confirmatory procedures and psychometric analysis supported the hypothesized theoretical model of two factors (Satisfaction/fun and Boredom). For female athletes, the 7-item model showed better goodness-of-fit indexes upon eliminating Item 2 from the Boredom subscale. Concurrent validity was explored through the correlations with the Perception of Success Questionnaire and Sport Commitment, obtaining positive correlations between Satisfaction/fun and Task Orientation and Sport Commitment, whereas Boredom correlated positively but less closely with Ego Orientation. The importance of Satisfaction/fun in the prediction of Sport Commitment, starting from task orientation, is emphasized.

Real-time eutrophication status evaluation of coastal waters using support vector machine with grid search algorithm.

PubMed

Kong, Xianyu; Sun, Yuyan; Su, Rongguo; Shi, Xiaoyong

2017-06-15

The development of techniques for real-time monitoring of the eutrophication status of coastal waters is of great importance for realizing potential cost savings in coastal monitoring programs and providing timely advice for marine health management. In this study, a GS optimized SVM was proposed to model relationships between 6 easily measured parameters (DO, Chl-a, C1, C2, C3 and C4) and the TRIX index for rapidly assessing marine eutrophication states of coastal waters. The good predictive performance of the developed method was indicated by the R 2 between the measured and predicted values (0.92 for the training dataset and 0.91 for the validation dataset) at a 95% confidence level. The classification accuracy of the eutrophication status was 86.5% for the training dataset and 85.6% for the validation dataset. The results indicated that it is feasible to develop an SVM technique for timely evaluation of the eutrophication status by easily measured parameters. Copyright © 2017. Published by Elsevier Ltd.

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

PubMed

Di Capua, Daniela; Garcia-Garcia, Maria Eugenia; Reig-Ferrer, Abilio; Fuentes-Ferrer, Manuel; Toledano, Rafael; Gil-Nagel, Antonio; Garcia-Ptaceck, Sara; Kurtis, Monica; Kanner, Andres M; Garcia-Morales, Irene

2012-08-01

To translate and validate into Spanish (Spain) the screening instrument of major depressive episodes (MDEs), Neurological Disorders Depression Inventory in Epilepsy (NDDI-E), in patients with epilepsy. A total of 121 outpatients, aged 18 years and older, with a diagnosis of epilepsy were included. The diagnosis of a current major depressive episode (MDE) was established with the Mini International Neuropsychiatric Interview (MINI). A diagnosis of current MDE was established in 20% of the patients with the MINI. Receiver operator characteristics (ROC) analysis showed an area under the curve of 0.89, with an internal consistency of 0.78. At a cutoff score >13, 22% of patients were considered to suffer from MDE with the NDDI-E (sensitivity: 84%; specificity: 78%; positive predictive value: 64.7%; and negative predictive value: 92.2%). The Spanish-Spain version of the NDDI-E appears to be a good screening instrument to identify MDE. Copyright © 2012 Elsevier Inc. All rights reserved.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

Enhancement of the Open National Combustion Code (OpenNCC) and Initial Simulation of Energy Efficient Engine Combustor

NASA Technical Reports Server (NTRS)

Miki, Kenji; Moder, Jeff; Liou, Meng-Sing

2016-01-01

In this paper, we present the recent enhancement of the Open National Combustion Code (OpenNCC) and apply the OpenNCC to model a realistic combustor configuration (Energy Efficient Engine (E3)). First, we perform a series of validation tests for the newly-implemented advection upstream splitting method (AUSM) and the extended version of the AUSM-family schemes (AUSM+-up). Compared with the analytical/experimental data of the validation tests, we achieved good agreement. In the steady-state E3 cold flow results using the Reynolds-averaged Navier-Stokes(RANS), we find a noticeable difference in the flow fields calculated by the two different numerical schemes, the standard Jameson- Schmidt-Turkel (JST) scheme and the AUSM scheme. The main differences are that the AUSM scheme is less numerical dissipative and it predicts much stronger reverse flow in the recirculation zone. This study indicates that two schemes could show different flame-holding predictions and overall flame structures.

Incremental value of the CT coronary calcium score for the prediction of coronary artery disease

PubMed Central

Genders, Tessa S. S.; Pugliese, Francesca; Mollet, Nico R.; Meijboom, W. Bob; Weustink, Annick C.; van Mieghem, Carlos A. G.; de Feyter, Pim J.

2010-01-01

Objectives: To validate published prediction models for the presence of obstructive coronary artery disease (CAD) in patients with new onset stable typical or atypical angina pectoris and to assess the incremental value of the CT coronary calcium score (CTCS). Methods: We searched the literature for clinical prediction rules for the diagnosis of obstructive CAD, defined as ≥50% stenosis in at least one vessel on conventional coronary angiography. Significant variables were re-analysed in our dataset of 254 patients with logistic regression. CTCS was subsequently included in the models. The area under the receiver operating characteristic curve (AUC) was calculated to assess diagnostic performance. Results: Re-analysing the variables used by Diamond & Forrester yielded an AUC of 0.798, which increased to 0.890 by adding CTCS. For Pryor, Morise 1994, Morise 1997 and Shaw the AUC increased from 0.838 to 0.901, 0.831 to 0.899, 0.840 to 0.898 and 0.833 to 0.899. CTCS significantly improved model performance in each model. Conclusions: Validation demonstrated good diagnostic performance across all models. CTCS improves the prediction of the presence of obstructive CAD, independent of clinical predictors, and should be considered in its diagnostic work-up. PMID:20559838

A contemporary risk model for predicting 30-day mortality following percutaneous coronary intervention in England and Wales.

PubMed

McAllister, Katherine S L; Ludman, Peter F; Hulme, William; de Belder, Mark A; Stables, Rodney; Chowdhary, Saqib; Mamas, Mamas A; Sperrin, Matthew; Buchan, Iain E

2016-05-01

The current risk model for percutaneous coronary intervention (PCI) in the UK is based on outcomes of patients treated in a different era of interventional cardiology. This study aimed to create a new model, based on a contemporary cohort of PCI treated patients, which would: predict 30 day mortality; provide good discrimination; and be well calibrated across a broad risk-spectrum. The model was derived from a training dataset of 336,433 PCI cases carried out between 2007 and 2011 in England and Wales, with 30 day mortality provided by record linkage. Candidate variables were selected on the basis of clinical consensus and data quality. Procedures in 2012 were used to perform temporal validation of the model. The strongest predictors of 30-day mortality were: cardiogenic shock; dialysis; and the indication for PCI and the degree of urgency with which it was performed. The model had an area under the receiver operator characteristic curve of 0.85 on the training data and 0.86 on validation. Calibration plots indicated a good model fit on development which was maintained on validation. We have created a contemporary model for PCI that encompasses a range of clinical risk, from stable elective PCI to emergency primary PCI and cardiogenic shock. The model is easy to apply and based on data reported in national registries. It has a high degree of discrimination and is well calibrated across the risk spectrum. The examination of key outcomes in PCI audit can be improved with this risk-adjusted model. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Validation of the Alcohol Use Disorders Identification Test in university students: AUDIT and AUDIT-C.

PubMed

García Carretero, Miguel Ángel; Novalbos Ruiz, José Pedro; Martínez Delgado, José Manuel; O'Ferrall González, Cristina

2016-03-02

The aim of this study was to determine the psychometric properties of the Alcohol Use Disorders Identification Test (AUDIT and AUDIT-C) in order to detect problems related to the consumption of alcohol in the university population. The sample consisted of 1309 students.A Weekly Alcohol Consumption Diary was used as a gold standard; Cronbach's Alpha, the Kappa index, Spearman's correlation coefficient and exploratory factor analysis were applied for diagnostic reliability and validity, with ROC curves used to establish the different cut-off points. Binge Drinking (BD) episodes were found in 3.9% of men and 4.0% of women with otherwise low-risk drinking patterns. AUDIT identified 20.1% as high-risk drinkers and 6.4% as drinkers with physical-psychological problems and probable alcohol dependence.Cronbach's alpha of 0.75 demonstrates good internal consistency. The best cut-off points for high-risk drinking students were 8 for males and 6 for females. As for problem drinkers and probable ADS, 13 was the best cut-off point for both sexes. In relation to AUDIT-C, 5 and 4 were the best cut-off points for males and females with high-risk patterns, respectively. The criterion validity of AUDIT and AUDIT-C to detect binge drinking episodes was found to have a moderate K value. The results obtained show that AUDIT has good psychometric properties to detect early alcohol abuse disorders in university students; however, it is recommended that the cut-off point be reduced to 8 in men. AUDIT-C improves its predictive value by raising the cut-off point by one unit. Items 2 and 3 should be reviewed to increase its predictive value for BD.

Multi-component testing using HZ-PAN and AgZ-PAN Sorbents for OSPREY Model validation

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

Garn, Troy G.; Greenhalgh, Mitchell; Lyon, Kevin L.

2015-04-01

In efforts to further develop the capability of the Off-gas SeParation and RecoverY (OSPREY) model, multi-component tests were completed using both HZ-PAN and AgZ-PAN sorbents. The primary purpose of this effort was to obtain multi-component xenon and krypton capacities for comparison to future OSPREY predicted multi-component capacities using previously acquired Langmuir equilibrium parameters determined from single component isotherms. Experimental capacities were determined for each sorbent using two feed gas compositions of 1000 ppmv xenon and 150 ppmv krypton in either a helium or air balance. Test temperatures were consistently held at 220 K and the gas flowrate was 50 sccm.more » Capacities were calculated from breakthrough curves using TableCurve® 2D software by Jandel Scientific. The HZ-PAN sorbent was tested in the custom designed cryostat while the AgZ-PAN was tested in a newly installed cooling apparatus. Previous modeling validation efforts indicated the OSPREY model can be used to effectively predict single component xenon and krypton capacities for both engineered form sorbents. Results indicated good agreement with the experimental and predicted capacity values for both krypton and xenon on the sorbents. Overall, the model predicted slightly elevated capacities for both gases which can be partially attributed to the estimation of the parameters and the uncertainty associated with the experimental measurements. Currently, OSPREY is configured such that one species adsorbs and one does not (i.e. krypton in helium). Modification of OSPREY code is currently being performed to incorporate multiple adsorbing species and non-ideal interactions of gas phase species with the sorbent and adsorbed phases. Once these modifications are complete, the sorbent capacities determined in the present work will be used to validate OSPREY multicomponent adsorption predictions.« less

The combination of indocyanine green clearance test and model for end-stage liver disease score predicts early graft outcome after liver transplantation.

PubMed

Yunhua, Tang; Weiqiang, Ju; Maogen, Chen; Sai, Yang; Zhiheng, Zhang; Dongping, Wang; Zhiyong, Guo; Xiaoshun, He

2018-06-01

Early allograft dysfunction (EAD) and early postoperative complications are two important clinical endpoints when evaluating clinical outcomes of liver transplantation (LT). We developed and validated two ICGR15-MELD models in 87 liver transplant recipients for predicting EAD and early postoperative complications after LT by incorporating the quantitative liver function tests (ICGR15) into the MELD score. Eighty seven consecutive patients who underwent LT were collected and divided into a training cohort (n = 61) and an internal validation cohort (n = 26). For predicting EAD after LT, the area under curve (AUC) for ICGR15-MELD score was 0.876, with a sensitivity of 92.0% and a specificity of 75.0%, which is better than MELD score or ICGR15 alone. The recipients with a ICGR15-MELD score ≥0.243 have a higher incidence of EAD than those with a ICGR15-MELD score <0.243 (P <0.001). For predicting early postoperative complications, the AUC of ICGR15-MELD score was 0.832, with a sensitivity of 90.9% and a specificity of 71.0%. Those recipients with an ICGR15-MELD score ≥0.098 have a higher incidence of early postoperative complications than those with an ICGR15-MELD score <0.098 (P < 0.001). Finally, application of the two ICGR15-MELD models in the validation cohort still gave good accuracy (AUC, 0.835 and 0.826, respectively) in predicting EAD and early postoperative complications after LT. The combination of quantitative liver function tests (ICGR15) and the preoperative MELD score is a reliable and effective predictor of EAD and early postoperative complications after LT, which is better than MELD score or ICGR15 alone.

The validity of Iran’s national university entrance examination (Konkoor) for predicting medical students’ academic performance

PubMed Central

2012-01-01

Background In Iran, admission to medical school is based solely on the results of the highly competitive, nationwide Konkoor examination. This paper examines the predictive validity of Konkoor scores, alone and in combination with high school grade point averages (hsGPAs), for the academic performance of public medical school students in Iran. Methods This study followed the cohort of 2003 matriculants at public medical schools in Iran from entrance through internship. The predictor variables were Konkoor total and subsection scores and hsGPAs. The outcome variables were (1) Comprehensive Basic Sciences Exam (CBSE) scores; (2) Comprehensive Pre-Internship Exam (CPIE) scores; and (3) medical school grade point averages (msGPAs) for the courses taken before internship. Pearson correlation and regression analyses were used to assess the relationships between the selection criteria and academic performance. Results There were 2126 matriculants (1374 women and 752 men) in 2003. Among the outcome variables, the CBSE had the strongest association with the Konkoor total score (r = 0.473), followed by msGPA (r = 0.339) and the CPIE (r = 0.326). While adding hsGPAs to the Konkoor total score almost doubled the power to predict msGPAs (R2 = 0.225), it did not have a substantial effect on CBSE or CPIE prediction. Conclusions The Konkoor alone, and even in combination with hsGPA, is a relatively poor predictor of medical students’ academic performance, and its predictive validity declines over the academic years of medical school. Care should be taken to develop comprehensive admissions criteria, covering both cognitive and non-cognitive factors, to identify the best applicants to become "good doctors" in the future. The findings of this study can be helpful for policy makers in the medical education field. PMID:22840211

Improving the detection and prediction of suicidal behavior among military personnel by measuring suicidal beliefs: an evaluation of the Suicide Cognitions Scale.

PubMed

Bryan, Craig J; David Rudd, M; Wertenberger, Evelyn; Etienne, Neysa; Ray-Sannerud, Bobbie N; Morrow, Chad E; Peterson, Alan L; Young-McCaughon, Stacey

2014-04-01

Newer approaches for understanding suicidal behavior suggest the assessment of suicide-specific beliefs and cognitions may improve the detection and prediction of suicidal thoughts and behaviors. The Suicide Cognitions Scale (SCS) was developed to measure suicide-specific beliefs, but it has not been tested in a military setting. Data were analyzed from two separate studies conducted at three military mental health clinics (one U.S. Army, two U.S. Air Force). Participants included 175 active duty Army personnel with acute suicidal ideation and/or a recent suicide attempt referred for a treatment study (Sample 1) and 151 active duty Air Force personnel receiving routine outpatient mental health care (Sample 2). In both samples, participants completed self-report measures and clinician-administered interviews. Follow-up suicide attempts were assessed via clinician-administered interview for Sample 1. Statistical analyses included confirmatory factor analysis, between-group comparisons by history of suicidality, and generalized regression modeling. Two latent factors were confirmed for the SCS: Unloveability and Unbearability. Each demonstrated good internal consistency, convergent validity, and divergent validity. Both scales significantly predicted current suicidal ideation (βs >0.316, ps <0.002) and significantly differentiated suicide attempts from nonsuicidal self-injury and control groups (F(6, 286)=9.801, p<0.001). Both scales significantly predicted future suicide attempts (AORs>1.07, ps <0.050) better than other risk factors. Self-report methodology, small sample sizes, predominantly male samples. The SCS is a reliable and valid measure that predicts suicidal ideation and suicide attempts among military personnel better than other well-established risk factors. Copyright © 2014 Elsevier B.V. All rights reserved.

Risk prediction score for death of traumatised and injured children

PubMed Central

2014-01-01

Background Injury prediction scores facilitate the development of clinical management protocols to decrease mortality. However, most of the previously developed scores are limited in scope and are non-specific for use in children. We aimed to develop and validate a risk prediction model of death for injured and Traumatised Thai children. Methods Our cross-sectional study included 43,516 injured children from 34 emergency services. A risk prediction model was derived using a logistic regression analysis that included 15 predictors. Model performance was assessed using the concordance statistic (C-statistic) and the observed per expected (O/E) ratio. Internal validation of the model was performed using a 200-repetition bootstrap analysis. Results Death occurred in 1.7% of the injured children (95% confidence interval [95% CI]: 1.57–1.82). Ten predictors (i.e., age, airway intervention, physical injury mechanism, three injured body regions, the Glasgow Coma Scale, and three vital signs) were significantly associated with death. The C-statistic and the O/E ratio were 0.938 (95% CI: 0.929–0.947) and 0.86 (95% CI: 0.70–1.02), respectively. The scoring scheme classified three risk stratifications with respective likelihood ratios of 1.26 (95% CI: 1.25–1.27), 2.45 (95% CI: 2.42–2.52), and 4.72 (95% CI: 4.57–4.88) for low, intermediate, and high risks of death. Internal validation showed good model performance (C-statistic = 0.938, 95% CI: 0.926–0.952) and a small calibration bias of 0.002 (95% CI: 0.0005–0.003). Conclusions We developed a simplified Thai pediatric injury death prediction score with satisfactory calibrated and discriminative performance in emergency room settings. PMID:24575982

Global concentration additivity and prediction of mixture toxicities, taking nitrobenzene derivatives as an example.

PubMed

Li, Tong; Liu, Shu-Shen; Qu, Rui; Liu, Hai-Ling

2017-10-01

The toxicity of a mixture depends not only on the mixture concentration level but also on the mixture ratio. For a multiple-component mixture (MCM) system with a definite chemical composition, the mixture toxicity can be predicted only if the global concentration additivity (GCA) is validated. The so-called GCA means that the toxicity of any mixture in the MCM system is the concentration additive, regardless of what its mixture ratio and concentration level. However, many mixture toxicity reports have usually employed one mixture ratio (such as the EC 50 ratio), the equivalent effect concentration ratio (EECR) design, to specify several mixtures. EECR mixtures cannot simulate the concentration diversity and mixture ratio diversity of mixtures in the real environment, and it is impossible to validate the GCA. Therefore, in this paper, the uniform design ray (UD-Ray) was used to select nine mixture ratios (rays) in the mixture system of five nitrobenzene derivatives (NBDs). The representative UD-Ray mixtures can effectively and rationally describe the diversity in the NBD mixture system. The toxicities of the mixtures to Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). For each UD-Ray mixture, the concentration addition (CA) model was used to validate whether the mixture toxicity is additive. All of the UD-Ray mixtures of five NBDs are global concentration additive. Afterwards, the CA is employed to predict the toxicities of the external mixtures from three EECR mixture rays with the NOEC, EC 30 , and EC 70 ratios. The predictive toxicities are in good agreement with the experimental toxicities, which testifies to the predictability of the mixture toxicity of the NBDs. Copyright © 2017. Published by Elsevier Inc.

Experimental validation of a numerical model for subway induced vibrations

NASA Astrophysics Data System (ADS)

Gupta, S.; Degrande, G.; Lombaert, G.

2009-04-01

This paper presents the experimental validation of a coupled periodic finite element-boundary element model for the prediction of subway induced vibrations. The model fully accounts for the dynamic interaction between the train, the track, the tunnel and the soil. The periodicity or invariance of the tunnel and the soil in the longitudinal direction is exploited using the Floquet transformation, which allows for an efficient formulation in the frequency-wavenumber domain. A general analytical formulation is used to compute the response of three-dimensional invariant or periodic media that are excited by moving loads. The numerical model is validated by means of several experiments that have been performed at a site in Regent's Park on the Bakerloo line of London Underground. Vibration measurements have been performed on the axle boxes of the train, on the rail, the tunnel invert and the tunnel wall, and in the free field, both at the surface and at a depth of 15 m. Prior to these vibration measurements, the dynamic soil characteristics and the track characteristics have been determined. The Bakerloo line tunnel of London Underground has been modelled using the coupled periodic finite element-boundary element approach and free field vibrations due to the passage of a train at different speeds have been predicted and compared to the measurements. The correspondence between the predicted and measured response in the tunnel is reasonably good, although some differences are observed in the free field. The discrepancies are explained on the basis of various uncertainties involved in the problem. The variation in the response with train speed is similar for the measurements as well as the predictions. This study demonstrates the applicability of the coupled periodic finite element-boundary element model to make realistic predictions of the vibrations from underground railways.

Memory Binding Test Predicts Incident Dementia: Results from the Einstein Aging Study.

PubMed

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

2018-01-01

The Memory Binding Test (MBT) demonstrated good cross-sectional discriminative validity and predicted incident aMCI. To assess whether the MBT predicts incident dementia better than a conventional list learning test in a longitudinal community-based study. As a sub-study in the Einstein Aging Study, 309 participants age≥70 initially free of dementia were administered the MBT and followed annually for incident dementia for up to 13 years. Based on previous work, poor memory binding was defined using an optimal empirical cut-score of≤17 on the binding measure of the MBT, Total Items in the Paired condition (TIP). Cox proportional hazards models were used to assess predictive validity adjusting for covariates. We compared the predictive validity of MBT TIP to that of the free and cued selective reminding test free recall score (FCSRT-FR; cut-score:≤24) and the single list recall measure of the MBT, Cued Recalled from List 1 (CR-L1; cut-score:≤12). Thirty-five of 309 participants developed incident dementia. When assessing each test alone, the hazard ratio (HR) for dementia was significant for MBT TIP (HR = 8.58, 95% CI: (3.58, 20.58), p < 0.0001), FCSRT-FR (HR = 4.19, 95% CI: (1.94, 9.04), p = 0.0003) and MBT CR-L1 (HR = 2.91, 95% CI: (1.37, 6.18), p = 0.006). MBT TIP remained a significant predictor of dementia (p = 0.0002) when adjusting for FCSRT-FR or CR-L1. Older adults with poor memory binding as measured by the MBT TIP were at increased risk for incident dementia. This measure outperforms conventional episodic memory measures of free and cued recall, supporting the memory binding hypothesis.

Posttreatment Variables Improve Outcome Prediction after Intra-Arterial Therapy for Acute Ischemic Stroke

PubMed Central

Prabhakaran, Shyam; Jovin, Tudor G.; Tayal, Ashis H.; Hussain, Muhammad S.; Nguyen, Thanh N.; Sheth, Kevin N.; Terry, John B.; Nogueira, Raul G.; Horev, Anat; Gandhi, Dheeraj; Wisco, Dolora; Glenn, Brenda A.; Ludwig, Bryan; Clemmons, Paul F.; Cronin, Carolyn A.; Tian, Melissa; Liebeskind, David; Zaidat, Osama O.; Castonguay, Alicia C.; Martin, Coleman; Mueller-Kronast, Nils; English, Joey D.; Linfante, Italo; Malisch, Timothy W.; Gupta, Rishi

2014-01-01

Background There are multiple clinical and radiographic factors that influence outcomes after endovascular reperfusion therapy (ERT) in acute ischemic stroke (AIS). We sought to derive and validate an outcome prediction score for AIS patients undergoing ERT based on readily available pretreatment and posttreatment factors. Methods The derivation cohort included 511 patients with anterior circulation AIS treated with ERT at 10 centers between September 2009 and July 2011. The prospective validation cohort included 223 patients with anterior circulation AIS treated in the North American Solitaire Acute Stroke registry. Multivariable logistic regression identified predictors of good outcome (modified Rankin score ≤2 at 3 months) in the derivation cohort; model β coefficients were used to assign points and calculate a risk score. Discrimination was tested using C statistics with 95% confidence intervals (CIs) in the derivation and validation cohorts. Calibration was assessed using the Hosmer-Lemeshow test and plots of observed to expected outcomes. We assessed the net reclassification improvement for the derived score compared to the Totaled Health Risks in Vascular Events (THRIVE) score. Subgroup analysis in patients with pretreatment Alberta Stroke Program Early CT Score (ASPECTS) and posttreatment final infarct volume measurements was also performed to identify whether these radiographic predictors improved the model compared to simpler models. Results Good outcome was noted in 186 (36.4%) and 100 patients (44.8%) in the derivation and validation cohorts, respectively. Combining readily available pretreatment and posttreatment variables, we created a score (acronym: SNARL) based on the following parameters: symptomatic hemorrhage [2 points: none, hemorrhagic infarction (HI)1–2 or parenchymal hematoma (PH) type 1; 0 points: PH2], baseline National Institutes of Health Stroke Scale score (3 points: 0–10; 1 point: 11–20; 0 points: >20), age (2 points: <60 years; 1 point: 60–79 years; 0 points: >79 years), reperfusion (3 points: Thrombolysis In Cerebral Ischemia score 2b or 3) and location of clot (1 point: M2; 0 points: M1 or internal carotid artery). The SNARL score demonstrated good discrimination in the derivation (C statistic 0.79, 95% CI 0.75–0.83) and validation cohorts (C statistic 0.74, 95% CI 0.68–0.81) and was superior to the THRIVE score (derivation cohort: C statistic 0.65, 95% CI 0.60–0.70; validation cohort: C-statistic 0.59, 95% CI 0.52–0.67; p < 0.01 in both cohorts) but was inferior to a score that included age, ASPECTS, reperfusion status and final infarct volume (C statistic 0.86, 95% CI 0.82–0.91; p = 0.04). Compared with the THRIVE score, the SNARL score resulted in a net reclassification improvement of 34.8%. Conclusions Among AIS patients treated with ERT, pretreatment scores such as the THRIVE score provide only fair prognostic information. Inclusion of posttreatment variables such as reperfusion and symptomatic hemorrhage greatly influences outcome and results in improved outcome prediction. PMID:24942008

Adaptation and Validation of the Psychological Need Thwarting Scale in Spanish Physical Education Teachers.

PubMed

Cuevas, Ricardo; Sánchez-Oliva, David; Bartholomew, Kimberley J; Ntoumanis, Nikos; García-Calvo, Tomás

2015-07-20

Drawing from self-determination theory (SDT; Deci & Ryan, 1985; Ryan & Deci, 2002), the aim of the study was to adapt and validate a Spanish version of the Psychological Need Thwarting Scale (PNTS; Bartholomew, Ntoumanis, Ryan, & Thørgersen-Ntoumani, 2011) in the educational domain. Psychological need thwarting and burnout were assessed in 619 physical education teachers from several high schools in Spain. Overall, the adapted measure demonstrated good content, factorial (χ2/gl = 4.87, p < .01, CFI = .95, IFI = .96, TLI = .94, RMSEA = .08, SRMR = .05), and external validity, as well as internal consistency (α ≥ .81) and invariance across gender. Moreover, burnout was strongly predicted by teachers' perceptions of competence (β = .53, p ≤ .01), autonomy (β = .34, p ≤ .01), and relatedness (β = .31, p ≤ .01) need thwarting. In conclusion, these results support the Spanish version of the PNTS as a valid and reliable instrument for assessing the understudied concept of psychological need thwarting in teachers.

Test-Analysis Correlation for Space Shuttle External Tank Foam Impacting RCC Wing Leading Edge Component Panels

NASA Technical Reports Server (NTRS)

Lyle, Karen H.

2008-01-01

The Space Shuttle Columbia Accident Investigation Board recommended that NASA develop, validate, and maintain a modeling tool capable of predicting the damage threshold for debris impacts on the Space Shuttle Reinforced Carbon-Carbon (RCC) wing leading edge and nosecap assembly. The results presented in this paper are one part of a multi-level approach that supported the development of the predictive tool used to recertify the shuttle for flight following the Columbia Accident. The assessment of predictive capability was largely based on test analysis comparisons for simpler component structures. This paper provides comparisons of finite element simulations with test data for external tank foam debris impacts onto 6-in. square RCC flat panels. Both quantitative displacement and qualitative damage assessment correlations are provided. The comparisons show good agreement and provided the Space Shuttle Program with confidence in the predictive tool.

Evaluation of ride quality prediction methods for helicopter interior noise and vibration environments

NASA Technical Reports Server (NTRS)

Leatherwood, J. D.; Clevenson, S. A.; Hollenbaugh, D. D.

1984-01-01

The results of a simulator study conducted to compare and validate various ride quality prediction methods for use in assessing passenger/crew ride comfort within helicopters are presented. Included are results quantifying 35 helicopter pilots discomfort responses to helicopter interior noise and vibration typical of routine flights, assessment of various ride quality metrics including the NASA ride comfort model, and examination of possible criteria approaches. Results of the study indicated that crew discomfort results from a complex interaction between vibration and interior noise. Overall measures such as weighted or unweighted root-mean-square acceleration level and A-weighted noise level were not good predictors of discomfort. Accurate prediction required a metric incorporating the interactive effects of both noise and vibration. The best metric for predicting crew comfort to the combined noise and vibration environment was the NASA discomfort index.

Estimation of brain network ictogenicity predicts outcome from epilepsy surgery

NASA Astrophysics Data System (ADS)

Goodfellow, M.; Rummel, C.; Abela, E.; Richardson, M. P.; Schindler, K.; Terry, J. R.

2016-07-01

Surgery is a valuable option for pharmacologically intractable epilepsy. However, significant post-operative improvements are not always attained. This is due in part to our incomplete understanding of the seizure generating (ictogenic) capabilities of brain networks. Here we introduce an in silico, model-based framework to study the effects of surgery within ictogenic brain networks. We find that factors conventionally determining the region of tissue to resect, such as the location of focal brain lesions or the presence of epileptiform rhythms, do not necessarily predict the best resection strategy. We validate our framework by analysing electrocorticogram (ECoG) recordings from patients who have undergone epilepsy surgery. We find that when post-operative outcome is good, model predictions for optimal strategies align better with the actual surgery undertaken than when post-operative outcome is poor. Crucially, this allows the prediction of optimal surgical strategies and the provision of quantitative prognoses for patients undergoing epilepsy surgery.

A mathematical model for the interactive behavior of sulfate-reducing bacteria and methanogens during anaerobic digestion.

PubMed

Ahammad, S Ziauddin; Gomes, James; Sreekrishnan, T R

2011-09-01

Anaerobic degradation of waste involves different classes of microorganisms, and there are different types of interactions among them for substrates, terminal electron acceptors, and so on. A mathematical model is developed based on the mass balance of different substrates, products, and microbes present in the system to study the interaction between methanogens and sulfate-reducing bacteria (SRB). The performance of major microbial consortia present in the system, such as propionate-utilizing acetogens, butyrate-utilizing acetogens, acetoclastic methanogens, hydrogen-utilizing methanogens, and SRB were considered and analyzed in the model. Different substrates consumed and products formed during the process also were considered in the model. The experimental observations and model predictions showed very good prediction capabilities of the model. Model prediction was validated statistically. It was observed that the model-predicted values matched the experimental data very closely, with an average error of 3.9%.

Convenient QSAR model for predicting the complexation of structurally diverse compounds with beta-cyclodextrins.

PubMed

Pérez-Garrido, Alfonso; Morales Helguera, Aliuska; Abellán Guillén, Adela; Cordeiro, M Natália D S; Garrido Escudero, Amalio

2009-01-15

This paper reports a QSAR study for predicting the complexation of a large and heterogeneous variety of substances (233 organic compounds) with beta-cyclodextrins (beta-CDs). Several different theoretical molecular descriptors, calculated solely from the molecular structure of the compounds under investigation, and an efficient variable selection procedure, like the Genetic Algorithm, led to models with satisfactory global accuracy and predictivity. But the best-final QSAR model is based on Topological descriptors meanwhile offering a reasonable interpretation. This QSAR model was able to explain ca. 84% of the variance in the experimental activity, and displayed very good internal cross-validation statistics and predictivity on external data. It shows that the driving forces for CD complexation are mainly hydrophobic and steric (van der Waals) interactions. Thus, the results of our study provide a valuable tool for future screening and priority testing of beta-CDs guest molecules.

International validation study for interim PET in ABVD-treated, advanced-stage hodgkin lymphoma: interpretation criteria and concordance rate among reviewers.

PubMed

Biggi, Alberto; Gallamini, Andrea; Chauvie, Stephane; Hutchings, Martin; Kostakoglu, Lale; Gregianin, Michele; Meignan, Michel; Malkowski, Bogdan; Hofman, Michael S; Barrington, Sally F

2013-05-01

At present, there are no standard criteria that have been validated for interim PET reporting in lymphoma. In 2009, an international workshop attended by hematologists and nuclear medicine experts in Deauville, France, proposed to develop simple and reproducible rules for interim PET reporting in lymphoma. Accordingly, an international validation study was undertaken with the primary aim of validating the prognostic role of interim PET using the Deauville 5-point score to evaluate images and with the secondary aim of measuring concordance rates among reviewers using the same 5-point score. This paper focuses on the criteria for interpretation of interim PET and on concordance rates. A cohort of advanced-stage Hodgkin lymphoma patients treated with doxorubicin, bleomycin, vinblastine, and dacarbazine (ABVD) were enrolled retrospectively from centers worldwide. Baseline and interim scans were reviewed by an international panel of 6 nuclear medicine experts using the 5-point score. Complete scan datasets of acceptable diagnostic quality were available for 260 of 440 (59%) enrolled patients. Independent agreement among reviewers was reached on 252 of 260 patients (97%), for whom at least 4 reviewers agreed the findings were negative (score of 1-3) or positive (score of 4-5). After discussion, consensus was reached in all cases. There were 45 of 260 patients (17%) with positive interim PET findings and 215 of 260 patients (83%) with negative interim PET findings. Thirty-three interim PET-positive scans were true-positive, and 12 were false-positive. Two hundred three interim PET-negative scans were true-negative, and 12 were false-negative. Sensitivity, specificity, and accuracy were 0.73, 0.94, and 0.91, respectively. Negative predictive value and positive predictive value were 0.94 and 0.73, respectively. The 3-y failure-free survival was 83%, 28%, and 95% for the entire population and for interim PET-positive and -negative patients, respectively (P < 0.0001). The agreement between pairs of reviewers was good or very good, ranging from 0.69 to 0.84 as measured with the Cohen kappa. Overall agreement was good at 0.76 as measured with the Krippendorf α. The 5-point score proposed at Deauville for reviewing interim PET scans in advanced Hodgkin lymphoma is accurate and reproducible enough to be accepted as a standard reporting criterion in clinical practice and for clinical trials.

An examination of three sets of MMPI-2 personality disorder scales.

PubMed

Jones, Alvin

2005-08-01

Three sets of personality disorder scales (PD scales) can be scored for the MMPI-2 (Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989). Two sets (Levitt & Gotts, 1995; Morey, Waugh, & Blashfield, 1985) are derived from the MMPI (Hathaway & McKinley, 1983), and a third set (Somwaru & Ben-Porath, 1995) is based on the MMPI-2. There is no validity research for the Levitt and Gotts scale, and limited validity research is available for the Somwaru and Ben-Porath scales. There is a large body of research suggesting that the Morey et al. scales have good to excellent convergent validity when compared to a variety of other measures of personality disorders. Since the Morey et al. scales have established validity, there is a question if additional sets of PD scales are needed. The primary purpose of this research was to determine if the PD scales developed by Levitt and Gotts and those developed by Somwaru and Ben-Porath contribute incrementally to the scales developed by Morey et al. in predicting corresponding scales on the MCMI-II (Millon, 1987). In a sample of 494 individuals evaluated at an Army medical center, a hierarchical regression analysis demonstrated that the Somwaru and Ben-Porath Borderline, Antisocial, and Schizoid PD scales and the Levitt and Gotts Narcissistic and Histrionic scales contributed significantly and meaningfully to the Morey et al. scales in predicting the corresponding MCMI-II (Millon, 1987) scale. However, only the Somwaru and Ben-Porath scales demonstrated acceptable internal consistency and convergent validity.

Developing an African youth psychosocial assessment: an application of item response theory.

PubMed

Betancourt, Theresa S; Yang, Frances; Bolton, Paul; Normand, Sharon-Lise

2014-06-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. Copyright © 2014 John Wiley & Sons, Ltd.

Developing an African youth psychosocial assessment: an application of item response theory

PubMed Central

BETANCOURT, THERESA S.; YANG, FRANCES; BOLTON, PAUL; NORMAND, SHARON-LISE

2014-01-01

This study aimed to refine a dimensional scale for measuring psychosocial adjustment in African youth using item response theory (IRT). A 60-item scale derived from qualitative data was administered to 667 war-affected adolescents (55% female). Exploratory factor analysis (EFA) determined the dimensionality of items based on goodness-of-fit indices. Items with loadings less than 0.4 were dropped. Confirmatory factor analysis (CFA) was used to confirm the scale's dimensionality found under the EFA. Item discrimination and difficulty were estimated using a graded response model for each subscale using weighted least squares means and variances. Predictive validity was examined through correlations between IRT scores (θ) for each subscale and ratings of functional impairment. All models were assessed using goodness-of-fit and comparative fit indices. Fisher's Information curves examined item precision at different underlying ranges of each trait. Original scale items were optimized and reconfigured into an empirically-robust 41-item scale, the African Youth Psychosocial Assessment (AYPA). Refined subscales assess internalizing and externalizing problems, prosocial attitudes/behaviors and somatic complaints without medical cause. The AYPA is a refined dimensional assessment of emotional and behavioral problems in African youth with good psychometric properties. Validation studies in other cultures are recommended. PMID:24478113