A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics

PubMed Central

Mabey, P.; Richardson, S.; White, T. G.; Fletcher, L. B.; Glenzer, S. H.; Hartley, N. J.; Vorberger, J.; Gericke, D. O.; Gregori, G.

2017-01-01

The state and evolution of planets, brown dwarfs and neutron star crusts is determined by the properties of dense and compressed matter. Due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ion modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. Our results have profound consequences in the interpretation of transport coefficients in dense plasmas. PMID:28134338

Effectiveness of genomic prediction of maize hybrid performance in different breeding populations and environments.

PubMed

Windhausen, Vanessa S; Atlin, Gary N; Hickey, John M; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E; Raman, Babu; Cairns, Jill E; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E

2012-11-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F(2)-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F(2)-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set.

Derivation and Validation of a Clostridium difficile Infection Recurrence Prediction Rule in a National Cohort of Veterans.

PubMed

Reveles, Kelly R; Mortensen, Eric M; Koeller, Jim M; Lawson, Kenneth A; Pugh, Mary Jo V; Rumbellow, Sarah A; Argamany, Jacqueline R; Frei, Christopher R

2018-03-01

Prior studies have identified risk factors for recurrent Clostridium difficile infection (CDI), but few studies have integrated these factors into a clinical prediction rule that can aid clinical decision-making. The objectives of this study were to derive and validate a CDI recurrence prediction rule to identify patients at risk for first recurrence in a national cohort of veterans. Retrospective cohort study. Veterans Affairs Informatics and Computing Infrastructure. A total of 22,615 adult Veterans Health Administration beneficiaries with first-episode CDI between October 1, 2002, and September 30, 2014; of these patients, 7538 were assigned to the derivation cohort and 15,077 to the validation cohort. A 60-day CDI recurrence prediction rule was created in a derivation cohort using backward logistic regression. Those variables significant at p<0.01 were assigned an integer score proportional to the regression coefficient. The model was then validated in the derivation cohort and a separate validation cohort. Patients were then split into three risk categories, and rates of recurrence were described for each category. The CDI recurrence prediction rule included the following predictor variables with their respective point values: prior third- and fourth-generation cephalosporins (1 point), prior proton pump inhibitors (1 point), prior antidiarrheals (1 point), nonsevere CDI (2 points), and community-onset CDI (3 points). In the derivation cohort, the 60-day CDI recurrence risk for each score ranged from 7.5% (0 points) to 57.9% (8 points). The risk score was strongly correlated with recurrence (R 2  = 0.94). Patients were split into low-risk (0-2 points), medium-risk (3-5 points), and high-risk (6-8 points) classes and had the following recurrence rates: 8.9%, 20.2%, and 35.0%, respectively. Findings were similar in the validation cohort. Several CDI and patient-specific factors were independently associated with 60-day CDI recurrence risk. When integrated into a clinical prediction rule, higher risk scores and risk classes were strongly correlated with CDI recurrence. This clinical prediction rule can be used by providers to identify patients at high risk for CDI recurrence and help guide preventive strategy decisions, while accounting for clinical judgment. © 2018 Pharmacotherapy Publications, Inc.

QCT/FEA predictions of femoral stiffness are strongly affected by boundary condition modeling

PubMed Central

Rossman, Timothy; Kushvaha, Vinod; Dragomir-Daescu, Dan

2015-01-01

Quantitative computed tomography-based finite element models of proximal femora must be validated with cadaveric experiments before using them to assess fracture risk in osteoporotic patients. During validation it is essential to carefully assess whether the boundary condition modeling matches the experimental conditions. This study evaluated proximal femur stiffness results predicted by six different boundary condition methods on a sample of 30 cadaveric femora and compared the predictions with experimental data. The average stiffness varied by 280% among the six boundary conditions. Compared with experimental data the predictions ranged from overestimating the average stiffness by 65% to underestimating it by 41%. In addition we found that the boundary condition that distributed the load to the contact surfaces similar to the expected contact mechanics predictions had the best agreement with experimental stiffness. We concluded that boundary conditions modeling introduced large variations in proximal femora stiffness predictions. PMID:25804260

Feasibility and validity of the structured attention module among economically disadvantaged preschool-age children.

PubMed

Bush, Hillary H; Eisenhower, Abbey; Briggs-Gowan, Margaret; Carter, Alice S

2015-01-01

Rooted in the theory of attention put forth by Mirsky, Anthony, Duncan, Ahearn, and Kellam (1991), the Structured Attention Module (SAM) is a developmentally sensitive, computer-based performance task designed specifically to assess sustained selective attention among 3- to 6-year-old children. The current study addressed the feasibility and validity of the SAM among 64 economically disadvantaged preschool-age children (mean age = 58 months; 55% female); a population known to be at risk for attention problems and adverse math performance outcomes. Feasibility was demonstrated by high completion rates and strong associations between SAM performance and age. Principal Factor Analysis with rotation produced robust support for a three-factor model (Accuracy, Speed, and Endurance) of SAM performance, which largely corresponded with existing theorized models of selective and sustained attention. Construct validity was evidenced by positive correlations between SAM Composite scores and all three SAM factors and IQ, and between SAM Accuracy and sequential memory. Value-added predictive validity was not confirmed through main effects of SAM on math performance above and beyond age and IQ; however, significant interactions by child sex were observed: Accuracy and Endurance both interacted with child sex to predict math performance. In both cases, the SAM factors predicted math performance more strongly for girls than for boys. There were no overall sex differences in SAM performance. In sum, the current findings suggest that interindividual variation in sustained selective attention, and potentially other aspects of attention and executive function, among young, high-risk children can be captured validly with developmentally sensitive measures.

Systematic review of the concurrent and predictive validity of MRI biomarkers in OA

PubMed Central

Hunter, D.J.; Zhang, W.; Conaghan, Philip G.; Hirko, K.; Menashe, L.; Li, L.; Reichmann, W.M.; Losina, E.

2012-01-01

SUMMARY Objective To summarize literature on the concurrent and predictive validity of MRI-based measures of osteoarthritis (OA) structural change. Methods An online literature search was conducted of the OVID, EMBASE, CINAHL, PsychInfo and Cochrane databases of articles published up to the time of the search, April 2009. 1338 abstracts obtained with this search were preliminarily screened for relevance by two reviewers. Of these, 243 were selected for data extraction for this analysis on validity as well as separate reviews on discriminate validity and diagnostic performance. Of these 142 manuscripts included data pertinent to concurrent validity and 61 manuscripts for the predictive validity review. For this analysis we extracted data on criterion (concurrent and predictive) validity from both longitudinal and cross-sectional studies for all synovial joint tissues as it relates to MRI measurement in OA. Results Concurrent validity of MRI in OA has been examined compared to symptoms, radiography, histology/pathology, arthroscopy, CT, and alignment. The relation of bone marrow lesions, synovitis and effusion to pain was moderate to strong. There was a weak or no relation of cartilage morphology or meniscal tears to pain. The relation of cartilage morphology to radiographic OA and radiographic joint space was inconsistent. There was a higher frequency of meniscal tears, synovitis and other features in persons with radiographic OA. The relation of cartilage to other constructs including histology and arthroscopy was stronger. Predictive validity of MRI in OA has been examined for ability to predict total knee replacement (TKR), change in symptoms, radiographic progression as well as MRI progression. Quantitative cartilage volume change and presence of cartilage defects or bone marrow lesions are potential predictors of TKR. Conclusion MRI has inherent strengths and unique advantages in its ability to visualize multiple individual tissue pathologies relating to pain and also predict clinical outcome. The complex disease of OA which involves an array of tissue abnormalities is best imaged using this imaging tool. PMID:21396463

Strong expectations cancel locality effects: evidence from Hindi.

PubMed

Husain, Samar; Vasishth, Shravan; Srinivasan, Narayanan

2014-01-01

Expectation-driven facilitation (Hale, 2001; Levy, 2008) and locality-driven retrieval difficulty (Gibson, 1998, 2000; Lewis & Vasishth, 2005) are widely recognized to be two critical factors in incremental sentence processing; there is accumulating evidence that both can influence processing difficulty. However, it is unclear whether and how expectations and memory interact. We first confirm a key prediction of the expectation account: a Hindi self-paced reading study shows that when an expectation for an upcoming part of speech is dashed, building a rarer structure consumes more processing time than building a less rare structure. This is a strong validation of the expectation-based account. In a second study, we show that when expectation is strong, i.e., when a particular verb is predicted, strong facilitation effects are seen when the appearance of the verb is delayed; however, when expectation is weak, i.e., when only the part of speech "verb" is predicted but a particular verb is not predicted, the facilitation disappears and a tendency towards a locality effect is seen. The interaction seen between expectation strength and distance shows that strong expectations cancel locality effects, and that weak expectations allow locality effects to emerge.

Strong Expectations Cancel Locality Effects: Evidence from Hindi

PubMed Central

Husain, Samar; Vasishth, Shravan; Srinivasan, Narayanan

2014-01-01

Expectation-driven facilitation (Hale, 2001; Levy, 2008) and locality-driven retrieval difficulty (Gibson, 1998, 2000; Lewis & Vasishth, 2005) are widely recognized to be two critical factors in incremental sentence processing; there is accumulating evidence that both can influence processing difficulty. However, it is unclear whether and how expectations and memory interact. We first confirm a key prediction of the expectation account: a Hindi self-paced reading study shows that when an expectation for an upcoming part of speech is dashed, building a rarer structure consumes more processing time than building a less rare structure. This is a strong validation of the expectation-based account. In a second study, we show that when expectation is strong, i.e., when a particular verb is predicted, strong facilitation effects are seen when the appearance of the verb is delayed; however, when expectation is weak, i.e., when only the part of speech “verb” is predicted but a particular verb is not predicted, the facilitation disappears and a tendency towards a locality effect is seen. The interaction seen between expectation strength and distance shows that strong expectations cancel locality effects, and that weak expectations allow locality effects to emerge. PMID:25010700

Assessing the risk of imminent aggression in institutionalized youth offenders using the dynamic appraisal of situational aggression

PubMed Central

Chu, Chi Meng; Hoo, Eric; Daffern, Michael; Tan, Jolie

2012-01-01

Aggressive behavior in incarcerated youth presents a significant problem for staff, co-residents and the functioning of the institution. This study aimed to examine the predictive validity of an empirically validated measure, designed to appraise the risk of imminent aggression within institutionalized adult psychiatric patients (Dynamic Appraisal of Situational Aggression; DASA), in adolescent male and female offenders. The supervising staff members on the residential units rated the DASA daily for 49 youth (29 males and 20 females) over two months. The results showed that DASA total scores significantly predicted institutional aggression in the following 24 and 48 hrs; however, the predictive validity of the DASA for institutional aggression was, at best, modest. Further analyses on male and female subsamples revealed that the DASA total scores only predicted imminent institutional aggression in the male subsample. Item analyses showed that negative attitudes, anger when requests are denied, and unwillingness to follow instructions predicted institutional aggression more strongly as compared with other behavioral manifestations of an irritable and unstable mental state as assessed by the DASA. PMID:25999797

Polycystic ovary syndrome

PubMed Central

Pedersen, Sue D.; Brar, Sony; Faris, Peter; Corenblum, Bernard

2007-01-01

OBJECTIVE To construct and validate a questionnaire for use in diagnosis of polycystic ovary syndrome (PCOS). DESIGN All participants completed a questionnaire, which asked clinical questions designed to assist in the diagnosis of PCOS, before their appointments with an endocrinologist. Following completion of the questionnaire, the endocrinologist (blinded to the answers) made or excluded a diagnosis of PCOS using clinical criteria and biochemical data as indicated. Questions were then evaluated for their power to predict PCOS, and a model was constructed using the most reliable items to establish a system to predict a diagnosis of PCOS. SETTING An outpatient reproductive endocrinology clinic in Calgary, Alta. PARTICIPANTS Adult women patients who had been referred to the clinic. Fifty patients with PCOS and 50 patients without PCOS were included in the study. MAIN OUTCOME MEASURES Demographic information, medical history, related diagnoses, menstrual history, and fertility history. RESULTS A history of infrequent menses, hirsutism, obesity, and acne were strongly predictive of a diagnosis of PCOS, whereas a history of failed pregnancy attempts was not useful. A history of nipple discharge outside of pregnancy strongly predicted no diagnosis of PCOS. We constructed a 4-item questionnaire for use in diagnosis of PCOS; the questionnaire yielded a sensitivity of 85% and a specificity of 85% on multivariate logistic regression and a sensitivity of 77% and a specificity of 94% using the 4-item questionnaire. Predictive accuracy was validated using a second sample of 117 patients, in addition to internal validation using bootstrap analysis. CONCLUSION We have constructed a simple clinical tool to help diagnose PCOS. This questionnaire can be easily incorporated into family physicians’ busy practices. PMID:17872783

Construction of Source Model of Huge Subduction Earthquakes for Strong Ground Motion Prediction

NASA Astrophysics Data System (ADS)

Iwata, T.; Asano, K.; Kubo, H.

2013-12-01

It is a quite important issue for strong ground motion prediction to construct the source model of huge subduction earthquakes. Iwata and Asano (2012, AGU) summarized the scaling relationships of large slip area of heterogeneous slip model and total SMGA sizes on seismic moment for subduction earthquakes and found the systematic change between the ratio of SMGA to the large slip area and the seismic moment. They concluded this tendency would be caused by the difference of period range of source modeling analysis. In this paper, we try to construct the methodology of construction of the source model for strong ground motion prediction for huge subduction earthquakes. Following to the concept of the characterized source model for inland crustal earthquakes (Irikura and Miyake, 2001; 2011) and intra-slab earthquakes (Iwata and Asano, 2011), we introduce the proto-type of the source model for huge subduction earthquakes and validate the source model by strong ground motion modeling.

Antenna gain of actively compensated free-space optical communication systems under strong turbulence conditions.

PubMed

Juarez, Juan C; Brown, David M; Young, David W

2014-05-19

Current Strehl ratio models for actively compensated free-space optical communications terminals do not accurately predict system performance under strong turbulence conditions as they are based on weak turbulence theory. For evaluation of compensated systems, we present an approach for simulating the Strehl ratio with both low-order (tip/tilt) and higher-order (adaptive optics) correction. Our simulation results are then compared to the published models and their range of turbulence validity is assessed. Finally, we propose a new Strehl ratio model and antenna gain equation that are valid for general turbulence conditions independent of the degree of compensation.

Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

PubMed Central

Windhausen, Vanessa S.; Atlin, Gary N.; Hickey, John M.; Crossa, Jose; Jannink, Jean-Luc; Sorrells, Mark E.; Raman, Babu; Cairns, Jill E.; Tarekegne, Amsal; Semagn, Kassa; Beyene, Yoseph; Grudloyma, Pichet; Technow, Frank; Riedelsheimer, Christian; Melchinger, Albrecht E.

2012-01-01

Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F2-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F2-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set. PMID:23173094

Refining a measure of brain injury sequelae to predict postacute rehabilitation outcome: rating scale analysis of the Mayo-Portland Adaptability Inventory.

PubMed

Malec, J F; Moessner, A M; Kragness, M; Lezak, M D

2000-02-01

Evaluate the psychometric properties of the Mayo-Portland Adaptability Inventory (MPAI). Rating scale (Rasch) analysis of MPAI and principal component analysis of residuals; the predictive validity of the MPAI measures and raw scores was assessed in a sample from a day rehabilitation program. Outpatient brain injury rehabilitation. 305 persons with brain injury. A 22-item scale reflecting severity of sequelae of brain injury that contained a mix of indicators of impairment, activity, and participation was identified. Scores and measures for MPAI scales were strongly correlated and their predictive validities were comparable. Impairment, activity, and participation define a single dimension of brain injury sequelae. The MPAI shows promise as a measure of this construct.

A strong diffusive ion mode in dense ionized matter predicted by Langevin dynamics

DOE PAGES

Mabey, P.; Richardson, S.; White, T. G.; ...

2017-01-30

We determined the state and evolution of planets, brown dwarfs and neutron star crusts by the properties of dense and compressed matter. Furthermore, due to the inherent difficulties in modelling strongly coupled plasmas, however, current predictions of transport coefficients differ by orders of magnitude. Collective modes are a prominent feature, whose spectra may serve as an important tool to validate theoretical predictions for dense matter. With recent advances in free electron laser technology, X-rays with small enough bandwidth have become available, allowing the investigation of the low-frequency ion modes in dense matter. Here, we present numerical predictions for these ionmore » modes and demonstrate significant changes to their strength and dispersion if dissipative processes are included by Langevin dynamics. Notably, a strong diffusive mode around zero frequency arises, which is not present, or much weaker, in standard simulations. These results have profound consequences in the interpretation of transport coefficients in dense plasmas.« less

Core OCD Symptoms: Exploration of Specificity and Relations with Psychopathology

PubMed Central

Stasik, Sara M.; Naragon-Gainey, Kristin; Chmielewski, Michael; Watson, David

2012-01-01

Obsessive-compulsive disorder (OCD) is a heterogeneous condition, comprised of multiple symptom domains. This study used aggregate composite scales representing three core OCD dimensions (Checking, Cleaning, Rituals), as well as Hoarding, to examine the discriminant validity, diagnostic specificity, and predictive ability of OCD symptom scales. The core OCD scales demonstrated strong patterns of convergent and discriminant validity – suggesting that these dimensions are distinct from other self-reported symptoms – whereas hoarding symptoms correlated just as strongly with OCD and non-OCD symptoms in most analyses. Across analyses, our results indicated that Checking is a particularly strong, specific marker of OCD diagnosis, whereas the specificity of Cleaning and Hoarding to OCD was less strong. Finally, the OCD Checking scale was the only significant predictor of OCD diagnosis in logistic regression analyses. Results are discussed with regard to the importance of assessing OCD symptom dimensions separately and implications for classification. PMID:23026094

How reliable are ligand-centric methods for Target Fishing?

NASA Astrophysics Data System (ADS)

Peon, Antonio; Dang, Cuong; Ballester, Pedro

2016-04-01

Computational methods for Target Fishing (TF), also known as Target Prediction or Polypharmacology Prediction, can be used to discover new targets for small-molecule drugs. This may result in repositioning the drug in a new indication or improving our current understanding of its efficacy and side effects. While there is a substantial body of research on TF methods, there is still a need to improve their validation, which is often limited to a small part of the available targets and not easily interpretable by the user. Here we discuss how target-centric TF methods are inherently limited by the number of targets that can possibly predict (this number is by construction much larger in ligand-centric techniques). We also propose a new benchmark to validate TF methods, which is particularly suited to analyse how predictive performance varies with the query molecule. On average over approved drugs, we estimate that only five predicted targets will have to be tested to find two true targets with submicromolar potency (a strong variability in performance is however observed). In addition, we find that an approved drug has currently an average of eight known targets, which reinforces the notion that polypharmacology is a common and strong event. Furthermore, with the assistance of a control group of randomly-selected molecules, we show that the targets of approved drugs are generally harder to predict.

Score Reliability and Validity of the Student Risk Screening Scale: A Psychometrically Sound, Feasible Tool for Use in Urban Middle Schools

ERIC Educational Resources Information Center

Lane, Kathleen Lynne; Bruhn, Allison L.; Eisner, Shanna L.; Kalberg, Jemma Robertson

2010-01-01

In this article, the authors examine the psychometric properties of the "Student Risk Screening Scale" (SRSS) for use in urban middle schools. Results of Studies 1 and 2 suggest strong internal consistency and test-retest stability. Study 1 supports the predictive validity of the SRSS, with students at low risk being able to be differentiated from…

The Environmental Reward Observation Scale (EROS): development, validity, and reliability.

PubMed

Armento, Maria E A; Hopko, Derek R

2007-06-01

Researchers acknowledge a strong association between the frequency and duration of environmental reward and affective mood states, particularly in relation to the etiology, assessment, and treatment of depression. Given behavioral theories that outline environmental reward as a strong mediator of affect and the unavailability of an efficient, reliable, and valid self-report measure of environmental reward, we developed the Environmental Reward Observation Scale (EROS) and examined its psychometric properties. In Experiment 1, exploratory factor analysis supported a unidimensional 10-item measure with strong internal consistency and test-retest reliability. When administered to a replication sample, confirmatory factor analysis suggested an excellent fit to the 1-factor model and convergent/discriminant validity data supported the construct validity of the EROS. In Experiment 2, further support for the convergent validity of the EROS was obtained via moderate correlations with the Pleasant Events Schedule (PES; MacPhillamy & Lewinsohn, 1976). In Experiment 3, hierarchical regression supported the ecological validity of the EROS toward predicting daily diary reports of time spent in highly rewarding behaviors and activities. Above and beyond variance accounted for by depressive symptoms (BDI), the EROS was associated with significant incremental variance in accounting for time spent in both low and high reward behaviors. The EROS may represent a brief, reliable and valid measure of environmental reward that may improve the psychological assessment of negative mood states such as clinical depression.

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.

The predictive validity of ideal partner preferences: a review and meta-analysis.

PubMed

Eastwick, Paul W; Luchies, Laura B; Finkel, Eli J; Hunt, Lucy L

2014-05-01

A central element of interdependence theory is that people have standards against which they compare their current outcomes, and one ubiquitous standard in the mating domain is the preference for particular attributes in a partner (ideal partner preferences). This article reviews research on the predictive validity of ideal partner preferences and presents a new integrative model that highlights when and why ideals succeed or fail to predict relational outcomes. Section 1 examines predictive validity by reviewing research on sex differences in the preference for physical attractiveness and earning prospects. Men and women reliably differ in the extent to which these qualities affect their romantic evaluations of hypothetical targets. Yet a new meta-analysis spanning the attraction and relationships literatures (k = 97) revealed that physical attractiveness predicted romantic evaluations with a moderate-to-strong effect size (r = ∼.40) for both sexes, and earning prospects predicted romantic evaluations with a small effect size (r = ∼.10) for both sexes. Sex differences in the correlations were small (r difference = .03) and uniformly nonsignificant. Section 2 reviews research on individual differences in ideal partner preferences, drawing from several theoretical traditions to explain why ideals predict relational evaluations at different relationship stages. Furthermore, this literature also identifies alternative measures of ideal partner preferences that have stronger predictive validity in certain theoretically sensible contexts. Finally, a discussion highlights a new framework for conceptualizing the appeal of traits, the difference between live and hypothetical interactions, and the productive interplay between mating research and broader psychological theories.

Convergent and diagnostic validity of STAVUX, a word and pseudoword spelling test for adults.

PubMed

Östberg, Per; Backlund, Charlotte; Lindström, Emma

2016-10-01

Few comprehensive spelling tests are available in Swedish, and none have been validated in adults with reading and writing disorders. The recently developed STAVUX test includes word and pseudoword spelling subtests with high internal consistency and adult norms stratified by education. This study evaluated the convergent and diagnostic validity of STAVUX in adults with dyslexia. Forty-six adults, 23 with dyslexia and 23 controls, took STAVUX together with a standard word-decoding test and a self-rated measure of spelling skills. STAVUX subtest scores showed moderate to strong correlations with word-decoding scores and predicted self-rated spelling skills. Word and pseudoword subtest scores both predicted dyslexia status. Receiver-operating characteristic (ROC) analysis showed excellent diagnostic discriminability. Sensitivity was 91% and specificity 96%. In conclusion, the results of this study support the convergent and diagnostic validity of STAVUX.

Spatio-temporal modeling of chronic PM 10 exposure for the Nurses' Health Study

NASA Astrophysics Data System (ADS)

Yanosky, Jeff D.; Paciorek, Christopher J.; Schwartz, Joel; Laden, Francine; Puett, Robin; Suh, Helen H.

2008-06-01

Chronic epidemiological studies of airborne particulate matter (PM) have typically characterized the chronic PM exposures of their study populations using city- or county-wide ambient concentrations, which limit the studies to areas where nearby monitoring data are available and which ignore within-city spatial gradients in ambient PM concentrations. To provide more spatially refined and precise chronic exposure measures, we used a Geographic Information System (GIS)-based spatial smoothing model to predict monthly outdoor PM10 concentrations in the northeastern and midwestern United States. This model included monthly smooth spatial terms and smooth regression terms of GIS-derived and meteorological predictors. Using cross-validation and other pre-specified selection criteria, terms for distance to road by road class, urban land use, block group and county population density, point- and area-source PM10 emissions, elevation, wind speed, and precipitation were found to be important determinants of PM10 concentrations and were included in the final model. Final model performance was strong (cross-validation R2=0.62), with little bias (-0.4 μg m-3) and high precision (6.4 μg m-3). The final model (with monthly spatial terms) performed better than a model with seasonal spatial terms (cross-validation R2=0.54). The addition of GIS-derived and meteorological predictors improved predictive performance over spatial smoothing (cross-validation R2=0.51) or inverse distance weighted interpolation (cross-validation R2=0.29) methods alone and increased the spatial resolution of predictions. The model performed well in both rural and urban areas, across seasons, and across the entire time period. The strong model performance demonstrates its suitability as a means to estimate individual-specific chronic PM10 exposures for large populations.

Validation of the FACT-B+4-UL questionnaire and exploration of its predictive value in women submitted to surgery for breast cancer.

PubMed

Andrade Ortega, Juan Alfonso; Millán Gómez, Ana Pilar; Ribeiro González, Marisa; Martínez Piró, Pilar; Jiménez Anula, Juan; Sánchez Andújar, María Belén

2017-06-21

The early detection of upper limb complications is important in women operated on for breast cancer. The "FACT-B+4-UL" questionnaire, a specific variant of the Functional Assessment of Cancer Therapy-Breast (FACT-B) is available among others to measure the upper limb function. The Spanish version of the upper limb subscale of the FACT-B+4 was validated in a prospective cohort of 201 women operated on for breast cancer (factor analysis, internal consistency, test-retest reliability, construct validity and sensitivity to change were determined). Its predictive capacity of subsequent lymphoedema and other complications in the upper limb was explored using logistic regression. This subscale is unifactorial and has a great internal consistency (Cronbach's alpha: 0.87), its test-retest reliability and construct validity are strong (intraclass correlation coefficient: 0.986; Pearson's R with "Quick DASH": 0.81) as is its sensitivity to change. It didn't predict the onset of lymphedema. Its predictive capacity for other upper limb complications is low. FACT-B+4-UL is useful in measuring upper limb disability in women surgically treated for breast cancer; but it does not predict the onset of lymphoedema and its predictive capacity for others complications in the upper limb is low. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Reliability and validity of the Fear of Intimacy Scale in China.

PubMed

Ingersoll, Travis S; Norvilitis, Jill M; Zhang, Jie; Jia, Shuhua; Tetewsky, Sheldon

2008-05-01

Participants in China (n = 343) and the United States (n = 283) completed measures to assess the reliability and validity of the Fear of Intimacy Scale (Descutner & Thelen, 1991) with a Chinese population. Internal consistency was strong in both cultures, and the factor structure was also similar between cultures, with confirmatory factor analysis (CFA) identifying three-factor models in both samples. As evidence of convergent validity, the scale was positively correlated with depression and negatively correlated with social support and self-esteem. There were gender differences between cultures, but low levels of femininity were predictive of fear of intimacy in both cultures. The influence of individualism and collectivism varied, with high levels of individualism more predictive of a fear of intimacy in China than in the United States.

Transformational and transactional leadership: a meta-analytic test of their relative validity.

PubMed

Judge, Timothy A; Piccolo, Ronald F

2004-10-01

This study provided a comprehensive examination of the full range of transformational, transactional, and laissez-faire leadership. Results (based on 626 correlations from 87 sources) revealed an overall validity of .44 for transformational leadership, and this validity generalized over longitudinal and multisource designs. Contingent reward (.39) and laissez-faire (-.37) leadership had the next highest overall relations; management by exception (active and passive) was inconsistently related to the criteria. Surprisingly, there were several criteria for which contingent reward leadership had stronger relations than did transformational leadership. Furthermore, transformational leadership was strongly correlated with contingent reward (.80) and laissez-faire (-.65) leadership. Transformational and contingent reward leadership generally predicted criteria controlling for the other leadership dimensions, although transformational leadership failed to predict leader job performance. (c) 2004 APA, all rights reserved

Validating Quantitative Measurement Using Qualitative Data: Combining Rasch Scaling and Latent Semantic Analysis in Psychiatry

NASA Astrophysics Data System (ADS)

Lange, Rense

2015-02-01

An extension of concurrent validity is proposed that uses qualitative data for the purpose of validating quantitative measures. The approach relies on Latent Semantic Analysis (LSA) which places verbal (written) statements in a high dimensional semantic space. Using data from a medical / psychiatric domain as a case study - Near Death Experiences, or NDE - we established concurrent validity by connecting NDErs qualitative (written) experiential accounts with their locations on a Rasch scalable measure of NDE intensity. Concurrent validity received strong empirical support since the variance in the Rasch measures could be predicted reliably from the coordinates of their accounts in the LSA derived semantic space (R2 = 0.33). These coordinates also predicted NDErs age with considerable precision (R2 = 0.25). Both estimates are probably artificially low due to the small available data samples (n = 588). It appears that Rasch scalability of NDE intensity is a prerequisite for these findings, as each intensity level is associated (at least probabilistically) with a well- defined pattern of item endorsements.

Integration of biological data by kernels on graph nodes allows prediction of new genes involved in mitotic chromosome condensation

PubMed Central

Hériché, Jean-Karim; Lees, Jon G.; Morilla, Ian; Walter, Thomas; Petrova, Boryana; Roberti, M. Julia; Hossain, M. Julius; Adler, Priit; Fernández, José M.; Krallinger, Martin; Haering, Christian H.; Vilo, Jaak; Valencia, Alfonso; Ranea, Juan A.; Orengo, Christine; Ellenberg, Jan

2014-01-01

The advent of genome-wide RNA interference (RNAi)–based screens puts us in the position to identify genes for all functions human cells carry out. However, for many functions, assay complexity and cost make genome-scale knockdown experiments impossible. Methods to predict genes required for cell functions are therefore needed to focus RNAi screens from the whole genome on the most likely candidates. Although different bioinformatics tools for gene function prediction exist, they lack experimental validation and are therefore rarely used by experimentalists. To address this, we developed an effective computational gene selection strategy that represents public data about genes as graphs and then analyzes these graphs using kernels on graph nodes to predict functional relationships. To demonstrate its performance, we predicted human genes required for a poorly understood cellular function—mitotic chromosome condensation—and experimentally validated the top 100 candidates with a focused RNAi screen by automated microscopy. Quantitative analysis of the images demonstrated that the candidates were indeed strongly enriched in condensation genes, including the discovery of several new factors. By combining bioinformatics prediction with experimental validation, our study shows that kernels on graph nodes are powerful tools to integrate public biological data and predict genes involved in cellular functions of interest. PMID:24943848

Polymer Brushes under High Load

PubMed Central

Balko, Suzanne M.; Kreer, Torsten; Costanzo, Philip J.; Patten, Tim E.; Johner, Albert; Kuhl, Tonya L.; Marques, Carlos M.

2013-01-01

Polymer coatings are frequently used to provide repulsive forces between surfaces in solution. After 25 years of design and study, a quantitative model to explain and predict repulsion under strong compression is still lacking. Here, we combine experiments, simulations, and theory to study polymer coatings under high loads and demonstrate a validated model for the repulsive forces, proposing that this universal behavior can be predicted from the polymer solution properties. PMID:23516470

Evaluation of the Cardiac Depression Visual Analogue Scale in a medical and non-medical sample.

PubMed

Di Benedetto, Mirella; Sheehan, Matthew

2014-01-01

Comorbid depression and medical illness is associated with a number of adverse health outcomes such as lower medication adherence and higher rates of subsequent mortality. Reliable and valid psychological measures capable of detecting a range of depressive symptoms found in medical settings are needed. The Cardiac Depression Visual Analogue Scale (CDVAS) is a recently developed, brief six-item measure originally designed to assess the range and severity of depressive symptoms within a cardiac population. The current study aimed to further investigate the psychometric properties of the CDVAS in a general and medical sample. The sample consisted of 117 participants, whose mean age was 40.0 years (SD = 19.0, range 18-84). Participants completed the CDVAS, the Cardiac Depression Scale (CDS), the Depression Anxiety Stress Scales (DASS) and a demographic and health questionnaire. The CDVAS was found to have adequate internal reliability (α = .76), strong concurrent validity with the CDS (r = .89) and the depression sub-scale of the DASS (r = .70), strong discriminant validity and strong predictive validity. The principal components analysis revealed that the CDVAS measured only one component, providing further support for the construct validity of the scale. Results of the current study indicate that the CDVAS is a short, simple, valid and reliable measure of depressive symptoms suitable for use in a general and medical sample.

Sex-specific lean body mass predictive equations are accurate in the obese paediatric population

PubMed Central

Jackson, Lanier B.; Henshaw, Melissa H.; Carter, Janet; Chowdhury, Shahryar M.

2015-01-01

Background The clinical assessment of lean body mass (LBM) is challenging in obese children. A sex-specific predictive equation for LBM derived from anthropometric data was recently validated in children. Aim The purpose of this study was to independently validate these predictive equations in the obese paediatric population. Subjects and methods Obese subjects aged 4–21 were analysed retrospectively. Predicted LBM (LBMp) was calculated using equations previously developed in children. Measured LBM (LBMm) was derived from dual-energy x-ray absorptiometry. Agreement was expressed as [(LBMm-LBMp)/LBMm] with 95% limits of agreement. Results Of 310 enrolled patients, 195 (63%) were females. The mean age was 11.8 ± 3.4 years and mean BMI Z-score was 2.3 ± 0.4. The average difference between LBMm and LBMp was −0.6% (−17.0%, 15.8%). Pearson’s correlation revealed a strong linear relationship between LBMm and LBMp (r=0.97, p<0.01). Conclusion This study validates the use of these clinically-derived sex-specific LBM predictive equations in the obese paediatric population. Future studies should use these equations to improve the ability to accurately classify LBM in obese children. PMID:26287383

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.

Determination of the criterion-related validity of hip joint angle test for estimating hamstring flexibility using a contemporary statistical approach.

PubMed

Sainz de Baranda, Pilar; Rodríguez-Iniesta, María; Ayala, Francisco; Santonja, Fernando; Cejudo, Antonio

2014-07-01

To examine the criterion-related validity of the horizontal hip joint angle (H-HJA) test and vertical hip joint angle (V-HJA) test for estimating hamstring flexibility measured through the passive straight-leg raise (PSLR) test using contemporary statistical measures. Validity study. Controlled laboratory environment. One hundred thirty-eight professional trampoline gymnasts (61 women and 77 men). Hamstring flexibility. Each participant performed 2 trials of H-HJA, V-HJA, and PSLR tests in a randomized order. The criterion-related validity of H-HJA and V-HJA tests was measured through the estimation equation, typical error of the estimate (TEEST), validity correlation (β), and their respective confidence limits. The findings from this study suggest that although H-HJA and V-HJA tests showed moderate to high validity scores for estimating hamstring flexibility (standardized TEEST = 0.63; β = 0.80), the TEEST statistic reported for both tests was not narrow enough for clinical purposes (H-HJA = 10.3 degrees; V-HJA = 9.5 degrees). Subsequently, the predicted likely thresholds for the true values that were generated were too wide (H-HJA = predicted value ± 13.2 degrees; V-HJA = predicted value ± 12.2 degrees). The results suggest that although the HJA test showed moderate to high validity scores for estimating hamstring flexibility, the prediction intervals between the HJA and PSLR tests are not strong enough to suggest that clinicians and sport medicine practitioners should use the HJA and PSLR tests interchangeably as gold standard measurement tools to evaluate and detect short hamstring muscle flexibility.

Development and Validation of the Faceted Inventory of the Five-Factor Model (FI-FFM).

PubMed

Watson, David; Nus, Ericka; Wu, Kevin D

2017-06-01

The Faceted Inventory of the Five-Factor Model (FI-FFM) is a comprehensive hierarchical measure of personality. The FI-FFM was created across five phases of scale development. It includes five facets apiece for neuroticism, extraversion, and conscientiousness; four facets within agreeableness; and three facets for openness. We present reliability and validity data obtained from three samples. The FI-FFM scales are internally consistent and highly stable over 2 weeks (retest rs ranged from .64 to .82, median r = .77). They show strong convergent and discriminant validity vis-à-vis the NEO, the Big Five Inventory, and the Personality Inventory for DSM-5. Moreover, self-ratings on the scales show moderate to strong agreement with corresponding ratings made by informants ( rs ranged from .26 to .66, median r = .42). Finally, in joint analyses with the NEO Personality Inventory-3, the FI-FFM neuroticism facet scales display significant incremental validity in predicting indicators of internalizing psychopathology.

Validating spatiotemporal predictions of an important pest of small grains.

PubMed

Merrill, Scott C; Holtzer, Thomas O; Peairs, Frank B; Lester, Philip J

2015-01-01

Arthropod pests are typically managed using tactics applied uniformly to the whole field. Precision pest management applies tactics under the assumption that within-field pest pressure differences exist. This approach allows for more precise and judicious use of scouting resources and management tactics. For example, a portion of a field delineated as attractive to pests may be selected to receive extra monitoring attention. Likely because of the high variability in pest dynamics, little attention has been given to developing precision pest prediction models. Here, multimodel synthesis was used to develop a spatiotemporal model predicting the density of a key pest of wheat, the Russian wheat aphid, Diuraphis noxia (Kurdjumov). Spatially implicit and spatially explicit models were synthesized to generate spatiotemporal pest pressure predictions. Cross-validation and field validation were used to confirm model efficacy. A strong within-field signal depicting aphid density was confirmed with low prediction errors. Results show that the within-field model predictions will provide higher-quality information than would be provided by traditional field scouting. With improvements to the broad-scale model component, the model synthesis approach and resulting tool could improve pest management strategy and provide a template for the development of spatially explicit pest pressure models. © 2014 Society of Chemical Industry.

Development of an Individualism-Collectivism Scale revisited: a Korean sample.

PubMed

Kim, Kitae; Cho, Bongsoon

2011-04-01

A 13-item Individualism-Collectivism scale comprising source of identity, goal priority, mode of social relation, and norm acceptance is presented. A validation of this scale was conducted using a survey of 773 Korean employees. An exploratory factor analysis and a second-order confirmatory factor analysis supported the measure as having theoretical face validity and acceptable internal consistency reliability. Among the four facets, goal priority most strongly predicted the general Individualism-Collectivism latent factor.

Analytical Modeling for Mechanical Strength Prediction with Raman Spectroscopy and Fractured Surface Morphology of Novel Coconut Shell Powder Reinforced: Epoxy Composites

NASA Astrophysics Data System (ADS)

Singh, Savita; Singh, Alok; Sharma, Sudhir Kumar

2017-06-01

In this paper, an analytical modeling and prediction of tensile and flexural strength of three dimensional micro-scaled novel coconut shell powder (CSP) reinforced epoxy polymer composites have been reported. The novel CSP has a specific mixing ratio of different coconut shell particle size. A comparison is made between obtained experimental strength and modified Guth model. The result shows a strong evidence for non-validation of modified Guth model for strength prediction. Consequently, a constitutive modeled equation named Singh model has been developed to predict the tensile and flexural strength of this novel CSP reinforced epoxy composite. Moreover, high resolution Raman spectrum shows that 40 % CSP reinforced epoxy composite has high dielectric constant to become an alternative material for capacitance whereas fractured surface morphology revealed that a strong bonding between novel CSP and epoxy polymer for the application as light weight composite materials in engineering.

Predictors of early growth in academic achievement: the head-toes-knees-shoulders task

PubMed Central

McClelland, Megan M.; Cameron, Claire E.; Duncan, Robert; Bowles, Ryan P.; Acock, Alan C.; Miao, Alicia; Pratt, Megan E.

2014-01-01

Children's behavioral self-regulation and executive function (EF; including attentional or cognitive flexibility, working memory, and inhibitory control) are strong predictors of academic achievement. The present study examined the psychometric properties of a measure of behavioral self-regulation called the Head-Toes-Knees-Shoulders (HTKS) by assessing construct validity, including relations to EF measures, and predictive validity to academic achievement growth between prekindergarten and kindergarten. In the fall and spring of prekindergarten and kindergarten, 208 children (51% enrolled in Head Start) were assessed on the HTKS, measures of cognitive flexibility, working memory (WM), and inhibitory control, and measures of emergent literacy, mathematics, and vocabulary. For construct validity, the HTKS was significantly related to cognitive flexibility, working memory, and inhibitory control in prekindergarten and kindergarten. For predictive validity in prekindergarten, a random effects model indicated that the HTKS significantly predicted growth in mathematics, whereas a cognitive flexibility task significantly predicted growth in mathematics and vocabulary. In kindergarten, the HTKS was the only measure to significantly predict growth in all academic outcomes. An alternative conservative analytical approach, a fixed effects analysis (FEA) model, also indicated that growth in both the HTKS and measures of EF significantly predicted growth in mathematics over four time points between prekindergarten and kindergarten. Results demonstrate that the HTKS involves cognitive flexibility, working memory, and inhibitory control, and is substantively implicated in early achievement, with the strongest relations found for growth in achievement during kindergarten and associations with emergent mathematics. PMID:25071619

Assessment of EchoMRI-AH versus dual-energy X-ray absorptiometry by iDXA to measure human body composition.

PubMed

Marlatt, K L; Greenway, F L; Ravussin, E

2017-04-01

Comparison of percent fat mass across different body composition analysis devices is important given variation in technology accuracy and precision, as well as the growing need for cross-validation of devices often applied across longitudinal studies. We compared EchoMRI-AH and Lunar iDXA quantification of percent body fat (PBF) in 84 adults (43M, 41F), with the mean age 39.7±15.9 years and body mass index (BMI) 26.2±5.3 kg/m 2 . PBF correlated strongly between devices (r>0.95, P<0.0001). A prediction equation was derived in half of the subjects, and the other half were used to cross-validate the proposed equation (EchoMRI-AH PBF=[(0.94 × iDXA PBF)+(0.14 × Age)+(3.3 × Female)-8.83). The mean PBF difference (predicted-measured) in the validation group was not different from 0 (diff=0.27%, 95% confidence interval: -0.42-0.96, P=0.430). Bland-Altman plots showed a bias with higher measured PBF on EchoMRI-AH versus iDXA in all 84 subjects (β=0.13, P<0.0001). The proposed prediction equation was valid in our cross-validation sample, and it has the potential to be applied across multicenter studies.

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.

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

PubMed

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

2015-01-01

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

Personality traits and achievement motives: theoretical and empirical relations between the NEO Personality Inventory-Revised and the Achievement Motives Scale.

PubMed

Diseth, Age; Martinsen, Øyvind

2009-04-01

Theoretical and empirical relations between personality traits and motive dispositions were investigated by comparing scores of 315 undergraduate psychology students on the NEO Personality Inventory-Revised and the Achievement Motives Scale. Analyses showed all NEO Personality Inventory-Revised factors except agreeableness were significantly correlated with the motive for success and the motive to avoid failure. A structural equation model showed that motive for success was predicted by Extraversion, Openness, Conscientiousness, and Neuroticism (negative relation), and motive to avoid failure was predicted by Neuroticism and Openness (negative relation). Although both achievement motives were predicted by several personality factors, motive for success was most strongly predicted by Openness, and motive to avoid failure was most strongly predicted by neuroticism. These findings extended previous research on the relations of personality traits and achievement motives and provided a basis for the discussion of motive dispositions in personality. The results also added to the construct validity of the Achievement Motives Scale.

How Students Create Motivationally Supportive Learning Environments for Themselves: The Concept of Agentic Engagement

ERIC Educational Resources Information Center

Reeve, Johnmarshall

2013-01-01

The present study introduced "agentic engagement" as a newly proposed student-initiated pathway to greater achievement and greater motivational support. Study 1 developed the brief, construct-congruent, and psychometrically strong Agentic Engagement Scale. Study 2 provided evidence for the scale's construct and predictive validity, as…

The Gender Difference: Validity of Standardized Admission Tests in Predicting MBA Performance.

ERIC Educational Resources Information Center

Hancock, Terence

1999-01-01

Of 120 female and 149 male master of business administration (MBA) students, women performed significantly less well on the Graduate Management Admission Test (GMAT). There were no differences in overall MBA grade point average, indicating no strong correlation between the GMAT and MBA performance. (SK)

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

PubMed

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

2015-07-01

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

The Irvine, Beatties, and Bresnahan (IBB) Forelimb Recovery Scale: An Assessment of Reliability and Validity

PubMed Central

Irvine, Karen-Amanda; Ferguson, Adam R.; Mitchell, Kathleen D.; Beattie, Stephanie B.; Lin, Amity; Stuck, Ellen D.; Huie, J. Russell; Nielson, Jessica L.; Talbott, Jason F.; Inoue, Tomoo; Beattie, Michael S.; Bresnahan, Jacqueline C.

2014-01-01

The IBB scale is a recently developed forelimb scale for the assessment of fine control of the forelimb and digits after cervical spinal cord injury [SCI; (1)]. The present paper describes the assessment of inter-rater reliability and face, concurrent and construct validity of this scale following SCI. It demonstrates that the IBB is a reliable and valid scale that is sensitive to severity of SCI and to recovery over time. In addition, the IBB correlates with other outcome measures and is highly predictive of biological measures of tissue pathology. Multivariate analysis using principal component analysis (PCA) demonstrates that the IBB is highly predictive of the syndromic outcome after SCI (2), and is among the best predictors of bio-behavioral function, based on strong construct validity. Altogether, the data suggest that the IBB, especially in concert with other measures, is a reliable and valid tool for assessing neurological deficits in fine motor control of the distal forelimb, and represents a powerful addition to multivariate outcome batteries aimed at documenting recovery of function after cervical SCI in rats. PMID:25071704

Defining physicians' readiness to screen and manage intimate partner violence in Greek primary care settings.

PubMed

Papadakaki, Maria; Prokopiadou, Dimitra; Petridou, Eleni; Kogevinas, Manolis; Lionis, Christos

2012-06-01

The current article aims to translate the PREMIS (Physician Readiness to Manage Intimate Partner Violence) survey into the Greek language and test its validity and reliability in a sample of primary care physicians. The validation study was conducted in 2010 and involved all the general practitioners serving two adjacent prefectures of Greece (n = 80). Maximum-likelihood factor analysis (MLF) was used to extract key survey factors. The instrument was further assessed for the following psychometric properties: (a) scale reliability, (b) item-specific reliability, (c) test-retest reliability, (d) scale construct validity, and (e) internal predictive validity. The MLF analysis of 23 opinion items revealed a seven-factor solution (preparation, constraint, workplace issues, screening, self-efficacy, alcohol/drugs, victim understanding), which was statistically sound (p = .293). Most of the newly derived scales displayed satisfactory internal consistency (α ≥ .60), high item-specific reliability, strong construct, and internal predictive validity (F = 2.82; p = .004), and high repeatability when retested with 20 individuals (intraclass correlation coefficient [ICC] > .70). The tool was found appropriate to facilitate the identification of competence deficits and the evaluation of training initiatives.

Anti-signal recognition particle autoantibody ELISA validation and clinical associations.

PubMed

Aggarwal, Rohit; Oddis, Chester V; Goudeau, Danielle; Fertig, Noreen; Metes, Ilinca; Stephens, Chad; Qi, Zengbiao; Koontz, Diane; Levesque, Marc C

2015-07-01

The aim of this study was to develop and validate a quantitative anti-signal recognition particle (SRP) autoantibody serum ELISA in patients with myositis and longitudinal association with myositis disease activity. We developed a serum ELISA using recombinant purified full-length human SRP coated on ELISA plates and a secondary antibody that bound human IgG to detect anti-SRP binding. Protein immunoprecipitation was used as the gold standard for the presence of anti-SRP. Serum samples from three groups were analysed: SRP(+) myositis subjects by immunoprecipitation, SRP(-) myositis subjects by immunoprecipitation and non-myositis controls. The ELISA's sensitivity, specificity, positive predictive value and negative predictive value were evaluated. Percentage agreement and test-retest reliability were assessed. Serial samples from seven SRP immunoprecipitation-positive subjects were also tested, along with serum muscle enzymes and manual muscle testing. Using immunoprecipitation, we identified 26 SRP(+) myositis patients and 77 SRP(-) controls (including 38 patients with necrotizing myopathy). Non-myositis control patients included SLE (n = 4) and SSc (n = 7) patients. Anti-SRP positivity by ELISA showed strong agreement (97.1%) with immunoprecipitation (κ = 0.94). The sensitivity, specificity, positive predictive value, and negative predictive value of the anti-SRP ELISA were 88, 100, 100 and 96, respectively. The area under the curve was 0.94, and test-retest reliability was strong (r = 0.91, P < 0.001). Serial samples showed that anti-SRP levels paralleled changes in muscle enzymes and manual muscle testing. We developed a quantitative ELISA for detecting serum anti-SRP autoantibodies and validated the assay in myositis. Longitudinal assessment of SRP levels by ELISA may be a useful biomarker for disease activity. © The Author 2014. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Automatic Avoidance Tendencies for Alcohol Cues Predict Drinking After Detoxification Treatment in Alcohol Dependence

PubMed Central

2016-01-01

Alcohol dependence is characterized by conflict between approach and avoidance motivational orientations for alcohol that operate in automatic and controlled processes. This article describes the first study to investigate the predictive validity of these motivational orientations for relapse to drinking after discharge from alcohol detoxification treatment in alcohol-dependent patients. One hundred twenty alcohol-dependent patients who were nearing the end of inpatient detoxification treatment completed measures of self-reported (Approach and Avoidance of Alcohol Questionnaire; AAAQ) and automatic (modified Stimulus-Response Compatibility task) approach and avoidance motivational orientations for alcohol. Their drinking behavior was assessed via telephone follow-ups at 2, 4, and 6 months after discharge from treatment. Results indicated that, after controlling for the severity of alcohol dependence, strong automatic avoidance tendencies for alcohol cues were predictive of higher percentage of heavy drinking days (PHDD) at 4-month (β = 0.22, 95% CI [0.07, 0.43]) and 6-month (β = 0.22, 95% CI [0.01, 0.42]) follow-ups. We failed to replicate previous demonstrations of the predictive validity of approach subscales of the AAAQ for relapse to drinking, and there were no significant predictors of PHDD at 2-month follow-up. In conclusion, strong automatic avoidance tendencies predicted relapse to drinking after inpatient detoxification treatment, but automatic approach tendencies and self-reported approach and avoidance tendencies were not predictive in this study. Our results extend previous findings and help to resolve ambiguities with earlier studies that investigated the roles of automatic and controlled cognitive processes in recovery from alcohol dependence. PMID:27935726

Development and validation of the Pediatric Anesthesia Behavior score--an objective measure of behavior during induction of anesthesia.

PubMed

Beringer, Richard M; Greenwood, Rosemary; Kilpatrick, Nicky

2014-02-01

Measuring perioperative behavior changes requires validated objective rating scales. We developed a simple score for children's behavior during induction of anesthesia (Pediatric Anesthesia Behavior score) and assessed its reliability, concurrent validity, and predictive validity. Data were collected as part of a wider observational study of perioperative behavior changes in children undergoing general anesthesia for elective dental extractions. One-hundred and two healthy children aged 2-12 were recruited. Previously validated behavioral scales were used as follows: the modified Yale Preoperative Anxiety Scale (m-YPAS); the induction compliance checklist (ICC); the Pediatric Anesthesia Emergence Delirium scale (PAED); and the Post-Hospitalization Behavior Questionnaire (PHBQ). Pediatric Anesthesia Behavior (PAB) score was independently measured by two investigators, to allow assessment of interobserver reliability. Concurrent validity was assessed by examining the correlation between the PAB score, the m-YPAS, and the ICC. Predictive validity was assessed by examining the association between the PAB score, the PAED scale, and the PHBQ. The PAB score correlated strongly with both the m-YPAS (P < 0.001) and the ICC (P < 0.001). PAB score was significantly associated with the PAED score (P = 0.031) and with the PHBQ (P = 0.034). Two independent investigators recorded identical PAB scores for 94% of children and overall, there was close agreement between scores (Kappa coefficient of 0.886 [P < 0.001]). The PAB score is simple to use and may predict which children are at increased risk of developing postoperative behavioral disturbance. This study provides evidence for its reliability and validity. © 2013 John Wiley & Sons Ltd.

Fractional viscoelasticity in fractal and non-fractal media: Theory, experimental validation, and uncertainty analysis

NASA Astrophysics Data System (ADS)

Mashayekhi, Somayeh; Miles, Paul; Hussaini, M. Yousuff; Oates, William S.

2018-02-01

In this paper, fractional and non-fractional viscoelastic models for elastomeric materials are derived and analyzed in comparison to experimental results. The viscoelastic models are derived by expanding thermodynamic balance equations for both fractal and non-fractal media. The order of the fractional time derivative is shown to strongly affect the accuracy of the viscoelastic constitutive predictions. Model validation uses experimental data describing viscoelasticity of the dielectric elastomer Very High Bond (VHB) 4910. Since these materials are known for their broad applications in smart structures, it is important to characterize and accurately predict their behavior across a large range of time scales. Whereas integer order viscoelastic models can yield reasonable agreement with data, the model parameters often lack robustness in prediction at different deformation rates. Alternatively, fractional order models of viscoelasticity provide an alternative framework to more accurately quantify complex rate-dependent behavior. Prior research that has considered fractional order viscoelasticity lacks experimental validation and contains limited links between viscoelastic theory and fractional order derivatives. To address these issues, we use fractional order operators to experimentally validate fractional and non-fractional viscoelastic models in elastomeric solids using Bayesian uncertainty quantification. The fractional order model is found to be advantageous as predictions are significantly more accurate than integer order viscoelastic models for deformation rates spanning four orders of magnitude.

Validation of a temperature prediction model for heat deaths in undocumented border crossers.

PubMed

Ruttan, Tim; Stolz, Uwe; Jackson-Vance, Sara; Parks, Bruce; Keim, Samuel M

2013-04-01

Heat exposure is a leading cause of death in undocumented border crossers along the Arizona-Mexico border. We performed a validation study of a weather prediction model that predicts the probability of heat related deaths among undocumented border crossers. We analyzed a medical examiner registry cohort of undocumented border crosser heat- related deaths from January 1, 2002 to August 31, 2009 and used logistic regression to model the probability of one or more heat deaths on a given day using daily high temperature (DHT) as the predictor. At a critical threshold DHT of 40 °C, the probability of at least one heat death was 50 %. The probability of a heat death along the Arizona-Mexico border for suspected undocumented border crossers is strongly associated with ambient temperature. These results can be used in prevention and response efforts to assess the daily risk of deaths among undocumented border crossers in the region.

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.

Do in-training evaluation reports deserve their bad reputations? A study of the reliability and predictive ability of ITER scores and narrative comments.

PubMed

Ginsburg, Shiphra; Eva, Kevin; Regehr, Glenn

2013-10-01

Although scores on in-training evaluation reports (ITERs) are often criticized for poor reliability and validity, ITER comments may yield valuable information. The authors assessed across-rotation reliability of ITER scores in one internal medicine program, ability of ITER scores and comments to predict postgraduate year three (PGY3) performance, and reliability and incremental predictive validity of attendings' analysis of written comments. Numeric and narrative data from the first two years of ITERs for one cohort of residents at the University of Toronto Faculty of Medicine (2009-2011) were assessed for reliability and predictive validity of third-year performance. Twenty-four faculty attendings rank-ordered comments (without scores) such that each resident was ranked by three faculty. Mean ITER scores and comment rankings were submitted to regression analyses; dependent variables were PGY3 ITER scores and program directors' rankings. Reliabilities of ITER scores across nine rotations for 63 residents were 0.53 for both postgraduate year one (PGY1) and postgraduate year two (PGY2). Interrater reliabilities across three attendings' rankings were 0.83 for PGY1 and 0.79 for PGY2. There were strong correlations between ITER scores and comments within each year (0.72 and 0.70). Regressions revealed that PGY1 and PGY2 ITER scores collectively explained 25% of variance in PGY3 scores and 46% of variance in PGY3 rankings. Comment rankings did not improve predictions. ITER scores across multiple rotations showed decent reliability and predictive validity. Comment ranks did not add to the predictive ability, but correlation analyses suggest that trainee performance can be measured through these comments.

Initial Retrieval Validation from the Joint Airborne IASI Validation Experiment (JAIVEx)

NASA Technical Reports Server (NTRS)

Zhou, Daniel K.; Liu, Xu; Smith, WIlliam L.; Larar, Allen M.; Taylor, Jonathan P.; Revercomb, Henry E.; Mango, Stephen A.; Schluessel, Peter; Calbet, Xavier

2007-01-01

The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite, but also included a strong component focusing on validation of the Atmospheric InfraRed Sounder (AIRS) aboard the AQUA satellite. The cross validation of IASI and AIRS is important for the joint use of their data in the global Numerical Weather Prediction process. Initial inter-comparisons of geophysical products have been conducted from different aspects, such as using different measurements from airborne ultraspectral Fourier transform spectrometers (specifically, the NPOESS Airborne Sounder Testbed Interferometer (NAST-I) and the Scanning-High resolution Interferometer Sounder (S-HIS) aboard the NASA WB-57 aircraft), UK Facility for Airborne Atmospheric Measurements (FAAM) BAe146-301 aircraft insitu instruments, dedicated dropsondes, radiosondes, and ground based Raman Lidar. An overview of the JAIVEx retrieval validation plan and some initial results of this field campaign are presented.

Predicting Persistent Back Symptoms by Psychosocial Risk Factors: Validity Criteria for the ÖMPSQ and the HKF-R 10 in Germany.

PubMed

Riewe, E; Neubauer, E; Pfeifer, A C; Schiltenwolf, M

2016-01-01

10% of all individuals in Germany develop persistent symptoms due to nonspecific back pain (NSBP) causing up to 90% of direct and indirect expenses for health care systems. Evidence indicates a strong relationship between chronic nonspecific back pain and psychosocial risk factors. The Örebro Musculoskeletal Pain Screening Questionnaire (ÖMPSQ) and the German Heidelberger Kurzfragebogen Rückenschmerz (HKF-R 10) are deemed valid in prediction of persistent pain, functional loss or amount of sick leave. This study provides and discusses validity criteria for these questionnaires using ROC-curve analyses. Quality measurements included sensitivity and specificity, likelihood-ratio related test-efficiencies and clinical utility in regard to predictive values. 265 patients recruited from primary and secondary care units completed both questionnaires during the same timeframe. From the total, 133 patients returned a 6-month follow-up questionnaire to assess the validity criteria for outcomes of pain, function and sick leave. Based on heterogeneous cut-offs for the ÖMPSQ, sensitivity and specificity were moderate for outcome of pain (72%/75%). Very high sensitivity was observed for function (97%/57%) and high specificity for sick leave (63%/85%). The latter also applied to the HKF-R 10 (pain 50%/84%). Proportions between sensitivity and specificity were unbalanced except for the ÖMPSQ outcome of pain. Likelihood-ratios and positive predictive values ranged from low to moderate. Although the ÖMPSQ may be considered useful in identification of long-term functional loss or pain, over- and underestimation of patients at risk of chronic noncspecific back pain led to limited test-efficiencies and clinical utility for both questionnaires. Further studies are required to quantify the predictive validity of both questionnaires in Germany.

Utility of metabolic profiling of serum in the diagnosis of pregnancy complications.

PubMed

Powell, Katie L; Carrozzi, Anthony; Stephens, Alexandre S; Tasevski, Vitomir; Morris, Jonathan M; Ashton, Anthony W; Dona, Anthony C

2018-06-01

Currently there are no clinical screening tests available to identify pregnancies at risk of developing preeclampsia (PET) and/or intrauterine growth restriction (IUGR), both of which are associated with abnormal placentation. Metabolic profiling is now a stable analytical platform used in many laboratories and has successfully been used to identify biomarkers associated with various pathological states. We used nuclear magnetic resonance spectroscopy (NMR) to metabolically profile serum samples collected from 143 pregnant women at 26-41 weeks gestation with pregnancy outcomes of PET, IUGR, PET IUGR or small for gestational age (SGA) that were age-matched to normal pre/term pregnancies. Spectral analysis found no difference in the measured metabolites from normal term, pre-term and SGA samples, and of 25 identified metabolites, only glutamate was marginally different between groups. Of the identified metabolites, 3-methylhistidine, creatinine, acetyl groups and acetate, were determined to be independent predictors of PET and produced area under the curves (AUC) = 0.938 and 0.936 for the discovery and validation sets. Only 3-hydroxybutyrate was determined to be an independent predictor of IUGR, however the model had low predictive power (AUC = 0.623 and 0.581 for the discovery and validation sets). A sub-panel of metabolites had strong predictive power for identifying PET samples in a validation dataset, however prediction of IUGR was more difficult using the identified metabolites. NMR based metabolomics can identify metabolites strongly associated with disease and has the potential to be useful in developing early clinical screening tests for at risk pregnancies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Predictive validity of pre-admission assessments on medical student performance.

PubMed

Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef; Mohamed, Ayman

2017-11-24

To examine the predictive validity of pre-admission variables on students' performance in a medical school in Saudi Arabia. In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students' progress test performance (p<0.001 and B=19.02). Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years.

Predictive validity of pre-admission assessments on medical student performance

PubMed Central

Dabaliz, Al-Awwab; Kaadan, Samy; Dabbagh, M. Marwan; Barakat, Abdulaziz; Shareef, Mohammad Abrar; Al-Tannir, Mohamad; Obeidat, Akef

2017-01-01

Objectives To examine the predictive validity of pre-admission variables on students’ performance in a medical school in Saudi Arabia.  Methods In this retrospective study, we collected admission and college performance data for 737 students in preclinical and clinical years. Data included high school scores and other standardized test scores, such as those of the National Achievement Test and the General Aptitude Test. Additionally, we included the scores of the Test of English as a Foreign Language (TOEFL) and the International English Language Testing System (IELTS) exams. Those datasets were then compared with college performance indicators, namely the cumulative Grade Point Average (cGPA) and progress test, using multivariate linear regression analysis. Results In preclinical years, both the National Achievement Test (p=0.04, B=0.08) and TOEFL (p=0.017, B=0.01) scores were positive predictors of cGPA, whereas the General Aptitude Test (p=0.048, B=-0.05) negatively predicted cGPA. Moreover, none of the pre-admission variables were predictive of progress test performance in the same group. On the other hand, none of the pre-admission variables were predictive of cGPA in clinical years. Overall, cGPA strongly predict-ed students’ progress test performance (p<0.001 and B=19.02). Conclusions Only the National Achievement Test and TOEFL significantly predicted performance in preclinical years. However, these variables do not predict progress test performance, meaning that they do not predict the functional knowledge reflected in the progress test. We report various strengths and deficiencies in the current medical college admission criteria, and call for employing more sensitive and valid ones that predict student performance and functional knowledge, especially in the clinical years. PMID:29176032

Validating the Hamilton Anatomy of Risk Management-Forensic Version and the Aggressive Incidents Scale.

PubMed

Cook, Alana N; Moulden, Heather M; Mamak, Mini; Lalani, Shams; Messina, Katrina; Chaimowitz, Gary

2018-06-01

The Hamilton Anatomy of Risk Management-Forensic Version (HARM-FV) is a structured professional judgement tool of violence risk developed for use in forensic inpatient psychiatric settings. The HARM-FV is used with the Aggressive Incidents Scale (AIS), which provides a standardized method of recording aggressive incidents. We report the findings of the concurrent validity of the HARM-FV and the AIS with widely used measures of violence risk and aggressive acts, the Historical, Clinical, Risk Management-20, Version 3 (HCR-20 V3 ) and a modified version of the Overt Aggression Scale. We also present findings on the predictive validity of the HARM-FV in the short term (1-month follow-up periods) for varying severities of aggressive acts. The results indicated strong support for the concurrent validity of the HARM-FV and AIS and promising support for the predictive accuracy of the tool for inpatient aggression. This article provides support for the continued clinical use of the HARM-FV within an inpatient forensic setting and highlights areas for further research.

Reliability and concurrent validity of the computer workstation checklist.

PubMed

Baker, Nancy A; Livengood, Heather; Jacobs, Karen

2013-01-01

Self-report checklists are used to assess computer workstation set up, typically by workers not trained in ergonomic assessment or checklist interpretation.Though many checklists exist, few have been evaluated for reliability and validity. This study examined reliability and validity of the Computer Workstation Checklist (CWC) to identify mismatches between workers' self-reported workstation problems. The CWC was completed at baseline and at 1 month to establish reliability. Validity was determined with CWC baseline data compared to an onsite workstation evaluation conducted by an expert in computer workstation assessment. Reliability ranged from fair to near perfect (prevalence-adjusted bias-adjusted kappa, 0.38-0.93); items with the strongest agreement were related to the input device, monitor, computer table, and document holder. The CWC had greater specificity (11 of 16 items) than sensitivity (3 of 16 items). The positive predictive value was greater than the negative predictive value for all questions. The CWC has strong reliability. Sensitivity and specificity suggested workers often indicated no problems with workstation setup when problems existed. The evidence suggests that while the CWC may not be valid when used alone, it may be a suitable adjunct to an ergonomic assessment completed by professionals.

External prognostic validations and comparisons of age- and gender-adjusted exercise capacity predictions.

PubMed

Kim, Esther S H; Ishwaran, Hemant; Blackstone, Eugene; Lauer, Michael S

2007-11-06

The purpose of this study was to externally validate the prognostic value of age- and gender-based nomograms and categorical definitions of impaired exercise capacity (EC). Exercise capacity predicts death, but its use in routine clinical practice is hampered by its close correlation with age and gender. For a median of 5 years, we followed 22,275 patients without known heart disease who underwent symptom-limited stress testing. Models for predicted or impaired EC were identified by literature search. Gender-specific multivariable proportional hazards models were constructed. Four methods were used to assess validity: Akaike Information Criterion (AIC), right-censored c-index in 100 out-of-bootstrap samples, the Nagelkerke Index R2, and calculation of calibration error in 100 bootstrap samples. There were 646 and 430 deaths in 13,098 men and 9,177 women, respectively. Of the 7 models tested in men, a model based on a Veterans Affairs cohort (predicted metabolic equivalents [METs] = 18 - [0.15 x age]) had the highest AIC and R2. In women, a model based on the St. James Take Heart Project (predicted METs = 14.7 - [0.13 x age]) performed best. Categorical definitions of fitness performed less well. Even after accounting for age and gender, there was still an important interaction with age, whereby predicted EC was a weaker predictor in older subjects (p for interaction <0.001 in men and 0.003 in women). Several methods describe EC accounting for age and gender-related differences, but their ability to predict mortality differ. Simple cutoff values fail to fully describe EC's strong predictive value.

Automatic avoidance tendencies for alcohol cues predict drinking after detoxification treatment in alcohol dependence.

PubMed

Field, Matt; Di Lemma, Lisa; Christiansen, Paul; Dickson, Joanne

2017-03-01

Alcohol dependence is characterized by conflict between approach and avoidance motivational orientations for alcohol that operate in automatic and controlled processes. This article describes the first study to investigate the predictive validity of these motivational orientations for relapse to drinking after discharge from alcohol detoxification treatment in alcohol-dependent patients. One hundred twenty alcohol-dependent patients who were nearing the end of inpatient detoxification treatment completed measures of self-reported (Approach and Avoidance of Alcohol Questionnaire; AAAQ) and automatic (modified Stimulus-Response Compatibility task) approach and avoidance motivational orientations for alcohol. Their drinking behavior was assessed via telephone follow-ups at 2, 4, and 6 months after discharge from treatment. Results indicated that, after controlling for the severity of alcohol dependence, strong automatic avoidance tendencies for alcohol cues were predictive of higher percentage of heavy drinking days (PHDD) at 4-month (β = 0.22, 95% CI [0.07, 0.43]) and 6-month (β = 0.22, 95% CI [0.01, 0.42]) follow-ups. We failed to replicate previous demonstrations of the predictive validity of approach subscales of the AAAQ for relapse to drinking, and there were no significant predictors of PHDD at 2-month follow-up. In conclusion, strong automatic avoidance tendencies predicted relapse to drinking after inpatient detoxification treatment, but automatic approach tendencies and self-reported approach and avoidance tendencies were not predictive in this study. Our results extend previous findings and help to resolve ambiguities with earlier studies that investigated the roles of automatic and controlled cognitive processes in recovery from alcohol dependence. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Construct measurement quality improves predictive accuracy in violence risk assessment: an illustration using the personality assessment inventory.

PubMed

Hendry, Melissa C; Douglas, Kevin S; Winter, Elizabeth A; Edens, John F

2013-01-01

Much of the risk assessment literature has focused on the predictive validity of risk assessment tools. However, these tools often comprise a list of risk factors that are themselves complex constructs, and focusing on the quality of measurement of individual risk factors may improve the predictive validity of the tools. The present study illustrates this concern using the Antisocial Features and Aggression scales of the Personality Assessment Inventory (Morey, 1991). In a sample of 1,545 prison inmates and offenders undergoing treatment for substance abuse (85% male), we evaluated (a) the factorial validity of the ANT and AGG scales, (b) the utility of original ANT and AGG scales and newly derived ANT and AGG scales for predicting antisocial outcomes (recidivism and institutional infractions), and (c) whether items with a stronger relationship to the underlying constructs (higher factor loadings) were in turn more strongly related to antisocial outcomes. Confirmatory factor analyses (CFAs) indicated that ANT and AGG items were not structured optimally in these data in terms of correspondence to the subscale structure identified in the PAI manual. Exploratory factor analyses were conducted on a random split-half of the sample to derive optimized alternative factor structures, and cross-validated in the second split-half using CFA. Four-factor models emerged for both the ANT and AGG scales, and, as predicted, the size of item factor loadings was associated with the strength with which items were associated with institutional infractions and community recidivism. This suggests that the quality by which a construct is measured is associated with its predictive strength. Implications for risk assessment are discussed. Copyright © 2013 John Wiley & Sons, Ltd.

Novel prediction model of renal function after nephrectomy from automated renal volumetry with preoperative multidetector computed tomography (MDCT).

PubMed

Isotani, Shuji; Shimoyama, Hirofumi; Yokota, Isao; Noma, Yasuhiro; Kitamura, Kousuke; China, Toshiyuki; Saito, Keisuke; Hisasue, Shin-ichi; Ide, Hisamitsu; Muto, Satoru; Yamaguchi, Raizo; Ukimura, Osamu; Gill, Inderbir S; Horie, Shigeo

2015-10-01

The predictive model of postoperative renal function may impact on planning nephrectomy. To develop the novel predictive model using combination of clinical indices with computer volumetry to measure the preserved renal cortex volume (RCV) using multidetector computed tomography (MDCT), and to prospectively validate performance of the model. Total 60 patients undergoing radical nephrectomy from 2011 to 2013 participated, including a development cohort of 39 patients and an external validation cohort of 21 patients. RCV was calculated by voxel count using software (Vincent, FUJIFILM). Renal function before and after radical nephrectomy was assessed via the estimated glomerular filtration rate (eGFR). Factors affecting postoperative eGFR were examined by regression analysis to develop the novel model for predicting postoperative eGFR with a backward elimination method. The predictive model was externally validated and the performance of the model was compared with that of the previously reported models. The postoperative eGFR value was associated with age, preoperative eGFR, preserved renal parenchymal volume (RPV), preserved RCV, % of RPV alteration, and % of RCV alteration (p < 0.01). The significant correlated variables for %eGFR alteration were %RCV preservation (r = 0.58, p < 0.01) and %RPV preservation (r = 0.54, p < 0.01). We developed our regression model as follows: postoperative eGFR = 57.87 - 0.55(age) - 15.01(body surface area) + 0.30(preoperative eGFR) + 52.92(%RCV preservation). Strong correlation was seen between postoperative eGFR and the calculated estimation model (r = 0.83; p < 0.001). The external validation cohort (n = 21) showed our model outperformed previously reported models. Combining MDCT renal volumetry and clinical indices might yield an important tool for predicting postoperative renal function.

A Comparison of the Fagerström Test for Cigarette Dependence and Cigarette Dependence Scale in a Treatment-Seeking Sample of Pregnant Smokers

PubMed Central

Singleton, Edward G.; Heishman, Stephen J.

2016-01-01

Introduction: Valid and reliable brief measures of cigarette dependence are essential for research purposes and effective clinical care. Two widely-used brief measures of cigarette dependence are the six-item Fagerström Test for Cigarette Dependence (FTCD) and five-item Cigarette Dependence Scale (CDS-5). Their respective metric characteristics among pregnant smokers have not yet been studied. Methods: This was a secondary analysis of data of pregnant smokers (N = 476) enrolled in a smoking cessation study. We assessed internal consistency, reliability, and examined correlations between the instruments and smoking-related behaviors for construct validity. We evaluated predictive validity by testing how well the measures predict abstinence 2 weeks after quit date. Results: Cronbach’s alpha coefficient for the CDS-5 was 0.62 and for the FTCD 0.55. Measures were strongly correlated with each other, although FTCD, but not CDS-5, was associated with saliva cotinine concentration. The FTCD, CDS-5, craving to smoke, and withdrawal symptoms failed to predict smoking status 2 weeks following the quit date. Conclusions: Suboptimal reliability estimates and failure to predict short-term smoking call into question the value of including either of the brief measures in studies that aim to explain the obstacles to smoking cessation during pregnancy. PMID:25995159

Finite Element Model of the Knee for Investigation of Injury Mechanisms: Development and Validation

PubMed Central

Kiapour, Ali; Kiapour, Ata M.; Kaul, Vikas; Quatman, Carmen E.; Wordeman, Samuel C.; Hewett, Timothy E.; Demetropoulos, Constantine K.; Goel, Vijay K.

2014-01-01

Multiple computational models have been developed to study knee biomechanics. However, the majority of these models are mainly validated against a limited range of loading conditions and/or do not include sufficient details of the critical anatomical structures within the joint. Due to the multifactorial dynamic nature of knee injuries, anatomic finite element (FE) models validated against multiple factors under a broad range of loading conditions are necessary. This study presents a validated FE model of the lower extremity with an anatomically accurate representation of the knee joint. The model was validated against tibiofemoral kinematics, ligaments strain/force, and articular cartilage pressure data measured directly from static, quasi-static, and dynamic cadaveric experiments. Strong correlations were observed between model predictions and experimental data (r > 0.8 and p < 0.0005 for all comparisons). FE predictions showed low deviations (root-mean-square (RMS) error) from average experimental data under all modes of static and quasi-static loading, falling within 2.5 deg of tibiofemoral rotation, 1% of anterior cruciate ligament (ACL) and medial collateral ligament (MCL) strains, 17 N of ACL load, and 1 mm of tibiofemoral center of pressure. Similarly, the FE model was able to accurately predict tibiofemoral kinematics and ACL and MCL strains during simulated bipedal landings (dynamic loading). In addition to minimal deviation from direct cadaveric measurements, all model predictions fell within 95% confidence intervals of the average experimental data. Agreement between model predictions and experimental data demonstrates the ability of the developed model to predict the kinematics of the human knee joint as well as the complex, nonuniform stress and strain fields that occur in biological soft tissue. Such a model will facilitate the in-depth understanding of a multitude of potential knee injury mechanisms with special emphasis on ACL injury. PMID:24763546

Assessing risk for violence among male and female civil psychiatric patients: the HCR-20, PCL:SV, and VSC.

PubMed

Nicholls, Tonia L; Ogloff, James R P; Douglas, Kevin S

2004-01-01

This study evaluated the predictive validity of violence risk assessments conducted using the HCR-20, the Psychopathy Checklist: Screening Version (PCL:SV), and by the Violence Screening Checklist (VSC) in a sample of 268 involuntarily hospitalized male and female psychiatric patients. Information pertaining to violence and crime was coded from medical charts and correctional records. The HCR-20/PCL:SV evidenced modest non-significant associations in postdictive assessments of inpatient violence among men. Moderate to strong significant associations were found between the HCR-20/PCL:SV and inpatient violence among women. Pseudo-prospective assessments using the HCR-20 and PCL:SV resulted in moderate to large relationships with violence and crime in men and women following community discharge. It is concluded that the VSC is a promising tool for assessing acute inpatient violence risk with men. Findings offer preliminary validation of the predictive validity of the HCR-20 and PCL:SV with female civil psychiatric patients. Copyright 2004 John Wiley & Sons, Ltd.

On vital aid: the why, what and how of validation

PubMed Central

Kleywegt, Gerard J.

2009-01-01

Limitations to the data and subjectivity in the structure-determination process may cause errors in macromolecular crystal structures. Appropriate validation techniques may be used to reveal problems in structures, ideally before they are analysed, published or deposited. Additionally, such tech­niques may be used a posteriori to assess the (relative) merits of a model by potential users. Weak validation methods and statistics assess how well a model reproduces the information that was used in its construction (i.e. experimental data and prior knowledge). Strong methods and statistics, on the other hand, test how well a model predicts data or information that were not used in the structure-determination process. These may be data that were excluded from the process on purpose, general knowledge about macromolecular structure, information about the biological role and biochemical activity of the molecule under study or its mutants or complexes and predictions that are based on the model and that can be tested experimentally. PMID:19171968

Cognitive Rationalizations for Tanning-Bed Use: A Preliminary Exploration

PubMed Central

Banerjee, Smita C.; Hay, Jennifer L.; Greene, Kathryn

2016-01-01

Objectives To examine construct and predictive utility of an adapted cognitive rationalization scale for tanning-bed use. Methods Current/former tanning-bed-using undergraduate students (N = 216; 87.6% females; 78.4% white) at a large northeastern university participated in a survey. A cognitive rationalization for tanning-bed use scale was adapted. Standardized self-report measures of past tanning-bed use, advantages of tanning, perceived vulnerability to photoaging, tanning-bed use dependence, and tanning- bed use intention were also administered. Results The cognitive rationalization scale exhibited strong construct and predictive validity. Current tanners and tanning-bed-use-dependent participants endorsed rationalizations more strongly than did former tanners and not-tanning-bed-use-dependent participants respectively. Conclusions Findings indicate that cognitive rationalizations help explain discrepancy between inconsistent cognitions. PMID:23985280

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

Predictive Validity of the Columbia-Suicide Severity Rating Scale for Short-Term Suicidal Behavior: A Danish Study of Adolescents at a High Risk of Suicide.

PubMed

Conway, Paul Maurice; Erlangsen, Annette; Teasdale, Thomas William; Jakobsen, Ida Skytte; Larsen, Kim Juul

2017-07-03

Using the Columbia-Suicide Severity Rating Scale (C-SSRS), we examined the predictive and incremental predictive validity of past-month suicidal behavior and ideation for short-term suicidal behavior among adolescents at high risk of suicide. The study was conducted in 2014 on a sample of 85 adolescents (90.6% females) who participated at follow-up (85.9%) out of the 99 (49.7%) baseline respondents. All adolescents were recruited from a specialized suicide-prevention clinic in Denmark. Through multivariate logistic regression analyses, we examined whether baseline suicidal behavior predicted subsequent suicidal behavior (actual attempts and suicidal behavior of any type, including preparatory acts, aborted, interrupted and actual attempts; mean follow-up of 80.8 days, SD = 52.4). Furthermore, we examined whether suicidal ideation severity and intensity incrementally predicted suicidal behavior at follow-up over and above suicidal behavior at baseline. Actual suicide attempts at baseline strongly predicted suicide attempts at follow-up. Baseline suicidal ideation severity and intensity did not significantly predict future actual attempts over and above baseline attempts. The suicidal ideation intensity items deterrents and duration were significant predictors of subsequent actual attempts after adjustment for baseline suicide attempts and suicidal behavior of any type, respectively. Suicidal ideation severity and intensity, and the intensity items frequency, duration and deterrents, all significantly predicted any type of suicidal behavior at follow-up, also after adjusting for baseline suicidal behavior. The present study points to an incremental predictive validity of the C-SSRS suicidal ideation scales for short-term suicidal behavior of any type among high-risk adolescents.

Development and validation of a set of six adaptable prognosis prediction (SAP) models based on time-series real-world big data analysis for patients with cancer receiving chemotherapy: A multicenter case crossover study

PubMed Central

Kanai, Masashi; Okamoto, Kazuya; Yamamoto, Yosuke; Yoshioka, Akira; Hiramoto, Shuji; Nozaki, Akira; Nishikawa, Yoshitaka; Yamaguchi, Daisuke; Tomono, Teruko; Nakatsui, Masahiko; Baba, Mika; Morita, Tatsuya; Matsumoto, Shigemi; Kuroda, Tomohiro; Okuno, Yasushi; Muto, Manabu

2017-01-01

Background We aimed to develop an adaptable prognosis prediction model that could be applied at any time point during the treatment course for patients with cancer receiving chemotherapy, by applying time-series real-world big data. Methods Between April 2004 and September 2014, 4,997 patients with cancer who had received systemic chemotherapy were registered in a prospective cohort database at the Kyoto University Hospital. Of these, 2,693 patients with a death record were eligible for inclusion and divided into training (n = 1,341) and test (n = 1,352) cohorts. In total, 3,471,521 laboratory data at 115,738 time points, representing 40 laboratory items [e.g., white blood cell counts and albumin (Alb) levels] that were monitored for 1 year before the death event were applied for constructing prognosis prediction models. All possible prediction models comprising three different items from 40 laboratory items (40C3 = 9,880) were generated in the training cohort, and the model selection was performed in the test cohort. The fitness of the selected models was externally validated in the validation cohort from three independent settings. Results A prognosis prediction model utilizing Alb, lactate dehydrogenase, and neutrophils was selected based on a strong ability to predict death events within 1–6 months and a set of six prediction models corresponding to 1,2, 3, 4, 5, and 6 months was developed. The area under the curve (AUC) ranged from 0.852 for the 1 month model to 0.713 for the 6 month model. External validation supported the performance of these models. Conclusion By applying time-series real-world big data, we successfully developed a set of six adaptable prognosis prediction models for patients with cancer receiving chemotherapy. PMID:28837592

Manual unloading of the lumbar spine: can it identify immediate responders to mechanical traction in a low back pain population? A study of reliability and criterion referenced predictive validity

PubMed Central

Swanson, Brian T.; Riley, Sean P.; Cote, Mark P.; Leger, Robin R.; Moss, Isaac L.; Carlos,, John

2016-01-01

Background To date, no research has examined the reliability or predictive validity of manual unloading tests of the lumbar spine to identify potential responders to lumbar mechanical traction. Purpose To determine: (1) the intra and inter-rater reliability of a manual unloading test of the lumbar spine and (2) the criterion referenced predictive validity for the manual unloading test. Methods Ten volunteers with low back pain (LBP) underwent a manual unloading test to establish reliability. In a separate procedure, 30 consecutive patients with LBP (age 50·86±11·51) were assessed for pain in their most provocative standing position (visual analog scale (VAS) 49·53±25·52 mm). Patients were assessed with a manual unloading test in their most provocative position followed by a single application of intermittent mechanical traction. Post traction, pain in the provocative position was reassessed and utilized as the outcome criterion. Results The test of unloading demonstrated substantial intra and inter-rater reliability K = 1·00, P = 0·002, K = 0·737, P = 0·001, respectively. There were statistically significant within group differences for pain response following traction for patients with a positive manual unloading test (P<0·001), while patients with a negative manual unloading test did not demonstrate a statistically significant change (P>0·05). There were significant between group differences for proportion of responders to traction based on manual unloading response (P = 0·031), and manual unloading response demonstrated a moderate to strong relationship with traction response Phi = 0·443, P = 0·015. Discussion and conclusion The manual unloading test appears to be a reliable test and has a moderate to strong correlation with pain relief that exceeds minimal clinically important difference (MCID) following traction supporting the validity of this test. PMID:27559274

Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study

PubMed Central

Müller, Daniel J.; Ng, Chee H.; Byron, Keith; Berk, Michael; Singh, Ajeet B.

2017-01-01

Background Pharmacogenetic-based dosing support tools have been developed to personalize antidepressant-prescribing practice. However, the clinical validity of these tools has not been adequately tested, particularly for specific antidepressants. Objective To examine the concordance between the actual dose and a polygene pharmacogenetic predicted dose of desvenlafaxine needed to achieve symptom remission. Materials and methods A 10-week, open-label, prospective trial of desvenlafaxine among Caucasian adults with major depressive disorder (n=119) was conducted. Dose was clinically adjusted and at the completion of the trial, the clinical dose needed to achieve remission was compared with the predicted dose needed to achieve remission. Results Among remitters (n=95), there was a strong concordance (Kendall’s τ-b=0.84, P=0.0001; Cohen’s κ=0.82, P=0.0001) between the actual and the predicted dose need to achieve symptom remission, showing high sensitivity (≥85%), specificity (≥86%), and accuracy (≥89%) of the tool. Conclusion Findings provide initial evidence for the clinical validity of a polygene pharmacogenetic-based tool for desvenlafaxine dosing. PMID:27779571

Concordance between actual and pharmacogenetic predicted desvenlafaxine dose needed to achieve remission in major depressive disorder: a 10-week open-label study.

PubMed

Bousman, Chad A; Müller, Daniel J; Ng, Chee H; Byron, Keith; Berk, Michael; Singh, Ajeet B

2017-01-01

Pharmacogenetic-based dosing support tools have been developed to personalize antidepressant-prescribing practice. However, the clinical validity of these tools has not been adequately tested, particularly for specific antidepressants. To examine the concordance between the actual dose and a polygene pharmacogenetic predicted dose of desvenlafaxine needed to achieve symptom remission. A 10-week, open-label, prospective trial of desvenlafaxine among Caucasian adults with major depressive disorder (n=119) was conducted. Dose was clinically adjusted and at the completion of the trial, the clinical dose needed to achieve remission was compared with the predicted dose needed to achieve remission. Among remitters (n=95), there was a strong concordance (Kendall's τ-b=0.84, P=0.0001; Cohen's κ=0.82, P=0.0001) between the actual and the predicted dose need to achieve symptom remission, showing high sensitivity (≥85%), specificity (≥86%), and accuracy (≥89%) of the tool. Findings provide initial evidence for the clinical validity of a polygene pharmacogenetic-based tool for desvenlafaxine dosing.

Development of an Itemwise Efficiency Scoring Method: Concurrent, Convergent, Discriminant, and Neuroimaging-Based Predictive Validity Assessed in a Large Community Sample

PubMed Central

Moore, Tyler M.; Reise, Steven P.; Roalf, David R.; Satterthwaite, Theodore D.; Davatzikos, Christos; Bilker, Warren B.; Port, Allison M.; Jackson, Chad T.; Ruparel, Kosha; Savitt, Adam P.; Baron, Robert B.; Gur, Raquel E.; Gur, Ruben C.

2016-01-01

Traditional “paper-and-pencil” testing is imprecise in measuring speed and hence limited in assessing performance efficiency, but computerized testing permits precision in measuring itemwise response time. We present a method of scoring performance efficiency (combining information from accuracy and speed) at the item level. Using a community sample of 9,498 youths age 8-21, we calculated item-level efficiency scores on four neurocognitive tests, and compared the concurrent, convergent, discriminant, and predictive validity of these scores to simple averaging of standardized speed and accuracy-summed scores. Concurrent validity was measured by the scores' abilities to distinguish men from women and their correlations with age; convergent and discriminant validity were measured by correlations with other scores inside and outside of their neurocognitive domains; predictive validity was measured by correlations with brain volume in regions associated with the specific neurocognitive abilities. Results provide support for the ability of itemwise efficiency scoring to detect signals as strong as those detected by standard efficiency scoring methods. We find no evidence of superior validity of the itemwise scores over traditional scores, but point out several advantages of the former. The itemwise efficiency scoring method shows promise as an alternative to standard efficiency scoring methods, with overall moderate support from tests of four different types of validity. This method allows the use of existing item analysis methods and provides the convenient ability to adjust the overall emphasis of accuracy versus speed in the efficiency score, thus adjusting the scoring to the real-world demands the test is aiming to fulfill. PMID:26866796

Mass Spectrometry of Human Leukocyte Antigen Class I Peptidomes Reveals Strong Effects of Protein Abundance and Turnover on Antigen Presentation*

PubMed Central

Bassani-Sternberg, Michal; Pletscher-Frankild, Sune; Jensen, Lars Juhl; Mann, Matthias

2015-01-01

HLA class I molecules reflect the health state of cells to cytotoxic T cells by presenting a repertoire of endogenously derived peptides. However, the extent to which the proteome shapes the peptidome is still largely unknown. Here we present a high-throughput mass-spectrometry-based workflow that allows stringent and accurate identification of thousands of such peptides and direct determination of binding motifs. Applying the workflow to seven cancer cell lines and primary cells, yielded more than 22,000 unique HLA peptides across different allelic binding specificities. By computing a score representing the HLA-I sampling density, we show a strong link between protein abundance and HLA-presentation (p < 0.0001). When analyzing overpresented proteins – those with at least fivefold higher density score than expected for their abundance – we noticed that they are degraded almost 3 h faster than similar but nonpresented proteins (top 20% abundance class; median half-life 20.8h versus 23.6h, p < 0.0001). This validates protein degradation as an important factor for HLA presentation. Ribosomal, mitochondrial respiratory chain, and nucleosomal proteins are particularly well presented. Taking a set of proteins associated with cancer, we compared the predicted immunogenicity of previously validated T-cell epitopes with other peptides from these proteins in our data set. The validated epitopes indeed tend to have higher immunogenic scores than the other detected HLA peptides. Remarkably, we identified five mutated peptides from a human colon cancer cell line, which have very recently been predicted to be HLA-I binders. Altogether, we demonstrate the usefulness of combining MS-analysis with immunogenesis prediction for identifying, ranking, and selecting peptides for therapeutic use. PMID:25576301

Improving risk assessment in schizophrenia: epidemiological investigation of criminal history factors

PubMed Central

Witt, Katrina; Lichtenstein, Paul; Fazel, Seena

2015-01-01

Background Violence risk assessment in schizophrenia relies heavily on criminal history factors. Aims To investigate which criminal history factors are most strongly associated with violent crime in schizophrenia. Method A total of 13 806 individuals (8891 men and 4915 women) with two or more hospital admissions for schizophrenia were followed up for violent convictions. Multivariate hazard ratios for 15 criminal history factors included in different risk assessment tools were calculated. The incremental predictive validity of these factors was estimated using tests of discrimination, calibration and reclassification. Results Over a mean follow-up of 12.0 years, 17.3% of men (n = 1535) and 5.7% of women (n = 281) were convicted of a violent offence. Criminal history factors most strongly associated with subsequent violence for both men and women were a previous conviction for a violent offence; for assault, illegal threats and/or intimidation; and imprisonment. However, only a previous conviction for a violent offence was associated with incremental predictive validity in both genders following adjustment for young age and comorbid substance use disorder. Conclusions Clinical and actuarial approaches to assess violence risk can be improved if included risk factors are tested using multiple measures of performance. PMID:25657352

Improving risk assessment in schizophrenia: epidemiological investigation of criminal history factors.

PubMed

Witt, Katrina; Lichtenstein, Paul; Fazel, Seena

2015-05-01

Violence risk assessment in schizophrenia relies heavily on criminal history factors. To investigate which criminal history factors are most strongly associated with violent crime in schizophrenia. A total of 13 806 individuals (8891 men and 4915 women) with two or more hospital admissions for schizophrenia were followed up for violent convictions. Multivariate hazard ratios for 15 criminal history factors included in different risk assessment tools were calculated. The incremental predictive validity of these factors was estimated using tests of discrimination, calibration and reclassification. Over a mean follow-up of 12.0 years, 17.3% of men (n = 1535) and 5.7% of women (n = 281) were convicted of a violent offence. Criminal history factors most strongly associated with subsequent violence for both men and women were a previous conviction for a violent offence; for assault, illegal threats and/or intimidation; and imprisonment. However, only a previous conviction for a violent offence was associated with incremental predictive validity in both genders following adjustment for young age and comorbid substance use disorder. Clinical and actuarial approaches to assess violence risk can be improved if included risk factors are tested using multiple measures of performance. © The Royal College of Psychiatrists 2015.

An experimental evaluation of two effective medium theories for ultrasonic wave propagation in concrete.

PubMed

Chaix, Jean-François; Rossat, Mathieu; Garnier, Vincent; Corneloup, Gilles

2012-06-01

This study compares ultrasonic wave propagation modeling and experimental data in concrete. As a consequence of its composition and manufacturing process, this material has a high elastic scattering (sand and aggregates) and air (microcracks and porosities) content. The behavior of the "Waterman-Truell" and "Generalized Self Consistent Method" dynamic homogenization models are analyzed in the context of an application for strong heterogeneous solid materials, in which the scatterers are of various concentrations and types. The experimental validations of results predicted by the models are carried out by making use of the phase velocity and the attenuation of longitudinal waves, as measured by an immersed transmission setup. The test specimen material has a cement-like matrix containing spherical inclusions of air or glass, with radius close to the ultrasonic wavelength. The models are adapted to the case of materials presenting several types of scattering particle, and allow the propagation of longitudinal waves to be described at the scale of materials such as concrete. The validity limits for frequency and for particle volume ratio can be approached through a comparison with experimental data. The potential of these homogenization models for the prediction of phase velocity and attenuation in strongly heterogeneous solids is demonstrated.

Examination of the Mild Brain Injury Atypical Symptom Scale and the Validity-10 Scale to detect symptom exaggeration in US military service members.

PubMed

Lange, Rael T; Brickell, Tracey A; French, Louis M

2015-01-01

The purpose of this study was to examine the clinical utility of two validity scales designed for use with the Neurobehavioral Symptom Inventory (NSI) and the PTSD Checklist-Civilian Version (PCL-C); the Mild Brain Injury Atypical Symptoms Scale (mBIAS) and Validity-10 scale. Participants were 63 U.S. military service members (age: M = 31.9 years, SD = 12.5; 90.5% male) who sustained a mild traumatic brain injury (MTBI) and were prospectively enrolled from Walter Reed National Military Medical Center. Participants were divided into two groups based on the validity scales of the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF): (a) symptom validity test (SVT)-Fail (n = 24) and (b) SVT-Pass (n = 39). Participants were evaluated on average 19.4 months postinjury (SD = 27.6). Participants in the SVT-Fail group had significantly higher scores (p < .05) on the mBIAS (d = 0.85), Validity-10 (d = 1.89), NSI (d = 2.23), and PCL-C (d = 2.47), and the vast majority of the MMPI-2-RF scales (d = 0.69 to d = 2.47). Sensitivity, specificity, and predictive power values were calculated across the range of mBIAS and Validity-10 scores to determine the optimal cutoff to detect symptom exaggeration. For the mBIAS, a cutoff score of ≥8 was considered optimal, which resulted in low sensitivity (.17), high specificity (1.0), high positive predictive power (1.0), and moderate negative predictive power (.69). For the Validity-10 scale, a cutoff score of ≥13 was considered optimal, which resulted in moderate-high sensitivity (.63), high specificity (.97), and high positive (.93) and negative predictive power (.83). These findings provide strong support for the use of the Validity-10 as a tool to screen for symptom exaggeration when administering the NSI and PCL-C. The mBIAS, however, was not a reliable tool for this purpose and failed to identify the vast majority of people who exaggerated symptoms.

Validation of the DECAF score to predict hospital mortality in acute exacerbations of COPD

PubMed Central

Echevarria, C; Steer, J; Heslop-Marshall, K; Stenton, SC; Hickey, PM; Hughes, R; Wijesinghe, M; Harrison, RN; Steen, N; Simpson, AJ; Gibson, GJ; Bourke, SC

2016-01-01

Background Hospitalisation due to acute exacerbations of COPD (AECOPD) is common, and subsequent mortality high. The DECAF score was derived for accurate prediction of mortality and risk stratification to inform patient care. We aimed to validate the DECAF score, internally and externally, and to compare its performance to other predictive tools. Methods The study took place in the two hospitals within the derivation study (internal validation) and in four additional hospitals (external validation) between January 2012 and May 2014. Consecutive admissions were identified by screening admissions and searching coding records. Admission clinical data, including DECAF indices, and mortality were recorded. The prognostic value of DECAF and other scores were assessed by the area under the receiver operator characteristic (AUROC) curve. Results In the internal and external validation cohorts, 880 and 845 patients were recruited. Mean age was 73.1 (SD 10.3) years, 54.3% were female, and mean (SD) FEV1 45.5 (18.3) per cent predicted. Overall mortality was 7.7%. The DECAF AUROC curve for inhospital mortality was 0.83 (95% CI 0.78 to 0.87) in the internal cohort and 0.82 (95% CI 0.77 to 0.87) in the external cohort, and was superior to other prognostic scores for inhospital or 30-day mortality. Conclusions DECAF is a robust predictor of mortality, using indices routinely available on admission. Its generalisability is supported by consistent strong performance; it can identify low-risk patients (DECAF 0–1) potentially suitable for Hospital at Home or early supported discharge services, and high-risk patients (DECAF 3–6) for escalation planning or appropriate early palliation. Trial registration number UKCRN ID 14214. PMID:26769015

Assessing attitude toward same-sex marriage: scale development and validation.

PubMed

Lannutti, Pamela J; Lachlan, Kenneth A

2007-01-01

This paper reports the results of three studies conducted to develop, refine, and validate a scale which assessed heterosexual adults' attitudes toward same-sex marriage, the Attitude Toward Same-Sex Marriage Scale (ASSMS). The need for such a scale is evidenced in the increasing importance of same-sex marriage in the political arena of the United States and other nations, as well as the growing body of empirical research examining same-sex marriage and related issues (e.g., Lannutti, 2005; Solomon, Rothblum, & Balsam, 2004). The results demonstrate strong reliability, convergent validity, and predictive validity for the ASSMS and suggest that the ASSMS may be adapted to measure attitudes toward civil unions and other forms of relational recognition for same-sex couples. Gender comparisons using the validated scale showed that in college and non-college samples, women had a significantly more positive attitude toward same-sex marriage than did men.

Theoretical study on second-harmonic generation of focused vortex beams

NASA Astrophysics Data System (ADS)

Tang, Daolong; Wang, Jing; Ma, Jingui; Zhou, Bingjie; Yuan, Peng; Xie, Guoqiang; Zhu, Heyuan; Qian, Liejia

2018-03-01

Second-harmonic generation (SHG) provides a promising route for generating vortex beams of both short wavelength and large topological charge. Here we theoretically investigate the efficiency optimization and beam characteristics of focused vortex-beam SHG. Owing to the increasing beam divergence, vortex beams have distinct features in SHG optimization compared with a Gaussian beam. We show that, under the noncritical phase-matching condition, the Boyd and Kleinman prediction of the optimal focusing parameter for Gaussian-beam SHG remains valid for vortex-beam SHG. However, under the critical phase-matching condition, which is sensitive to the beam divergence, the Boyd and Kleinman prediction is no longer valid. In contrast, the optimal focusing parameter for maximizing the SHG efficiency strongly depends on the vortex order. We also investigate the effects of focusing and phase-matching conditions on the second-harmonic beam characteristics.

Application of all relevant feature selection for failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, W.; Wrzesień, M.; Niemiec, R.; Rudnicki, W. R.

2015-07-01

The climate models are extremely complex pieces of software. They reflect best knowledge on physical components of the climate, nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a crash of simulation. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to crash of simulation, and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the dataset used in this research using different methodology. We confirm the main conclusion of the original study concerning suitability of machine learning for prediction of crashes. We show, that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three other are relevant but redundant, and two are not relevant at all. We also show that the variance due to split of data between training and validation sets has large influence both on accuracy of predictions and relative importance of variables, hence only cross-validated approach can deliver robust prediction of performance and relevance of variables.

An evaluation of the Psychache Scale on an offender population.

PubMed

Mills, Jeremy F; Green, Kate; Reddon, John R

2005-10-01

This study examined the generalizability of a self-report measure of psychache to an offender population. The factor structure, construct validity, and criterion validity of the Psychache Scale was assessed on 136 male prison inmates. The results showed the Psychache Scale has a single underlying factor structure and to be strongly associated with measures of depression and hopelessness and moderately associated with psychiatric symptoms and the criterion variable of a history of prior suicide attempts. The variables of depression, hopelessness, and psychiatric symptoms all contributed unique variance to psychache. Discussion centers on psychache's theoretical application to the prediction of suicide.

Predicting active school travel: the role of planned behavior and habit strength.

PubMed

Murtagh, Shemane; Rowe, David A; Elliott, Mark A; McMinn, David; Nelson, Norah M

2012-05-30

Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model's predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children's active school travel. Participants (N = 126 children aged 8-9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. The TPB significantly predicts children's active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children's intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these antecedents of children's active school travel.

Development of machine learning models for diagnosis of glaucoma.

PubMed

Kim, Seong Jae; Cho, Kyong Jin; Oh, Sejong

2017-01-01

The study aimed to develop machine learning models that have strong prediction power and interpretability for diagnosis of glaucoma based on retinal nerve fiber layer (RNFL) thickness and visual field (VF). We collected various candidate features from the examination of retinal nerve fiber layer (RNFL) thickness and visual field (VF). We also developed synthesized features from original features. We then selected the best features proper for classification (diagnosis) through feature evaluation. We used 100 cases of data as a test dataset and 399 cases of data as a training and validation dataset. To develop the glaucoma prediction model, we considered four machine learning algorithms: C5.0, random forest (RF), support vector machine (SVM), and k-nearest neighbor (KNN). We repeatedly composed a learning model using the training dataset and evaluated it by using the validation dataset. Finally, we got the best learning model that produces the highest validation accuracy. We analyzed quality of the models using several measures. The random forest model shows best performance and C5.0, SVM, and KNN models show similar accuracy. In the random forest model, the classification accuracy is 0.98, sensitivity is 0.983, specificity is 0.975, and AUC is 0.979. The developed prediction models show high accuracy, sensitivity, specificity, and AUC in classifying among glaucoma and healthy eyes. It will be used for predicting glaucoma against unknown examination records. Clinicians may reference the prediction results and be able to make better decisions. We may combine multiple learning models to increase prediction accuracy. The C5.0 model includes decision rules for prediction. It can be used to explain the reasons for specific predictions.

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

The Cord Blood Apgar: a novel scoring system to optimize selection of banked cord blood grafts for transplantation

PubMed Central

Page, Kristin M.; Zhang, Lijun; Mendizabal, Adam; Wease, Stephen; Carter, Shelly; Shoulars, Kevin; Gentry, Tracy; Balber, Andrew E.; Kurtzberg, Joanne

2012-01-01

BACKGROUND Engraftment failure and delays, likely due to diminished cord blood unit (CBU) potency, remain major barriers to the overall success of unrelated umbilical cord blood transplantation (UCBT). To address this problem, we developed and retrospectively validated a novel scoring system, the Cord Blood Apgar (CBA), which is predictive of engraftment after UCBT. STUDY DESIGN AND METHODS In a single-center retrospective study, utilizing a database of 435 consecutive single cord myeloablative UCBTs performed between January 1, 2000, to December 31, 2008, precryopreservation and postthaw graft variables (total nucleated cell, CD34+, colony-forming units, mononuclear cell content, and volume) were initially correlated with neutrophil engraftment. Subsequently, based on the magnitude of hazard ratios (HRs) in univariate analysis, a weighted scoring system to predict CBU potency was developed using a randomly selected training data set and internally validated on the remaining data set. RESULTS The CBA assigns transplanted CBUs three scores: a precryopreservation score (PCS), a postthaw score (PTS), and a composite score (CS), which incorporates the PCS and PTS values. CBA-PCS scores, which could be used for initial unit selection, were predictive of neutrophil (CBA-PCS ≥ 7.75 vs. <7.75, HR 3.5; p < 0.0001) engraftment. Likewise, CBA-PTS and CS scores were strongly predictive of Day 42 neutrophil engraftment (CBA-PTS ≥ 9.5 vs. <9.5, HR 3.16, p < 0.0001; CBA-CS ≥ 17.75 vs. <17.75, HR 4.01, p < 0.0001). CONCLUSION The CBA is strongly predictive of engraftment after UCBT and shows promise for optimizing screening of CBU donors for transplantation. In the future, a segment could be assayed for the PTS score providing data to apply the CS for final CBU selection. PMID:21810098

Predicting skeletal muscle mass from dual-energy X-ray absorptiometry in Japanese prepubertal children.

PubMed

Midorikawa, T; Ohta, M; Hikihara, Y; Torii, S; Sakamoto, S

2017-10-01

We aimed to develop regression-based prediction equations for estimating total and regional skeletal muscle mass (SMM) from measurements of lean soft tissue mass (LSTM) using dual-energy X-ray absorptiometry (DXA) and investigate the validity of these equations. In total, 144 healthy Japanese prepubertal children aged 6-12 years were divided into 2 groups: the model development group (62 boys and 38 girls) and the validation group (26 boys and 18 girls). Contiguous MRI images with a 1-cm slice thickness were obtained from the first cervical vertebra to the ankle joints as reference data. The SMM was calculated from the summation of the digitized cross-sectional areas. Total and regional LSTM was measured using DXA. Strong significant correlations were observed between the site-matched SMM (total, arms, trunk and legs) measured by MRI and the LSTM obtained by DXA in the model development group for both boys and girls (R 2 adj =0.86-0.97, P<0.01, standard error of the estimate (SEE)=0.08-0.44 kg). When these SMM prediction equations were applied to the validation group, the measured total (boys 9.47±2.21 kg; girls 8.18±2.62 kg) and regional SMM were very similar to the predicted values for both boys (total SMM 9.40±2.39 kg) and girls (total SMM 8.17±2.57 kg). The results of the Bland-Altman analysis for the validation group did not indicate any bias for either boys or girls with the exception of the arm region for the girls. These results suggest that the DXA-derived prediction equations are precise and accurate for the estimation of total and regional SMM in Japanese prepubertal boys and girls.

Agility performance in high-level junior basketball players: the predictive value of anthropometrics and power qualities.

PubMed

Sisic, Nedim; Jelicic, Mario; Pehar, Miran; Spasic, Miodrag; Sekulic, Damir

2016-01-01

In basketball, anthropometric status is an important factor when identifying and selecting talents, while agility is one of the most vital motor performances. The aim of this investigation was to evaluate the influence of anthropometric variables and power capacities on different preplanned agility performances. The participants were 92 high-level, junior-age basketball players (16-17 years of age; 187.6±8.72 cm in body height, 78.40±12.26 kg in body mass), randomly divided into a validation and cross-validation subsample. The predictors set consisted of 16 anthropometric variables, three tests of power-capacities (Sargent-jump, broad-jump and medicine-ball-throw) as predictors. The criteria were three tests of agility: a T-Shape-Test; a Zig-Zag-Test, and a test of running with a 180-degree turn (T180). Forward stepwise multiple regressions were calculated for validation subsamples and then cross-validated. Cross validation included correlations between observed and predicted scores, dependent samples t-test between predicted and observed scores; and Bland Altman graphics. Analysis of the variance identified centres being advanced in most of the anthropometric indices, and medicine-ball-throw (all at P<0.05); with no significant between-position-differences for other studied motor performances. Multiple regression models originally calculated for the validation subsample were then cross-validated, and confirmed for Zig-zag-Test (R of 0.71 and 0.72 for the validation and cross-validation subsample, respectively). Anthropometrics were not strongly related to agility performance, but leg length is found to be negatively associated with performance in basketball-specific agility. Power capacities are confirmed to be an important factor in agility. The results highlighted the importance of sport-specific tests when studying pre-planned agility performance in basketball. The improvement in power capacities will probably result in an improvement in agility in basketball athletes, while anthropometric indices should be used in order to identify those athletes who can achieve superior agility performance.

Predicting Overall Survival After Stereotactic Ablative Radiation Therapy in Early-Stage Lung Cancer: Development and External Validation of the Amsterdam Prognostic Model

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

Louie, Alexander V., E-mail: Dr.alexlouie@gmail.com; Department of Radiation Oncology, London Regional Cancer Program, University of Western Ontario, London, Ontario; Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston, Massachusetts

Purpose: A prognostic model for 5-year overall survival (OS), consisting of recursive partitioning analysis (RPA) and a nomogram, was developed for patients with early-stage non-small cell lung cancer (ES-NSCLC) treated with stereotactic ablative radiation therapy (SABR). Methods and Materials: A primary dataset of 703 ES-NSCLC SABR patients was randomly divided into a training (67%) and an internal validation (33%) dataset. In the former group, 21 unique parameters consisting of patient, treatment, and tumor factors were entered into an RPA model to predict OS. Univariate and multivariate models were constructed for RPA-selected factors to evaluate their relationship with OS. A nomogrammore » for OS was constructed based on factors significant in multivariate modeling and validated with calibration plots. Both the RPA and the nomogram were externally validated in independent surgical (n=193) and SABR (n=543) datasets. Results: RPA identified 2 distinct risk classes based on tumor diameter, age, World Health Organization performance status (PS) and Charlson comorbidity index. This RPA had moderate discrimination in SABR datasets (c-index range: 0.52-0.60) but was of limited value in the surgical validation cohort. The nomogram predicting OS included smoking history in addition to RPA-identified factors. In contrast to RPA, validation of the nomogram performed well in internal validation (r{sup 2}=0.97) and external SABR (r{sup 2}=0.79) and surgical cohorts (r{sup 2}=0.91). Conclusions: The Amsterdam prognostic model is the first externally validated prognostication tool for OS in ES-NSCLC treated with SABR available to individualize patient decision making. The nomogram retained strong performance across surgical and SABR external validation datasets. RPA performance was poor in surgical patients, suggesting that 2 different distinct patient populations are being treated with these 2 effective modalities.« less

Predictive validity of childhood oppositional defiant disorder and conduct disorder: implications for the DSM-V.

PubMed

Burke, Jeffrey D; Waldman, Irwin; Lahey, Benjamin B

2010-11-01

Data are presented from 3 studies of children and adolescents to evaluate the predictive validity of childhood oppositional defiant disorder (ODD) and conduct disorder (CD) as defined in the Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV; American Psychiatric Association, 1994) and the International Classification of Diseases, Version 10 (ICD-10; World Health Organization, 1992). The present analyses strongly support the predictive validity of these diagnoses by showing that they predict both future psychopathology and enduring functional impairment. Furthermore, the present findings generally support the hierarchical developmental hypothesis in DSM-IV that some children with ODD progress to childhood-onset CD, and some youth with CD progress to antisocial personality disorder (APD). Nonetheless, they reveal that CD does not always co-occur with ODD, particularly during adolescence. Importantly, the present findings suggest that ICD-10 diagnostic criteria for ODD, which treat CD symptoms as ODD symptoms when diagnostic criteria for CD are not met, identify more functionally impaired children than the more restrictive DSM-IV definition of ODD. Filling this "hole" in the DSM-IV criteria for ODD should be a priority for the DSM-V. In addition, the present findings suggest that although the psychopathic trait of interpersonal callousness in childhood independently predicts future APD, these findings do not confirm the hypothesis that callousness distinguishes a subset of children with CD with an elevated risk for APD. PsycINFO Database Record (c) 2010 APA, all rights reserved

Prospective evaluation of a bivalirudin to warfarin transition nomogram.

PubMed

Hohlfelder, Benjamin; Sylvester, Katelyn W; Rimsans, Jessica; DeiCicchi, David; Connors, Jean M

2017-05-01

Bivalirudin may cause a falsely prolonged international normalized ratio (INR) that complicates the discontinuation of bivalirudin when used as a bridge to warfarin. To prospectively validate our novel bivalirudin to warfarin transition nomogram, adult patients who received bivalirudin as a bridge to warfarin between July 2015 and June 2016 were prospectively evaluated, utilizing our predictive nomogram. The major outcome of our analysis was the correlation between the predicted change in INR upon bivalirudin discontinuation based on the nomogram, and the actual change in INR upon bivalirudin discontinuation. The major outcome was analyzed using the Pearson's correlation test. A Pearson's correlation coefficient >0.6 was considered to be a strong correlation. Bivalirudin was used as a bridge to warfarin in 29 patients. The majority of patients (86%) included in the analysis had a ventricular assist device. The median initial bivalirudin rate was 0.07 mg/kg/h and the mean increase in INR when starting bivalirudin was 0.6. The mean final weight-based bivalirudin rate was 0.08 mg/kg/h and the mean change in INR after stopping bivalirudin was 0.7. The Pearson correlation coefficient between the predicted change in INR upon bivalirudin discontinuation and the actual change in INR upon bivalirudin discontinuation was 0.86 (p < 0.001). After bivalirudin discontinuation, 68% of patients had a therapeutic INR. The results of this prospective analysis successfully validated our novel bivalirudin to warfarin transition nomogram. There was a very strong correlation between the predicted change and actual change in INR upon bivalirudin discontinuation.

Use of assisted reproductive technology treatment as reported by mothers in comparison with registry data: the Upstate KIDS Study.

PubMed

Buck Louis, Germaine M; Druschel, Charlotte; Bell, Erin; Stern, Judy E; Luke, Barbara; McLain, Alexander; Sundaram, Rajeshwari; Yeung, Edwina

2015-06-01

To assess the validity of maternally reported assisted reproductive technologies (ART) use and to identify predictors of reporting errors. Linkage study. Not applicable. A total of 5,034 (27%) mothers enrolled, from whom 4,886 (97%) self-reported information about use of infertility treatment, including ART, for the index birth. None. Four measures of validity (sensitivity, specificity, positive and negative predictive values) and use of net reclassification improvement (NRI) methods to identify predictors associated with concordant/discordant maternal reporting. The Upstate New York Infant Development Screening Program (Update KIDS Study) was linked with the Society for Assisted Reproductive Technology Clinic Outcome Reporting System (SART CORS) using a defined algorithm for 2008-2010. The sensitivity, specificity, positive and negative predictive values were high (0.93, 0.99, 0.80, and 1.00, respectively). The validity of maternal report was high, reflecting few differences by participant characteristics except for maternal age dichotomized at 29 years as identified with NRI methods. Maternally reported ART is valid, with little variation across various characteristics. No strong predictors of discordant reporting were found, supporting the utility of population-based research with SART CORS linkage. Published by Elsevier Inc.

Acquaintance ratings of the Big Five personality traits: incremental validity beyond and interactive effects with self-reports in the prediction of workplace deviance.

PubMed

Kluemper, Donald H; McLarty, Benjamin D; Bing, Mark N

2015-01-01

It is widely established that the Big Five personality traits of conscientiousness, agreeableness, and emotional stability are antecedents to workplace deviance (Berry, Ones, & Sackett, 2007). However, these meta-analytic findings are based on self-reported personality traits. A recent meta-analysis by Oh, Wang, and Mount (2011) identified the value of acquaintance-reported personality in the prediction of job performance. The current investigation extends prior work by comparing the validities of self- and acquaintance-reported personality in the prediction of workplace deviance across 2 studies. We also hypothesized and tested an interactive, value-added integration of self- with acquaintance-reported personality using socioanalytic personality theory (R. T. Hogan, 1991). Both studies assessed self- and acquaintance-rated Big Five traits, along with supervisor-rated workplace deviance. However, the studies varied the measures of workplace deviance, and the 2nd study also included a self-rated workplace deviance criterion for additional comparison. Across both studies, the traits of conscientiousness and agreeableness were strong predictors of workplace deviance, and acquaintance-reported personality provided incremental validity beyond self-reports. Additionally, acquaintance-reported conscientiousness and agreeableness moderated the prediction of workplace deviance by interacting with the corresponding self-reported traits. Implications for personality theory and measurement are discussed along with applications for practice. (c) 2015 APA, all rights reserved.

Validation of a Method To Screen for Pulmonary Hypertension in Advanced Idiopathic Pulmonary Fibrosis*

PubMed Central

Zisman, David A.; Karlamangla, Arun S.; Kawut, Steven M.; Shlobin, Oksana A.; Saggar, Rajeev; Ross, David J.; Schwarz, Marvin I.; Belperio, John A.; Ardehali, Abbas; Lynch, Joseph P.; Nathan, Steven D.

2008-01-01

Background We have developed a method to screen for pulmonary hypertension (PH) in idiopathic pulmonary fibrosis (IPF) patients, based on a formula to predict mean pulmonary artery pressure (MPAP) from standard lung function measurements. The objective of this study was to validate this method in a separate group of IPF patients. Methods Cross-sectional study of 60 IPF patients from two institutions. The accuracy of the MPAP estimation was assessed by examining the correlation between the predicted and measured MPAPs and the magnitude of the estimation error. The discriminatory ability of the method for PH was assessed using the area under the receiver operating characteristic curve (AUC). Results There was strong correlation in the expected direction between the predicted and measured MPAPs (r = 0.72; p < 0.0001). The estimated MPAP was within 5 mm Hg of the measured MPAP 72% of the time. The AUC for predicting PH was 0.85, and did not differ by institution. A formula-predicted MPAP > 21 mm Hg was associated with a sensitivity, specificity, positive predictive value, and negative predictive value of 95%, 58%, 51%, and 96%, respectively, for PH defined as MPAP from right-heart catheterization > 25 mm Hg. Conclusions A prediction formula for MPAP using standard lung function measurements can be used to screen for PH in IPF patients. PMID:18198245

The accuracy of Genomic Selection in Norwegian red cattle assessed by cross-validation.

PubMed

Luan, Tu; Woolliams, John A; Lien, Sigbjørn; Kent, Matthew; Svendsen, Morten; Meuwissen, Theo H E

2009-11-01

Genomic Selection (GS) is a newly developed tool for the estimation of breeding values for quantitative traits through the use of dense markers covering the whole genome. For a successful application of GS, accuracy of the prediction of genomewide breeding value (GW-EBV) is a key issue to consider. Here we investigated the accuracy and possible bias of GW-EBV prediction, using real bovine SNP genotyping (18,991 SNPs) and phenotypic data of 500 Norwegian Red bulls. The study was performed on milk yield, fat yield, protein yield, first lactation mastitis traits, and calving ease. Three methods, best linear unbiased prediction (G-BLUP), Bayesian statistics (BayesB), and a mixture model approach (MIXTURE), were used to estimate marker effects, and their accuracy and bias were estimated by using cross-validation. The accuracies of the GW-EBV prediction were found to vary widely between 0.12 and 0.62. G-BLUP gave overall the highest accuracy. We observed a strong relationship between the accuracy of the prediction and the heritability of the trait. GW-EBV prediction for production traits with high heritability achieved higher accuracy and also lower bias than health traits with low heritability. To achieve a similar accuracy for the health traits probably more records will be needed.

Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance

USGS Publications Warehouse

Loman, Zachary G.; DeLuca, William; Harrison, Daniel J.; Loftin, Cynthia S.; Rolek, Brian W.; Wood, Petra B.

2018-01-01

ContextSpecies-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.ObjectivesWe tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.MethodsWe compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.ResultsBlackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.ConclusionsLC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.

Multilingual Validation of the Questionnaire for Verifying Stroke-Free Status in West Africa.

PubMed

Sarfo, Fred; Gebregziabher, Mulugeta; Ovbiagele, Bruce; Akinyemi, Rufus; Owolabi, Lukman; Obiako, Reginald; Akpa, Onoja; Armstrong, Kevin; Akpalu, Albert; Adamu, Sheila; Obese, Vida; Boa-Antwi, Nana; Appiah, Lambert; Arulogun, Oyedunni; Mensah, Yaw; Adeoye, Abiodun; Tosin, Aridegbe; Adeleye, Osimhiarherhuo; Tabi-Ajayi, Eric; Phillip, Ibinaiye; Sani, Abubakar; Isah, Suleiman; Tabari, Nasir; Mande, Aliyu; Agunloye, Atinuke; Ogbole, Godwin; Akinyemi, Joshua; Laryea, Ruth; Melikam, Sylvia; Uvere, Ezinne; Adekunle, Gregory; Kehinde, Salaam; Azuh, Paschal; Dambatta, Abdul; Ishaq, Naser; Saulson, Raelle; Arnett, Donna; Tiwari, Hemnant; Jenkins, Carolyn; Lackland, Dan; Owolabi, Mayowa

2016-01-01

The Questionnaire for Verifying Stroke-Free Status (QVSFS), a method for verifying stroke-free status in participants of clinical, epidemiological, and genetic studies, has not been validated in low-income settings where populations have limited knowledge of stroke symptoms. We aimed to validate QVSFS in 3 languages, Yoruba, Hausa and Akan, for ascertainment of stroke-free status of control subjects enrolled in an on-going stroke epidemiological study in West Africa. Data were collected using a cross-sectional study design where 384 participants were consecutively recruited from neurology and general medicine clinics of 5 tertiary referral hospitals in Nigeria and Ghana. Ascertainment of stroke status was by neurologists using structured neurological examination, review of case records, and neuroimaging (gold standard). Relative performance of QVSFS without and with pictures of stroke symptoms (pictograms) was assessed using sensitivity, specificity, positive predictive value, and negative predictive value. The overall median age of the study participants was 54 years and 48.4% were males. Of 165 stroke cases identified by gold standard, 98% were determined to have had stroke, whereas of 219 without stroke 87% were determined to be stroke-free by QVSFS. Negative predictive value of the QVSFS across the 3 languages was 0.97 (range, 0.93-1.00), sensitivity, specificity, and positive predictive value were 0.98, 0.82, and 0.80, respectively. Agreement between the questionnaire with and without the pictogram was excellent/strong with Cohen k=0.92. QVSFS is a valid tool for verifying stroke-free status across culturally diverse populations in West Africa. © 2015 American Heart Association, Inc.

Mutual Influence of Moral Values, Mental Models and Social Dynamics on Intergroup Conflict

DTIC Science & Technology

2013-10-10

Ground-truthed previous human subjects’ data from Guatemala to test overall validity of psychological findings for predicting actual behavior, thus...of findings for development of social science disciplines: In psychology , our research program on Sacred Values has strong implications for Construal...affording them psychological knowledge of how culturally diverse individuals and groups advance values and interests that are potentially compatible or

The utility of single-item readiness screeners in middle school.

PubMed

Lewis, Crystal G; Herman, Keith C; Huang, Francis L; Stormont, Melissa; Grossman, Caroline; Eddy, Colleen; Reinke, Wendy M

2017-10-01

This study examined the benefit of utilizing one-item academic and one-item behavior readiness teacher-rated screeners at the beginning of the school year to predict end-of-school year outcomes for middle school students. The Middle School Academic and Behavior Readiness (M-ABR) screeners were developed to provide an efficient and effective way to assess readiness in students. Participants included 889 students in 62 middle school classrooms in an urban Missouri school district. Concurrent validity with the M-ABR items and other indicators of readiness in the fall were evaluated using Pearson product-moment correlation coefficients, with the academic readiness item having medium to strong correlations with other baseline academic indicators (r=±0.56 to 0.91) and the behavior readiness item having low to strong correlations with baseline behavior items (r=±0.20 to 0.79). Next, the predictive validity of the M-ABR items was analyzed with hierarchical linear regressions using end-of-year outcomes as the dependent variable. The academic and behavior readiness items demonstrated adequate validity for all outcomes with moderate effects (β=±0.31 to 0.73 for academic outcomes and β=±0.24 to 0.59 for behavioral outcomes) after controlling for baseline demographics. Even after controlling for baseline scores, the M-ABR items predicted unique variance in almost all outcome variables. Four conditional probability indices were calculated to obtain an optimal cut score, to determine ready vs. not ready, for both single-item M-ABR scales. The cut point of "fair" yielded the most acceptable values for the indices. The odd ratios (OR) of experiencing negative outcomes given a "fair" or lower readiness rating (2 or below on the M-ABR screeners) at the beginning of the year were significant and strong for all outcomes (OR=2.29 to OR=14.46), except for internalizing problems. These findings suggest promise for using single readiness items to screen for varying negative end-of-year student outcomes. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Canine hip dysplasia is predictable by genotyping.

PubMed

Guo, G; Zhou, Z; Wang, Y; Zhao, K; Zhu, L; Lust, G; Hunter, L; Friedenberg, S; Li, J; Zhang, Y; Harris, S; Jones, P; Sandler, J; Krotscheck, U; Todhunter, R; Zhang, Z

2011-04-01

To establish a predictive method using whole genome genotyping for early intervention in canine hip dysplasia (CHD) risk management, for the prevention of the progression of secondary osteoarthritis (OA), and for selective breeding. Two sets of dogs (six breeds) were genotyped with dense SNPs covering the entire canine genome. The first set contained 359 dogs upon which a predictive formula for genomic breeding value (GBV) was derived by using their estimated breeding value (EBV) of the Norberg angle (a measure of CHD) and their genotypes. To investigate how well the formula would work for an individual dog with genotype only (without using EBV), a cross validation was performed by masking the EBV of one dog at a time. The genomic data and the EBV of the remaining dogs were used to predict the GBV for the single dog that was left out. The second set of dogs included 38 new Labrador retriever dogs, which had no pedigree relationship to the dogs in the first set. The cross validation showed a strong correlation (R>0.7) between the EBV and the GBV. The independent validation showed a moderate correlation (R=0.5) between GBV for the Norberg angle and the observed Norberg angle (no EBV was available for the new 38 dogs). Sensitivity, specificity, positive and negative predictive values of the genomic data were all above 70%. Prediction of CHD from genomic data is feasible, and can be applied for risk management of CHD and early selection for genetic improvement to reduce the prevalence of CHD in breeding programs. The prediction can be implemented before maturity, at which age current radiographic screening programs are traditionally applied, and as soon as DNA is available. Copyright © 2010 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.

Prediction of medial and lateral contact force of the knee joint during normal and turning gait after total knee replacement.

PubMed

Purevsuren, Tserenchimed; Dorj, Ariunzaya; Kim, Kyungsoo; Kim, Yoon Hyuk

2016-04-01

The computational modeling approach has commonly been used to predict knee joint contact forces, muscle forces, and ligament loads during activities of daily living. Knowledge of these forces has several potential applications, for example, within design of equipment to protect the knee joint from injury and to plan adequate rehabilitation protocols, although clinical applications of computational models are still evolving and one of the limiting factors is model validation. The objective of this study was to extend previous modeling technique and to improve the validity of the model prediction using publicly available data set of the fifth "Grand Challenge Competition to Predict In Vivo Knee Loads." A two-stage modeling approach, which combines conventional inverse dynamic analysis (the first stage) with a multi-body subject-specific lower limb model (the second stage), was used to calculate medial and lateral compartment contact forces. The validation was performed by direct comparison of model predictions and experimental measurement of medial and lateral compartment contact forces during normal and turning gait. The model predictions of both medial and lateral contact forces showed strong correlations with experimental measurements in normal gait (r = 0.75 and 0.71) and in turning gait trials (r = 0.86 and 0.72), even though the current technique over-estimated medial compartment contact forces in swing phase. The correlation coefficient, Sprague and Geers metrics, and root mean squared error indicated that the lateral contact forces were predicted better than medial contact forces in comparison with the experimental measurements during both normal and turning gait trials. © IMechE 2016.

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.

Analysis of Square Cup Deep-Drawing Test of Pure Titanium

NASA Astrophysics Data System (ADS)

Ogawa, Takaki; Ma, Ninshu; Ueyama, Minoru; Harada, Yasunori

2016-08-01

The prediction of formability of titunium is more difficult than steels since its strong anisotropy. If computer simulation can estimate the formability of titanium, we can select the optimal forming conditions. The purpose of this study was to acquire knowledge for the formability prediction by the computer simulation of the square cup deep-drawing of pure titanium. In this paper, the results of FEM analsis of pure titanium were compared with the experimental results to examine the analysis validity. We analyzed the formability of deepdrawing square cup of titanium by the FEM using solid elements. Compared the analysis results with the experimental results such as the forming shape, the punch load, and the thickness, the validity was confirmed. Further, through analyzing the change of the thickness around the forming corner, it was confirmed that the thickness increased to its maximum value during forming process at the stroke of 35mm more than the maximum stroke.

Motivation and reasons to quit: predictive validity among adolescent smokers.

PubMed

Turner, Lindsey R; Mermelstein, Robin

2004-01-01

To examine reasons to quit among adolescents in a smoking cessation program, and whether reasons were associated with subsequent cessation. Participants were 351 adolescents. At baseline, adolescents reported motivation, reasons to quit, and stage of change for cessation. Quit status was assessed at end of treatment. Girls were more likely to endorse image and appearance reasons to quit. Cessation was more likely among adolescents with higher motivation and those wanting to quit because of friends. Different reasons to quit were associated with motivation and cessation. Baseline motivation strongly predicted cessation, suggesting the relative value of assessing global motivation.

Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation.

PubMed

Wahl, Simone; Boulesteix, Anne-Laure; Zierer, Astrid; Thorand, Barbara; van de Wiel, Mark A

2016-10-26

Missing values are a frequent issue in human studies. In many situations, multiple imputation (MI) is an appropriate missing data handling strategy, whereby missing values are imputed multiple times, the analysis is performed in every imputed data set, and the obtained estimates are pooled. If the aim is to estimate (added) predictive performance measures, such as (change in) the area under the receiver-operating characteristic curve (AUC), internal validation strategies become desirable in order to correct for optimism. It is not fully understood how internal validation should be combined with multiple imputation. In a comprehensive simulation study and in a real data set based on blood markers as predictors for mortality, we compare three combination strategies: Val-MI, internal validation followed by MI on the training and test parts separately, MI-Val, MI on the full data set followed by internal validation, and MI(-y)-Val, MI on the full data set omitting the outcome followed by internal validation. Different validation strategies, including bootstrap und cross-validation, different (added) performance measures, and various data characteristics are considered, and the strategies are evaluated with regard to bias and mean squared error of the obtained performance estimates. In addition, we elaborate on the number of resamples and imputations to be used, and adopt a strategy for confidence interval construction to incomplete data. Internal validation is essential in order to avoid optimism, with the bootstrap 0.632+ estimate representing a reliable method to correct for optimism. While estimates obtained by MI-Val are optimistically biased, those obtained by MI(-y)-Val tend to be pessimistic in the presence of a true underlying effect. Val-MI provides largely unbiased estimates, with a slight pessimistic bias with increasing true effect size, number of covariates and decreasing sample size. In Val-MI, accuracy of the estimate is more strongly improved by increasing the number of bootstrap draws rather than the number of imputations. With a simple integrated approach, valid confidence intervals for performance estimates can be obtained. When prognostic models are developed on incomplete data, Val-MI represents a valid strategy to obtain estimates of predictive performance measures.

Use of support vector machines for disease risk prediction in genome-wide association studies: concerns and opportunities.

PubMed

Mittag, Florian; Büchel, Finja; Saad, Mohamad; Jahn, Andreas; Schulte, Claudia; Bochdanovits, Zoltan; Simón-Sánchez, Javier; Nalls, Mike A; Keller, Margaux; Hernandez, Dena G; Gibbs, J Raphael; Lesage, Suzanne; Brice, Alexis; Heutink, Peter; Martinez, Maria; Wood, Nicholas W; Hardy, John; Singleton, Andrew B; Zell, Andreas; Gasser, Thomas; Sharma, Manu

2012-12-01

The success of genome-wide association studies (GWAS) in deciphering the genetic architecture of complex diseases has fueled the expectations whether the individual risk can also be quantified based on the genetic architecture. So far, disease risk prediction based on top-validated single-nucleotide polymorphisms (SNPs) showed little predictive value. Here, we applied a support vector machine (SVM) to Parkinson disease (PD) and type 1 diabetes (T1D), to show that apart from magnitude of effect size of risk variants, heritability of the disease also plays an important role in disease risk prediction. Furthermore, we performed a simulation study to show the role of uncommon (frequency 1-5%) as well as rare variants (frequency <1%) in disease etiology of complex diseases. Using a cross-validation model, we were able to achieve predictions with an area under the receiver operating characteristic curve (AUC) of ~0.88 for T1D, highlighting the strong heritable component (∼90%). This is in contrast to PD, where we were unable to achieve a satisfactory prediction (AUC ~0.56; heritability ~38%). Our simulations showed that simultaneous inclusion of uncommon and rare variants in GWAS would eventually lead to feasible disease risk prediction for complex diseases such as PD. The used software is available at http://www.ra.cs.uni-tuebingen.de/software/MACLEAPS/. © 2012 Wiley Periodicals, Inc.

Comparison of Methods for Estimating Prevalence of Chronic Diseases and Health Behaviors for Small Geographic Areas: Boston Validation Study, 2013

PubMed Central

Holt, James B.; Zhang, Xingyou; Lu, Hua; Shah, Snehal N.; Dooley, Daniel P.; Matthews, Kevin A.; Croft, Janet B.

2017-01-01

Introduction Local health authorities need small-area estimates for prevalence of chronic diseases and health behaviors for multiple purposes. We generated city-level and census-tract–level prevalence estimates of 27 measures for the 500 largest US cities. Methods To validate the methodology, we constructed multilevel logistic regressions to predict 10 selected health indicators among adults aged 18 years or older by using 2013 Behavioral Risk Factor Surveillance System (BRFSS) data; we applied their predicted probabilities to census population data to generate city-level, neighborhood-level, and zip-code–level estimates for the city of Boston, Massachusetts. Results By comparing the predicted estimates with their corresponding direct estimates from a locally administered survey (Boston BRFSS 2010 and 2013), we found that our model-based estimates for most of the selected health indicators at the city level were close to the direct estimates from the local survey. We also found strong correlation between the model-based estimates and direct survey estimates at neighborhood and zip code levels for most indicators. Conclusion Findings suggest that our model-based estimates are reliable and valid at the city level for certain health outcomes. Local health authorities can use the neighborhood-level estimates if high quality local health survey data are not otherwise available. PMID:29049020

Testing the Relations Between Impulsivity-Related Traits, Suicidality, and Nonsuicidal Self-Injury: A Test of the Incremental Validity of the UPPS Model

PubMed Central

Lynam, Donald R.; Miller, Joshua D.; Miller, Drew J.; Bornovalova, Marina A.; Lejuez, C. W.

2011-01-01

Borderline personality disorder (BPD) has received significant attention as a predictor of suicidal behavior (SB) and nonsuicidal self-injury (NSSI). Despite significant promise, trait impulsivity has received less attention. Understanding the relations between impulsivity and SB and NSSI is confounded, unfortunately, by the heterogeneous nature of impulsivity. This study examined the relations among 4 personality pathways to impulsive behavior studied via the UPPS model of impulsivity and SB and NSSI in a residential sample of drug abusers (N = 76). In this study, we tested whether these 4 impulsivity-related traits (i.e., Negative Urgency, Sensation Seeking, Lack of Premeditation, and Lack of Perseverance) provide incremental validity in the statistical prediction of SB and NSSI above and beyond BPD; they do. We also tested whether BPD symptoms provide incremental validity in the prediction of SB and NSSI above and beyond these impulsivity-related traits; they do not. In addition to the main effects of Lack of Premeditation and Negative Urgency, we found evidence of a robust interaction between these 2 personality traits. The current results argue strongly for the consideration of these 2 impulsivity-related domains—alone and in interaction—when attempting to understand and predict SB and NSSI. PMID:21833346

Testing the relations between impulsivity-related traits, suicidality, and nonsuicidal self-injury: a test of the incremental validity of the UPPS model.

PubMed

Lynam, Donald R; Miller, Joshua D; Miller, Drew J; Bornovalova, Marina A; Lejuez, C W

2011-04-01

Borderline personality disorder (BPD) has received significant attention as a predictor of suicidal behavior (SB) and nonsuicidal self-injury (NSSI). Despite significant promise, trait impulsivity has received less attention. Understanding the relations between impulsivity and SB and NSSI is confounded, unfortunately, by the heterogeneous nature of impulsivity. This study examined the relations among 4 personality pathways to impulsive behavior studied via the UPPS model of impulsivity and SB and NSSI in a residential sample of drug abusers (N = 76). In this study, we tested whether these 4 impulsivity-related traits (i.e., Negative Urgency, Sensation Seeking, Lack of Premeditation, and Lack of Perseverance) provide incremental validity in the statistical prediction of SB and NSSI above and beyond BPD; they do. We also tested whether BPD symptoms provide incremental validity in the prediction of SB and NSSI above and beyond these impulsivity-related traits; they do not. In addition to the main effects of Lack of Premeditation and Negative Urgency, we found evidence of a robust interaction between these 2 personality traits. The current results argue strongly for the consideration of these 2 impulsivity-related domains--alone and in interaction--when attempting to understand and predict SB and NSSI.

Discrimination of fish populations using parasites: Random Forests on a 'predictable' host-parasite system.

PubMed

Pérez-Del-Olmo, A; Montero, F E; Fernández, M; Barrett, J; Raga, J A; Kostadinova, A

2010-10-01

We address the effect of spatial scale and temporal variation on model generality when forming predictive models for fish assignment using a new data mining approach, Random Forests (RF), to variable biological markers (parasite community data). Models were implemented for a fish host-parasite system sampled along the Mediterranean and Atlantic coasts of Spain and were validated using independent datasets. We considered 2 basic classification problems in evaluating the importance of variations in parasite infracommunities for assignment of individual fish to their populations of origin: multiclass (2-5 population models, using 2 seasonal replicates from each of the populations) and 2-class task (using 4 seasonal replicates from 1 Atlantic and 1 Mediterranean population each). The main results are that (i) RF are well suited for multiclass population assignment using parasite communities in non-migratory fish; (ii) RF provide an efficient means for model cross-validation on the baseline data and this allows sample size limitations in parasite tag studies to be tackled effectively; (iii) the performance of RF is dependent on the complexity and spatial extent/configuration of the problem; and (iv) the development of predictive models is strongly influenced by seasonal change and this stresses the importance of both temporal replication and model validation in parasite tagging studies.

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.

Assessing teachers' positive psychological functioning at work: Development and validation of the Teacher Subjective Wellbeing Questionnaire.

PubMed

Renshaw, Tyler L; Long, Anna C J; Cook, Clayton R

2015-06-01

This study reports on the initial development and validation of the Teacher Subjective Wellbeing Questionnaire (TSWQ) with 2 samples of educators-a general sample of 185 elementary and middle school teachers, and a target sample of 21 elementary school teachers experiencing classroom management challenges. The TSWQ is an 8-item self-report instrument for assessing teachers' subjective wellbeing, which is operationalized via subscales measuring school connectedness and teaching efficacy. The conceptualization and development processes underlying the TSWQ are described, and results from a series of preliminary psychometric and exploratory analyses are reported to establish initial construct validity. Findings indicated that the TSWQ was characterized by 2 conceptually sound latent factors, that both subscales and the composite scale demonstrated strong internal consistency, and that all scales demonstrated convergent validity with self-reported school supports and divergent validity with self-reported stress and emotional burnout. Furthermore, results indicated that TSWQ scores did not differ according to teachers' school level (i.e., elementary vs. middle), but that they did differ according to unique school environment (e.g., 1 middle school vs. another middle school) and teacher stressors (i.e., general teachers vs. teachers experiencing classroom management challenges). Results also indicated that, for teachers experiencing classroom challenges, the TSWQ had strong short-term predictive validity for psychological distress, accounting for approximately half of the variance in teacher stress and emotional burnout. Implications for theory, research, and the practice of school psychology are discussed. (c) 2015 APA, all rights reserved).

Limits on determining the skill of North Atlantic Ocean decadal predictions.

PubMed

Menary, Matthew B; Hermanson, Leon

2018-04-27

The northern North Atlantic is important globally both through its impact on the Atlantic Meridional Overturning Circulation (AMOC) and through widespread atmospheric teleconnections. The region has been shown to be potentially predictable a decade ahead with the skill of decadal predictions assessed against reanalyses of the ocean state. Here, we show that the prediction skill in this region is strongly dependent on the choice of reanalysis used for validation, and describe the causes. Multiannual skill in key metrics such as Labrador Sea density and the AMOC depends on more than simply the choice of the prediction model. Instead, this skill is related to the similarity between the nature of interannual density variability in the underlying climate model and the chosen reanalysis. The climate models used in these decadal predictions are also used in climate projections, which raises questions about the sensitivity of these projections to the models' innate North Atlantic density variability.

Euler flow predictions for an oscillating cascade using a high resolution wave-split scheme

NASA Technical Reports Server (NTRS)

Huff, Dennis L.; Swafford, Timothy W.; Reddy, T. S. R.

1991-01-01

A compressible flow code that can predict the nonlinear unsteady aerodynamics associated with transonic flows over oscillating cascades is developed and validated. The code solves the two dimensional, unsteady Euler equations using a time-marching, flux-difference splitting scheme. The unsteady pressures and forces can be determined for arbitrary input motions, although only harmonic pitching and plunging motions are addressed. The code solves the flow equations on a H-grid which is allowed to deform with the airfoil motion. Predictions are presented for both flat plate cascades and loaded airfoil cascades. Results are compared to flat plate theory and experimental data. Predictions are also presented for several oscillating cascades with strong normal shocks where the pitching amplitudes, cascade geometry and interblade phase angles are varied to investigate nonlinear behavior.

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

USGS Publications Warehouse

Brown, M.; Dinsmore, J.J.

1988-01-01

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

Why don't you exercise? Development of the Amotivation Toward Exercise Scale among older inactive individuals.

PubMed

Vlachopoulos, Symeon P; Gigoudi, Maria A

2008-07-01

This article reports on the development and initial validation of the Amotivation Toward Exercise Scale (ATES), which reflects a taxonomy of older adults' reasons to refrain from exercise. Drawing on work by Pelletier, Dion, Tuson, and Green-Demers (1999) and Legault, Green-Demers, and Pelletier (2006), these dimensions were the outcome beliefs, capacity beliefs, effort beliefs, and value amotivation beliefs toward exercise. The results supported a 4-factor correlated model that fit the data better than either a unidimensional model or a 4-factor uncorrelated model or a hierarchical model with strong internal reliability for all the subscales. Evidence also emerged for the discriminant validity of the subscale scores. Furthermore, the predictive validity of the subscale scores was supported, and satisfactory measurement invariance was demonstrated across the calibration and validation samples, supporting the generalizability of the scale's measurement properties.

A five-factor measure of obsessive-compulsive personality traits.

PubMed

Samuel, Douglas B; Riddell, Ashley D B; Lynam, Donald R; Miller, Joshua D; Widiger, Thomas A

2012-01-01

This study provides convergent, discriminant, and incremental validity data for the Five-Factor Obsessive-Compulsive Inventory (FFOCI), a newly developed measure of traits relevant to obsessive-compulsive personality disorder (OCPD) from the perspective of the Five-factor model (FFM). Twelve scales were constructed as maladaptive variants of specific FFM facets (e.g., Perfectionism as a maladaptive variant of FFM competence). On the basis of data from 407 undergraduates (oversampled for OCPD symptoms) these 12 scales demonstrated convergent correlations with established measures of OCPD and the FFM. Further, they obtained strong discriminant validity with respect to facets from other FFM domains. Most important, the individual scales and total score of the FFOCI obtained incremental validity beyond existing measures of the FFM and OCPD for predicting a composite measure of obsessive-compulsive symptomatology. The findings support the validity of the FFOCI as a measure of obsessive-compulsive personality traits, as well as of maladaptive variants of the FFM.

Incremental validity of the MMPI-2-RF over-reporting scales and RBS in assessing the veracity of memory complaints.

PubMed

Gervais, Roger O; Ben-Porath, Yossef S; Wygant, Dustin B; Sellbom, Martin

2010-06-01

The Response Bias Scale (RBS) has been found to be a better predictor of over-reported memory complaints than Minnesota Multiphasic Personality Inventory-2 (MMPI-2) F, Back Infrequency (Fb), Infrequency-Psychopathology (Fp), and FBS scales. The MMPI-2-Restructured Form (RF) validity scales were designed to meet or exceed the sensitivity of their MMPI-2 counterparts to symptom over-reporting. This study examined the incremental validity of MMPI-2-RF validity scales and RBS in assessing memory complaints. The MMPI-2-RF over-reporting validity scales were more strongly associated with mean Memory Complaints Inventory scores than their MMPI-2 counterparts (d = 0.22 to 0.49). RBS showed the strongest relationship with memory complaints. Regression analyses demonstrated the incremental validity of the MMPI-2-RF Infrequent Responses, Infrequent Psychopathology Responses, Infrequent Somatic Responses, and FBS-r scales relative to MMPI-2 F, Fp, and FBS in predicting memory complaints. This is consistent with the development objectives of the MMPI-2-RF validity scales as more efficient and sensitive measures of symptom over-reporting.

Addressing criticisms of existing predictive bias research: cognitive ability test scores still overpredict African Americans' job performance.

PubMed

Berry, Christopher M; Zhao, Peng

2015-01-01

Predictive bias studies have generally suggested that cognitive ability test scores overpredict job performance of African Americans, meaning these tests are not predictively biased against African Americans. However, at least 2 issues call into question existing over-/underprediction evidence: (a) a bias identified by Aguinis, Culpepper, and Pierce (2010) in the intercept test typically used to assess over-/underprediction and (b) a focus on the level of observed validity instead of operational validity. The present study developed and utilized a method of assessing over-/underprediction that draws on the math of subgroup regression intercept differences, does not rely on the biased intercept test, allows for analysis at the level of operational validity, and can use meta-analytic estimates as input values. Therefore, existing meta-analytic estimates of key parameters, corrected for relevant statistical artifacts, were used to determine whether African American job performance remains overpredicted at the level of operational validity. African American job performance was typically overpredicted by cognitive ability tests across levels of job complexity and across conditions wherein African American and White regression slopes did and did not differ. Because the present study does not rely on the biased intercept test and because appropriate statistical artifact corrections were carried out, the present study's results are not affected by the 2 issues mentioned above. The present study represents strong evidence that cognitive ability tests generally overpredict job performance of African Americans. (c) 2015 APA, all rights reserved.

Acoustic characterization of high intensity focused ultrasound fields generated from a transmitter with a large aperture

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

Chen, Tao; Fan, Tingbo; Jiangsu Province Institute for Medical Equipment Testing, Nanjing 210012

Prediction and measurement of the acoustic field emitted from a high intensity focused ultrasound (HIFU) is essential for the accurate ultrasonic treatment. In this study, the acoustic field generated from a strongly focused HIFU transmitter was characterized by a combined experiment and simulation method. The spheroidal beam equation (SBE) was utilized to describe the nonlinear sound propagation. The curve of the source pressure amplitude versus voltage excitation was determined by fitting the measured ratio of the second harmonic to the fundamental component of the focal waveform to the simulation result; finally, the acoustic pressure field generated by the strongly focusedmore » HIFU transmitter was predicted by using the SBE model. A commercial fiber optic probe hydrophone was utilized to measure the acoustic pressure field generated from a 1.1 MHz HIFU transmitter with a large half aperture angle of 30°. The maximum measured peak-to-peak pressure was up to 72 MPa. The validity of this combined approach was confirmed by the comparison between the measured results and the calculated ones. The results indicate that the current approach might be useful to describe the HIFU field. The results also suggest that this method is not valid for low excitations owing to low sensitivity of the second harmonic.« less

Implementation and validation of an economic module in the Be-FAST model to predict costs generated by livestock disease epidemics: Application to classical swine fever epidemics in Spain.

PubMed

Fernández-Carrión, E; Ivorra, B; Martínez-López, B; Ramos, A M; Sánchez-Vizcaíno, J M

2016-04-01

Be-FAST is a computer program based on a time-spatial stochastic spread mathematical model for studying the transmission of infectious livestock diseases within and between farms. The present work describes a new module integrated into Be-FAST to model the economic consequences of the spreading of classical swine fever (CSF) and other infectious livestock diseases within and between farms. CSF is financially one of the most damaging diseases in the swine industry worldwide. Specifically in Spain, the economic costs in the two last CSF epidemics (1997 and 2001) reached jointly more than 108 million euros. The present analysis suggests that severe CSF epidemics are associated with significant economic costs, approximately 80% of which are related to animal culling. Direct costs associated with control measures are strongly associated with the number of infected farms, while indirect costs are more strongly associated with epidemic duration. The economic model has been validated with economic information around the last outbreaks in Spain. These results suggest that our economic module may be useful for analysing and predicting economic consequences of livestock disease epidemics. Copyright © 2016 Elsevier B.V. All rights reserved.

Finite-Difference Modeling of Acoustic and Gravity Wave Propagation in Mars Atmosphere: Application to Infrasounds Emitted by Meteor Impacts

NASA Astrophysics Data System (ADS)

Garcia, Raphael F.; Brissaud, Quentin; Rolland, Lucie; Martin, Roland; Komatitsch, Dimitri; Spiga, Aymeric; Lognonné, Philippe; Banerdt, Bruce

2017-10-01

The propagation of acoustic and gravity waves in planetary atmospheres is strongly dependent on both wind conditions and attenuation properties. This study presents a finite-difference modeling tool tailored for acoustic-gravity wave applications that takes into account the effect of background winds, attenuation phenomena (including relaxation effects specific to carbon dioxide atmospheres) and wave amplification by exponential density decrease with height. The simulation tool is implemented in 2D Cartesian coordinates and first validated by comparison with analytical solutions for benchmark problems. It is then applied to surface explosions simulating meteor impacts on Mars in various Martian atmospheric conditions inferred from global climate models. The acoustic wave travel times are validated by comparison with 2D ray tracing in a windy atmosphere. Our simulations predict that acoustic waves generated by impacts can refract back to the surface on wind ducts at high altitude. In addition, due to the strong nighttime near-surface temperature gradient on Mars, the acoustic waves are trapped in a waveguide close to the surface, which allows a night-side detection of impacts at large distances in Mars plains. Such theoretical predictions are directly applicable to future measurements by the INSIGHT NASA Discovery mission.

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

PubMed

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

2006-02-15

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

Prediction of Low Community Sanitation Coverage Using Environmental and Sociodemographic Factors in Amhara Region, Ethiopia

PubMed Central

Oswald, William E.; Stewart, Aisha E. P.; Flanders, W. Dana; Kramer, Michael R.; Endeshaw, Tekola; Zerihun, Mulat; Melaku, Birhanu; Sata, Eshetu; Gessesse, Demelash; Teferi, Tesfaye; Tadesse, Zerihun; Guadie, Birhan; King, Jonathan D.; Emerson, Paul M.; Callahan, Elizabeth K.; Moe, Christine L.; Clasen, Thomas F.

2016-01-01

This study developed and validated a model for predicting the probability that communities in Amhara Region, Ethiopia, have low sanitation coverage, based on environmental and sociodemographic conditions. Community sanitation coverage was measured between 2011 and 2014 through trachoma control program evaluation surveys. Information on environmental and sociodemographic conditions was obtained from available data sources and linked with community data using a geographic information system. Logistic regression was used to identify predictors of low community sanitation coverage (< 20% versus ≥ 20%). The selected model was geographically and temporally validated. Model-predicted probabilities of low community sanitation coverage were mapped. Among 1,502 communities, 344 (22.90%) had coverage below 20%. The selected model included measures for high topsoil gravel content, an indicator for low-lying land, population density, altitude, and rainfall and had reasonable predictive discrimination (area under the curve = 0.75, 95% confidence interval = 0.72, 0.78). Measures of soil stability were strongly associated with low community sanitation coverage, controlling for community wealth, and other factors. A model using available environmental and sociodemographic data predicted low community sanitation coverage for areas across Amhara Region with fair discrimination. This approach could assist sanitation programs and trachoma control programs, scaling up or in hyperendemic areas, to target vulnerable areas with additional activities or alternate technologies. PMID:27430547

Thermodynamic Constraints Improve Metabolic Networks.

PubMed

Krumholz, Elias W; Libourel, Igor G L

2017-08-08

In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Application of all-relevant feature selection for the failure analysis of parameter-induced simulation crashes in climate models

NASA Astrophysics Data System (ADS)

Paja, Wiesław; Wrzesien, Mariusz; Niemiec, Rafał; Rudnicki, Witold R.

2016-03-01

Climate models are extremely complex pieces of software. They reflect the best knowledge on the physical components of the climate; nevertheless, they contain several parameters, which are too weakly constrained by observations, and can potentially lead to a simulation crashing. Recently a study by Lucas et al. (2013) has shown that machine learning methods can be used for predicting which combinations of parameters can lead to the simulation crashing and hence which processes described by these parameters need refined analyses. In the current study we reanalyse the data set used in this research using different methodology. We confirm the main conclusion of the original study concerning the suitability of machine learning for the prediction of crashes. We show that only three of the eight parameters indicated in the original study as relevant for prediction of the crash are indeed strongly relevant, three others are relevant but redundant and two are not relevant at all. We also show that the variance due to the split of data between training and validation sets has a large influence both on the accuracy of predictions and on the relative importance of variables; hence only a cross-validated approach can deliver a robust prediction of performance and relevance of variables.

External validation of anti-Müllerian hormone based prediction of live birth in assisted conception

PubMed Central

2013-01-01

Background Chronological age and oocyte yield are independent determinants of live birth in assisted conception. Anti-Müllerian hormone (AMH) is strongly associated with oocyte yield after controlled ovarian stimulation. We have previously assessed the ability of AMH and age to independently predict live birth in an Italian assisted conception cohort. Herein we report the external validation of the nomogram in 822 UK first in vitro fertilization (IVF) cycles. Methods Retrospective cohort consisting of 822 patients undergoing their first IVF treatment cycle at Glasgow Centre for Reproductive Medicine. Analyses were restricted to women aged between 25 and 42 years of age. All women had an AMH measured prior to commencing their first IVF cycle. The performance of the model was assessed; discrimination by the area under the receiver operator curve (ROCAUC) and model calibration by the predicted probability versus observed probability. Results Live births occurred in 29.4% of the cohort. The observed and predicted outcomes showed no evidence of miscalibration (p = 0.188). The ROCAUC was 0.64 (95% CI: 0.60, 0.68), suggesting moderate and similar discrimination to the original model. The ROCAUC for a continuous model of age and AMH was 0.65 (95% CI 0.61, 0.69), suggesting that the original categories of AMH were appropriate. Conclusions We confirm by external validation that AMH and age are independent predictors of live birth. Although the confidence intervals for each category are wide, our results support the assessment of AMH in larger cohorts with detailed baseline phenotyping for live birth prediction. PMID:23294733

Multiattribute health utility scoring for the computerized adaptive measure CAT-5D-QOL was developed and validated.

PubMed

Kopec, Jacek A; Sayre, Eric C; Rogers, Pamela; Davis, Aileen M; Badley, Elizabeth M; Anis, Aslam H; Abrahamowicz, Michal; Russell, Lara; Rahman, Md Mushfiqur; Esdaile, John M

2015-10-01

The CAT-5D-QOL is a previously reported item response theory (IRT)-based computerized adaptive tool to measure five domains (attributes) of health-related quality of life. The objective of this study was to develop and validate a multiattribute health utility (MAHU) scoring method for this instrument. The MAHU scoring system was developed in two stages. In phase I, we obtained standard gamble (SG) utilities for 75 hypothetical health states in which only one domain varied (15 states per domain). In phase II, we obtained SG utilities for 256 multiattribute states. We fit a multiplicative regression model to predict SG utilities from the five IRT domain scores. The prediction model was constrained using data from phase I. We validated MAHU scores by comparing them with the Health Utilities Index Mark 3 (HUI3) and directly measured utilities and by assessing between-group discrimination. MAHU scores have a theoretical range from -0.842 to 1. In the validation study, the scores were, on average, higher than HUI3 utilities and lower than directly measured SG utilities. MAHU scores correlated strongly with the HUI3 (Spearman ρ = 0.78) and discriminated well between groups expected to differ in health status. Results reported here provide initial evidence supporting the validity of the MAHU scoring system for the CAT-5D-QOL. Copyright © 2015 Elsevier Inc. All rights reserved.

A Comparison of the Fagerström Test for Cigarette Dependence and Cigarette Dependence Scale in a Treatment-Seeking Sample of Pregnant Smokers.

PubMed

Berlin, Ivan; Singleton, Edward G; Heishman, Stephen J

2016-04-01

Valid and reliable brief measures of cigarette dependence are essential for research purposes and effective clinical care. Two widely-used brief measures of cigarette dependence are the six-item Fagerström Test for Cigarette Dependence (FTCD) and five-item Cigarette Dependence Scale (CDS-5). Their respective metric characteristics among pregnant smokers have not yet been studied. This was a secondary analysis of data of pregnant smokers (N = 476) enrolled in a smoking cessation study. We assessed internal consistency, reliability, and examined correlations between the instruments and smoking-related behaviors for construct validity. We evaluated predictive validity by testing how well the measures predict abstinence 2 weeks after quit date. Cronbach's alpha coefficient for the CDS-5 was 0.62 and for the FTCD 0.55. Measures were strongly correlated with each other, although FTCD, but not CDS-5, was associated with saliva cotinine concentration. The FTCD, CDS-5, craving to smoke, and withdrawal symptoms failed to predict smoking status 2 weeks following the quit date. Suboptimal reliability estimates and failure to predict short-term smoking call into question the value of including either of the brief measures in studies that aim to explain the obstacles to smoking cessation during pregnancy. © The Author 2015. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

Evaluating the validity of using unverified indices of body condition

USGS Publications Warehouse

Schamber, J.L.; Esler, Daniel N.; Flint, Paul L.

2009-01-01

Condition indices are commonly used in an attempt to link body condition of birds to ecological variables of interest, including demographic attributes such as survival and reproduction. Most indices are based on body mass adjusted for structural body size, calculated as simple ratios or residuals from regressions. However, condition indices are often applied without confirming their predictive value (i.e., without being validated against measured values of fat and protein), which we term ‘unverified’ use. We evaluated the ability of a number of unverified indices frequently found in the literature to predict absolute and proportional levels of fat and protein across five species of waterfowl. Among indices we considered, those accounting for body size never predicted absolute protein more precisely than body mass, however, some indices improved predictability of fat, although the form of the best index varied by species. Further, the gain in precision by using a condition index to predict either absolute or percent fat was minimal (rise in r2≤0.13), and in many cases model fit was actually reduced. Our data agrees with previous assertions that the assumption that indices provide more precise indicators of body condition than body mass alone is often invalid. We strongly discourage the use of unverified indices, because subjectively selecting indices likely does little to improve precision and might in fact decrease predictability relative to using body mass alone.

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.

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.

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.

The development of a probabilistic approach to forecast coastal change

USGS Publications Warehouse

Lentz, Erika E.; Hapke, Cheryl J.; Rosati, Julie D.; Wang, Ping; Roberts, Tiffany M.

2011-01-01

This study demonstrates the applicability of a Bayesian probabilistic model as an effective tool in predicting post-storm beach changes along sandy coastlines. Volume change and net shoreline movement are modeled for two study sites at Fire Island, New York in response to two extratropical storms in 2007 and 2009. Both study areas include modified areas adjacent to unmodified areas in morphologically different segments of coast. Predicted outcomes are evaluated against observed changes to test model accuracy and uncertainty along 163 cross-shore transects. Results show strong agreement in the cross validation of predictions vs. observations, with 70-82% accuracies reported. Although no consistent spatial pattern in inaccurate predictions could be determined, the highest prediction uncertainties appeared in locations that had been recently replenished. Further testing and model refinement are needed; however, these initial results show that Bayesian networks have the potential to serve as important decision-support tools in forecasting coastal change.

Prediction of risk of recurrence of venous thromboembolism following treatment for a first unprovoked venous thromboembolism: systematic review, prognostic model and clinical decision rule, and economic evaluation.

PubMed

Ensor, Joie; Riley, Richard D; Jowett, Sue; Monahan, Mark; Snell, Kym Ie; Bayliss, Susan; Moore, David; Fitzmaurice, David

2016-02-01

Unprovoked first venous thromboembolism (VTE) is defined as VTE in the absence of a temporary provoking factor such as surgery, immobility and other temporary factors. Recurrent VTE in unprovoked patients is highly prevalent, but easily preventable with oral anticoagulant (OAC) therapy. The unprovoked population is highly heterogeneous in terms of risk of recurrent VTE. The first aim of the project is to review existing prognostic models which stratify individuals by their recurrence risk, therefore potentially allowing tailored treatment strategies. The second aim is to enhance the existing research in this field, by developing and externally validating a new prognostic model for individual risk prediction, using a pooled database containing individual patient data (IPD) from several studies. The final aim is to assess the economic cost-effectiveness of the proposed prognostic model if it is used as a decision rule for resuming OAC therapy, compared with current standard treatment strategies. Standard systematic review methodology was used to identify relevant prognostic model development, validation and cost-effectiveness studies. Bibliographic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched using terms relating to the clinical area and prognosis. Reviewing was undertaken by two reviewers independently using pre-defined criteria. Included full-text articles were data extracted and quality assessed. Critical appraisal of included full texts was undertaken and comparisons made of model performance. A prognostic model was developed using IPD from the pooled database of seven trials. A novel internal-external cross-validation (IECV) approach was used to develop and validate a prognostic model, with external validation undertaken in each of the trials iteratively. Given good performance in the IECV approach, a final model was developed using all trials data. A Markov patient-level simulation was used to consider the economic cost-effectiveness of using a decision rule (based on the prognostic model) to decide on resumption of OAC therapy (or not). Three full-text articles were identified by the systematic review. Critical appraisal identified methodological and applicability issues; in particular, all three existing models did not have external validation. To address this, new prognostic models were sought with external validation. Two potential models were considered: one for use at cessation of therapy (pre D-dimer), and one for use after cessation of therapy (post D-dimer). Model performance measured in the external validation trials showed strong calibration performance for both models. The post D-dimer model performed substantially better in terms of discrimination (c = 0.69), better separating high- and low-risk patients. The economic evaluation identified that a decision rule based on the final post D-dimer model may be cost-effective for patients with predicted risk of recurrence of over 8% annually; this suggests continued therapy for patients with predicted risks ≥ 8% and cessation of therapy otherwise. The post D-dimer model performed strongly and could be useful to predict individuals' risk of recurrence at any time up to 2-3 years, thereby aiding patient counselling and treatment decisions. A decision rule using this model may be cost-effective for informing clinical judgement and patient opinion in treatment decisions. Further research may investigate new predictors to enhance model performance and aim to further externally validate to confirm performance in new, non-trial populations. Finally, it is essential that further research is conducted to develop a model predicting bleeding risk on therapy, to manage the balance between the risks of recurrence and bleeding. This study is registered as PROSPERO CRD42013003494. The National Institute for Health Research Health Technology Assessment programme.

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.

Relationship of patient characteristics and rehabilitation services to outcomes following spinal cord injury: The SCIRehab Project

PubMed Central

Whiteneck, Gale; Gassaway, Julie; Dijkers, Marcel P.; Heinemann, Allen W.; Kreider, Scott E. D.

2012-01-01

Background/objective To examine associations of patient characteristics along with treatment quantity delivered by seven clinical disciplines during inpatient spinal cord injury (SCI) rehabilitation with outcomes at rehabilitation discharge and 1-year post-injury. Methods Six inpatient SCI rehabilitation centers enrolled 1376 patients during the 5-year SCIRehab study. Clinicians delivering standard care documented details of treatment. Outcome data were derived from SCI Model Systems Form I and II and a project-specific interview conducted at approximately 1-year post-injury. Regression modeling was used to predict outcomes; models were cross-validated by examining relative shrinkage of the original model R2 using 75% of the dataset to the R2 for the same outcome using a validation subsample. Results Patient characteristics are strong predictors of outcome; treatment duration adds slightly more predictive power. More time in physical therapy was associated positively with motor Functional Independence Measure at discharge and the 1-year anniversary, CHART Physical Independence, Social Integration, and Mobility dimensions, and smaller likelihood of rehospitalization after discharge and reporting of pressure ulcer at the interview. More time in therapeutic recreation also had multiple similar positive associations. Time spent in other disciplines had fewer and mixed relationships. Seven models validated well, two validated moderately well, and four validated poorly. Conclusion Patient characteristics explain a large proportion of variation in multiple outcomes after inpatient rehabilitation. The total amount of treatment received during rehabilitation from each of seven disciplines explains little additional variance. Reasons for this and the phenomenon that sometimes more hours of service predict poorer outcome, need additional study. Note This is the first of nine articles in the SCIRehab series. PMID:23318033

Predicting active school travel: The role of planned behavior and habit strength

PubMed Central

2012-01-01

Background Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model’s predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children’s active school travel. Method Participants (N = 126 children aged 8–9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. Results The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. Conclusions The TPB significantly predicts children’s active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children’s intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these antecedents of children’s active school travel. PMID:22647194

HLA-DQA1 and PLA2R1 polymorphisms and risk of idiopathic membranous nephropathy.

PubMed

Bullich, Gemma; Ballarín, José; Oliver, Artur; Ayasreh, Nadia; Silva, Irene; Santín, Sheila; Díaz-Encarnación, Montserrat M; Torra, Roser; Ars, Elisabet

2014-02-01

Single nucleotide polymorphisms (SNPs) within HLA complex class II HLA-DQ α-chain 1 (HLA-DQA1) and M-type phospholipase A2 receptor (PLA2R1) genes were identified as strong risk factors for idiopathic membranous nephropathy (IMN) development in a recent genome-wide association study. Copy number variants (CNVs) within the Fc gamma receptor III (FCGR3) locus have been associated with several autoimmune diseases, but their role in IMN has not been studied. This study aimed to validate the association of HLA-DQA1 and PLA2R1 risk alleles with IMN in a Spanish cohort, test the putative association of FCGR3A and FCGR3B CNVs with IMN, and assess the use of these genetic factors to predict the clinical outcome of the disease. A Spanish cohort of 89 IMN patients and 286 matched controls without nephropathy was recruited between October of 2009 and July of 2012. Case-control studies for SNPs within HLA-DQA1 (rs2187668) and PLA2R1 (rs4664308) genes and CNVs for FCGR3A and FCGR3B genes were performed. The contribution of these polymorphisms to predict clinical outcome and renal function decline was analyzed. This study validated the association of these HLA-DQA1 and PLA2R1 SNPs with IMN in a Spanish cohort and its increased risk when combining both risk genotypes. No significant association was found between FCGR3 CNVs and IMN. These results revealed that HLA-DQA1 and PLA2R1 genotype combination adjusted for baseline proteinuria strongly predicted response to immunosuppressive therapy. HLA-DQA1 genotype adjusted for proteinuria was also linked with renal function decline. This study confirms that HLA-DQA1 and PLA2R1 genotypes are risk factors for IMN, whereas no association was identified for FCGR3 CNVs. This study provides, for the first time, evidence of the contribution of these HLA-DQA1 and PLA2R1 polymorphisms in predicting IMN response to immunosuppressors and disease progression. Future studies are needed to validate and identify prognostic markers.

Validating the energy transport modeling of the DIII-D and EAST ramp up experiments using TSC

NASA Astrophysics Data System (ADS)

Liu, Li; Guo, Yong; Chan, Vincent; Mao, Shifeng; Wang, Yifeng; Pan, Chengkang; Luo, Zhengping; Zhao, Hailin; Ye, Minyou

2017-06-01

The confidence in ramp up scenario design of the China fusion engineering test reactor (CFETR) can be significantly enhanced using validated transport models to predict the current profile and temperature profile. In the tokamak simulation code (TSC), two semi-empirical energy transport models (the Coppi-Tang (CT) and BGB model) and three theory-based models (the GLF23, MMM95 and CDBM model) are investigated on the CFETR relevant ramp up discharges, including three DIII-D ITER-like ramp up discharges and one EAST ohmic discharge. For the DIII-D discharges, all the transport models yield dynamic {{\\ell}\\text{i}} within +/- 0.15 deviations except for some time points where the experimental fluctuation is very strong. All the models agree with the experimental {β\\text{p}} except that the CT model strongly overestimates {β\\text{p}} in the first half of ramp up phase. When applying the CT, CDBM and GLF23 model to estimate the internal flux, they show maximum deviations of more than 10% because of inaccuracies in the temperature profile predictions, while the BGB model performs best on the internal flux. Although all the models fall short in reproducing the dynamic {{\\ell}\\text{i}} evolution for the EAST tokamak, the result of the BGB model is the closest to the experimental {{\\ell}\\text{i}} . Based on these comparisons, we conclude that the BGB model is the most consistent among these models for simulating CFETR ohmic ramp-up. The CT model with improvement for better simulation of the temperature profiles in the first half of ramp up phase will also be attractive. For the MMM95, GLF23 and CDBM model, better prediction of the edge temperature will improve the confidence for CFETR L-mode simulation. Conclusive validation of any transport model will require extensive future investigation covering a larger variety discharges.

Off-Design Performance of a Multi-Stage Supersonic Turbine

NASA Technical Reports Server (NTRS)

Dorney, Daniel J.; Griffin, Lisa W.; Huber, Frank; Sondak, Douglas L.

2003-01-01

The drive towards high-work turbines has led to designs which can be compact, transonic, supersonic, counter rotating, or use a dense drive gas. These aggressive designs can lead to strong unsteady secondary flows and flow separation. The amplitude and extent of these unsteady flow phenomena can be amplified at off-design operating conditions. Pre-test off-design predictions have been performed for a new two-stage supersonic turbine design that is currently being tested in air. The simulations were performed using a three-dimensional unsteady Navier-Stokes analysis, and the predicted results have been compared with solutions from a validated meanline analysis.

VLF Trimpi modelling on the path NWC-Dunedin using both finite element and 3D Born modelling

NASA Astrophysics Data System (ADS)

Nunn, D.; Hayakawa, K. B. M.

1998-10-01

This paper investigates the numerical modelling of VLF Trimpis, produced by a D region inhomogeneity on the great circle path. Two different codes are used to model Trimpis on the path NWC-Dunedin. The first is a 2D Finite Element Method Code (FEM), whose solutions are rigorous and valid in the strong scattering or non-Born limit. The second code is a 3D model that invokes the Born approximation. The predicted Trimpis from these codes compare very closely, thus confirming the validity of both models. The modal scattering matrices for both codes are analysed in some detail and are found to have a comparable structure. They indicate strong scattering between the dominant TM modes. Analysis of the scattering matrix from the FEM code shows that departure from linear Born behaviour occurs when the inhomogeneity has a horizontal scale size of about 100 km and a maximum electron density enhancement at 75 km altitude of about 6 electrons.

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

PubMed

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

2018-03-01

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

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.

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

Lafata, K; Ren, L; Wu, Q

Purpose: To develop a data-mining methodology based on quantum clustering and machine learning to predict expected dosimetric endpoints for lung SBRT applications based on patient-specific anatomic features. Methods: Ninety-three patients who received lung SBRT at our clinic from 2011–2013 were retrospectively identified. Planning information was acquired for each patient, from which various features were extracted using in-house semi-automatic software. Anatomic features included tumor-to-OAR distances, tumor location, total-lung-volume, GTV and ITV. Dosimetric endpoints were adopted from RTOG-0195 recommendations, and consisted of various OAR-specific partial-volume doses and maximum point-doses. First, PCA analysis and unsupervised quantum-clustering was used to explore the feature-space tomore » identify potentially strong classifiers. Secondly, a multi-class logistic regression algorithm was developed and trained to predict dose-volume endpoints based on patient-specific anatomic features. Classes were defined by discretizing the dose-volume data, and the feature-space was zero-mean normalized. Fitting parameters were determined by minimizing a regularized cost function, and optimization was performed via gradient descent. As a pilot study, the model was tested on two esophageal dosimetric planning endpoints (maximum point-dose, dose-to-5cc), and its generalizability was evaluated with leave-one-out cross-validation. Results: Quantum-Clustering demonstrated a strong separation of feature-space at 15Gy across the first-and-second Principle Components of the data when the dosimetric endpoints were retrospectively identified. Maximum point dose prediction to the esophagus demonstrated a cross-validation accuracy of 87%, and the maximum dose to 5cc demonstrated a respective value of 79%. The largest optimized weighting factor was placed on GTV-to-esophagus distance (a factor of 10 greater than the second largest weighting factor), indicating an intuitively strong correlation between this feature and both endpoints. Conclusion: This pilot study shows that it is feasible to predict dose-volume endpoints based on patient-specific anatomic features. The developed methodology can potentially help to identify patients at risk for higher OAR doses, thus improving the efficiency of treatment planning. R01-184173.« less

Computational Design and Discovery of Ni-Based Alloys and Coatings: Thermodynamic Approaches Validated by Experiments

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

Liu, Zi-Kui; Gleeson, Brian; Shang, Shunli

This project developed computational tools that can complement and support experimental efforts in order to enable discovery and more efficient development of Ni-base structural materials and coatings. The project goal was reached through an integrated computation-predictive and experimental-validation approach, including first-principles calculations, thermodynamic CALPHAD (CALculation of PHAse Diagram), and experimental investigations on compositions relevant to Ni-base superalloys and coatings in terms of oxide layer growth and microstructure stabilities. The developed description included composition ranges typical for coating alloys and, hence, allow for prediction of thermodynamic properties for these material systems. The calculation of phase compositions, phase fraction, and phase stabilities,more » which are directly related to properties such as ductility and strength, was a valuable contribution, along with the collection of computational tools that are required to meet the increasing demands for strong, ductile and environmentally-protective coatings. Specifically, a suitable thermodynamic description for the Ni-Al-Cr-Co-Si-Hf-Y system was developed for bulk alloy and coating compositions. Experiments were performed to validate and refine the thermodynamics from the CALPHAD modeling approach. Additionally, alloys produced using predictions from the current computational models were studied in terms of their oxidation performance. Finally, results obtained from experiments aided in the development of a thermodynamic modeling automation tool called ESPEI/pycalphad - for more rapid discovery and development of new materials.« less

Demonstration of successful malaria forecasts for Botswana using an operational seasonal climate model

NASA Astrophysics Data System (ADS)

MacLeod, Dave A.; Jones, Anne; Di Giuseppe, Francesca; Caminade, Cyril; Morse, Andrew P.

2015-04-01

The severity and timing of seasonal malaria epidemics is strongly linked with temperature and rainfall. Advance warning of meteorological conditions from seasonal climate models can therefore potentially anticipate unusually strong epidemic events, building resilience and adapting to possible changes in the frequency of such events. Here we present validation of a process-based, dynamic malaria model driven by hindcasts from a state-of-the-art seasonal climate model from the European Centre for Medium-Range Weather Forecasts. We validate the climate and malaria models against observed meteorological and incidence data for Botswana over the period 1982-2006 the longest record of observed incidence data which has been used to validate a modeling system of this kind. We consider the impact of climate model biases, the relationship between climate and epidemiological predictability and the potential for skillful malaria forecasts. Forecast skill is demonstrated for upper tercile malaria incidence for the Botswana malaria season (January-May), using forecasts issued at the start of November; the forecast system anticipates six out of the seven upper tercile malaria seasons in the observational period. The length of the validation time series gives confidence in the conclusion that it is possible to make reliable forecasts of seasonal malaria risk, forming a key part of a health early warning system for Botswana and contributing to efforts to adapt to climate change.

Strong water absorption in the dayside emission spectrum of the planet HD 189733b.

PubMed

Grillmair, Carl J; Burrows, Adam; Charbonneau, David; Armus, Lee; Stauffer, John; Meadows, Victoria; van Cleve, Jeffrey; von Braun, Kaspar; Levine, Deborah

2008-12-11

Recent observations of the extrasolar planet HD 189733b did not reveal the presence of water in the emission spectrum of the planet. Yet models of such 'hot-Jupiter' planets predict an abundance of atmospheric water vapour. Validating and constraining these models is crucial to understanding the physics and chemistry of planetary atmospheres in extreme environments. Indications of the presence of water in the atmosphere of HD 189733b have recently been found in transmission spectra, where the planet's atmosphere selectively absorbs the light of the parent star, and in broadband photometry. Here we report the detection of strong water absorption in a high-signal-to-noise, mid-infrared emission spectrum of the planet itself. We find both a strong downturn in the flux ratio below 10 microm and discrete spectral features that are characteristic of strong absorption by water vapour. The differences between these and previous observations are significant and admit the possibility that predicted planetary-scale dynamical weather structures may alter the emission spectrum over time. Models that match the observed spectrum and the broadband photometry suggest that heat redistribution from the dayside to the nightside is weak. Reconciling this with the high nightside temperature will require a better understanding of atmospheric circulation or possible additional energy sources.

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation

PubMed Central

Dhingra, Madhur S; Artois, Jean; Robinson, Timothy P; Linard, Catherine; Chaiban, Celia; Xenarios, Ioannis; Engler, Robin; Liechti, Robin; Kuznetsov, Dmitri; Xiao, Xiangming; Dobschuetz, Sophie Von; Claes, Filip; Newman, Scott H; Dauphin, Gwenaëlle; Gilbert, Marius

2016-01-01

Global disease suitability models are essential tools to inform surveillance systems and enable early detection. We present the first global suitability model of highly pathogenic avian influenza (HPAI) H5N1 and demonstrate that reliable predictions can be obtained at global scale. Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. Our results also support a more systematic use of spatial cross-validation in large-scale disease suitability modelling compared to standard random cross-validation that can lead to unreliable measure of extrapolation accuracy. A global suitability model of the H5 clade 2.3.4.4 viruses, a group of viruses that recently spread extensively in Asia and the US, shows in comparison a lower spatial extrapolation capacity than the HPAI H5N1 models, with a stronger association with intensively raised chicken densities and anthropogenic factors. DOI: http://dx.doi.org/10.7554/eLife.19571.001 PMID:27885988

Lung Cancer Risk Prediction Model Incorporating Lung Function: Development and Validation in the UK Biobank Prospective Cohort Study.

PubMed

Muller, David C; Johansson, Mattias; Brennan, Paul

2017-03-10

Purpose Several lung cancer risk prediction models have been developed, but none to date have assessed the predictive ability of lung function in a population-based cohort. We sought to develop and internally validate a model incorporating lung function using data from the UK Biobank prospective cohort study. Methods This analysis included 502,321 participants without a previous diagnosis of lung cancer, predominantly between 40 and 70 years of age. We used flexible parametric survival models to estimate the 2-year probability of lung cancer, accounting for the competing risk of death. Models included predictors previously shown to be associated with lung cancer risk, including sex, variables related to smoking history and nicotine addiction, medical history, family history of lung cancer, and lung function (forced expiratory volume in 1 second [FEV1]). Results During accumulated follow-up of 1,469,518 person-years, there were 738 lung cancer diagnoses. A model incorporating all predictors had excellent discrimination (concordance (c)-statistic [95% CI] = 0.85 [0.82 to 0.87]). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected c-statistic = 0.84). The full model, including FEV1, also had modestly superior discriminatory power than one that was designed solely on the basis of questionnaire variables (c-statistic = 0.84 [0.82 to 0.86]; optimism-corrected c-statistic = 0.83; p FEV1 = 3.4 × 10 -13 ). The full model had better discrimination than standard lung cancer screening eligibility criteria (c-statistic = 0.66 [0.64 to 0.69]). Conclusion A risk prediction model that includes lung function has strong predictive ability, which could improve eligibility criteria for lung cancer screening programs.

Prediction methods of spudcan penetration for jack-up units

NASA Astrophysics Data System (ADS)

Zhang, Ai-xia; Duan, Meng-lan; Li, Hai-ming; Zhao, Jun; Wang, Jian-jun

2012-12-01

Jack-up units are extensively playing a successful role in drilling engineering around the world, and their safety and efficiency take more and more attraction in both research and engineering practice. An accurate prediction of the spudcan penetration depth is quite instrumental in deciding on whether a jack-up unit is feasible to operate at the site. The prediction of a too large penetration depth may lead to the hesitation or even rejection of a site due to potential difficulties in the subsequent extraction process; the same is true of a too small depth prediction due to the problem of possible instability during operation. However, a deviation between predictive results and final field data usually exists, especially when a strong-over-soft soil is included in the strata. The ultimate decision sometimes to a great extent depends on the practical experience, not the predictive results given by the guideline. It is somewhat risky, but no choice. Therefore, a feasible predictive method for the spudcan penetration depth, especially in strata with strong-over-soft soil profile, is urgently needed by the jack-up industry. In view of this, a comprehensive investigation on methods of predicting spudcan penetration is executed. For types of different soil profiles, predictive methods for spudcan penetration depth are proposed, and the corresponding experiment is also conducted to validate these methods. In addition, to further verify the feasibility of the proposed methods, a practical engineering case encountered in the South China Sea is also presented, and the corresponding numerical and experimental results are also presented and discussed.

Prediction and validation of concentration gradient generation in a paper-based microfluidic channel

NASA Astrophysics Data System (ADS)

Jang, Ilhoon; Kim, Gang-June; Song, Simon

2016-11-01

A paper-based microfluidic channel has obtained attention as a diagnosis device that can implement various chemical or biological reactions. With benefits of thin, flexible, and strong features of paper devices, for example, it is often utilized for cell culture where controlling oxygen, nutrients, metabolism, and signaling molecules gradient affects the growth and movement of the cells. Among various features of paper-based microfluidic devices, we focus on establishment of concentration gradient in a paper channel. The flow is subject to dispersion and capillary effects because a paper is a porous media. In this presentation, we describe facile, fast and accurate method of generating a concentration gradient by using flow mixing of different concentrations. Both theoretical prediction and experimental validation are discussed along with inter-diffusion characteristics of porous flows. This work was supported by the National Research Foundation of Korea(NRF) Grant funded by the Korea government(MSIP) (No. 2016R1A2B3009541).

Atomistic mechanisms underlying selectivities in C 1 and C 2 products from electrochemical reduction of CO on Cu(111)

DOE PAGES

Xiao, Hai; Cheng, Tao; Goddard, III, William A.

2016-12-07

Practical environmental and energy applications of the electrochemical reduction of CO 2 to chemicals and fuels require far more efficient and selective electrocatalysts beyond the only working material Cu, but the wealth of experimental data on Cu can serve to validate any proposed mechanisms. To provide design guidelines, we use quantum mechanics to predict the detailed atomistic mechanisms responsible for C 1 and C 2 products on Cu. Thus, we report the pH dependent routes to the major products, methane and ethylene, and identify the key intermediates where branches to methanol, ketene, ethanol, acetylene, and ethane are kinetically blocked. Furthermore,more » we discovered that surface water on Cu plays a key role in the selectivity for hydrocarbon products over the oxygen-containing alcohol products by serving as a strong proton donor for electrochemical dehydration reductions. We suggest new experiments to validate our predicted mechanisms.« less

Stable isotopes of fossil teeth corroborate key general circulation model predictions for the Last Glacial Maximum in North America

NASA Astrophysics Data System (ADS)

Kohn, Matthew J.; McKay, Moriah

2010-11-01

Oxygen isotope data provide a key test of general circulation models (GCMs) for the Last Glacial Maximum (LGM) in North America, which have otherwise proved difficult to validate. High δ18O pedogenic carbonates in central Wyoming have been interpreted to indicate increased summer precipitation sourced from the Gulf of Mexico. Here we show that tooth enamel δ18O of large mammals, which is strongly correlated with local water and precipitation δ18O, is lower during the LGM in Wyoming, not higher. Similar data from Texas, California, Florida and Arizona indicate higher δ18O values than in the Holocene, which is also predicted by GCMs. Tooth enamel data closely validate some recent models of atmospheric circulation and precipitation δ18O, including an increase in the proportion of winter precipitation for central North America, and summer precipitation in the southern US, but suggest aridity can bias pedogenic carbonate δ18O values significantly.

Predicting the need for institutional care shortly after admission to rehabilitation: Rasch analysis and predictive validity of the BRASS Index.

PubMed

Panella, L; La Porta, F; Caselli, S; Marchisio, S; Tennant, A

2012-09-01

Effective discharge planning is increasingly recognised as a critical component of hospital-based Rehabilitation. The BRASS index is a risk screening tool for identification, shortly after hospital admission, of patients who are at risk of post-discharge problems. To evaluate the internal construct validity and reliability of the Blaylock Risk Assessment Screening Score (BRASS) within the rehabilitation setting. Observational prospective study. Rehabilitation ward of an Italian district hospital. One hundred and four consecutively admitted patients. Using classical psychometric methods and Rasch analysis (RA), the internal construct validity and reliability of the BRASS were examined. Also, external and predictive validity of the Rasch-modified BRASS (RMB) score were determined. Reliability of the original BRASS was low (Cronbach's alpha=0.595) and factor analyses showed that it was clearly multidimensional. A RA, based on a reduced 7-BRASS item set (RMB), satisfied model's expectations. Reliability was 0.777. The RMB scores strongly correlated with the original BRASS (rho=0.952; P<0.000) and with FIM™ admission scores (rho=-0.853; P<0.000). A RMB score of 12 was associated with an increased risk of nursing home admission (RR=2.1, 95%CI=1.7-2.5), whereas a score of 17 was associated to a higher risk of length of stay >28 days (RR=7.6, 95%CI=1.8-31.9). This study demonstrated that the original BRASS was multidimensional and unreliable. However, the RMB holds adequate internal construct validity and is sufficiently reliable as a predictor of discharge problems for group, but not individual use. The application of tools and methods (such as the BRASS Index) developed under the biomedical paradigm in a Physical and Rehabilitation Medicine setting may have limitations. Further research is needed to develop, within the rehabilitation setting, a valid measuring tool of risk of post-discharge problems at the individual level.

Development of the design concepts for a medium-scale wind tunnel magnetic suspension system

NASA Technical Reports Server (NTRS)

Humphris, R. R.; Zapata, R. N.

1982-01-01

The magnitude of AC losses from a superconducting coil strongly indicates that the predicted scaling lawa are valid. The stainless steel bands around the test coil were the source of additional helium boiloff due to a transformer action and, hence, caused erroneously high AC loss measurements in the first run. However, removal of these bands for the second run produced data which are consistent with previous results on small scale multifilamentary superconducting coils.

A Novel Animal Model for Panic Disorder: Attempted Reproduction of the Fear of Fear

DTIC Science & Technology

1999-11-04

and haloperidol . Buspirone, ipsapirone, flesi noxin, and 8- O H-DPAT (aI1 5HT IA agoni sts) strongly reduced USV in treated animals. T he 5HT 1A...Robinson & Shrol, 1989). Alprazolam (an effective anti-panic agent) and haloperidol (3 dopamine antagonist), produced similar profiles. Both drugs...identical to a drug serving as a negative control ( haloperidol ) suggests this model has poor predictive validity. Furthermore, the benzodiazepine

Understanding the nucleon as a Borromean bound-state

DOE PAGES

Segovia, Jorge; Roberts, Craig D.; Schmidt, Sebastian M.

2015-08-20

Analyses of the three valence-quark bound-state problem in relativistic quantum field theory predict that the nucleon may be understood primarily as a Borromean bound-state, in which binding arises mainly from two separate effects. One originates in non-Abelian facets of QCD that are expressed in the strong running coupling and generate confined but strongly-correlated colourantitriplet diquark clusters in both the scalar-isoscalar and pseudovector-isotriplet channels. That attraction is magnified by quark exchange associated with diquark breakup and reformation. Diquark clustering is driven by the same mechanism which dynamically breaks chiral symmetry in the Standard Model. It has numerous observable consequences, the completemore » elucidation of which requires a framework that also simultaneously expresses the running of the coupling and masses in the strong interaction. Moreover, planned experiments are capable of validating this picture.« less

The Crucial Role of Error Correlation for Uncertainty Modeling of CFD-Based Aerodynamics Increments

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Walker, Eric L.

2011-01-01

The Ares I ascent aerodynamics database for Design Cycle 3 (DAC-3) was built from wind-tunnel test results and CFD solutions. The wind tunnel results were used to build the baseline response surfaces for wind-tunnel Reynolds numbers at power-off conditions. The CFD solutions were used to build increments to account for Reynolds number effects. We calculate the validation errors for the primary CFD code results at wind tunnel Reynolds number power-off conditions and would like to be able to use those errors to predict the validation errors for the CFD increments. However, the validation errors are large compared to the increments. We suggest a way forward that is consistent with common practice in wind tunnel testing which is to assume that systematic errors in the measurement process and/or the environment will subtract out when increments are calculated, thus making increments more reliable with smaller uncertainty than absolute values of the aerodynamic coefficients. A similar practice has arisen for the use of CFD to generate aerodynamic database increments. The basis of this practice is the assumption of strong correlation of the systematic errors inherent in each of the results used to generate an increment. The assumption of strong correlation is the inferential link between the observed validation uncertainties at wind-tunnel Reynolds numbers and the uncertainties to be predicted for flight. In this paper, we suggest a way to estimate the correlation coefficient and demonstrate the approach using code-to-code differences that were obtained for quality control purposes during the Ares I CFD campaign. Finally, since we can expect the increments to be relatively small compared to the baseline response surface and to be typically of the order of the baseline uncertainty, we find that it is necessary to be able to show that the correlation coefficients are close to unity to avoid overinflating the overall database uncertainty with the addition of the increments.

Prediction of Maximal Oxygen Uptake by Six-Minute Walk Test and Body Mass Index in Healthy Boys.

PubMed

Jalili, Majid; Nazem, Farzad; Sazvar, Akbar; Ranjbar, Kamal

2018-05-14

To develop an equation to predict maximal oxygen uptake (VO2max) based on the 6-minute walk test (6MWT) and body composition in healthy boys. Direct VO2max, 6-minute walk distance, and anthropometric characteristics were measured in 349 healthy boys (12.49 ± 2.72 years). Multiple regression analysis was used to generate VO2max prediction equations. Cross-validation of the VO2max prediction equations was assessed with predicted residual sum of squares statistics. Pearson correlation was used to assess the correlation between measured and predicted VO2max. Objectively measured VO2max had a significant correlation with demographic and 6MWT characteristics (R = 0.11-0.723, P < .01). Multiple regression analysis revealed the following VO2max prediction equation: VO2max (mL/kg/min) = 12.701 + (0.06 × 6-minute walk distance m ) - (0.732 × body mass index kg/m2 ) (R 2 = 0.79, standard error of the estimate [SEE] = 2.91 mL/kg/min, %SEE = 6.9%). There was strong correlation between measured and predicted VO2max (r = 0.875, P < .001). Cross-validation revealed minimal shrinkage (R 2 p = 0.78 and predicted residual sum of squares SEE = 2.99 mL/kg/min). This study provides a relatively accurate and convenient VO2max prediction equation based on the 6MWT and body mass index in healthy boys. This model can be used for evaluation of cardiorespiratory fitness of boys in different settings. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Nonlinear Brillouin amplification of finite-duration seeds in the strong coupling regime

NASA Astrophysics Data System (ADS)

Lehmann, G.; Spatschek, K. H.

2013-07-01

Parametric plasma processes received renewed interest in the context of generating ultra-intense and ultra-short laser pulses up to the exawatt-zetawatt regime. Both Raman as well as Brillouin amplifications of seed pulses were proposed. Here, we investigate Brillouin processes in the one-dimensional (1D) backscattering geometry with the help of numerical simulations. For optimal seed amplification, Brillouin scattering is considered in the so called strong coupling (sc) regime. Special emphasis lies on the dependence of the amplification process on the finite duration of the initial seed pulses. First, the standard plane-wave instability predictions are generalized to pulse models, and the changes of initial seed pulse forms due to parametric instabilities are investigated. Three-wave-interaction results are compared to predictions by a new (kinetic) Vlasov code. The calculations are then extended to the nonlinear region with pump depletion. Generation of different seed layers is interpreted by self-similar solutions of the three-wave interaction model. Similar to Raman amplification, shadowing of the rear layers by the leading layers of the seed occurs. The shadowing is more pronounced for initially broad seed pulses. The effect is quantified for Brillouin amplification. Kinetic Vlasov simulations agree with the three-wave interaction predictions and thereby affirm the universal validity of self-similar layer formation during Brillouin seed amplification in the strong coupling regime.

Mammographic density, breast cancer risk and risk prediction

PubMed Central

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

2007-01-01

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

Why does self-reported emotional intelligence predict job performance? A meta-analytic investigation of mixed EI.

PubMed

Joseph, Dana L; Jin, Jing; Newman, Daniel A; O'Boyle, Ernest H

2015-03-01

Recent empirical reviews have claimed a surprisingly strong relationship between job performance and self-reported emotional intelligence (also commonly called trait EI or mixed EI), suggesting self-reported/mixed EI is one of the best known predictors of job performance (e.g., ρ = .47; Joseph & Newman, 2010b). Results further suggest mixed EI can robustly predict job performance beyond cognitive ability and Big Five personality traits (Joseph & Newman, 2010b; O'Boyle, Humphrey, Pollack, Hawver, & Story, 2011). These criterion-related validity results are problematic, given the paucity of evidence and the questionable construct validity of mixed EI measures themselves. In the current research, we update and reevaluate existing evidence for mixed EI, in light of prior work regarding the content of mixed EI measures. Results of the current meta-analysis demonstrate that (a) the content of mixed EI measures strongly overlaps with a set of well-known psychological constructs (i.e., ability EI, self-efficacy, and self-rated performance, in addition to Conscientiousness, Emotional Stability, Extraversion, and general mental ability; multiple R = .79), (b) an updated estimate of the meta-analytic correlation between mixed EI and supervisor-rated job performance is ρ = .29, and (c) the mixed EI-job performance relationship becomes nil (β = -.02) after controlling for the set of covariates listed above. Findings help to establish the construct validity of mixed EI measures and further support an intuitive theoretical explanation for the uncommonly high association between mixed EI and job performance--mixed EI instruments assess a combination of ability EI and self-perceptions, in addition to personality and cognitive ability. PsycINFO Database Record (c) 2015 APA, all rights reserved.

A Random Forest Approach to Predict the Spatial Distribution ...

EPA Pesticide Factsheets

Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment contamination from the sub-estuary to broader estuary extent. For this study, a Random Forest (RF) model was implemented to predict the distribution of a model contaminant, triclosan (5-chloro-2-(2,4-dichlorophenoxy)phenol) (TCS), in Narragansett Bay, Rhode Island, USA. TCS is an unregulated contaminant used in many personal care products. The RF explanatory variables were associated with TCS transport and fate (proxies) and direct and indirect environmental entry. The continuous RF TCS concentration predictions were discretized into three levels of contamination (low, medium, and high) for three different quantile thresholds. The RF model explained 63% of the variance with a minimum number of variables. Total organic carbon (TOC) (transport and fate proxy) was a strong predictor of TCS contamination causing a mean squared error increase of 59% when compared to permutations of randomized values of TOC. Additionally, combined sewer overflow discharge (environmental entry) and sand (transport and fate proxy) were strong predictors. The discretization models identified a TCS area of greatest concern in the northern reach of Narragansett Bay (Providence River sub-estuary), which was validated wi

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.

PubMed

Ding, H; Chen, C; Zhang, X

2016-01-01

The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r(2) (r(2)adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q(2) ([Formula: see text]) was 0.79, suggesting the robustness of the model was satisfactory. The external Q(2) ([Formula: see text]) and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model's strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.

Nanoscale Imaging of Light-Matter Coupling Inside Metal-Coated Cavities with a Pulsed Electron Beam.

PubMed

Moerland, Robert J; Weppelman, I Gerward C; Scotuzzi, Marijke; Hoogenboom, Jacob P

2018-05-02

Many applications in (quantum) nanophotonics rely on controlling light-matter interaction through strong, nanoscale modification of the local density of states (LDOS). All-optical techniques probing emission dynamics in active media are commonly used to measure the LDOS and benchmark experimental performance against theoretical predictions. However, metal coatings needed to obtain strong LDOS modifications in, for instance, nanocavities, are incompatible with all-optical characterization. So far, no reliable method exists to validate theoretical predictions. Here, we use subnanosecond pulses of focused electrons to penetrate the metal and excite a buried active medium at precisely defined locations inside subwavelength resonant nanocavities. We reveal the spatial layout of the spontaneous-emission decay dynamics inside the cavities with deep-subwavelength detail, directly mapping the LDOS. We show that emission enhancement converts to inhibition despite an increased number of modes, emphasizing the critical role of optimal emitter location. Our approach yields fundamental insight in dynamics at deep-subwavelength scales for a wide range of nano-optical systems.

Using Magnetic Fields to Control Convection during Protein Crystallization: Analysis and Validation Studies

NASA Technical Reports Server (NTRS)

Ramachandran, N.; Leslie, F. W.

2004-01-01

The effect of convection during the crystallization of proteins is not very well understood. In a gravitational field, convection is caused by crystal sedimentation and by solutal buoyancy induced flow and these can lead to crystal imperfections. While crystallization in microgravity can approach diffusion limited growth conditions (no convection), terrestrially strong magnetic fields can be used to control fluid flow and sedimentation effects. In this work, we develop the analysis for magnetic flow control and test the predictions using analog experiments. Specifically, experiments on solutal convection in a paramagnetic fluid were conducted in a strong magnetic field gradient using a dilute solution of Manganese Chloride. The observed flows indicate that the magnetic field can completely counter the settling effects of gravity locally and are consistent with the theoretical predictions presented. This phenomenon suggests that magnetic fields may be useful in mimicking the microgravity environment of space for some crystal growth ana biological applications where fluid convection is undesirable.

DEVELOPMENT AND VALIDATION OF A MULTIFIELD MODEL OF CHURN-TURBULENT GAS/LIQUID FLOWS

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

Elena A. Tselishcheva; Steven P. Antal; Michael Z. Podowski

The accuracy of numerical predictions for gas/liquid two-phase flows using Computational Multiphase Fluid Dynamics (CMFD) methods strongly depends on the formulation of models governing the interaction between the continuous liquid field and bubbles of different sizes. The purpose of this paper is to develop, test and validate a multifield model of adiabatic gas/liquid flows at intermediate gas concentrations (e.g., churn-turbulent flow regime), in which multiple-size bubbles are divided into a specified number of groups, each representing a prescribed range of sizes. The proposed modeling concept uses transport equations for the continuous liquid field and for each bubble field. The overallmore » model has been implemented in the NPHASE-CMFD computer code. The results of NPHASE-CMFD simulations have been validated against the experimental data from the TOPFLOW test facility. Also, a parametric analysis on the effect of various modeling assumptions has been performed.« less

Evaluation of magical thinking: validation of the Illusory Beliefs Inventory.

PubMed

Shihata, Sarah; Egan, Sarah J; Rees, Clare S

2014-01-01

Magical thinking has been related to obsessive-compulsive disorder; yet, little research has examined this construct in other anxiety disorders. The Illusory Beliefs Inventory (IBI) is a recently developed measure of magical thinking. The aim of this study was to investigate the psychometric properties of this new measure and to determine if magical thinking accounts for pathological worry beyond the well-researched constructs of intolerance of uncertainty (IU) and perfectionism. A sample of 502 participants completed an online survey. Confirmatory factor analysis identified a three-factor solution for the IBI, and the measure had good internal consistency (α = .92), test-retest reliability (r = .94) and discriminant validity. Magical thinking, IU, and perfectionism all predicted pathological worry; however, magical thinking accounted for less than 1% of unique variance in worry, suggesting that it is not strongly related to worry. Further investigation regarding the validity and clinical utility of the IBI is required.

Analysis and prediction of Doppler noise during solar conjunctions

NASA Technical Reports Server (NTRS)

Berman, A. L.; Rockwell, S. T.

1975-01-01

The results of a study of Doppler data noise during solar conjunctions were presented. During the first half of 1975, a sizeable data base of Doppler data noise (estimates) for the Pioneer 10, Pioneer 11, and Helios 1 solar conjunctions was accumulated. To analyze this data, certain physical assumptions are made, leading to the development of a geometric parameter ("ISI") which correlates strongly with Doppler data noise under varying sun-earth-spacecraft geometries. Doppler noise models are then constructed from this parameter, resulting in the newfound ability to predict Doppler data noise during solar conjunctions, and hence to additionally be in a position to validate Doppler data acquired during solar conjunctions.

Assessment of Mars Exploration Rover Landing Site Predictions

NASA Technical Reports Server (NTRS)

Golombek, M. P.; Arvidson, R. E.; Bell, J. F., III; Christensen, P. R.; Crisp, J. A.; Ehlmann, B. L.; Fergason, R. L.; Grant, J. A.; Haldemann, A. F. C.; Parker, T. J.;

Numerical Modelling of Femur Fracture and Experimental Validation Using Bone Simulant.

PubMed

Marco, Miguel; Giner, Eugenio; Larraínzar-Garijo, Ricardo; Caeiro, José Ramón; Miguélez, María Henar

2017-10-01

Bone fracture pattern prediction is still a challenge and an active field of research. The main goal of this article is to present a combined methodology (experimental and numerical) for femur fracture onset analysis. Experimental work includes the characterization of the mechanical properties and fracture testing on a bone simulant. The numerical work focuses on the development of a model whose material properties are provided by the characterization tests. The fracture location and the early stages of the crack propagation are modelled using the extended finite element method and the model is validated by fracture tests developed in the experimental work. It is shown that the accuracy of the numerical results strongly depends on a proper bone behaviour characterization.

Psychometric properties of the Brunel Mood Scale in Chinese adolescents and adults.

PubMed

Zhang, Chun-Qing; Si, Gangyan; Chung, Pak-Kwong; Du, Mengmeng; Terry, Peter C

2014-01-01

Building on the work of Terry and colleagues (Terry, P. C., Lane, A. M., Lane, H. J., & Keohane, L. (1999). Development and validation of a mood measure for adolescents. Journal of Sports Sciences, 17, 861-872; Terry, P. C., Lane, A. M., & Fogarty, G. J. (2003). Construct validity of the Profile of Mood States-Adolescents for use with adults. Psychology of Sport & Exercise, 4, 125-139.), the present study examined the validity and internal consistency reliability of the Chinese version of the Brunel Mood Scale (BRUMS-C) among 2,548 participants, comprising adolescent athletes (n = 520), adult athletes (n = 434), adolescent students (n = 673), and adult students (n = 921). Both adolescent and adult athletes completed the BRUMS-C before, during, or after regular training and both adolescent and adult students completed the BRUMS-C in a classroom setting. Confirmatory factor analyses (CFAs) provided support for the factorial validity of a 23-item six-factor model, with one item removed from the hypothesised measurement model. Internal consistency reliabilities were satisfactory for all subscales across each of the four samples. Criterion validity was supported with strong relationships between the BRUMS-C, abbreviated POMS, and Chinese Affect Scale consistent with theoretical predictions. Multi-sample CFAs showed the BRUMS-C to be invariant at the configural, metric, strong, and structural levels for all samples. Furthermore, latent mean difference analyses showed that athletes reported significantly higher levels of fatigue than students while maintaining almost the same levels of vigour, and adolescent students reported significantly higher levels of depressed mood than the other three samples.

Objective estimation of patient age through a new composite scale for facial aging assessment: The face - Objective assessment scale.

PubMed

La Padula, Simone; Hersant, Barbara; SidAhmed, Mounia; Niddam, Jeremy; Meningaud, Jean Paul

2016-07-01

Most patients requesting aesthetic rejuvenation treatment expect to look healthier and younger. Some scales for ageing assessment have been proposed, but none is focused on patient age prediction. The aim of this study was to develop and validate a new facial rating scale assessing facial ageing sign severity. One thousand Caucasian patients were included and assessed. The Rasch model was used as part of the validation process. A score was attributed to each patient, based on the scales we developed. The correlation between the real age and scores obtained, the inter-rater reliability and test-retest reliability were analysed. The objective was to develop a tool enabling the assigning of a patient to a specific age range based on the calculated score. All scales exceeded criteria for acceptability, reliability and validity. The real age strongly correlated with the total facial score in both sex groups. The test-retest reliability confirmed this strong correlation. We developed a facial ageing scale which could be a useful tool to assess patients before and after rejuvenation treatment and an important new metrics to be used in facial rejuvenation and regenerative clinical research. Copyright © 2016 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

The effects of majority versus minority source status on persuasion: a self-validation analysis.

PubMed

Horcajo, Javier; Petty, Richard E; Briñol, Pablo

2010-09-01

The present research proposes that sources in the numerical majority (vs. minority) can affect persuasion by influencing the confidence with which people hold their thoughts in response to the persuasive message. Participants received a persuasive message composed of either strong or weak arguments that was presented by a majority or a minority source. Consistent with the self-validation hypothesis, we predicted and found that the majority (vs. minority) status of the source increased the confidence with which recipients held their thoughts. As a consequence, majority (vs. minority) sources increased argument quality effects in persuasion when source status information followed message processing (Experiment 1). In contrast, when the information regarding source status preceded (rather than followed) the persuasive message, it validated the perception of the position advocated, reducing message processing. As a consequence of having more confidence in the position advocated before receiving the message, majority (vs. minority) sources reduced argument quality effects in persuasion (Experiment 2). Finally, Experiment 3 isolated the timing of the source status manipulation, revealing that sources in the numerical majority (vs. minority) can increase or decrease persuasion to strong arguments depending on whether source status is introduced before or after processing the message. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

The Usability of Noise Level from Rock Cutting for the Prediction of Physico-Mechanical Properties of Rocks

NASA Astrophysics Data System (ADS)

Delibalta, M. S.; Kahraman, S.; Comakli, R.

2015-11-01

Because the indirect tests are easier and cheaper than the direct tests, the prediction of rock properties from the indirect testing methods is important especially for the preliminary investigations. In this study, the predictability of the physico-mechanical rock properties from the noise level measured during cutting rock with diamond saw was investigated. Noise measurement test, uniaxial compressive strength (UCS) test, Brazilian tensile strength (BTS) test, point load strength (Is) test, density test, and porosity test were carried out on 54 different rock types in the laboratory. The results were statistically analyzed to derive estimation equations. Strong correlations between the noise level and the mechanical rock properties were found. The relations follow power functions. Increasing rock strength increases the noise level. Density and porosity also correlated strongly with the noise level. The relations follow linear functions. Increasing density increases the noise level while increasing porosity decreases the noise level. The developed equations are valid for the rocks with a compressive strength below 150 MPa. Concluding remark is that the physico-mechanical rock properties can reliably be estimated from the noise level measured during cutting the rock with diamond saw.

A comparison of the psychometric properties of the psychopathic personality inventory full-length and short-form versions.

PubMed

Kastner, Rebecca M; Sellbom, Martin; Lilienfeld, Scott O

2012-03-01

The Psychopathic Personality Inventory (PPI) has shown promising construct validity as a measure of psychopathy. Because of its relative efficiency, a short-form version of the PPI (PPI-SF) was developed and has proven useful in many psychopathy studies. The validity of the PPI-SF, however, has not been thoroughly examined, and no studies have directly compared the validity of the short form with that of the full-length version. The current study was designed to compare the psychometric properties of both PPI versions, with an emphasis on convergent and discriminant validity in predicting external criteria conceptually relevant to psychopathy. We used both prison (n = 558) and college samples (n = 322) for this investigation. PPI scale scores were more reliable and more strongly correlated with the conceptually relevant criterion measures compared with the PPI-SF, particularly in the prison sample. There were no differences in relative discriminant validity. Thus, overall, the PPI full-length version showed more evidence of construct validity than did the short form, and the consequences of this psychometric difference should be considered when evaluating the clinical utility of each measure.

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study.

PubMed

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank; Sylvester, Karl G; Widen, Eric; Ling, Xuefeng

2015-09-22

The increasing rate of health care expenditures in the United States has placed a significant burden on the nation's economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. In the HealthInfoNet, Maine's health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient's next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree-based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes.

Online Prediction of Health Care Utilization in the Next Six Months Based on Electronic Health Record Information: A Cohort and Validation Study

PubMed Central

Hu, Zhongkai; Hao, Shiying; Jin, Bo; Shin, Andrew Young; Zhu, Chunqing; Huang, Min; Wang, Yue; Zheng, Le; Dai, Dorothy; Culver, Devore S; Alfreds, Shaun T; Rogow, Todd; Stearns, Frank

2015-01-01

Background The increasing rate of health care expenditures in the United States has placed a significant burden on the nation’s economy. Predicting future health care utilization of patients can provide useful information to better understand and manage overall health care deliveries and clinical resource allocation. Objective This study developed an electronic medical record (EMR)-based online risk model predictive of resource utilization for patients in Maine in the next 6 months across all payers, all diseases, and all demographic groups. Methods In the HealthInfoNet, Maine’s health information exchange (HIE), a retrospective cohort of 1,273,114 patients was constructed with the preceding 12-month EMR. Each patient’s next 6-month (between January 1, 2013 and June 30, 2013) health care resource utilization was retrospectively scored ranging from 0 to 100 and a decision tree–based predictive model was developed. Our model was later integrated in the Maine HIE population exploration system to allow a prospective validation analysis of 1,358,153 patients by forecasting their next 6-month risk of resource utilization between July 1, 2013 and December 31, 2013. Results Prospectively predicted risks, on either an individual level or a population (per 1000 patients) level, were consistent with the next 6-month resource utilization distributions and the clinical patterns at the population level. Results demonstrated the strong correlation between its care resource utilization and our risk scores, supporting the effectiveness of our model. With the online population risk monitoring enterprise dashboards, the effectiveness of the predictive algorithm has been validated by clinicians and caregivers in the State of Maine. Conclusions The model and associated online applications were designed for tracking the evolving nature of total population risk, in a longitudinal manner, for health care resource utilization. It will enable more effective care management strategies driving improved patient outcomes. PMID:26395541

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.

Spectrometric Estimation of Total Nitrogen Concentration in Douglas-Fir Foliage

NASA Technical Reports Server (NTRS)

Johnson, Lee F.; Billow, Christine R.; Peterson, David L. (Technical Monitor)

1995-01-01

Spectral measurements of fresh and dehydrated Douglas-fir foliage, from trees cultivated under three fertilization treatments, were acquired with a laboratory spectrophotometer. The slope (first-derivative) of the fresh- and dry-leaf absorbance spectra at locations near known protein absorption features was strongly correlated with total nitrogen (TN) concentration of the foliage samples. Particularly strong correlation was observed between the first-derivative spectra in the 2150-2170 nm region and TN, reaching a local maximum in the fresh-leaf spectra of -0.84 at 2 160 nm. Stepwise regression was used to generate calibration equations relating first derivative spectra from fresh, dry/intact, and dry/ground samples to TN concentration. Standard errors of calibration were 1.52 mg g-1 (fresh), 1.33 (dry/intact), and 1.20 (dry/ground), with goodness-of-fit 0.94 and greater. Cross-validation was performed with the fresh-leaf dataset to examine the predictive capability of the regression method; standard errors of prediction ranged from 1.47 - 2.37 mg g(exp -1) across seven different validation sets, prediction goodness of fit ranged from .85-.94, and wavelength selection was fairly insensitive to the membership of the calibration set. All regressions in this study tended to select wavelengths in the 2100-2350 nm region, with the primary selection in the 2142-2172 nm region. The study provides positive evidence concerning the feasibility of assessing TN status of fresh-leaf samples by spectrometric means. We assert that the ability to extract biochemical information from fresh-leaf spectra is a necessary but insufficient condition regarding the use of remote sensing for canopy-level biochemical estimation.

RandomForest4Life: a Random Forest for predicting ALS disease progression.

PubMed

Hothorn, Torsten; Jung, Hans H

2014-09-01

We describe a method for predicting disease progression in amyotrophic lateral sclerosis (ALS) patients. The method was developed as a submission to the DREAM Phil Bowen ALS Prediction Prize4Life Challenge of summer 2012. Based on repeated patient examinations over a three- month period, we used a random forest algorithm to predict future disease progression. The procedure was set up and internally evaluated using data from 1197 ALS patients. External validation by an expert jury was based on undisclosed information of an additional 625 patients; all patient data were obtained from the PRO-ACT database. In terms of prediction accuracy, the approach described here ranked third best. Our interpretation of the prediction model confirmed previous reports suggesting that past disease progression is a strong predictor of future disease progression measured on the ALS functional rating scale (ALSFRS). We also found that larger variability in initial ALSFRS scores is linked to faster future disease progression. The results reported here furthermore suggested that approaches taking the multidimensionality of the ALSFRS into account promise some potential for improved ALS disease prediction.

Real-world use of the risk-need-responsivity model and the level of service/case management inventory with community-supervised offenders.

PubMed

Dyck, Heather L; Campbell, Mary Ann; Wershler, Julie L

2018-06-01

The risk-need-responsivity model (RNR; Bonta & Andrews, 2017) has become a leading approach for effective offender case management, but field tests of this model are still required. The present study first assessed the predictive validity of the RNR-informed Level of Service/Case Management Inventory (LS/CMI; Andrews, Bonta, & Wormith, 2004) with a sample of Atlantic Canadian male and female community-supervised provincial offenders (N = 136). Next, the case management plans prepared from these LS/CMI results were analyzed for adherence to the principles of risk, need, and responsivity. As expected, the LS/CMI was a strong predictor of general recidivism for both males (area under the curve = .75, 95% confidence interval [.66, .85]), and especially females (area under the curve = .94, 95% confidence interval [.84, 1.00]), over an average 3.42-year follow-up period. The LS/CMI was predictive of time to recidivism, with lower risk cases taking longer to reoffend than higher risk cases. Despite the robust predictive validity of the LS/CMI, case management plans developed by probation officers generally reflected poor adherence to the RNR principles. These findings highlight the need for better training on how to transfer risk appraisal information from valid risk tools to case plans to better meet the best-practice principles of risk, need, and responsivity for criminal behavior risk reduction. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A Linguistic Analysis of Suicide-Related Twitter Posts.

PubMed

O'Dea, Bridianne; Larsen, Mark E; Batterham, Philip J; Calear, Alison L; Christensen, Helen

2017-09-01

Suicide is a leading cause of death worldwide. Identifying those at risk and delivering timely interventions is challenging. Social media site Twitter is used to express suicidality. Automated linguistic analysis of suicide-related posts may help to differentiate those who require support or intervention from those who do not. This study aims to characterize the linguistic profiles of suicide-related Twitter posts. Using a dataset of suicide-related Twitter posts previously coded for suicide risk by experts, Linguistic Inquiry and Word Count (LIWC) and regression analyses were conducted to determine differences in linguistic profiles. When compared with matched non-suicide-related Twitter posts, strongly concerning suicide-related posts were characterized by a higher word count, increased use of first-person pronouns, and more references to death. When compared with safe-to-ignore suicide-related posts, strongly concerning suicide-related posts were characterized by increased use of first-person pronouns, greater anger, and increased focus on the present. Other differences were found. The predictive validity of the identified features needs further testing before these results can be used for interventional purposes. This study demonstrates that strongly concerning suicide-related Twitter posts have unique linguistic profiles. The examination of Twitter data for the presence of such features may help to validate online risk assessments and determine those in need of further support or intervention.

Using genome-scale metabolic models to compare serovars of the foodborne pathogen Listeria monocytogenes.

PubMed

Metz, Zachary P; Ding, Tong; Baumler, David J

2018-01-01

Listeria monocytogenes is a microorganism of great concern for the food industry and the cause of human foodborne disease. Therefore, novel methods of control are needed, and systems biology is one such approach to identify them. Using a combination of computational techniques and laboratory methods, genome-scale metabolic models (GEMs) can be created, validated, and used to simulate growth environments and discern metabolic capabilities of microbes of interest, including L. monocytogenes. The objective of the work presented here was to generate GEMs for six different strains of L. monocytogenes, and to both qualitatively and quantitatively validate these GEMs with experimental data to examine the diversity of metabolic capabilities of numerous strains from the three different serovar groups most associated with foodborne outbreaks and human disease. Following qualitative validation, 57 of the 95 carbon sources tested experimentally were present in the GEMs, and; therefore, these were the compounds from which comparisons could be drawn. Of these 57 compounds, agreement between in silico predictions and in vitro results for carbon source utilization ranged from 80.7% to 91.2% between strains. Nutrient utilization agreement between in silico predictions and in vitro results were also conducted for numerous nitrogen, phosphorous, and sulfur sources. Additionally, quantitative validation showed that the L. monocytogenes GEMs were able to generate in silico predictions for growth rate and growth yield that were strongly and significantly (p < 0.0013 and p < 0.0015, respectively) correlated with experimental results. These findings are significant because they show that these GEMs for L. monocytogenes are comparable to published GEMs of other organisms for agreement between in silico predictions and in vitro results. Therefore, as with the other GEMs, namely those for Escherichia coli, Staphylococcus aureus, Vibrio vulnificus, and Salmonella spp., they can be used to determine new methods of growth control and disease treatment.

Overt attention in contextual cuing of visual search is driven by the attentional set, but not by the predictiveness of distractors.

PubMed

Beesley, Tom; Hanafi, Gunadi; Vadillo, Miguel A; Shanks, David R; Livesey, Evan J

2018-05-01

Two experiments examined biases in selective attention during contextual cuing of visual search. When participants were instructed to search for a target of a particular color, overt attention (as measured by the location of fixations) was biased strongly toward distractors presented in that same color. However, when participants searched for targets that could be presented in 1 of 2 possible colors, overt attention was not biased between the different distractors, regardless of whether these distractors predicted the location of the target (repeating) or did not (randomly arranged). These data suggest that selective attention in visual search is guided only by the demands of the target detection task (the attentional set) and not by the predictive validity of the distractor elements. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Usefulness and limitations of various guinea-pig test methods in detecting human skin sensitizers-validation of guinea-pig tests for skin hypersensitivity.

PubMed

Marzulli, F; Maguire, H C

1982-02-01

Several guinea-pig predictive test methods were evaluated by comparison of results with those obtained with human predictive tests, using ten compounds that have been used in cosmetics. The method involves the statistical analysis of the frequency with which guinea-pig tests agree with the findings of tests in humans. In addition, the frequencies of false positive and false negative predictive findings are considered and statistically analysed. The results clearly demonstrate the superiority of adjuvant tests (complete Freund's adjuvant) in determining skin sensitizers and the overall superiority of the guinea-pig maximization test in providing results similar to those obtained by human testing. A procedure is suggested for utilizing adjuvant and non-adjuvant test methods for characterizing compounds as of weak, moderate or strong sensitizing potential.

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Analytical approach to an integrate-and-fire model with spike-triggered adaptation

NASA Astrophysics Data System (ADS)

Schwalger, Tilo; Lindner, Benjamin

2015-12-01

The calculation of the steady-state probability density for multidimensional stochastic systems that do not obey detailed balance is a difficult problem. Here we present the analytical derivation of the stationary joint and various marginal probability densities for a stochastic neuron model with adaptation current. Our approach assumes weak noise but is valid for arbitrary adaptation strength and time scale. The theory predicts several effects of adaptation on the statistics of the membrane potential of a tonically firing neuron: (i) a membrane potential distribution with a convex shape, (ii) a strongly increased probability of hyperpolarized membrane potentials induced by strong and fast adaptation, and (iii) a maximized variability associated with the adaptation current at a finite adaptation time scale.

Validity and Reliability of the Verbal Numerical Rating Scale for Children Aged 4 to 17 Years With Acute Pain.

PubMed

Tsze, Daniel S; von Baeyer, Carl L; Pahalyants, Vartan; Dayan, Peter S

2018-06-01

The Verbal Numerical Rating Scale is the most commonly used self-report measure of pain intensity. It is unclear how the validity and reliability of the scale scores vary across children's ages. We aimed to determine the validity and reliability of the scale for children presenting to the emergency department across a comprehensive spectrum of age. This was a cross-sectional study of children aged 4 to 17 years. Children self-reported their pain intensity, using the Verbal Numerical Rating Scale and Faces Pain Scale-Revised at 2 serial assessments. We evaluated convergent validity (strong validity defined as correlation coefficient ≥0.60), agreement (difference between concurrent Verbal Numerical Rating Scale and Faces Pain Scale-Revised scores), known-groups validity (difference in score between children with painful versus nonpainful conditions), responsivity (decrease in score after analgesic administration), and reliability (test-retest at 2 serial assessments) in the total sample and subgroups based on age. We enrolled 760 children; 27 did not understand the Verbal Numerical Rating Scale and were removed. Of the remainder, Pearson correlations were strong to very strong (0.62 to 0.96) in all years of age except 4 and 5 years, and agreement was strong for children aged 8 and older. Known-groups validity and responsivity were strong in all years of age. Reliability was strong in all age subgroups, including each year of age from 4 to 7 years. Convergent validity, known-groups validity, responsivity, and reliability of the Verbal Numerical Rating Scale were strong for children aged 6 to 17 years. Convergent validity was not strong for children aged 4 and 5 years. Our findings support the use of the Verbal Numerical Rating Scale for most children aged 6 years and older, but not for those aged 4 and 5 years. Copyright © 2017 American College of Emergency Physicians. Published by Elsevier Inc. All rights reserved.

Alternative Fistula Risk Score for Pancreatoduodenectomy (a-FRS): Design and International External Validation.

PubMed

Mungroop, Timothy H; van Rijssen, L Bengt; van Klaveren, David; Smits, F Jasmijn; van Woerden, Victor; Linnemann, Ralph J; de Pastena, Matteo; Klompmaker, Sjors; Marchegiani, Giovanni; Ecker, Brett L; van Dieren, Susan; Bonsing, Bert; Busch, Olivier R; van Dam, Ronald M; Erdmann, Joris; van Eijck, Casper H; Gerhards, Michael F; van Goor, Harry; van der Harst, Erwin; de Hingh, Ignace H; de Jong, Koert P; Kazemier, Geert; Luyer, Misha; Shamali, Awad; Barbaro, Salvatore; Armstrong, Thomas; Takhar, Arjun; Hamady, Zaed; Klaase, Joost; Lips, Daan J; Molenaar, I Quintus; Nieuwenhuijs, Vincent B; Rupert, Coen; van Santvoort, Hjalmar C; Scheepers, Joris J; van der Schelling, George P; Bassi, Claudio; Vollmer, Charles M; Steyerberg, Ewout W; Abu Hilal, Mohammed; Groot Koerkamp, Bas; Besselink, Marc G

2017-12-12

The aim of this study was to develop an alternative fistula risk score (a-FRS) for postoperative pancreatic fistula (POPF) after pancreatoduodenectomy, without blood loss as a predictor. Blood loss, one of the predictors of the original-FRS, was not a significant factor during 2 recent external validations. The a-FRS was developed in 2 databases: the Dutch Pancreatic Cancer Audit (18 centers) and the University Hospital Southampton NHS. Primary outcome was grade B/C POPF according to the 2005 International Study Group on Pancreatic Surgery (ISGPS) definition. The score was externally validated in 2 independent databases (University Hospital of Verona and University Hospital of Pennsylvania), using both 2005 and 2016 ISGPS definitions. The a-FRS was also compared with the original-FRS. For model design, 1924 patients were included of whom 12% developed POPF. Three predictors were strongly associated with POPF: soft pancreatic texture [odds ratio (OR) 2.58, 95% confidence interval (95% CI) 1.80-3.69], small pancreatic duct diameter (per mm increase, OR: 0.68, 95% CI: 0.61-0.76), and high body mass index (BMI) (per kg/m increase, OR: 1.07, 95% CI: 1.04-1.11). Discrimination was adequate with an area under curve (AUC) of 0.75 (95% CI: 0.71-0.78) after internal validation, and 0.78 (0.74-0.82) after external validation. The predictive capacity of a-FRS was comparable with the original-FRS, both for the 2005 definition (AUC 0.78 vs 0.75, P = 0.03), and 2016 definition (AUC 0.72 vs 0.70, P = 0.05). The a-FRS predicts POPF after pancreatoduodenectomy based on 3 easily available variables (pancreatic texture, duct diameter, BMI) without blood loss and pathology, and was successfully validated for both the 2005 and 2016 POPF definition.

Measuring decision quality: psychometric evaluation of a new instrument for breast cancer surgery

PubMed Central

2012-01-01

Background The purpose of this paper is to examine the acceptability, feasibility, reliability and validity of a new decision quality instrument that assesses the extent to which patients are informed and receive treatments that match their goals. Methods Cross-sectional mail survey of recent breast cancer survivors, providers and healthy controls and a retest survey of survivors. The decision quality instrument includes knowledge questions and a set of goals, and results in two scores: a breast cancer surgery knowledge score and a concordance score, which reflects the percentage of patients who received treatments that match their goals. Hypotheses related to acceptability, feasibility, discriminant validity, content validity, predictive validity and retest reliability of the survey instrument were examined. Results We had responses from 440 eligible patients, 88 providers and 35 healthy controls. The decision quality instrument was feasible to implement in this study, with low missing data. The knowledge score had good retest reliability (intraclass correlation coefficient = 0.70) and discriminated between providers and patients (mean difference 35%, p < 0.001). The majority of providers felt that the knowledge items covered content that was essential for the decision. Five of the 6 treatment goals met targets for content validity. The five goals had moderate to strong retest reliability (0.64 to 0.87). The concordance score was 89%, indicating that a majority had treatments concordant with that predicted by their goals. Patients who had concordant treatment had similar levels of confidence and regret as those who did not. Conclusions The decision quality instrument met the criteria of feasibility, reliability, discriminant and content validity in this sample. Additional research to examine performance of the instrument in prospective studies and more diverse populations is needed. PMID:22681763

Development, test-retest reliability and validity of the Pharmacy Value-Added Services Questionnaire (PVASQ).

PubMed

Tan, Christine L; Hassali, Mohamed A; Saleem, Fahad; Shafie, Asrul A; Aljadhey, Hisham; Gan, Vincent B

2015-01-01

(i) To develop the Pharmacy Value-Added Services Questionnaire (PVASQ) using emerging themes generated from interviews. (ii) To establish reliability and validity of questionnaire instrument. Using an extended Theory of Planned Behavior as the theoretical model, face-to-face interviews generated salient beliefs of pharmacy value-added services. The PVASQ was constructed initially in English incorporating important themes and later translated into the Malay language with forward and backward translation. Intention (INT) to adopt pharmacy value-added services is predicted by attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), knowledge and expectations. Using a 7-point Likert-type scale and a dichotomous scale, test-retest reliability (N=25) was assessed by administrating the questionnaire instrument twice at an interval of one week apart. Internal consistency was measured by Cronbach's alpha and construct validity between two administrations was assessed using the kappa statistic and the intraclass correlation coefficient (ICC). Confirmatory Factor Analysis, CFA (N=410) was conducted to assess construct validity of the PVASQ. The kappa coefficients indicate a moderate to almost perfect strength of agreement between test and retest. The ICC for all scales tested for intra-rater (test-retest) reliability was good. The overall Cronbach' s alpha (N=25) is 0.912 and 0.908 for the two time points. The result of CFA (N=410) showed most items loaded strongly and correctly into corresponding factors. Only one item was eliminated. This study is the first to develop and establish the reliability and validity of the Pharmacy Value-Added Services Questionnaire instrument using the Theory of Planned Behavior as the theoretical model. The translated Malay language version of PVASQ is reliable and valid to predict Malaysian patients' intention to adopt pharmacy value-added services to collect partial medicine supply.

HLA-DQA1 and PLA2R1 Polymorphisms and Risk of Idiopathic Membranous Nephropathy

PubMed Central

Bullich, Gemma; Ballarín, José; Oliver, Artur; Ayasreh, Nadia; Silva, Irene; Santín, Sheila; Díaz-Encarnación, Montserrat M.; Torra, Roser

2014-01-01

Summary Background and objectives Single nucleotide polymorphisms (SNPs) within HLA complex class II HLA-DQ α-chain 1 (HLA-DQA1) and M-type phospholipase A2 receptor (PLA2R1) genes were identified as strong risk factors for idiopathic membranous nephropathy (IMN) development in a recent genome-wide association study. Copy number variants (CNVs) within the Fc gamma receptor III (FCGR3) locus have been associated with several autoimmune diseases, but their role in IMN has not been studied. This study aimed to validate the association of HLA-DQA1 and PLA2R1 risk alleles with IMN in a Spanish cohort, test the putative association of FCGR3A and FCGR3B CNVs with IMN, and assess the use of these genetic factors to predict the clinical outcome of the disease. Design, settings, participants, & measurements A Spanish cohort of 89 IMN patients and 286 matched controls without nephropathy was recruited between October of 2009 and July of 2012. Case-control studies for SNPs within HLA-DQA1 (rs2187668) and PLA2R1 (rs4664308) genes and CNVs for FCGR3A and FCGR3B genes were performed. The contribution of these polymorphisms to predict clinical outcome and renal function decline was analyzed. Results This study validated the association of these HLA-DQA1 and PLA2R1 SNPs with IMN in a Spanish cohort and its increased risk when combining both risk genotypes. No significant association was found between FCGR3 CNVs and IMN. These results revealed that HLA-DQA1 and PLA2R1 genotype combination adjusted for baseline proteinuria strongly predicted response to immunosuppressive therapy. HLA-DQA1 genotype adjusted for proteinuria was also linked with renal function decline. Conclusion This study confirms that HLA-DQA1 and PLA2R1 genotypes are risk factors for IMN, whereas no association was identified for FCGR3 CNVs. This study provides, for the first time, evidence of the contribution of these HLA-DQA1 and PLA2R1 polymorphisms in predicting IMN response to immunosuppressors and disease progression. Future studies are needed to validate and identify prognostic markers. PMID:24262501

Development and Initial Validation of the Pain Resilience Scale.

PubMed

Slepian, P Maxwell; Ankawi, Brett; Himawan, Lina K; France, Christopher R

2016-04-01

Over the past decade, the role of positive psychology in pain experience has gained increasing attention. One such positive factor, identified as resilience, has been defined as the ability to maintain positive emotional and physical functioning despite physical or psychological adversity. Although cross-situational measures of resilience have been shown to be related to pain, it was hypothesized that a pain-specific resilience measure would serve as a stronger predictor of acute pain experience. To test this hypothesis, we conducted a series of studies to develop and validate the Pain Resilience Scale. Study 1 described exploratory and confirmatory factor analyses that support a scale with 2 distinct factors, Cognitive/Affective Positivity and Behavioral Perseverance. Study 2 showed test-retest reliability and construct validity of this new scale, including moderate positive relationships with measures of positive psychological functioning and small to moderate negative relationships with vulnerability measures such as pain catastrophizing. Finally, consistent with our initial hypothesis, study 3 showed that the Pain Resilience Scale is more strongly related to ischemic pain responses than existing measures of general resilience. Together, these studies support the predictive utility of this new pain-specific measure of resilience in the context of acute experimental pain. The Pain Resilience Scale represents a novel measure of Cognitive/Affective Positivity and Behavioral Perseverance during exposure to noxious stimuli. Construct validity is supported by expected relationships with existing pain-coping measures, and predictive validity is shown by individual differences in response to acute experimental pain. Copyright © 2016 American Pain Society. Published by Elsevier Inc. All rights reserved.

Antisocial personality disorder and psychopathy in women: a literature review on the reliability and validity of assessment instruments.

PubMed

Dolan, Mairead; Völlm, Birgit

2009-01-01

Crime rates are low in women compared to men. The two disorders most commonly associated with offending behaviour, antisocial personality disorder (ASPD) and psychopathy, are also less prevalent in female samples. However, developments in forensic psychiatry have often ignored gender, and the utility of constructs such as psychopathy and their assessment instruments in female samples remains unclear. This article presents a review of studies looking at rates of ASPD and psychopathy and on the reliability and validity of assessment instruments of these disorders in women. Gender differences in symptom patterns will be considered. The literature seems to suggest that DSM-IV criteria for ASPD may lead to an underestimation of the prevalence of the disorder in women due to the requirement of childhood conduct disorder symptoms. The Psychopathy Checklist-Revised (PCL-R) is a valid and reliable instrument to identify psychopathy in women but there are gender differences in the factor structure and item loadings on this measure. Research to date seems to suggest a three-factor model may be most strongly supported in females. Preliminary evidence suggests the PCL-R may have some value in predicting future offending while the PCL:SV may be useful in predicting institutional violence. Clinical implications are discussed.

Physical functional outcome assessment of patients with major burns admitted to a UK Burn Intensive Care Unit.

PubMed

Smailes, Sarah T; Engelsman, Kayleen; Dziewulski, Peter

2013-02-01

Determining the discharge outcome of burn patients can be challenging and therefore a validated objective measure of functional independence would assist with this process. We developed the Functional Assessment for Burns (FAB) score to measure burn patients' functional independence. FAB scores were taken on discharge from ICU (FAB 1) and on discharge from inpatient burn care (FAB 2) in 56 patients meeting the American Burn Association criteria for major burn. We retrospectively analysed prospectively collected data to measure the progress of patients' physical functional outcomes and to evaluate the predictive validity of the FAB score for discharge outcome. Mean age was 38.6 years and median burn size 35%. Significant improvements were made in the physical functional outcomes between FAB 1 and FAB 2 scores (p<0.0001). 48 patients were discharged home, 8 of these with social care. 8 patients were transferred to another hospital for further inpatient rehabilitation. FAB 1 score (≤ 9) is strongly associated with discharge outcome (p<0.006) and as such can be used to facilitate early discharge planning. FAB 2 score (≤ 26) independently predicts discharge outcome (p<0.0001) and therefore is a valid outcome measure to determine discharge outcome of burn patients. Copyright © 2012 Elsevier Ltd and ISBI. All rights reserved.

Validation of automatic wheeze detection in patients with obstructed airways and in healthy subjects.

PubMed

Guntupalli, Kalpalatha K; Alapat, Philip M; Bandi, Venkata D; Kushnir, Igal

2008-12-01

Computerized lung-sound analysis is a sensitive and quantitative method to identify wheezing by its typical pattern on spectral analysis. We evaluated the accuracy of the VRI, a multi-sensor, computer-based device with an automated technique of wheeze detection. The method was validated in 100 sound files from seven subjects with asthma or chronic obstructive pulmonary disease and seven healthy subjects by comparison of auscultation findings, examination of audio files, and computer detection of wheezes. Three blinded physicians identified 40 sound files with wheezes and 60 sound files without wheezes. Sensitivity and specificity were 83% and 85%, respectively. Negative predictive value and positive predictive value were 89% and 79%, respectively. Overall inter-rater agreement was 84%. False positive cases were found to contain sounds that simulate wheezes, such as background noises with high frequencies or strong noises from the throat that could be heard and identified without a stethoscope. The present findings demonstrate that the wheeze detection algorithm has good accuracy, sensitivity, specificity, negative predictive value and positive predictive value for wheeze detection in regional analyses with a single sensor and multiple sensors. Results are similar to those reported in the literature. The device is user-friendly, requires minimal patient effort, and, distinct from other devices, it provides a dynamic image of breath sound distribution with wheeze detection output in less than 1 minute.

Development and validation of a cancer-specific swallowing assessment tool: MASA-C.

PubMed

Carnaby, Giselle D; Crary, Michael A

2014-03-01

We present data from a sample of patients receiving radiotherapy for head/neck cancer to define and measure the validity of a new clinical assessment measure for swallowing. Fifty-eight patients undergoing radiotherapy (±chemotherapy) for head/neck cancer (HNC) supported the development of a physiology-based assessment tool of swallowing (Mann Assessment of Swallowing Ability--Cancer: MASA-C) administered at two time points (baseline and following radiotherapy treatment). The new exam was evaluated for internal consistency of items using Cronbach's alpha. Reliability of measurement was evaluated with intraclass correlation (ICC) and the Kappa statistic between two independent raters. Concurrent validity was established through comparison with the original MASA examination and against the referent standard videofluoroscopic swallowing examination (VFE). Sensitivity, specificity, and likelihood ratios along with 95 % confidence intervals (CIs) were derived for comparison of the two evaluation forms (MASA vs. MASA-C). Accuracy of diagnostic precision was displayed using receiver operator characteristic curves. The new MASA-C tool demonstrated superior validity to the original MASA examination applied to a HNC population. In comparison to the VFE referent exam, the MASA-C revealed strong sensitivity and specificity (Se 83, Sp 96), predictive values (positive predictive value (PPV) 0.95, negative predictive value (NPV) 0.86), and likelihood ratios (21.6). In addition, it demonstrated good reliability (ICC = 0.96) between speech-language pathology raters. The MASA-C is a reliable and valid scale that is sensitive to differences in swallowing performance in HNC patients with and without dysphagia. Future longitudinal evaluation of this tool in larger samples is suggested. The development and refinement of this swallowing assessment tool for use in multidisciplinary HNC teams will facilitate earlier identification of patients with swallowing difficulties and enable more efficient allocation of resources to the management of dysphagia in this population. The MASA-C may also prove useful in future clinical HNC rehabilitation trials with this population.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies.

PubMed

McManus, I C; Dewberry, Chris; Nicholson, Sandra; Dowell, Jonathan S; Woolf, Katherine; Potts, Henry W W

2013-11-14

Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, 'dark matter' and 'dark energy' are posited to balance various theoretical equations, so medical student selection must also have its 'dark variance', whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills.

Construct-level predictive validity of educational attainment and intellectual aptitude tests in medical student selection: meta-regression of six UK longitudinal studies

PubMed Central

2013-01-01

Background Measures used for medical student selection should predict future performance during training. A problem for any selection study is that predictor-outcome correlations are known only in those who have been selected, whereas selectors need to know how measures would predict in the entire pool of applicants. That problem of interpretation can be solved by calculating construct-level predictive validity, an estimate of true predictor-outcome correlation across the range of applicant abilities. Methods Construct-level predictive validities were calculated in six cohort studies of medical student selection and training (student entry, 1972 to 2009) for a range of predictors, including A-levels, General Certificates of Secondary Education (GCSEs)/O-levels, and aptitude tests (AH5 and UK Clinical Aptitude Test (UKCAT)). Outcomes included undergraduate basic medical science and finals assessments, as well as postgraduate measures of Membership of the Royal Colleges of Physicians of the United Kingdom (MRCP(UK)) performance and entry in the Specialist Register. Construct-level predictive validity was calculated with the method of Hunter, Schmidt and Le (2006), adapted to correct for right-censorship of examination results due to grade inflation. Results Meta-regression analyzed 57 separate predictor-outcome correlations (POCs) and construct-level predictive validities (CLPVs). Mean CLPVs are substantially higher (.450) than mean POCs (.171). Mean CLPVs for first-year examinations, were high for A-levels (.809; CI: .501 to .935), and lower for GCSEs/O-levels (.332; CI: .024 to .583) and UKCAT (mean = .245; CI: .207 to .276). A-levels had higher CLPVs for all undergraduate and postgraduate assessments than did GCSEs/O-levels and intellectual aptitude tests. CLPVs of educational attainment measures decline somewhat during training, but continue to predict postgraduate performance. Intellectual aptitude tests have lower CLPVs than A-levels or GCSEs/O-levels. Conclusions Educational attainment has strong CLPVs for undergraduate and postgraduate performance, accounting for perhaps 65% of true variance in first year performance. Such CLPVs justify the use of educational attainment measure in selection, but also raise a key theoretical question concerning the remaining 35% of variance (and measurement error, range restriction and right-censorship have been taken into account). Just as in astrophysics, ‘dark matter’ and ‘dark energy’ are posited to balance various theoretical equations, so medical student selection must also have its ‘dark variance’, whose nature is not yet properly characterized, but explains a third of the variation in performance during training. Some variance probably relates to factors which are unpredictable at selection, such as illness or other life events, but some is probably also associated with factors such as personality, motivation or study skills. PMID:24229353

The predictive validity of criminogenic needs for male and female offenders: comparing the relative impact of needs in predicting recidivism.

PubMed

van der Knaap, Leontien M; Alberda, Daphne L; Oosterveld, Paul; Born, Marise Ph

2012-10-01

Most instruments used to assess offenders' risk of recidivism were developed and validated on male samples. Use of these instruments with female offenders is, however, common practice. This use with female offenders implies the assumption that the risk of recidivism can be predicted on the basis of the same risk factors for women as for men. Yet, this implied gender-neutrality of offender risk instruments has been the topic of much debate. This study compared criminogenic needs in male and female offenders and their relevance in predicting recidivism. A large sample of male and female offenders (N = 16,239) charged with a range of index offenses was studied. Results mainly support the gender neutrality of existing offender risk and needs assessment. However, results do suggest that some criminogenic needs may indeed have a different impact on recidivism for men and women. Problems with accommodation, education and work, and relationships with friends were more strongly correlated to general recidivism in men than in women. For women, difficulties with emotional well-being had a stronger correlation with recidivism than for men. In addition, relative to all other criminogenic needs, problems with emotional well-being were more important for women than for men in predicting general as well as violent recidivism. However, because the bivariate correlation for female offenders between emotional difficulties and recidivism is weak (as it is for male offenders), the question remains whether the relative importance of emotional difficulties in predicting recidivism in women actually has clinical relevance. PsycINFO Database Record (c) 2012 APA, all rights reserved.

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

ERIC Educational Resources Information Center

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

2018-01-01

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

Refining calibration and predictions of a Bayesian statistical-dynamical model for long term avalanche forecasting using dendrochronological reconstructions

NASA Astrophysics Data System (ADS)

Eckert, Nicolas; Schläppy, Romain; Jomelli, Vincent; Naaim, Mohamed

2013-04-01

A crucial step for proposing relevant long-term mitigation measures in long term avalanche forecasting is the accurate definition of high return period avalanches. Recently, "statistical-dynamical" approach combining a numerical model with stochastic operators describing the variability of its inputs-outputs have emerged. Their main interests is to take into account the topographic dependency of snow avalanche runout distances, and to constrain the correlation structure between model's variables by physical rules, so as to simulate the different marginal distributions of interest (pressure, flow depth, etc.) with a reasonable realism. Bayesian methods have been shown to be well adapted to achieve model inference, getting rid of identifiability problems thanks to prior information. An important problem which has virtually never been considered before is the validation of the predictions resulting from a statistical-dynamical approach (or from any other engineering method for computing extreme avalanches). In hydrology, independent "fossil" data such as flood deposits in caves are sometimes confronted to design discharges corresponding to high return periods. Hence, the aim of this work is to implement a similar comparison between high return period avalanches obtained with a statistical-dynamical approach and independent validation data resulting from careful dendrogeomorphological reconstructions. To do so, an up-to-date statistical model based on the depth-averaged equations and the classical Voellmy friction law is used on a well-documented case study. First, parameter values resulting from another path are applied, and the dendrological validation sample shows that this approach fails in providing realistic prediction for the case study. This may be due to the strongly bounded behaviour of runouts in this case (the extreme of their distribution is identified as belonging to the Weibull attraction domain). Second, local calibration on the available avalanche chronicle is performed with various prior distributions resulting from expert knowledge and/or other paths. For all calibrations, a very successful convergence is obtained, which confirms the robustness of the used Metropolis-Hastings estimation algorithm. This also demonstrates the interest of the Bayesian framework for aggregating information by sequential assimilation in the frequently encountered case of limited data quantity. Confrontation with the dendrological sample stresses the predominant role of the Coulombian friction coefficient distribution's variance on predicted high magnitude runouts. The optimal fit is obtained for a strong prior reflecting the local bounded behavior, and results in a 10-40 m difference for return periods ranging between 10 and 300 years. Implementing predictive simulations shows that this is largely within the range of magnitude of uncertainties to be taken into account. On the other hand, the different priors tested for the turbulent friction coefficient influence predictive performances only slightly, but have a large influence on predicted velocity and flow depth distributions. This all may be of high interest to refine calibration and predictive use of the statistical-dynamical model for any engineering application.

The 3-D CFD modeling of gas turbine combustor-integral bleed flow interaction

NASA Technical Reports Server (NTRS)

Chen, D. Y.; Reynolds, R. S.

1993-01-01

An advanced 3-D Computational Fluid Dynamics (CFD) model was developed to analyze the flow interaction between a gas turbine combustor and an integral bleed plenum. In this model, the elliptic governing equations of continuity, momentum and the k-e turbulence model were solved on a boundary-fitted, curvilinear, orthogonal grid system. The model was first validated against test data from public literature and then applied to a gas turbine combustor with integral bleed. The model predictions agreed well with data from combustor rig testing. The model predictions also indicated strong flow interaction between the combustor and the integral bleed. Integral bleed flow distribution was found to have a great effect on the pressure distribution around the gas turbine combustor.

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

PubMed

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

Quicksilver: Fast predictive image registration - A deep learning approach.

PubMed

Yang, Xiao; Kwitt, Roland; Styner, Martin; Niethammer, Marc

2017-09-01

This paper introduces Quicksilver, a fast deformable image registration method. Quicksilver registration for image-pairs works by patch-wise prediction of a deformation model based directly on image appearance. A deep encoder-decoder network is used as the prediction model. While the prediction strategy is general, we focus on predictions for the Large Deformation Diffeomorphic Metric Mapping (LDDMM) model. Specifically, we predict the momentum-parameterization of LDDMM, which facilitates a patch-wise prediction strategy while maintaining the theoretical properties of LDDMM, such as guaranteed diffeomorphic mappings for sufficiently strong regularization. We also provide a probabilistic version of our prediction network which can be sampled during the testing time to calculate uncertainties in the predicted deformations. Finally, we introduce a new correction network which greatly increases the prediction accuracy of an already existing prediction network. We show experimental results for uni-modal atlas-to-image as well as uni-/multi-modal image-to-image registrations. These experiments demonstrate that our method accurately predicts registrations obtained by numerical optimization, is very fast, achieves state-of-the-art registration results on four standard validation datasets, and can jointly learn an image similarity measure. Quicksilver is freely available as an open-source software. Copyright © 2017 Elsevier Inc. All rights reserved.

AHRQ's hospital survey on patient safety culture: psychometric analyses.

PubMed

Blegen, Mary A; Gearhart, Susan; O'Brien, Roxanne; Sehgal, Niraj L; Alldredge, Brian K

2009-09-01

This project analyzed the psychometric properties of the Agency for Healthcare Research and Quality Hospital Survey on Patient Safety Culture (HSOPSC) including factor structure, interitem reliability and intraclass correlations, usefulness for assessment, predictive validity, and sensitivity. The survey was administered to 454 health care staff in 3 hospitals before and after a series of multidisciplinary interventions designed to improve safety culture. Respondents (before, 434; after, 368) included nurses, physicians, pharmacists, and other hospital staff members. Factor analysis partially confirmed the validity of the HSOPSC subscales. Interitem consistency reliability was above 0.7 for 5 subscales; the staffing subscale had the lowest reliability coefficients. The intraclass correlation coefficients, agreement among the members of each unit, were within recommended ranges. The pattern of high and low scores across the subscales of the HSOPSC in the study hospitals were similar to the sample of Pacific region hospitals reported by the Agency for Healthcare Research and Quality and corresponded to the proportion of items in each subscale that are worded negatively (reverse scored). Most of the unit and hospital dimensions were correlated with the Safety Grade outcome measure in the tool. Overall, the tool was shown to have moderate-to-strong validity and reliability, with the exception of the staffing subscale. The usefulness in assessing areas of strength and weakness for hospitals or units among the culture subscales is questionable. The culture subscales were shown to correlate with the perceived outcomes, but further study is needed to determine true predictive validity.

Predictive Validity of an Empirical Approach for Selecting Promising Message Topics: A Randomized-Controlled Study

PubMed Central

Lee, Stella Juhyun; Brennan, Emily; Gibson, Laura Anne; Tan, Andy S. L.; Kybert-Momjian, Ani; Liu, Jiaying; Hornik, Robert

2016-01-01

Several message topic selection approaches propose that messages based on beliefs pretested and found to be more strongly associated with intentions will be more effective in changing population intentions and behaviors when used in a campaign. This study aimed to validate the underlying causal assumption of these approaches which rely on cross-sectional belief–intention associations. We experimentally tested whether messages addressing promising themes as identified by the above criterion were more persuasive than messages addressing less promising themes. Contrary to expectations, all messages increased intentions. Interestingly, mediation analyses showed that while messages deemed promising affected intentions through changes in targeted promising beliefs, messages deemed less promising also achieved persuasion by influencing nontargeted promising beliefs. Implications for message topic selection are discussed. PMID:27867218

Robust d -wave pairing symmetry in multiorbital cobalt high-temperature superconductors

NASA Astrophysics Data System (ADS)

Li, Yinxiang; Han, Xinloong; Qin, Shengshan; Le, Congcong; Wang, Qiang-Hua; Hu, Jiangping

2017-07-01

The pairing symmetry of the cobalt high-temperature (high-Tc) superconductors formed by vertex-shared cation-anion tetrahedral complexes is studied by the methods of mean-field, random phase approximation (RPA), and functional renormalization-group (FRG) analyses. The results of all of these methods show that the dx2-y2 pairing symmetry is robustly favored near half filling. The RPA and FRG methods, which are valid in weak-interaction regions, predict that the superconducting state is also strongly orbital selective, namely, the dx2-y2 orbital that has the largest density near half filling among the three t2 g orbitals dominates superconducting pairing. These results suggest that these materials, if synthesized, can provide an indisputable test of the high-Tc pairing mechanism and the validity of different theoretical methods.

Thermal comfort modelling of body temperature and psychological variations of a human exercising in an outdoor environment

NASA Astrophysics Data System (ADS)

Vanos, Jennifer K.; Warland, Jon S.; Gillespie, Terry J.; Kenny, Natasha A.

2012-01-01

Human thermal comfort assessments pertaining to exercise while in outdoor environments can improve urban and recreational planning. The current study applied a simple four-segment skin temperature approach to the COMFA (COMfort FormulA) outdoor energy balance model. Comparative results of measured mean skin temperature ( {{bar{T}}}nolimits_{{Msk}} ) with predicted {{bar{T}}}nolimits_{{sk}} indicate that the model accurately predicted {{bar{T}}}nolimits_{{sk}} , showing significantly strong agreement ( r = 0.859, P < 0.01) during outdoor exercise (cycling and running). The combined 5-min mean variation of the {{bar{T}}}nolimits_{{sk}} RMSE was 1.5°C, with separate cycling and running giving RMSE of 1.4°C and 1.6°C, respectively, and no significant difference in residuals. Subjects' actual thermal sensation (ATS) votes displayed significant strong rank correlation with budget scores calculated using both measured and predicted {{bar{T}}}nolimits_{{sk}} ( r s = 0.507 and 0.517, respectively, P < 0.01). These results show improved predictive strength of ATS of subjects as compared to the original and updated COMFA models. This psychological improvement, plus {{bar{T}}}nolimits_{{sk}} and T c validations, enables better application to a variety of outdoor spaces. This model can be used in future research studying linkages between thermal discomfort, subsequent decreases in physical activity, and negative health trends.

DEM modeling of ball mills with experimental validation: influence of contact parameters on charge motion and power draw

NASA Astrophysics Data System (ADS)

Boemer, Dominik; Ponthot, Jean-Philippe

2017-01-01

Discrete element method simulations of a 1:5-scale laboratory ball mill are presented in this paper to study the influence of the contact parameters on the charge motion and the power draw. The position density limit is introduced as an efficient mathematical tool to describe and to compare the macroscopic charge motion in different scenarios, i.a. with different values of the contact parameters. While the charge motion and the power draw are relatively insensitive to the stiffness and the damping coefficient of the linear spring-slider-damper contact law, the coefficient of friction has a strong influence since it controls the sliding propensity of the charge. Based on the experimental calibration and validation by charge motion photographs and power draw measurements, the descriptive and predictive capabilities of the position density limit and the discrete element method are demonstrated, i.e. the real position of the charge is precisely delimited by the respective position density limit and the power draw can be predicted with an accuracy of about 5 %.

QSAR models for anti-malarial activity of 4-aminoquinolines.

PubMed

Masand, Vijay H; Toropov, Andrey A; Toropova, Alla P; Mahajan, Devidas T

2014-03-01

In the present study, predictive quantitative structure - activity relationship (QSAR) models for anti-malarial activity of 4-aminoquinolines have been developed. CORAL, which is freely available on internet (http://www.insilico.eu/coral), has been used as a tool of QSAR analysis to establish statistically robust QSAR model of anti-malarial activity of 4-aminoquinolines. Six random splits into the visible sub-system of the training and invisible subsystem of validation were examined. Statistical qualities for these splits vary, but in all these cases, statistical quality of prediction for anti-malarial activity was quite good. The optimal SMILES-based descriptor was used to derive the single descriptor based QSAR model for a data set of 112 aminoquinolones. All the splits had r(2)> 0.85 and r(2)> 0.78 for subtraining and validation sets, respectively. The three parametric multilinear regression (MLR) QSAR model has Q(2) = 0.83, R(2) = 0.84 and F = 190.39. The anti-malarial activity has strong correlation with presence/absence of nitrogen and oxygen at a topological distance of six.

Validation of a Quality of Life Questionnaire for Bronchiectasis: psychometric analyses of the Spanish QOL-B-V3.0.

PubMed

Olveira, Casilda; Olveira, Gabriel; Espildora, Francisco; Giron, Rosa-Maria; Muñoz, Gerard; Quittner, Alexandra L; Martinez-Garcia, Miguel-Angel

2014-05-01

Bronchiectasis is a chronic disease, leading to worsening of health-related quality of life. This study evaluated the psychometric properties of a new patient-reported outcome for non-cystic fibrosis bronchiectasis, the Quality of Life Questionnaire Bronchiectasis, translated into Spanish (QOL-B-Sp-V3.0). This prospective study recruited clinically stable patients with non-cystic fibrosis bronchiectasis at 4 Spanish centers. Health status was assessed with multiple indicators (dyspnea, exacerbations, bronchorrhea, etc.), microbiological, radiological, spirometric, and anthropometric parameters plus St-George Respiratory Questionnaire (SGRQ). Psychometric analyses included internal consistency, test-retest reliability, convergent validity, predictive validity, and responsivity to change. The 207 stable patients (mean age 57.2 years) had a Bhalla score of 11.53 ± 7.39 and FEV1% of 68.3 ± 22.2 %. One hundred and sixty-one stable patients repeated the test 2 weeks later, and 80 patients who had an exacerbation within 6 months of the assessment also repeated it. Internal consistency was high across all scales (Cronbach's alpha >0.70). Thirty-six of 37 items correlated more strongly with their assigned scale than a competing scale. Test-retest coefficients were strong (intraclass correlations r = 0.68-0.88). All scales, except Treatment Burden, discriminated significantly between patients with mild, moderate, and severe disease according to FEV1% and other respiratory parameters. Strong convergence was found between the QOL-B-Sp-V3.0 and SGRQ. Significant correlations were found between QOL-B-Sp-V3.0 and various clinical, spirometric, radiological, and anthropometric variables. Significant differences were found on all QOL-B-Sp-V3.0 scales, except emotional functioning, between the baseline responses and onset of an exacerbation; robust sensitivity to change was observed on the Respiratory Symptoms scale. The QOL-B-Sp-V3.0 questionnaire demonstrated strong reliability and validity. Scores were reproducible after 2 weeks, and it discriminated between patients who varied in severity and was responsive to changes related to exacerbation.

Prediction of skin sensitization potency using machine learning approaches.

PubMed

Zang, Qingda; Paris, Michael; Lehmann, David M; Bell, Shannon; Kleinstreuer, Nicole; Allen, David; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Strickland, Judy

2017-07-01

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Droplet Deformation in an Extensional Flow: The Role of Surfactant Physical Chemistry

NASA Technical Reports Server (NTRS)

Stebe, Kathleen J.

1996-01-01

Surfactant-induced Marangoni effects strongly alter the stresses exerted along fluid particle interfaces. In low gravity processes, these stresses can dictate the system behavior. The dependence of Marangoni effects on surfactant physical chemistry is not understood, severely impacting our ability to predict and control fluid particle flows. A droplet in an extensional flow allows the controlled study of stretching and deforming interfaces. The deformations of the drop allow both Marangoni stresses, which resist tangential shear, and Marangoni elasticities, which resist surface dilatation, to develop. This flow presents an ideal model system for studying these effects. Prior surfactant-related work in this flow considered a linear dependence of the surface tension on the surface concentration, valid only at dilute surface concentrations, or a non-linear framework at concentrations sufficiently dilute that the linear approximation was valid. The linear framework becomes inadequate for several reasons. The finite dimensions of surfactant molecules must be taken into account with a model that includes surfaces saturation. Nonideal interactions between adsorbed surfactant molecules alter the partitioning of surfactant between the bulk and the interface, the dynamics of surfactant adsorptive/desorptive exchange, and the sensitivity of the surface tension to adsorbed surfactant. For example, cohesion between hydrocarbon chains favors strong adsorption. Cohesion also slows the rate of desorption from interfaces, and decreases the sensitivity of the surface tension to adsorbed surfactant. Strong cohesive interactions result in first order surface phase changes with a plateau in the surface tension vs surface concentration. Within this surface concentration range, the surface tension is decoupled from surface concentration gradients. We are engaged in the study of the role of surfactant physical chemistry in determining the Marangoni stresses on a drop in an extensional flow in a numerical and experimental program. Using surfactants whose dynamics and equilibrium behavior have been characterized in our laboratory, drop deformation will be studied in ground-based experiment. In an accompanying numerical study, predictive drop deformations will be determined based on the isotherm and equation of state determined in our laboratory. This work will improve our abilities to predict and control all fluid particle flows.

Proteomic Biomarkers for Acute Interstitial Lung Disease in Gefitinib-Treated Japanese Lung Cancer Patients

PubMed Central

Kawakami, Takao; Nagasaka, Keiko; Takami, Sachiko; Wada, Kazuya; Tu, Hsiao-Kun; Otsuji, Makiko; Kyono, Yutaka; Dobashi, Tae; Komatsu, Yasuhiko; Kihara, Makoto; Akimoto, Shingo; Peers, Ian S.; South, Marie C.; Higenbottam, Tim; Fukuoka, Masahiro; Nakata, Koichiro; Ohe, Yuichiro; Kudoh, Shoji; Clausen, Ib Groth; Nishimura, Toshihide; Marko-Varga, György; Kato, Harubumi

2011-01-01

Interstitial lung disease (ILD) events have been reported in Japanese non-small-cell lung cancer (NSCLC) patients receiving EGFR tyrosine kinase inhibitors. We investigated proteomic biomarkers for mechanistic insights and improved prediction of ILD. Blood plasma was collected from 43 gefitinib-treated NSCLC patients developing acute ILD (confirmed by blinded diagnostic review) and 123 randomly selected controls in a nested case-control study within a pharmacoepidemiological cohort study in Japan. We generated ∼7 million tandem mass spectrometry (MS/MS) measurements with extensive quality control and validation, producing one of the largest proteomic lung cancer datasets to date, incorporating rigorous study design, phenotype definition, and evaluation of sample processing. After alignment, scaling, and measurement batch adjustment, we identified 41 peptide peaks representing 29 proteins best predicting ILD. Multivariate peptide, protein, and pathway modeling achieved ILD prediction comparable to previously identified clinical variables; combining the two provided some improvement. The acute phase response pathway was strongly represented (17 of 29 proteins, p = 1.0×10−25), suggesting a key role with potential utility as a marker for increased risk of acute ILD events. Validation by Western blotting showed correlation for identified proteins, confirming that robust results can be generated from an MS/MS platform implementing strict quality control. PMID:21799770

PREDICT: A next generation platform for near real-time prediction of cholera

NASA Astrophysics Data System (ADS)

Jutla, A.; Aziz, S.; Akanda, A. S.; Alam, M.; Ahsan, G. U.; Huq, A.; Colwell, R. R.

2017-12-01

Data on disease prevalence and infectious pathogens is sparingly collected/available in region(s) where climatic variability and extreme natural events intersect with population vulnerability (such as lack of access to water and sanitation infrastructure). Therefore, traditional time series modeling approach of calibration and validation of a model is inadequate. Hence, prediction of diarrheal infections (such as cholera, Shigella etc) remain a challenge even though disease causing pathogens are strongly associated with modalities of regional climate and weather system. Here we present an algorithm that integrates satellite derived data on several hydroclimatic and ecological processes into a framework that can determine high resolution cholera risk on global scales. Cholera outbreaks can be classified in three forms- epidemic (sudden or seasonal outbreaks), endemic (recurrence and persistence of the disease for several consecutive years) and mixed-mode endemic (combination of certain epidemic and endemic conditions) with significant spatial and temporal heterogeneity. Using data from multiple satellites (AVHRR, TRMM, GPM, MODIS, VIIRS, GRACE), we will show examples from Haiti, Yemen, Nepal and several other regions where our algorithm has been successful in capturing risk of outbreak of infection in human population. A spatial model validation algorithm will also be presented that has capabilities to self-calibrate as new hydroclimatic and disease data become available.

Experimental and theoretical investigations on the validity of the geometrical optics model for calculating the stability of optical traps.

PubMed

Schut, T C; Hesselink, G; de Grooth, B G; Greve, J

1991-01-01

We have developed a computer program based on the geometrical optics approach proposed by Roosen to calculate the forces on dielectric spheres in focused laser beams. We have explicitly taken into account the polarization of the laser light and thd divergence of the laser beam. The model can be used to evaluate the stability of optical traps in a variety of different optical configurations. Our calculations explain the experimental observation by Ashkin that a stable single-beam optical trap, without the help of the gravitation force, can be obtained with a strongly divergent laser beam. Our calculations also predict a different trap stability in the directions orthogonal and parallel to the polarization direction of the incident light. Different experimental methods were used to test the predictions of the model for the gravity trap. A new method for measuring the radiation force along the beam axis in both the stable and instable regions is presented. Measurements of the radiation force on polystyrene spheres with diameters of 7.5 and 32 microns in a TEM00-mode laser beam showed a good qualitative correlation with the predictions and a slight quantitative difference. The validity of the geometrical approximations involved in the model will be discussed for spheres of different sizes and refractive indices.

Quantitative Determination of Fusarium proliferatum Concentration in Intact Garlic Cloves Using Near-Infrared Spectroscopy.

PubMed

Tamburini, Elena; Mamolini, Elisabetta; De Bastiani, Morena; Marchetti, Maria Gabriella

2016-07-15

Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional assays. Preventive detection of infection before seeding is of great interest for farmers, because it could avoid serious losses of yield during harvesting and storage. Spectra were collected on 95 garlic cloves, divided in five classes of infection (from 1-healthy to 5-very highly infected) in the range of fungal concentration 0.34-7231.15 ppb. Calibration and cross validation models were developed with partial least squares regression (PLSR) on pretreated spectra (standard normal variate, SNV, and derivatives), providing good accuracy in prediction, with a coefficient of determination (R²) of 0.829 and 0.774, respectively, a standard error of calibration (SEC) of 615.17 ppb, and a standard error of cross validation (SECV) of 717.41 ppb. The calibration model was then used to predict fungal concentration in unknown samples, peeled and unpeeled. The results showed that NIRS could be used as a reliable tool to directly detect and quantify F. proliferatum infection in peeled intact garlic cloves, but the presence of the external peel strongly affected the prediction reliability.

Increasing the utility of the Functional Assessment for Burns Score: Not just for major burns.

PubMed

Smailes, Sarah T; Engelsman, Kayleen; Rodgers, Louise; Upson, Clara

2016-02-01

The Functional Assessment for Burns (FAB) score is established as an objective measure of physical function that predicts discharge outcome in adult patients with major burn. However, its validity in patients with minor and moderate burn is unknown. This is a multi-centre evaluation of the predictive validity of the FAB score for discharge outcome in adult inpatients with minor and moderate burns. FAB assessments were undertaken within 48 h of admission to (FAB 1), and within 48 h of discharge (FAB 2) from burn wards in 115 patients. Median age was 45 years and median burn size 4%. There were significant improvements in the patients' FAB scores (p<0.0001), 98 patients were discharged home (no social care) and 17 patients discharged to further inpatient rehabilitation or home with social care. FAB 1 score (≤ 14) is strongly associated with discharge to inpatient rehabilitation or home with social care (p=0.0001) and as such can be used to facilitate early discharge planning. FAB 2 (≤ 30) independently predicts discharge outcome to inpatient rehabilitation or home with social care (p<0.0001), increasing its utility to patients with minor and moderate burns. Copyright © 2015 Elsevier Ltd and ISBI. All rights reserved.

Modeling of indoor radon concentration from radon exhalation rates of building materials and validation through measurements.

PubMed

Kumar, Amit; Chauhan, R P; Joshi, Manish; Sahoo, B K

2014-01-01

Building materials are the second major source of indoor radon after soil. The contribution of building materials towards indoor radon depends upon the radium content and exhalation rates and can be used as a primary index for radon levels in the dwellings. The radon flux data from the building materials was used for calculation of the indoor radon concentrations and doses by many researchers using one and two dimensional model suggested by various researchers. In addition to radium content, the radon wall flux from a surface strongly depends upon the radon diffusion length (L) and thickness of the wall (2d). In the present work the indoor radon concentrations from the measured radon exhalation rate of building materials calculated using different models available in literature and validation of models was made through measurement. The variation in the predicted radon flux from different models was compared with d/L value for wall and roofs of different dwellings. The results showed that the radon concentrations predicted by models agree with experimental value. The applicability of different model with d/L ratio was discussed. The work aims to select a more appropriate and general model among available models in literature for the prediction of indoor radon. Copyright © 2013 Elsevier Ltd. All rights reserved.

A new model of cavern diameter based on a validated CFD study on stirring of a highly shear-thinning fluid.

PubMed

Story, Anna; Jaworski, Zdzisław

2017-01-01

Results of numerical simulations of momentum transfer for a highly shear-thinning fluid (0.2% Carbopol) in a stirred tank equipped with a Prochem Maxflo T type impeller are presented. The simulation results were validated using LDA data and both tangential and axial force measurements in the laminar and early transitional flow range. A good agreement between the predicted and experimental results of the local fluid velocity components was found. From the predicted and experimental values of both tangential and axial forces, the power number, Po , and thrust number, Th , were also calculated. Values of the absolute relative deviations were below 4.0 and 10.5%, respectively, for Po and Th , which confirms a satisfactory agreement with experiments. An intensive mixing zone, known as cavern, was observed near the impeller. In this zone, the local values of fluid velocity, strain rate, Metzner-Otto coefficient, shear stress and intensity of energy dissipation were all characterized by strong variability. Based on the results of experimental study a new model using non-dimensional impeller force number was proposed to predict the cavern diameter. Comparative numerical simulations were also carried out for a Newtonian fluid (water) and their results were similarly well verified using LDA measurements, as well as experimental power number values.

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

PubMed Central

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

2013-01-01

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

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.

Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

PubMed

Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

2010-12-01

The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Plasma proteins predict conversion to dementia from prodromal disease

PubMed Central

Hye, Abdul; Riddoch-Contreras, Joanna; Baird, Alison L.; Ashton, Nicholas J.; Bazenet, Chantal; Leung, Rufina; Westman, Eric; Simmons, Andrew; Dobson, Richard; Sattlecker, Martina; Lupton, Michelle; Lunnon, Katie; Keohane, Aoife; Ward, Malcolm; Pike, Ian; Zucht, Hans Dieter; Pepin, Danielle; Zheng, Wei; Tunnicliffe, Alan; Richardson, Jill; Gauthier, Serge; Soininen, Hilkka; Kłoszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon

2014-01-01

Background The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. Methods Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. Results Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). Conclusions We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints. PMID:25012867

Plasma proteins predict conversion to dementia from prodromal disease.

PubMed

Hye, Abdul; Riddoch-Contreras, Joanna; Baird, Alison L; Ashton, Nicholas J; Bazenet, Chantal; Leung, Rufina; Westman, Eric; Simmons, Andrew; Dobson, Richard; Sattlecker, Martina; Lupton, Michelle; Lunnon, Katie; Keohane, Aoife; Ward, Malcolm; Pike, Ian; Zucht, Hans Dieter; Pepin, Danielle; Zheng, Wei; Tunnicliffe, Alan; Richardson, Jill; Gauthier, Serge; Soininen, Hilkka; Kłoszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon

2014-11-01

The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia. Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays. Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%). We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Why are men more likely to support group-based dominance than women? The mediating role of gender identification.

PubMed

Dambrun, Michaël; Duarte, Sandra; Guimond, Serge

2004-06-01

Arguing from a sociobiological perspective, Sidanius and Pratto (1999) have shown that the male/female difference in social dominance orientation (SDO) is largely invariant across cultural, situational and contextual boundaries. The main objective of this study was to test the validity of Social Dominance Theory (SDT) by contrasting it with a model derived from Social Identity Theory (SIT). More specifically, while SIT predicts that gender identification mediates the effect of gender on SDO, SDT predicts the reverse. According to SDT, the degree to which men and women endorse status legitimizing ideology should determine to what extent they identify with their gender group. Using structural equation modelling, the results provide strong support for the SIT model and no support for SDT predictions. Implications of these results for social dominance theory and its sociobiologically based invariance hypothesis are discussed.

A probabilistic framework to infer brain functional connectivity from anatomical connections.

PubMed

Deligianni, Fani; Varoquaux, Gael; Thirion, Bertrand; Robinson, Emma; Sharp, David J; Edwards, A David; Rueckert, Daniel

2011-01-01

We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.

Resolving the mystery of transport within internal transport barriersa)

NASA Astrophysics Data System (ADS)

Staebler, G. M.; Kinsey, J. E.; Belli, E. A.; Candy, J.; Waltz, R. E.; Greenfield, C. M.; Lao, L. L.; Smith, S. P.; Grierson, B. A.; Chrystal, C.

2014-05-01

The Trapped Gyro-Landau Fluid (TGLF) quasi-linear model [G. M. Staebler, et al., Phys. Plasmas 12, 102508 (2005)], which is calibrated to nonlinear gyrokinetic turbulence simulations, is now able to predict the electron density, electron and ion temperatures, and ion toroidal rotation simultaneously for internal transport barrier (ITB) discharges. This is a strong validation of gyrokinetic theory of ITBs, requiring multiple instabilities responsible for transport in different channels at different scales. The mystery of transport inside the ITB is that momentum and particle transport is far above the predicted neoclassical levels in apparent contradiction with the expectation from the theory of suppression of turbulence by E ×B velocity shear. The success of TGLF in predicting ITB transport is due to the inclusion of ion gyro-radius scale modes that become dominant at high E ×B velocity shear and to improvements to TGLF that allow momentum transport from gyrokinetic turbulence to be faithfully modeled.

Resolving the mystery of transport within internal transport barriers

DOE PAGES

Staebler, Gary M.; Kinsey, Jon E.; Belli, Emily A.; ...

2014-05-02

Here, the Trapped Gyro-Landau Fluid (TGLF) quasi-linear model, which is calibrated to nonlinear gyrokinetic turbulence simulations, is now able to predict the electron density, electron and ion temperatures and ion toroidal rotation simultaneously for internal transport barrier (ITB) discharges. This is a strong validation of gyrokinetic theory of ITBs, requiring multiple instabilities responsible for transport in different channels at different scales. The mystery of transport inside the ITB is that momentum and particle transport is far above the predicted neoclassical levels in apparent contradiction with the expectation from the theory of suppression of turbulence by E × B velocity shear.more » The success of TGLF in predicting ITB transport is due to the inclusion of ion gyro-radius scale modes that become dominant at high E × B velocity shear and to improvements to TGLF that allow momentum transport from gyrokinetic turbulence to be faithfully modeled.« less

"Blue flags", development of a short clinical questionnaire on work-related psychosocial risk factors - a validation study in primary care.

PubMed

Post Sennehed, Charlotte; Gard, Gunvor; Holmberg, Sara; Stigmar, Kjerstin; Forsbrand, Malin; Grahn, Birgitta

2017-07-24

Working conditions substantially influence health, work ability and sick leave. Useful instruments to help clinicians pay attention to working conditions are lacking in primary care (PC). The aim of this study was to test the validity of a short "Blue flags" questionnaire, which focuses on work-related psychosocial risk factors and any potential need for contacts and/or actions at the workplace. From the original"The General Nordic Questionnaire" (QPS Nordic ) the research group identified five content areas with a total of 51 items which were considered to be most relevant focusing on work-related psychosocial risk factors. Fourteen items were selected from the identified QPS Nordic content areas and organised in a short questionnaire "Blue flags". These 14 items were validated towards the 51 QPS Nordic items. Content validity was reviewed by a professional panel and a patient panel. Structural and concurrent validity were also tested within a randomised clinical trial. The two panels (n = 111) considered the 14 psychosocial items to be relevant. A four-factor model was extracted with an explained variance of 25.2%, 14.9%, 10.9% and 8.3% respectively. All 14 items showed satisfactory loadings on all factors. Concerning concurrent validity the overall correlation was very strong r s  = 0.87 (p < 0.001).). Correlations were moderately strong for factor one, r s  = 0.62 (p < 0.001) and factor two, r s  = 0.74 (p < 0.001). Factor three and factor four were weaker, bur still fair and significant at r s  = 0.53 (p < 0.001) and r s  = 0.41 (p < 0.001) respectively. The internal consistency of the whole "Blue flags" was good with Cronbach's alpha of 0.76. The content, structural and concurrent validity were satisfactory in this first step of development of the "Blue flags" questionnaire. In summary, the overall validity is considered acceptable. Testing in clinical contexts and in other patient populations is recommended to ensure predictive validity and usefulness.

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

PubMed

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

2016-08-01

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

Direct Validation of Differential Prediction.

ERIC Educational Resources Information Center

Lunneborg, Clifford E.

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

Swedish Acceptance and Action Questionnaire (SAAQ): a psychometric evaluation.

PubMed

Lundgren, Tobias; Parling, Thomas

2017-06-01

Psychological inflexibility and experiential avoidance are equivalent (with somewhat different connotations) concepts and refer to an unwillingness to remain in contact with particular private events. This concept is most often measured by the Acceptance and Action Questionnaire (AAQ-II) and is strongly related to psychopathology and behavioral effectiveness. In this study, the preliminary psychometric properties of the Swedish version of the AAQ-II (Swedish Acceptance and Action Questionnaire-SAAQ) are presented. The study is done in two steps. In the first step, the 10-item version of the AAQ-II is investigated through principal component analysis (n = 147). Secondly, due to problems with the component structure, the instrument is reduced to a six-item version and its validity and internal consistency are investigated (n = 154). The six-item version shows good concurrent and convergent validity as well as satisfying internal consistency (α = .85). Furthermore, the Swedish six-item version of the AAQ-II showed one strong component. Test-retest reliability was satisfactory (r = .80; n = 228). In future research, predictive and external validity would be important to investigate in order to further ensure that the SAAQ is a useful measure for clinical research. In conclusion, the SAAQ has satisfactory psychometric properties, but more data need to be gathered to further explore the possibilities for the instruments in Swedish contexts.

Retrieval of pine forest biomass using JPL AIRSAR data

NASA Technical Reports Server (NTRS)

Beaudoin, A.; Letoan, T.; Zagolski, F.; Hsu, C. C.; Han, H. C.; Kong, J. A.

1992-01-01

The analysis of Jet Propulsion Laboratory (JPL) Airborne Synthetic Aperture Radar (AIRSAR) data over the Landes forest in South-West France revealed strong correlation between L- and especially P-band sigma degrees and the pine forest biomass. To explain the physical link of radar backscatter to biomass, a polarimetric backscattering model was developed and validated. Then the model was used in a simulation study to predict sigma degree sensitivity to undesired canopy and environmental parameters. Main results concerning the data analysis, modeling, and simulation at P-band are reported.

Ionospheric Irregularities Predictions and Plumes Characterization for Satellite Data Validation and Calibration

DTIC Science & Technology

2014-01-17

at São José dos Campos, São Paulo - Brazil Good S4 agreement for the 6 receivers and for moderate scintillations – no strong scintillations tested...Space Research - INPE Fundação de Ciências, Aplicações e Tecnologia Espaciais, Av. Dr. João Guilhermino, 429/11 – São José dos Campos, São Paulo ...The ionospheric plumes were characterized for 3 longitudinal sectors (east of Brazil , Peruvian coast and pacific zone)using VHF radars and algorithms

Strong Ground Motion Prediction By Composite Source Model

NASA Astrophysics Data System (ADS)

Burjanek, J.; Irikura, K.; Zahradnik, J.

2003-12-01

A composite source model, incorporating different sized subevents, provides a possible description of complex rupture processes during earthquakes. The number of subevents with characteristic dimension greater than R is proportional to R-2. The subevents do not overlap with each other, and the sum of their areas equals to the area of the target event (e.g. mainshock). The subevents are distributed randomly over the fault. Each subevent is modeled either as a finite or point source, differences between these choices are shown. The final slip and duration of each subevent is related to its characteristic dimension, using constant stress-drop scaling. Absolute value of subevents' stress drop is free parameter. The synthetic Green's functions are calculated by the discrete-wavenumber method in a 1D horizontally layered crustal model. An estimation of subevents' stress drop is based on fitting empirical attenuation relations for PGA and PGV, as they represent robust information on strong ground motion caused by earthquakes, including both path and source effect. We use the 2000 M6.6 Western Tottori, Japan, earthquake as validation event, providing comparison between predicted and observed waveforms.

In-vivo detectability index: development and validation of an automated methodology

NASA Astrophysics Data System (ADS)

Smith, Taylor Brunton; Solomon, Justin; Samei, Ehsan

2017-03-01

The purpose of this study was to develop and validate a method to estimate patient-specific detectability indices directly from patients' CT images (i.e., "in vivo"). The method works by automatically extracting noise (NPS) and resolution (MTF) properties from each patient's CT series based on previously validated techniques. Patient images are thresholded into skin-air interfaces to form edge-spread functions, which are further binned, differentiated, and Fourier transformed to form the MTF. The NPS is likewise estimated from uniform areas of the image. These are combined with assumed task functions (reference function: 10 mm disk lesion with contrast of -15 HU) to compute detectability indices for a non-prewhitening matched filter model observer predicting observer performance. The results were compared to those from a previous human detection study on 105 subtle, hypo-attenuating liver lesions, using a two-alternative-forcedchoice (2AFC) method, over 6 dose levels using 16 readers. The in vivo detectability indices estimated for all patient images were compared to binary 2AFC outcomes with a generalized linear mixed-effects statistical model (Probit link function, linear terms only, no interactions, random term for readers). The model showed that the in vivo detectability indices were strongly predictive of 2AFC outcomes (P < 0.05). A linear comparison between the human detection accuracy and model-predicted detection accuracy (for like conditions) resulted in Pearson and Spearman correlations coefficients of 0.86 and 0.87, respectively. These data provide evidence that the in vivo detectability index could potentially be used to automatically estimate and track image quality in a clinical operation.

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.

Multiscale framework for predicting the coupling between deformation and fluid diffusion in porous rocks

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

Andrade, José E; Rudnicki, John W

2012-12-14

In this project, a predictive multiscale framework will be developed to simulate the strong coupling between solid deformations and fluid diffusion in porous rocks. We intend to improve macroscale modeling by incorporating fundamental physical modeling at the microscale in a computationally efficient way. This is an essential step toward further developments in multiphysics modeling, linking hydraulic, thermal, chemical, and geomechanical processes. This research will focus on areas where severe deformations are observed, such as deformation bands, where classical phenomenology breaks down. Multiscale geometric complexities and key geomechanical and hydraulic attributes of deformation bands (e.g., grain sliding and crushing, and poremore » collapse, causing interstitial fluid expulsion under saturated conditions), can significantly affect the constitutive response of the skeleton and the intrinsic permeability. Discrete mechanics (DEM) and the lattice Boltzmann method (LBM) will be used to probe the microstructure---under the current state---to extract the evolution of macroscopic constitutive parameters and the permeability tensor. These evolving macroscopic constitutive parameters are then directly used in continuum scale predictions using the finite element method (FEM) accounting for the coupled solid deformation and fluid diffusion. A particularly valuable aspect of this research is the thorough quantitative verification and validation program at different scales. The multiscale homogenization framework will be validated using X-ray computed tomography and 3D digital image correlation in situ at the Advanced Photon Source in Argonne National Laboratories. Also, the hierarchical computations at the specimen level will be validated using the aforementioned techniques in samples of sandstone undergoing deformation bands.« less

Noninvasive assessment of mitral inertness [correction of inertance]: clinical results with numerical model validation.

PubMed

Firstenberg, M S; Greenberg, N L; Smedira, N G; McCarthy, P M; Garcia, M J; Thomas, J D

2001-01-01

Inertial forces (Mdv/dt) are a significant component of transmitral flow, but cannot be measured with Doppler echo. We validated a method of estimating Mdv/dt. Ten patients had a dual sensor transmitral (TM) catheter placed during cardiac surgery. Doppler and 2D echo was performed while acquiring LA and LV pressures. Mdv/dt was determined from the Bernoulli equation using Doppler velocities and TM gradients. Results were compared with numerical modeling. TM gradients (range: 1.04-14.24 mmHg) consisted of 74.0 +/- 11.0% inertial forcers (range: 0.6-12.9 mmHg). Multivariate analysis predicted Mdv/dt = -4.171(S/D (RATIO)) + 0.063(LAvolume-max) + 5. Using this equation, a strong relationship was obtained for the clinical dataset (y=0.98x - 0.045, r=0.90) and the results of numerical modeling (y=0.96x - 0.16, r=0.84). TM gradients are mainly inertial and, as validated by modeling, can be estimated with echocardiography.

Noninvasive assessment of mitral inertness: clinical results with numerical model validation

NASA Technical Reports Server (NTRS)

Firstenberg, M. S.; Greenberg, N. L.; Smedira, N. G.; McCarthy, P. M.; Garcia, M. J.; Thomas, J. D.

2001-01-01

Inertial forces (Mdv/dt) are a significant component of transmitral flow, but cannot be measured with Doppler echo. We validated a method of estimating Mdv/dt. Ten patients had a dual sensor transmitral (TM) catheter placed during cardiac surgery. Doppler and 2D echo was performed while acquiring LA and LV pressures. Mdv/dt was determined from the Bernoulli equation using Doppler velocities and TM gradients. Results were compared with numerical modeling. TM gradients (range: 1.04-14.24 mmHg) consisted of 74.0 +/- 11.0% inertial forcers (range: 0.6-12.9 mmHg). Multivariate analysis predicted Mdv/dt = -4.171(S/D (RATIO)) + 0.063(LAvolume-max) + 5. Using this equation, a strong relationship was obtained for the clinical dataset (y=0.98x - 0.045, r=0.90) and the results of numerical modeling (y=0.96x - 0.16, r=0.84). TM gradients are mainly inertial and, as validated by modeling, can be estimated with echocardiography.

Emergency department triage scales and their components: a systematic review of the scientific evidence.

PubMed

Farrohknia, Nasim; Castrén, Maaret; Ehrenberg, Anna; Lind, Lars; Oredsson, Sven; Jonsson, Håkan; Asplund, Kjell; Göransson, Katarina E

2011-06-30

Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED?2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (≥ 15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted.We found ED triage scales to be supported, at best, by limited and often insufficient evidence.The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity).

Emergency Department Triage Scales and Their Components: A Systematic Review of the Scientific Evidence

PubMed Central

2011-01-01

Emergency department (ED) triage is used to identify patients' level of urgency and treat them based on their triage level. The global advancement of triage scales in the past two decades has generated considerable research on the validity and reliability of these scales. This systematic review aims to investigate the scientific evidence for published ED triage scales. The following questions are addressed: 1. Does assessment of individual vital signs or chief complaints affect mortality during the hospital stay or within 30 days after arrival at the ED? 2. What is the level of agreement between clinicians' triage decisions compared to each other or to a gold standard for each scale (reliability)? 3. How valid is each triage scale in predicting hospitalization and hospital mortality? A systematic search of the international literature published from 1966 through March 31, 2009 explored the British Nursing Index, Business Source Premier, CINAHL, Cochrane Library, EMBASE, and PubMed. Inclusion was limited to controlled studies of adult patients (≥15 years) visiting EDs for somatic reasons. Outcome variables were death in ED or hospital and need for hospitalization (validity). Methodological quality and clinical relevance of each study were rated as high, medium, or low. The results from the studies that met the inclusion criteria and quality standards were synthesized applying the internationally developed GRADE system. Each conclusion was then assessed as having strong, moderately strong, limited, or insufficient scientific evidence. If studies were not available, this was also noted. We found ED triage scales to be supported, at best, by limited and often insufficient evidence. The ability of the individual vital signs included in the different scales to predict outcome is seldom, if at all, studied in the ED setting. The scientific evidence to assess interrater agreement (reliability) was limited for one triage scale and insufficient or lacking for all other scales. Two of the scales yielded limited scientific evidence, and one scale yielded insufficient evidence, on which to assess the risk of early death or hospitalization in patients assigned to the two lowest triage levels on a 5-level scale (validity). PMID:21718476

Development and validation of the Core Beliefs Questionnaire in a sample of individuals with social anxiety disorder.

PubMed

Wong, Quincy J J; Gregory, Bree; Gaston, Jonathan E; Rapee, Ronald M; Wilson, Judith K; Abbott, Maree J

2017-01-01

Prominent cognitive models of social anxiety have consistently emphasised the importance of beliefs about the self in the aetiology and maintenance of social anxiety. The present study sought to develop and validate a new measure of core beliefs about the self for SAD, the Core Beliefs Questionnaire (CBQ). Three versions of the CBQ were developed: a Trait version (fundamental absolute statements about the self), a Contingent version (statements about the self related to a specific social-evaluative situation), and an Other version (statements about how others view the self in social-evaluative situations generally). The psychometric features of the scales were examined in clinical (n=269) and non-clinical (n=67) samples. Exploratory factor analysis yielded a one factor model for all three versions of the questionnaire. Total scores differentiated individuals with SAD from individuals without a psychiatric condition, and demonstrated excellent internal consistency. The three CBQ versions had positive associations with social anxiety while controlling for depression, although zero-order correlations indicated the Trait version was more strongly related to depression than social anxiety, the Contingent version was similarly related to depression and social anxiety, and the Other version was more strongly related to social anxiety than depression. Scores on all three versions of the CBQ reduced from pre- to post-treatment and this change predicted treatment outcome. This is the first validation study of the CBQ. This study provides initial support for the reliability and validity of the CBQ. Copyright © 2016 Elsevier B.V. All rights reserved.

The development of a brief self-report questionnaire to measure 'recent' rash impulsivity: a preliminary investigation of its validity and association with recent alcohol consumption.

PubMed

Mayhew, Matthew J; Powell, Jane H

2014-11-01

Traditionally, impulsivity has been regarded as a stable trait. However, a series of longitudinal and behavioural laboratory studies has found that impulsivity can fluctuate within individuals, suggesting that it has a state as well as a trait manifestation. Whilst existing impulsivity questionnaires tap the former, there is no self-report instrument to assess recent fluctuations in impulsivity. Research aims and design The present study set out to develop and undertake preliminary validation of a measure of 'recent' impulsivity, focusing in particular on Rash Impulsivity. Part of the construct validation of the resulting Recent Rash Impulsivity Scale (RRIS) entailed examining its association with recent alcohol intake, since there are well-documented reciprocal relationships between alcohol consumption and inhibitory control. In developing the RRIS, items from existing trait impulsivity questionnaires were converted into a 'previous two weeks' format. The pilot RRIS was then administered, along with a parallel trait version (Trait Rash Impulsivity Scale; TRIS) and a well-established trait impulsivity measure (the BIS-11; Patton, Stanford & Barratt, 1995), to two cohorts of first-year undergraduates aged 17 to 25 (N=240), on two occasions one month apart. Information about habitual and recent alcohol intake was also gathered. Factor analyses on both the RRIS and TRIS identified two factors: 'Cognitive Impulsivity' (CogImp) and 'Motor Impulsivity' (MotImp). Consistent with the RRIS being sensitive to fluctuations in impulsivity, it was found that, as predicted: i) the RRIS was somewhat less strongly correlated than the TRIS with an established trait measure (the BIS-11; Patton et al., 1995); ii) the test-retest stability of 'Total' scores (CogImp and MotImp) was weaker for the RRIS than the TRIS; iii) there was evidence that the RRIS MotImp and Total scales were more strongly predicted by recent alcohol intake than were their trait equivalents; and iv) the RRIS CogImp and Total scales correlated more strongly with their trait equivalents in participants whose alcohol consumption had remained stable recently (relative to their habitual intake), compared to those whose consumption had recently changed. These data suggest that transient changes in impulsivity can be assessed via self-report, and that the RRIS is sensitive to recent changes in alcohol intake. Subject to a more intensive and detailed validation, it is thus promising as a tool for tapping and characterising fluctuations in behavioural control and for exploring a range of factors to which this might be associated. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development of polyparameter linear free energy relationship models for octanol-air partition coefficients of diverse chemicals.

PubMed

Jin, Xiaochen; Fu, Zhiqiang; Li, Xuehua; Chen, Jingwen

2017-03-22

The octanol-air partition coefficient (K OA ) is a key parameter describing the partition behavior of organic chemicals between air and environmental organic phases. As the experimental determination of K OA is costly, time-consuming and sometimes limited by the availability of authentic chemical standards for the compounds to be determined, it becomes necessary to develop credible predictive models for K OA . In this study, a polyparameter linear free energy relationship (pp-LFER) model for predicting K OA at 298.15 K and a novel model incorporating pp-LFERs with temperature (pp-LFER-T model) were developed from 795 log K OA values for 367 chemicals at different temperatures (263.15-323.15 K), and were evaluated with the OECD guidelines on QSAR model validation and applicability domain description. Statistical results show that both models are well-fitted, robust and have good predictive capabilities. Particularly, the pp-LFER model shows a strong predictive ability for polyfluoroalkyl substances and organosilicon compounds, and the pp-LFER-T model maintains a high predictive accuracy within a wide temperature range (263.15-323.15 K).

Development and validation of optimal cut-off value in inter-arm systolic blood pressure difference for prediction of cardiovascular events.

PubMed

Hirono, Akira; Kusunose, Kenya; Kageyama, Norihito; Sumitomo, Masayuki; Abe, Masahiro; Fujinaga, Hiroyuki; Sata, Masataka

2018-01-01

An inter-arm systolic blood pressure difference (IAD) is associated with cardiovascular disease. The aim of this study was to develop and validate the optimal cut-off value of IAD as a predictor of major adverse cardiac events in patients with arteriosclerosis risk factors. From 2009 to 2014, 1076 patients who had at least one cardiovascular risk factor were included in the analysis. We defined 700 randomly selected patients as a development cohort to confirm that IAD was the predictor of cardiovascular events and to determine optimal cut-off value of IAD. Next, we validated outcomes in the remaining 376 patients as a validation cohort. The blood pressure (BP) of both arms measurements were done simultaneously using the ankle-brachial blood pressure index (ABI) form of automatic device. The primary endpoint was the cardiovascular event and secondary endpoint was the all-cause mortality. During a median period of 2.8 years, 143 patients reached the primary endpoint in the development cohort. In the multivariate Cox proportional hazards analysis, IAD was the strong predictor of cardiovascular events (hazard ratio: 1.03, 95% confidence interval: 1.01-1.05, p=0.005). The receiver operating characteristic curve revealed that 5mmHg was the optimal cut-off point of IAD to predict cardiovascular events (p<0.001). In the validation cohort, the presence of a large IAD (IAD ≥5mmHg) was significantly associated with the primary endpoint (p=0.021). IAD is significantly associated with future cardiovascular events in patients with arteriosclerosis risk factors. The optimal cut-off value of IAD is 5mmHg. Copyright © 2017 Japanese College of Cardiology. Published by Elsevier Ltd. All rights reserved.

The development of Attitudes of People from Ethnic Minorities to Help-Seeking for Dementia (APEND): a questionnaire to measure attitudes to help-seeking for dementia in people from South Asian backgrounds in the UK.

PubMed

Hailstone, Julia; Mukadam, Naaheed; Owen, Tamsin; Cooper, Claudia; Livingston, Gill

2017-03-01

People from South Asian backgrounds present to dementia services relatively late, often responding to crises. We aimed to devise and validate a theory of planned behaviour questionnaire to measure attitudes that predict medical help-seeking for UK-based South Asian people, to assess the effectiveness of future interventions promoting earlier help-seeking. We used focus groups to establish the content validity of culturally relevant questionnaire items, then asked participants to complete the questionnaire. We analysed reliability and validity and established the concurrent validity of questionnaire attitudes through correlation with willingness to seek help from a doctor for memory problems. We also correlated the scale with knowledge of dementia. The strongest predictor of willingness to seek help was perceived social pressure from significant others around help-seeking; these attitudes were associated with beliefs about the views of family members and embarrassment around help-seeking. Willingness to seek help was also strongly associated with attitudes about the benefits of seeing a doctor for memory problems, attitudes that were related to specific beliefs about what doctors can do to help. Attitudes in the questionnaire predicted 77% of variance in willingness to seek help, but no relationship was found with dementia knowledge. We present the Attitudes of People from Ethnic Minorities to Help-Seeking for Dementia (APEND) questionnaire, a valid and reliable measure of attitudes that influence help-seeking for dementia in people from South Asian backgrounds, which could assess the impact of intervention studies. We suggest that interventions target attitudes specified here, rather than dementia knowledge. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

PubMed

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

2016-08-01

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

Applications of machine learning in cancer prediction and prognosis.

PubMed

Cruz, Joseph A; Wishart, David S

2007-02-11

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to "learn" from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on "older" technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15-25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression.

Applications of Machine Learning in Cancer Prediction and Prognosis

PubMed Central

Cruz, Joseph A.; Wishart, David S.

2006-01-01

Machine learning is a branch of artificial intelligence that employs a variety of statistical, probabilistic and optimization techniques that allows computers to “learn” from past examples and to detect hard-to-discern patterns from large, noisy or complex data sets. This capability is particularly well-suited to medical applications, especially those that depend on complex proteomic and genomic measurements. As a result, machine learning is frequently used in cancer diagnosis and detection. More recently machine learning has been applied to cancer prognosis and prediction. This latter approach is particularly interesting as it is part of a growing trend towards personalized, predictive medicine. In assembling this review we conducted a broad survey of the different types of machine learning methods being used, the types of data being integrated and the performance of these methods in cancer prediction and prognosis. A number of trends are noted, including a growing dependence on protein biomarkers and microarray data, a strong bias towards applications in prostate and breast cancer, and a heavy reliance on “older” technologies such artificial neural networks (ANNs) instead of more recently developed or more easily interpretable machine learning methods. A number of published studies also appear to lack an appropriate level of validation or testing. Among the better designed and validated studies it is clear that machine learning methods can be used to substantially (15–25%) improve the accuracy of predicting cancer susceptibility, recurrence and mortality. At a more fundamental level, it is also evident that machine learning is also helping to improve our basic understanding of cancer development and progression. PMID:19458758

Random Forests to Predict Rectal Toxicity Following Prostate Cancer Radiation Therapy

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

Ospina, Juan D.; INSERM, U1099, Rennes; Escuela de Estadística, Universidad Nacional de Colombia Sede Medellín, Medellín

2014-08-01

Purpose: To propose a random forest normal tissue complication probability (RF-NTCP) model to predict late rectal toxicity following prostate cancer radiation therapy, and to compare its performance to that of classic NTCP models. Methods and Materials: Clinical data and dose-volume histograms (DVH) were collected from 261 patients who received 3-dimensional conformal radiation therapy for prostate cancer with at least 5 years of follow-up. The series was split 1000 times into training and validation cohorts. A RF was trained to predict the risk of 5-year overall rectal toxicity and bleeding. Parameters of the Lyman-Kutcher-Burman (LKB) model were identified and a logistic regression modelmore » was fit. The performance of all the models was assessed by computing the area under the receiving operating characteristic curve (AUC). Results: The 5-year grade ≥2 overall rectal toxicity and grade ≥1 and grade ≥2 rectal bleeding rates were 16%, 25%, and 10%, respectively. Predictive capabilities were obtained using the RF-NTCP model for all 3 toxicity endpoints, including both the training and validation cohorts. The age and use of anticoagulants were found to be predictors of rectal bleeding. The AUC for RF-NTCP ranged from 0.66 to 0.76, depending on the toxicity endpoint. The AUC values for the LKB-NTCP were statistically significantly inferior, ranging from 0.62 to 0.69. Conclusions: The RF-NTCP model may be a useful new tool in predicting late rectal toxicity, including variables other than DVH, and thus appears as a strong competitor to classic NTCP models.« less

An FMRI-compatible Symbol Search task.

PubMed

Liebel, Spencer W; Clark, Uraina S; Xu, Xiaomeng; Riskin-Jones, Hannah H; Hawkshead, Brittany E; Schwarz, Nicolette F; Labbe, Donald; Jerskey, Beth A; Sweet, Lawrence H

2015-03-01

Our objective was to determine whether a Symbol Search paradigm developed for functional magnetic resonance imaging (FMRI) is a reliable and valid measure of cognitive processing speed (CPS) in healthy older adults. As all older adults are expected to experience cognitive declines due to aging, and CPS is one of the domains most affected by age, establishing a reliable and valid measure of CPS that can be administered inside an MR scanner may prove invaluable in future clinical and research settings. We evaluated the reliability and construct validity of a newly developed FMRI Symbol Search task by comparing participants' performance in and outside of the scanner and to the widely used and standardized Symbol Search subtest of the Wechsler Adult Intelligence Scale (WAIS). A brief battery of neuropsychological measures was also administered to assess the convergent and discriminant validity of the FMRI Symbol Search task. The FMRI Symbol Search task demonstrated high test-retest reliability when compared to performance on the same task administered out of the scanner (r=.791; p<.001). The criterion validity of the new task was supported, as it exhibited a strong positive correlation with the WAIS Symbol Search (r=.717; p<.001). Predicted convergent and discriminant validity patterns of the FMRI Symbol Search task were also observed. The FMRI Symbol Search task is a reliable and valid measure of CPS in healthy older adults and exhibits expected sensitivity to the effects of age on CPS performance.

Predictive equations for lung volumes from computed tomography for size matching in pulmonary transplantation.

PubMed

Konheim, Jeremy A; Kon, Zachary N; Pasrija, Chetan; Luo, Qingyang; Sanchez, Pablo G; Garcia, Jose P; Griffith, Bartley P; Jeudy, Jean

2016-04-01

Size matching for lung transplantation is widely accomplished using height comparisons between donors and recipients. This gross approximation allows for wide variation in lung size and, potentially, size mismatch. Three-dimensional computed tomography (3D-CT) volumetry comparisons could offer more accurate size matching. Although recipient CT scans are universally available, donor CT scans are rarely performed. Therefore, predicted donor lung volumes could be used for comparison to measured recipient lung volumes, but no such predictive equations exist. We aimed to use 3D-CT volumetry measurements from a normal patient population to generate equations for predicted total lung volume (pTLV), predicted right lung volume (pRLV), and predicted left lung volume (pLLV), for size-matching purposes. Chest CT scans of 400 normal patients were retrospectively evaluated. 3D-CT volumetry was performed to measure total lung volume, right lung volume, and left lung volume of each patient, and predictive equations were generated. The fitted model was tested in a separate group of 100 patients. The model was externally validated by comparison of total lung volume with total lung capacity from pulmonary function tests in a subset of those patients. Age, gender, height, and race were independent predictors of lung volume. In the test group, there were strong linear correlations between predicted and actual lung volumes measured by 3D-CT volumetry for pTLV (r = 0.72), pRLV (r = 0.72), and pLLV (r = 0.69). A strong linear correlation was also observed when comparing pTLV and total lung capacity (r = 0.82). We successfully created a predictive model for pTLV, pRLV, and pLLV. These may serve as reference standards and predict donor lung volume for size matching in lung transplantation. Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.

The relation of rational and experiential information processing styles to personality, basic beliefs, and the ratio-bias phenomenon.

PubMed

Pacini, R; Epstein, S

1999-06-01

A new version of the Rational-Experiential Inventory (REI), which measures rational and experiential thinking styles and includes subscales of self-reported ability and engagement, was examined in two studies. In Study 1, the two main scales were independent, and they and their subscales exhibited discriminant validity and contributed to the prediction of a variety of measures beyond the contribution of the Big Five scales. A rational thinking style was most strongly and directly related to Ego Strength, Openness, Conscientiousness, and favorable basic beliefs about the self and the world, and it was most strongly inversely related to Neuroticism and Conservatism. An experiential thinking style was most strongly directly related to Extraversion, Agreeableness, Favorable Relationships Beliefs, and Emotional Expressivity, and it was most strongly inversely related to Categorical Thinking, Distrust of Others, and Intolerance. In Study 2, a rational thinking style was inversely related and an experiential thinking style was unrelated to nonoptimal responses in a game of chance. It was concluded that the new REI is a significant improvement over the previous version and measures unique aspects of personality.

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.

Predicting Global Fund grant disbursements for procurement of artemisinin-based combination therapies

PubMed Central

Cohen, Justin M; Singh, Inder; O'Brien, Megan E

2008-01-01

Background An accurate forecast of global demand is essential to stabilize the market for artemisinin-based combination therapy (ACT) and to ensure access to high-quality, life-saving medications at the lowest sustainable prices by avoiding underproduction and excessive overproduction, each of which can have negative consequences for the availability of affordable drugs. A robust forecast requires an understanding of the resources available to support procurement of these relatively expensive antimalarials, in particular from the Global Fund, at present the single largest source of ACT funding. Methods Predictive regression models estimating the timing and rate of disbursements from the Global Fund to recipient countries for each malaria grant were derived using a repeated split-sample procedure intended to avoid over-fitting. Predictions were compared against actual disbursements in a group of validation grants, and forecasts of ACT procurement extrapolated from disbursement predictions were evaluated against actual procurement in two sub-Saharan countries. Results Quarterly forecasts were correlated highly with actual smoothed disbursement rates (r = 0.987, p < 0.0001). Additionally, predicted ACT procurement, extrapolated from forecasted disbursements, was correlated strongly with actual ACT procurement supported by two grants from the Global Fund's first (r = 0.945, p < 0.0001) and fourth (r = 0.938, p < 0.0001) funding rounds. Conclusion This analysis derived predictive regression models that successfully forecasted disbursement patterning for individual Global Fund malaria grants. These results indicate the utility of this approach for demand forecasting of ACT and, potentially, for other commodities procured using funding from the Global Fund. Further validation using data from other countries in different regions and environments will be necessary to confirm its generalizability. PMID:18831742

The PRONE score: an algorithm for predicting doctors’ risks of formal patient complaints using routinely collected administrative data

PubMed Central

Spittal, Matthew J; Bismark, Marie M; Studdert, David M

2015-01-01

Background Medicolegal agencies—such as malpractice insurers, medical boards and complaints bodies—are mostly passive regulators; they react to episodes of substandard care, rather than intervening to prevent them. At least part of the explanation for this reactive role lies in the widely recognised difficulty of making robust predictions about medicolegal risk at the individual clinician level. We aimed to develop a simple, reliable scoring system for predicting Australian doctors’ risks of becoming the subject of repeated patient complaints. Methods Using routinely collected administrative data, we constructed a national sample of 13 849 formal complaints against 8424 doctors. The complaints were lodged by patients with state health service commissions in Australia over a 12-year period. We used multivariate logistic regression analysis to identify predictors of subsequent complaints, defined as another complaint occurring within 2 years of an index complaint. Model estimates were then used to derive a simple predictive algorithm, designed for application at the doctor level. Results The PRONE (Predicted Risk Of New Event) score is a 22-point scoring system that indicates a doctor's future complaint risk based on four variables: a doctor's specialty and sex, the number of previous complaints and the time since the last complaint. The PRONE score performed well in predicting subsequent complaints, exhibiting strong validity and reliability and reasonable goodness of fit (c-statistic=0.70). Conclusions The PRONE score appears to be a valid method for assessing individual doctors’ risks of attracting recurrent complaints. Regulators could harness such information to target quality improvement interventions, and prevent substandard care and patient dissatisfaction. The approach we describe should be replicable in other agencies that handle large numbers of patient complaints or malpractice claims. PMID:25855664

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

PubMed Central

Gusenleitner, Daniel; Auerbach, Scott S.; Melia, Tisha; Gómez, Harold F.; Sherr, David H.; Monti, Stefano

2014-01-01

Background Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity. Results In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical's carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors. Conclusion Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure. PMID:25058030

Genome-Enabled Estimates of Additive and Nonadditive Genetic Variances and Prediction of Apple Phenotypes Across Environments

PubMed Central

Kumar, Satish; Molloy, Claire; Muñoz, Patricio; Daetwyler, Hans; Chagné, David; Volz, Richard

2015-01-01

The nonadditive genetic effects may have an important contribution to total genetic variation of phenotypes, so estimates of both the additive and nonadditive effects are desirable for breeding and selection purposes. Our main objectives were to: estimate additive, dominance and epistatic variances of apple (Malus × domestica Borkh.) phenotypes using relationship matrices constructed from genome-wide dense single nucleotide polymorphism (SNP) markers; and compare the accuracy of genomic predictions using genomic best linear unbiased prediction models with or without including nonadditive genetic effects. A set of 247 clonally replicated individuals was assessed for six fruit quality traits at two sites, and also genotyped using an Illumina 8K SNP array. Across several fruit quality traits, the additive, dominance, and epistatic effects contributed about 30%, 16%, and 19%, respectively, to the total phenotypic variance. Models ignoring nonadditive components yielded upwardly biased estimates of additive variance (heritability) for all traits in this study. The accuracy of genomic predicted genetic values (GEGV) varied from about 0.15 to 0.35 for various traits, and these were almost identical for models with or without including nonadditive effects. However, models including nonadditive genetic effects further reduced the bias of GEGV. Between-site genotypic correlations were high (>0.85) for all traits, and genotype-site interaction accounted for <10% of the phenotypic variability. The accuracy of prediction, when the validation set was present only at one site, was generally similar for both sites, and varied from about 0.50 to 0.85. The prediction accuracies were strongly influenced by trait heritability, and genetic relatedness between the training and validation families. PMID:26497141

Mechanistic modelling of infrared mediated energy transfer during the primary drying step of a continuous freeze-drying process.

PubMed

Van Bockstal, Pieter-Jan; Mortier, Séverine Thérèse F C; De Meyer, Laurens; Corver, Jos; Vervaet, Chris; Nopens, Ingmar; De Beer, Thomas

2017-05-01

Conventional pharmaceutical freeze-drying is an inefficient and expensive batch-wise process, associated with several disadvantages leading to an uncontrolled end product variability. The proposed continuous alternative, based on spinning the vials during freezing and on optimal energy supply during drying, strongly increases process efficiency and improves product quality (uniformity). The heat transfer during continuous drying of the spin frozen vials is provided via non-contact infrared (IR) radiation. The energy transfer to the spin frozen vials should be optimised to maximise the drying efficiency while avoiding cake collapse. Therefore, a mechanistic model was developed which allows computing the optimal, dynamic IR heater temperature in function of the primary drying progress and which, hence, also allows predicting the primary drying endpoint based on the applied dynamic IR heater temperature. The model was validated by drying spin frozen vials containing the model formulation (3.9mL in 10R vials) according to the computed IR heater temperature profile. In total, 6 validation experiments were conducted. The primary drying endpoint was experimentally determined via in-line near-infrared (NIR) spectroscopy and compared with the endpoint predicted by the model (50min). The mean ratio of the experimental drying time to the predicted value was 0.91, indicating a good agreement between the model predictions and the experimental data. The end product had an elegant product appearance (visual inspection) and an acceptable residual moisture content (Karl Fischer). Copyright © 2017 Elsevier B.V. All rights reserved.

Robust prediction of individual creative ability from brain functional connectivity.

PubMed

Beaty, Roger E; Kenett, Yoed N; Christensen, Alexander P; Rosenberg, Monica D; Benedek, Mathias; Chen, Qunlin; Fink, Andreas; Qiu, Jiang; Kwapil, Thomas R; Kane, Michael J; Silvia, Paul J

2018-01-30

People's ability to think creatively is a primary means of technological and cultural progress, yet the neural architecture of the highly creative brain remains largely undefined. Here, we employed a recently developed method in functional brain imaging analysis-connectome-based predictive modeling-to identify a brain network associated with high-creative ability, using functional magnetic resonance imaging (fMRI) data acquired from 163 participants engaged in a classic divergent thinking task. At the behavioral level, we found a strong correlation between creative thinking ability and self-reported creative behavior and accomplishment in the arts and sciences ( r = 0.54). At the neural level, we found a pattern of functional brain connectivity related to high-creative thinking ability consisting of frontal and parietal regions within default, salience, and executive brain systems. In a leave-one-out cross-validation analysis, we show that this neural model can reliably predict the creative quality of ideas generated by novel participants within the sample. Furthermore, in a series of external validation analyses using data from two independent task fMRI samples and a large task-free resting-state fMRI sample, we demonstrate robust prediction of individual creative thinking ability from the same pattern of brain connectivity. The findings thus reveal a whole-brain network associated with high-creative ability comprised of cortical hubs within default, salience, and executive systems-intrinsic functional networks that tend to work in opposition-suggesting that highly creative people are characterized by the ability to simultaneously engage these large-scale brain networks.

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.

The development and validation of the AMPREDICT model for predicting mobility outcome after dysvascular lower extremity amputation.

PubMed

Czerniecki, Joseph M; Turner, Aaron P; Williams, Rhonda M; Thompson, Mary Lou; Landry, Greg; Hakimi, Kevin; Speckman, Rebecca; Norvell, Daniel C

2017-01-01

The objective of this study was the development of AMPREDICT-Mobility, a tool to predict the probability of independence in either basic or advanced (iBASIC or iADVANCED) mobility 1 year after dysvascular major lower extremity amputation. Two prospective cohort studies during consecutive 4-year periods (2005-2009 and 2010-2014) were conducted at seven medical centers. Multiple demographic and biopsychosocial predictors were collected in the periamputation period among individuals undergoing their first major amputation because of complications of peripheral arterial disease or diabetes. The primary outcomes were iBASIC and iADVANCED mobility, as measured by the Locomotor Capabilities Index. Combined data from both studies were used for model development and internal validation. Backwards stepwise logistic regression was used to develop the final prediction models. The discrimination and calibration of each model were assessed. Internal validity of each model was assessed with bootstrap sampling. Twelve-month follow-up was reached by 157 of 200 (79%) participants. Among these, 54 (34%) did not achieve iBASIC mobility, 103 (66%) achieved at least iBASIC mobility, and 51 (32%) also achieved iADVANCED mobility. Predictive factors associated with reduced odds of achieving iBASIC mobility were increasing age, chronic obstructive pulmonary disease, dialysis, diabetes, prior history of treatment for depression or anxiety, and very poor to fair self-rated health. Those who were white, were married, and had at least a high-school degree had a higher probability of achieving iBASIC mobility. The odds of achieving iBASIC mobility increased with increasing body mass index up to 30 kg/m 2 and decreased with increasing body mass index thereafter. The prediction model of iADVANCED mobility included the same predictors with the exception of diabetes, chronic obstructive pulmonary disease, and education level. Both models showed strong discrimination with C statistics of 0.85 and 0.82, respectively. The mean difference in predicted probabilities for those who did and did not achieve iBASIC and iADVANCED mobility was 33% and 29%, respectively. Tests for calibration and observed vs predicted plots suggested good fit for both models; however, the precision of the estimates of the predicted probabilities was modest. Internal validation through bootstrapping demonstrated some overoptimism of the original model development, with the optimism-adjusted C statistic for iBASIC and iADVANCED mobility being 0.74 and 0.71, respectively, and the discrimination slope 19% and 16%, respectively. AMPREDICT-Mobility is a user-friendly prediction tool that can inform the patient undergoing a dysvascular amputation and the patient's provider about the probability of independence in either basic or advanced mobility at each major lower extremity amputation level. Copyright © 2016 Society for Vascular Surgery. All rights reserved.

Heaviest Nuclei: New Element with Atomic Number 117

ScienceCinema

Oganessian, Yuri

2018-01-24

One of the fundamental outcomes of the nuclear shell model is the prediction of the 'stability islands' in the domain of the hypothetical super heavy elements. The talk is devoted to the experimental verification of these predictions - the synthesis and study of both the decay and chemical properties of the super heavy elements. The discovery of a new chemical element with atomic number Z=117 is reported. The isotopes 293117 and 294117 were produced in fusion reactions between 48Ca and 249Bk. Decay chains involving 11 new nuclei were identified by means of the Dubna gas-filled recoil separator. The measured decay properties show a strong rise of stability for heavier isotopes with Z =111, validating the concept of the long sought island of enhanced stability for heaviest nuclei.

Ares I-X Post Flight Ignition Overpressure Review

NASA Technical Reports Server (NTRS)

Alvord, David A.

2010-01-01

Ignition Overpressure (IOP) is an unsteady fluid flow and acoustic phenomena caused by the rapid expansion of gas from the rocket nozzle within a ducted launching space resulting in an initially higher amplitude pressure wave. This wave is potentially dangerous to the structural integrity of the vehicle. An in-depth look at the IOP environments resulting from the Ares I-X Solid Rocket Booster configuration showed high correlation between the pre-flight predictions and post-flight analysis results. Correlation between the chamber pressure and IOP transients showed successful acoustic mitigation, containing the strongest IOP waves below the Mobile Launch Pad deck. The flight data allowed subsequent verification and validation of Ares I-X unsteady fluid ducted launcher predictions, computational fluid dynamic models, and strong correlation with historical Shuttle data.

Early Prognostication Markers in Cardiac Arrest Patients Treated with Hypothermia

PubMed Central

Karapetkova, Maria; Koenig, Matthew A.; Jia, Xiaofeng

2015-01-01

Background and purpose Established prognostication markers, such as clinical findings, electroencephalography (EEG), and biochemical markers, used by clinicians to predict neurologic outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. Methods MEDLINE and EMBASE were searched for evidence on the current standards for neurologic outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers, and multimodal approaches for prognostication were included and reviewed. Results While the prognostic accuracy of various tests has been questioned after TH, pupillary light reflexes and somatosensory evoked potentials (SSEP) are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 hours after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as MRI and CT, can identify functional and structural brain injury, but are not readily available at the patient’s bedside because of limited availability and high costs. Conclusions A multimodal algorithm composed of neurological examination, EEG-based quantitative testing, and SSEP, in conjunction with newer MRI sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed later than 72 hours after CA. PMID:26228521

Early prognostication markers in cardiac arrest patients treated with hypothermia.

PubMed

Karapetkova, M; Koenig, M A; Jia, X

2016-03-01

Established prognostication markers, such as clinical findings, electroencephalography (EEG) and biochemical markers, used by clinicians to predict neurological outcome after cardiac arrest (CA) are altered under therapeutic hypothermia (TH) conditions and their validity remains uncertain. MEDLINE and Embase were searched for evidence on the current standards for neurological outcome prediction for out-of-hospital CA patients treated with TH and the validity of a wide range of prognostication markers. Relevant studies that suggested one or several established biomarkers and multimodal approaches for prognostication are included and reviewed. Whilst the prognostic accuracy of various tests after TH has been questioned, pupillary light reflexes and somatosensory evoked potentials are still strongly associated with negative outcome for early prognostication. Increasingly, EEG background activity has also been identified as a valid predictor for outcome after 72 h after CA and a preferred prognostic method in clinical settings. Neuroimaging techniques, such as magnetic resonance imaging and computed tomography, can identify functional and structural brain injury but are not readily available at the patient's bedside because of limited availability and high costs. A multimodal algorithm composed of neurological examination, EEG-based quantitative testing and somatosensory evoked potentials, in conjunction with newer magnetic resonance imaging sequences, if available, holds promise for accurate prognostication in CA patients treated with TH. In order to avoid premature withdrawal of care, prognostication should be performed more than 72 h after CA. © 2015 EAN.

A hybrid approach to estimating national scale spatiotemporal variability of PM2.5 in the contiguous United States.

PubMed

Beckerman, Bernardo S; Jerrett, Michael; Serre, Marc; Martin, Randall V; Lee, Seung-Jae; van Donkelaar, Aaron; Ross, Zev; Su, Jason; Burnett, Richard T

2013-07-02

Airborne fine particulate matter exhibits spatiotemporal variability at multiple scales, which presents challenges to estimating exposures for health effects assessment. Here we created a model to predict ambient particulate matter less than 2.5 μm in aerodynamic diameter (PM2.5) across the contiguous United States to be applied to health effects modeling. We developed a hybrid approach combining a land use regression model (LUR) selected with a machine learning method, and Bayesian Maximum Entropy (BME) interpolation of the LUR space-time residuals. The PM2.5 data set included 104,172 monthly observations at 1464 monitoring locations with approximately 10% of locations reserved for cross-validation. LUR models were based on remote sensing estimates of PM2.5, land use and traffic indicators. Normalized cross-validated R(2) values for LUR were 0.63 and 0.11 with and without remote sensing, respectively, suggesting remote sensing is a strong predictor of ground-level concentrations. In the models including the BME interpolation of the residuals, cross-validated R(2) were 0.79 for both configurations; the model without remotely sensed data described more fine-scale variation than the model including remote sensing. Our results suggest that our modeling framework can predict ground-level concentrations of PM2.5 at multiple scales over the contiguous U.S.

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

PubMed

Stanhope, Victoria; Solomon, Phyllis

2007-06-01

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

Analysis of general power counting rules in effective field theory

DOE PAGES

Gavela, Belen; Jenkins, Elizabeth E.; Manohar, Aneesh V.; ...

2016-09-02

We derive the general counting rules for a quantum effective field theory (EFT) in d dimensions. The rules are valid for strongly and weakly coupled theories, and they predict that all kinetic energy terms are canonically normalized. They determine the energy dependence of scattering cross sections in the range of validity of the EFT expansion. We show that the size of the cross sections is controlled by the Λ power counting of EFT, not by chiral counting, even for chiral perturbation theory (χPT). The relation between Λ and f is generalized to d dimensions. We show that the naive dimensionalmore » analysis 4π counting is related to ℏ counting. The EFT counting rules are applied to χPT, low-energy weak interactions, Standard Model EFT and the non-trivial case of Higgs EFT.« less

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

ERIC Educational Resources Information Center

Jones, Robert F.; Thomae-Forgues, Maria

1984-01-01

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

Real-time monitoring of high-gravity corn mash fermentation using in situ raman spectroscopy.

PubMed

Gray, Steven R; Peretti, Steven W; Lamb, H Henry

2013-06-01

In situ Raman spectroscopy was employed for real-time monitoring of simultaneous saccharification and fermentation (SSF) of corn mash by an industrial strain of Saccharomyces cerevisiae. An accurate univariate calibration model for ethanol was developed based on the very strong 883 cm(-1) C-C stretching band. Multivariate partial least squares (PLS) calibration models for total starch, dextrins, maltotriose, maltose, glucose, and ethanol were developed using data from eight batch fermentations and validated using predictions for a separate batch. The starch, ethanol, and dextrins models showed significant prediction improvement when the calibration data were divided into separate high- and low-concentration sets. Collinearity between the ethanol and starch models was avoided by excluding regions containing strong ethanol peaks from the starch model and, conversely, excluding regions containing strong saccharide peaks from the ethanol model. The two-set calibration models for starch (R(2)  = 0.998, percent error = 2.5%) and ethanol (R(2)  = 0.999, percent error = 2.1%) provide more accurate predictions than any previously published spectroscopic models. Glucose, maltose, and maltotriose are modeled to accuracy comparable to previous work on less complex fermentation processes. Our results demonstrate that Raman spectroscopy is capable of real time in situ monitoring of a complex industrial biomass fermentation. To our knowledge, this is the first PLS-based chemometric modeling of corn mash fermentation under typical industrial conditions, and the first Raman-based monitoring of a fermentation process with glucose, oligosaccharides and polysaccharides present. Copyright © 2013 Wiley Periodicals, Inc.

One-electron reduced density matrices of strongly correlated harmonium atoms.

PubMed

Cioslowski, Jerzy

2015-03-21

Explicit asymptotic expressions are derived for the reduced one-electron density matrices (the 1-matrices) of strongly correlated two- and three-electron harmonium atoms in the ground and first excited states. These expressions, which are valid at the limit of small confinement strength ω, yield electron densities and kinetic energies in agreement with the published values. In addition, they reveal the ω(5/6) asymptotic scaling of the exchange components of the electron-electron repulsion energies that differs from the ω(2/3) scaling of their Coulomb and correlation counterparts. The natural orbitals of the totally symmetric ground state of the two-electron harmonium atom are found to possess collective occupancies that follow a mixed power/Gaussian dependence on the angular momentum in variance with the simple power-law prediction of Hill's asymptotics. Providing rigorous constraints on energies as functionals of 1-matrices, these results are expected to facilitate development of approximate implementations of the density matrix functional theory and ensure their proper description of strongly correlated systems.

Real-time numerical forecast of global epidemic spreading: case study of 2009 A/H1N1pdm.

PubMed

Tizzoni, Michele; Bajardi, Paolo; Poletto, Chiara; Ramasco, José J; Balcan, Duygu; Gonçalves, Bruno; Perra, Nicola; Colizza, Vittoria; Vespignani, Alessandro

2012-12-13

Mathematical and computational models for infectious diseases are increasingly used to support public-health decisions; however, their reliability is currently under debate. Real-time forecasts of epidemic spread using data-driven models have been hindered by the technical challenges posed by parameter estimation and validation. Data gathered for the 2009 H1N1 influenza crisis represent an unprecedented opportunity to validate real-time model predictions and define the main success criteria for different approaches. We used the Global Epidemic and Mobility Model to generate stochastic simulations of epidemic spread worldwide, yielding (among other measures) the incidence and seeding events at a daily resolution for 3,362 subpopulations in 220 countries. Using a Monte Carlo Maximum Likelihood analysis, the model provided an estimate of the seasonal transmission potential during the early phase of the H1N1 pandemic and generated ensemble forecasts for the activity peaks in the northern hemisphere in the fall/winter wave. These results were validated against the real-life surveillance data collected in 48 countries, and their robustness assessed by focusing on 1) the peak timing of the pandemic; 2) the level of spatial resolution allowed by the model; and 3) the clinical attack rate and the effectiveness of the vaccine. In addition, we studied the effect of data incompleteness on the prediction reliability. Real-time predictions of the peak timing are found to be in good agreement with the empirical data, showing strong robustness to data that may not be accessible in real time (such as pre-exposure immunity and adherence to vaccination campaigns), but that affect the predictions for the attack rates. The timing and spatial unfolding of the pandemic are critically sensitive to the level of mobility data integrated into the model. Our results show that large-scale models can be used to provide valuable real-time forecasts of influenza spreading, but they require high-performance computing. The quality of the forecast depends on the level of data integration, thus stressing the need for high-quality data in population-based models, and of progressive updates of validated available empirical knowledge to inform these models.

Multilingual Validation of the Questionnaire for Verifying Stroke-Free Status in West Africa

PubMed Central

Sarfo, Fred; Gebregziabher, Mulugeta; Ovbiagele, Bruce; Akinyemi, Rufus; Owolabi, Lukman; Obiako, Reginald; Akpa, Onoja; Armstrong, Kevin; Akpalu, Albert; Adamu, Sheila; Obese, Vida; Boa-Antwi, Nana; Appiah, Lambert; Arulogun, Oyedunni; Mensah, Yaw; Adeoye, Abiodun; Tosin, Aridegbe; Adeleye, Osimhiarherhuo; Tabi-Ajayi, Eric; Phillip, Ibinaiye; Sani, Abubakar; Isah, Suleiman; Tabari, Nasir; Mande, Aliyu; Agunloye, Atinuke; Ogbole, Godwin; Akinyemi, Joshua; Laryea, Ruth; Melikam, Sylvia; Uvere, Ezinne; Adekunle, Gregory; Kehinde, Salaam; Azuh, Paschal; Dambatta, Abdul; Ishaq, Naser; Saulson, Raelle; Arnett, Donna; Tiwari, Hemnant; Jenkins, Carolyn; Lackland, Dan; Owolabi, Mayowa

2015-01-01

Background and Purpose The Questionnaire for Verifying Stroke-free Status (QVSFS), a method for verifying stroke-free status in participants of clinical, epidemiological and genetic studies, has not been validated in low-income settings where populations have limited knowledge of stroke symptoms. We aimed to validate QVSFS in 3 languages-Yoruba, Hausa and Akan- for ascertainment of stroke-free status of control subjects enrolled in an ongoing stroke epidemiological study in West Africa. Methods Data were collected using a cross-sectional study design where 384 participants were consecutively recruited from neurology and general medicine clinics of 5 tertiary referral hospitals in Nigeria and Ghana. Ascertainment of stroke status was by neurologists using structured neurological examination, review of case records and neuro-imaging (Gold standard). Relative performance of QVSFS without and with pictures of stroke symptoms (pictograms) was assessed using sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Results The overall median age of the study participants was 54 years and 48.4% were males. Of 165 stroke cases identified by Gold standard, 98% were determined to have had stroke while of 219 without stroke 87% were determined to be stroke-free by QVSFS. NPV of the QVSFS across the 3 languages was 0.97 (range, 0.93 – 1.00), sensitivity, specificity and PPV were 0.98, 0.82 and 0.80 respectively. Agreement between the questionnaire with and without the pictogram was excellent/strong with Cohen’s k=0.92. Conclusions QVSFS is a valid tool for verifying stroke-free status across culturally diverse populations in West Africa. PMID:26578660

A Comparison of EAST Shock-Tube Radiation Measurements with a New Air Radiation Model

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.

2008-01-01

This paper presents a comparison between the recent EAST shock tube radiation measurements (Grinstead et al., AIAA 2008-1244) and the HARA radiation model. The equilibrium and nonequilibrium radiation measurements are studied for conditions relevant to lunar-return shock-layers; specifically shock velocities ranging from 9 to 11 kilometers per second at initial pressures of 0.1 and 0.3 Torr. The simulated shock-tube flow is assumed one-dimensional and is calculated using the LAURA code, while a detailed nonequilibrium radiation prediction is obtained in an uncoupled manner from the HARA code. The measured and predicted intensities are separated into several spectral ranges to isolate significant spectral features, mainly strong atomic line multiplets. The equations and physical data required for the prediction of these strong atomic lines are reviewed and their uncertainties identified. The 700-1020 nm wavelength range, which accounts for roughly 30% of the radiative flux to a peak-heating lunar return shock-layer, is studied in detail and the measurements and predictions are shown to agree within 15% in equilibrium. The plus or minus 1.5% uncertainty on the measured shock velocity is shown to cause up to a plus or minus 30% difference in the predicted radiation. This band of predictions contains the measured values in almost all cases. For the highly nonequilibrium 0.1 Torr cases, the nonequilibrium radiation peaks are under-predicted by about half. This under-prediction is considered acceptable when compared to the order-of-magnitude over-prediction obtained using a Boltzmann population of electronic states. The reasonable comparison in the nonequilibrium regions provides validation for both the non-Boltzmann modeling in HARA and the thermochemical nonequilibrium modeling in LAURA. The N2 (+)(1-) and N2(2+) molecular band systems are studied in the 290 480 nm wavelength range for both equilibrium and nonequilibrium regimes. The non-Boltzmann rate models for these systems, which have significant uncertainties, are tuned to improve the comparison with measurements.

Long-term prediction of fish growth under varying ambient temperature using a multiscale dynamic model

PubMed Central

2009-01-01

Background Feed composition has a large impact on the growth of animals, particularly marine fish. We have developed a quantitative dynamic model that can predict the growth and body composition of marine fish for a given feed composition over a timespan of several months. The model takes into consideration the effects of environmental factors, particularly temperature, on growth, and it incorporates detailed kinetics describing the main metabolic processes (protein, lipid, and central metabolism) known to play major roles in growth and body composition. Results For validation, we compared our model's predictions with the results of several experimental studies. We showed that the model gives reliable predictions of growth, nutrient utilization (including amino acid retention), and body composition over a timespan of several months, longer than most of the previously developed predictive models. Conclusion We demonstrate that, despite the difficulties involved, multiscale models in biology can yield reasonable and useful results. The model predictions are reliable over several timescales and in the presence of strong temperature fluctuations, which are crucial factors for modeling marine organism growth. The model provides important improvements over existing models. PMID:19903354

Comparative values of medical school assessments in the prediction of internship performance.

PubMed

Lee, Ming; Vermillion, Michelle

2018-02-01

Multiple undergraduate achievements have been used for graduate admission consideration. Their relative values in the prediction of residency performance are not clear. This study compared the contributions of major undergraduate assessments to the prediction of internship performance. Internship performance ratings of the graduates of a medical school were collected from 2012 to 2015. Hierarchical multiple regression analyses were used to examine the predictive values of undergraduate measures assessing basic and clinical sciences knowledge and clinical performances, after controlling for differences in the Medical College Admission Test (MCAT). Four hundred eighty (75%) graduates' archived data were used in the study. Analyses revealed that clinical competencies, assessed by the USMLE Step 2 CK, NBME medicine exam, and an eight-station objective structured clinical examination (OSCE), were strong predictors of internship performance. Neither the USMLE Step 1 nor the inpatient internal medicine clerkship evaluation predicted internship performance. The undergraduate assessments as a whole showed a significant collective relationship with internship performance (ΔR 2  = 0.12, p < 0.001). The study supports the use of clinical competency assessments, instead of pre-clinical measures, in graduate admission consideration. It also provides validity evidence for OSCE scores in the prediction of workplace performance.

Comparison of Antioxidant Evaluation Assays for Investigating Antioxidative Activity of Gallic Acid and Its Alkyl Esters in Different Food Matrices.

PubMed

Phonsatta, Natthaporn; Deetae, Pawinee; Luangpituksa, Pairoj; Grajeda-Iglesias, Claudia; Figueroa-Espinoza, Maria Cruz; Le Comte, Jérôme; Villeneuve, Pierre; Decker, Eric A; Visessanguan, Wonnop; Panya, Atikorn

2017-08-30

The addition of antioxidants is one of the strategies to inhibit lipid oxidation, a major cause of lipid deterioration in foods leading to rancidity development and nutritional losses. However, several studies have been reported that conventional antioxidant assays, e.g., TPC, ABTS, FRAP, and ORAC could not predict antioxidant performance in several foods. This study aimed to investigate the performance of two recently developed assays, e.g., the conjugated autoxidizable triene (CAT) and the apolar radical-initiated conjugated autoxidizable triene (ApoCAT) assays to predict the antioxidant effectiveness of gallic acid and its esters in selected food models in comparison with the conventional antioxidant assays. The results indicated that the polarities of the antioxidants have a strong impact on antioxidant activities. In addition, different oxidant locations demonstrated by the CAT and ApoCAT assays influenced the overall antioxidant performances of the antioxidants with different polarities. To validate the predictability of the assays, the antioxidative performance of gallic acid and its alkyl esters was investigated in oil-in-water (O/W) emulsions, bulk soybean oils, and roasted peanuts as the lipid food models. The results showed that only the ApoCAT assay could be able to predict the antioxidative performances in O/W emulsions regardless of the antioxidant polarities. This study demonstrated that the relevance of antioxidant assays to food models was strongly dependent on physical similarities between the tested assays and the food structure matrices.

An attempt at predicting blood β-hydroxybutyrate from Fourier-transform mid-infrared spectra of milk using multivariate mixed models in Polish dairy cattle.

PubMed

Belay, T K; Dagnachew, B S; Kowalski, Z M; Ådnøy, T

2017-08-01

Fourier transform mid-infrared (FT-MIR) spectra of milk are commonly used for phenotyping of traits of interest through links developed between the traits and milk FT-MIR spectra. Predicted traits are then used in genetic analysis for ultimate phenotypic prediction using a single-trait mixed model that account for cows' circumstances at a given test day. Here, this approach is referred to as indirect prediction (IP). Alternatively, FT-MIR spectral variable can be kept multivariate in the form of factor scores in REML and BLUP analyses. These BLUP predictions, including phenotype (predicted factor scores), were converted to single-trait through calibration outputs; this method is referred to as direct prediction (DP). The main aim of this study was to verify whether mixed modeling of milk spectra in the form of factors scores (DP) gives better prediction of blood β-hydroxybutyrate (BHB) than the univariate approach (IP). Models to predict blood BHB from milk spectra were also developed. Two data sets that contained milk FT-MIR spectra and other information on Polish dairy cattle were used in this study. Data set 1 (n = 826) also contained BHB measured in blood samples, whereas data set 2 (n = 158,028) did not contain measured blood values. Part of data set 1 was used to calibrate a prediction model (n = 496) and the remaining part of data set 1 (n = 330) was used to validate the calibration models, as well as to evaluate the DP and IP approaches. Dimensions of FT-MIR spectra in data set 2 were reduced either into 5 or 10 factor scores (DP) or into a single trait (IP) with calibration outputs. The REML estimates for these factor scores were found using WOMBAT. The BLUP values and predicted BHB for observations in the validation set were computed using the REML estimates. Blood BHB predicted from milk FT-MIR spectra by both approaches were regressed on reference blood BHB that had not been used in the model development. Coefficients of determination in cross-validation for untransformed blood BHB were from 0.21 to 0.32, whereas that for the log-transformed BHB were from 0.31 to 0.38. The corresponding estimates in validation were from 0.29 to 0.37 and 0.21 to 0.43, respectively, for untransformed and logarithmic BHB. Contrary to expectation, slightly better predictions of BHB were found when univariate variance structure was used (IP) than when multivariate covariance structures were used (DP). Conclusive remarks on the importance of keeping spectral data in multivariate form for prediction of phenotypes may be found in data sets where the trait of interest has strong relationships with spectral variables. The Authors. Published by the Federation of Animal Science Societies and Elsevier Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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

PubMed

Donatelli, Richard E; Lee, Shin-Jae

2015-02-01

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

Predictive validity of the structured assessment of violence risk in youth: A 4-year follow-up.

PubMed

Gammelgård, Monica; Koivisto, Anna-Maija; Eronen, Markku; Kaltiala-Heino, Riittakerttu

2015-07-01

Structured violence risk assessment is an essential part of treatment planning for violent young people. The Structured Assessment of Violence Risk in Youth (SAVRY) has been shown to have good reliability and validity in a range of settings but has hardly been studied in adolescent mental health services. This study aimed to evaluate the long-term predictive validity of the SAVRY in adolescent psychiatry settings. In a prospective study, 200 SAVRY assessments of adolescents were acquired from psychiatric, forensic and correctional settings. Re-offending records from the Finnish National Crime Register were collected. Receiver operating curve statistics were applied. High SAVRY total and individual subscale scores and low values on the protective factor subscale were significantly associated with subsequent adverse outcomes, but the predictive value of the total score was weak. At the risk item level, those indicating antisocial lifestyle, absence of social support and pro-social involvement were strong indicators of subsequent criminal convictions, with or without violence. The SAVRY summary risk rating was the best indicator of likelihood of being convicted of a violent crime. After allowing for sex, age, psychiatric diagnosis and treatment setting, for example, conviction for a violent crime was over nine times more likely among those young people given high SAVRY summary risk ratings. The SAVRY is a valid and useful method for assessing both short-term and long-term risks of violent and non-violent crime by young people in psychiatric as well as criminal justice settings, adding to a traditional risk-centred assessment approach by also indicating where future preventive treatment efforts should be targeted. The next steps should be to evaluate its role in everyday clinical practice when using the knowledge generated to inform and monitor management and treatment strategies. Copyright © 2014 John Wiley & Sons, Ltd.

Does the Current Minimum Validate (or Invalidate) Cycle Prediction Methods?

NASA Technical Reports Server (NTRS)

Hathaway, David H.

2010-01-01

This deep, extended solar minimum and the slow start to Cycle 24 strongly suggest that Cycle 24 will be a small cycle. A wide array of solar cycle prediction techniques have been applied to predicting the amplitude of Cycle 24 with widely different results. Current conditions and new observations indicate that some highly regarded techniques now appear to have doubtful utility. Geomagnetic precursors have been reliable in the past and can be tested with 12 cycles of data. Of the three primary geomagnetic precursors only one (the minimum level of geomagnetic activity) suggests a small cycle. The Sun's polar field strength has also been used to successfully predict the last three cycles. The current weak polar fields are indicative of a small cycle. For the first time, dynamo models have been used to predict the size of a solar cycle but with opposite predictions depending on the model and the data assimilation. However, new measurements of the surface meridional flow indicate that the flow was substantially faster on the approach to Cycle 24 minimum than at Cycle 23 minimum. In both dynamo predictions a faster meridional flow should have given a shorter cycle 23 with stronger polar fields. This suggests that these dynamo models are not yet ready for solar cycle prediction.

Scaling laws and bulk-boundary decoupling in heat flow.

PubMed

del Pozo, Jesús J; Garrido, Pedro L; Hurtado, Pablo I

2015-03-01

When driven out of equilibrium by a temperature gradient, fluids respond by developing a nontrivial, inhomogeneous structure according to the governing macroscopic laws. Here we show that such structure obeys strikingly simple scaling laws arbitrarily far from equilibrium, provided that both macroscopic local equilibrium and Fourier's law hold. Extensive simulations of hard disk fluids confirm the scaling laws even under strong temperature gradients, implying that Fourier's law remains valid in this highly nonlinear regime, with putative corrections absorbed into a nonlinear conductivity functional. In addition, our results show that the scaling laws are robust in the presence of strong finite-size effects, hinting at a subtle bulk-boundary decoupling mechanism which enforces the macroscopic laws on the bulk of the finite-sized fluid. This allows one to measure the marginal anomaly of the heat conductivity predicted for hard disks.

Criterion validation of two submaximal aerobic fitness tests, the self-monitoring Fox-walk test and the Åstrand cycle test in people with rheumatoid arthritis.

PubMed

Nordgren, Birgitta; Fridén, Cecilia; Jansson, Eva; Österlund, Ted; Grooten, Wilhelmus Johannes; Opava, Christina H; Rickenlund, Anette

2014-09-17

Aerobic capacity tests are important to evaluate exercise programs and to encourage individuals to have a physically active lifestyle. Submaximal tests, if proven valid and reliable could be used for estimation of maximal oxygen uptake (VO2max). The purpose of the study was to examine the criterion-validity of the submaximal self-monitoring Fox-walk test and the submaximal Åstrand cycle test against a maximal cycle test in people with rheumatoid arthritis (RA). A secondary aim was to study the influence of different formulas for age predicted maximal heart rate when estimating VO2max by the Åstrand test. Twenty seven subjects (81% female), mean (SD) age 62 (8.1) years, diagnosed with RA since 17.9 (11.7) years, participated in the study. They performed the Fox-walk test (775 meters), the Åstrand test and the maximal cycle test (measured VO2max test). Pearson's correlation coefficients were calculated to determine the direction and strength of the association between the tests, and paired t-tests were used to test potential differences between the tests. Bland and Altman methods were used to assess whether there was any systematic disagreement between the submaximal tests and the maximal test. The correlation between the estimated and measured VO2max values were strong and ranged between r = 0.52 and r = 0.82 including the use of different formulas for age predicted maximal heart rate, when estimating VO2max by the Åstrand test. VO2max was overestimated by 30% by the Fox-walk test and underestimated by 10% by the Åstrand test corrected for age. When the different formulas for age predicted maximal heart rate were used, the results showed that two formulas better predicted maximal heart rate and consequently a more precise estimation of VO2max. Despite the fact that the Fox-walk test overestimated VO2max substantially, the test is a promising method for self-monitoring VO2max and further development of the test is encouraged. The Åstrand test should be considered as highly valid and feasible and the two newly developed formulas for predicting maximal heart rate according to age are preferable to use when estimating VO2max by the Åstrand test.

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

PubMed

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

2015-03-01

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

Real-time sampling of reasons for hedonic food consumption: further validation of the Palatable Eating Motives Scale

PubMed Central

Boggiano, Mary M.; Wenger, Lowell E.; Turan, Bulent; Tatum, Mindy M.; Sylvester, Maria D.; Morgan, Phillip R.; Morse, Kathryn E.; Burgess, Emilee E.

2015-01-01

Highly palatable foods play a salient role in obesity and binge-eating, and if habitually eaten to deal with intrinsic and extrinsic factors unrelated to metabolic need, may compromise adaptive coping and interpersonal skills. This study used event sampling methodology (ESM) to examine whether individuals who report eating palatable foods primarily to cope, to enhance reward, to be social, or to conform, as measured by the Palatable Eating Motives Scale (PEMS), actually eat these foods primarily for the motive(s) they report on the PEMS. Secondly this study examined if the previously reported ability of the PEMS Coping motive to predict BMI would replicate if the real-time (ESM-reported) coping motive was used to predict BMI. A total of 1691 palatable eating events were collected from 169 college students over 4 days. Each event included the day, time, and types of tasty foods or drinks consumed followed by a survey that included an abbreviated version of the PEMS, hunger as an additional possible motive, and a question assessing general perceived stress during the eating event. Two-levels mixed modeling confirmed that ESM-reported motives correlated most strongly with their respective PEMS motives and that all were negatively associated with eating for hunger. While stress surrounding the eating event was strongly associated with the ESM-coping motive, its inclusion in the model as a predictor of this motive did not abolish the significant association between ESM and PEMS Coping scores. Regression models confirmed that scores on the ESM-coping motive predicted BMI. These findings provide ecological validity for the PEMS to identify true-to-life motives for consuming palatable foods. This further adds to the utility of the PEMS in individualizing, and hence improving, treatment strategies for obesity, binge-eating, dietary nutrition, coping, reward acquisition, and psychosocial skills. PMID:26082744

Right Heart End-Systolic Remodeling Index Strongly Predicts Outcomes in Pulmonary Arterial Hypertension: Comparison With Validated Models.

PubMed

Amsallem, Myriam; Sweatt, Andrew J; Aymami, Marie C; Kuznetsova, Tatiana; Selej, Mona; Lu, HongQuan; Mercier, Olaf; Fadel, Elie; Schnittger, Ingela; McConnell, Michael V; Rabinovitch, Marlene; Zamanian, Roham T; Haddad, Francois

2017-06-01

Right ventricular (RV) end-systolic dimensions provide information on both size and function. We investigated whether an internally scaled index of end-systolic dimension is incremental to well-validated prognostic scores in pulmonary arterial hypertension. From 2005 to 2014, 228 patients with pulmonary arterial hypertension were prospectively enrolled. RV end-systolic remodeling index (RVESRI) was defined by lateral length divided by septal height. The incremental values of RV free wall longitudinal strain and RVESRI to risk scores were determined. Mean age was 49±14 years, 78% were female, 33% had connective tissue disease, 52% were in New York Heart Association class ≥III, and mean pulmonary vascular resistance was 11.2±6.4 WU. RVESRI and right atrial area were strongly connected to the other right heart metrics. Three zones of adaptation (adapted, maladapted, and severely maladapted) were identified based on the RVESRI to RV systolic pressure relationship. During a mean follow-up of 3.9±2.4 years, the primary end point of death, transplant, or admission for heart failure was reached in 88 patients. RVESRI was incremental to risk prediction scores in pulmonary arterial hypertension, including the Registry to Evaluate Early and Long-Term PAH Disease Management score, the Pulmonary Hypertension Connection equation, and the Mayo Clinic model. Using multivariable analysis, New York Heart Association class III/IV, RVESRI, and log NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) were retained (χ 2 , 62.2; P <0.0001). Changes in RVESRI at 1 year (n=203) were predictive of outcome; patients initiated on prostanoid therapy showed the greatest improvement in RVESRI. Among right heart metrics, RVESRI demonstrated the best test-retest characteristics. RVESRI is a simple reproducible prognostic marker in patients with pulmonary arterial hypertension. © 2017 American Heart Association, Inc.

Passion: Does one scale fit all? Construct validity of two-factor passion scale and psychometric invariance over different activities and languages.

PubMed

Marsh, Herbert W; Vallerand, Robert J; Lafrenière, Marc-André K; Parker, Philip; Morin, Alexandre J S; Carbonneau, Noémie; Jowett, Sophia; Bureau, Julien S; Fernet, Claude; Guay, Frédéric; Salah Abduljabbar, Adel; Paquet, Yvan

2013-09-01

The passion scale, based on the dualistic model of passion, measures 2 distinct types of passion: Harmonious and obsessive passions are predictive of adaptive and less adaptive outcomes, respectively. In a substantive-methodological synergy, we evaluate the construct validity (factor structure, reliability, convergent and discriminant validity) of Passion Scale responses (N = 3,571). The exploratory structural equation model fit to the data was substantially better than the confirmatory factor analysis solution, and resulted in better differentiated (less correlated) factors. Results from a 13-model taxonomy of measurement invariance supported complete invariance (factor loadings, factor correlations, item uniquenesses, item intercepts, and latent means) over language (French vs. English; the instrument was originally devised in French, then translated into English) and gender. Strong measurement partial invariance over 5 passion activity groups (leisure, sport, social, work, education) indicates that the same set of items is appropriate for assessing passion across a wide variety of activities--a previously untested, implicit assumption that greatly enhances practical utility. Support was found for the convergent and discriminant validity of the harmonious and obsessive passion scales, based on a set of validity correlates: life satisfaction, rumination, conflict, time investment, activity liking and valuation, and perceiving the activity as a passion.

A Framework for the Validation of Probabilistic Seismic Hazard Analysis Maps Using Strong Ground Motion Data

NASA Astrophysics Data System (ADS)

Bydlon, S. A.; Beroza, G. C.

2015-12-01

Recent debate on the efficacy of Probabilistic Seismic Hazard Analysis (PSHA), and the utility of hazard maps (i.e. Stein et al., 2011; Hanks et al., 2012), has prompted a need for validation of such maps using recorded strong ground motion data. Unfortunately, strong motion records are limited spatially and temporally relative to the area and time windows hazard maps encompass. We develop a framework to test the predictive powers of PSHA maps that is flexible with respect to a map's specified probability of exceedance and time window, and the strong motion receiver coverage. Using a combination of recorded and interpolated strong motion records produced through the ShakeMap environment, we compile a record of ground motion intensity measures for California from 2002-present. We use this information to perform an area-based test of California PSHA maps inspired by the work of Ward (1995). Though this framework is flexible in that it can be applied to seismically active areas where ShakeMap-like ground shaking interpolations have or can be produced, this testing procedure is limited by the relatively short lifetime of strong motion recordings and by the desire to only test with data collected after the development of the PSHA map under scrutiny. To account for this, we use the assumption that PSHA maps are time independent to adapt the testing procedure for periods of recorded data shorter than the lifetime of a map. We note that accuracy of this testing procedure will only improve as more data is collected, or as the time-horizon of interest is reduced, as has been proposed for maps of areas experiencing induced seismicity. We believe that this procedure can be used to determine whether PSHA maps are accurately portraying seismic hazard and whether discrepancies are localized or systemic.

Modeling and validation of autoinducer-mediated bacterial gene expression in microfluidic environments

PubMed Central

Austin, Caitlin M.; Stoy, William; Su, Peter; Harber, Marie C.; Bardill, J. Patrick; Hammer, Brian K.; Forest, Craig R.

2014-01-01

Biosensors exploiting communication within genetically engineered bacteria are becoming increasingly important for monitoring environmental changes. Currently, there are a variety of mathematical models for understanding and predicting how genetically engineered bacteria respond to molecular stimuli in these environments, but as sensors have miniaturized towards microfluidics and are subjected to complex time-varying inputs, the shortcomings of these models have become apparent. The effects of microfluidic environments such as low oxygen concentration, increased biofilm encapsulation, diffusion limited molecular distribution, and higher population densities strongly affect rate constants for gene expression not accounted for in previous models. We report a mathematical model that accurately predicts the biological response of the autoinducer N-acyl homoserine lactone-mediated green fluorescent protein expression in reporter bacteria in microfluidic environments by accommodating these rate constants. This generalized mass action model considers a chain of biomolecular events from input autoinducer chemical to fluorescent protein expression through a series of six chemical species. We have validated this model against experimental data from our own apparatus as well as prior published experimental results. Results indicate accurate prediction of dynamics (e.g., 14% peak time error from a pulse input) and with reduced mean-squared error with pulse or step inputs for a range of concentrations (10 μM–30 μM). This model can help advance the design of genetically engineered bacteria sensors and molecular communication devices. PMID:25379076

Quantitative Determination of Fusarium proliferatum Concentration in Intact Garlic Cloves Using Near-Infrared Spectroscopy

PubMed Central

Tamburini, Elena; Mamolini, Elisabetta; De Bastiani, Morena; Marchetti, Maria Gabriella

2016-01-01

Fusarium proliferatum is considered to be a pathogen of many economically important plants, including garlic. The objective of this research was to apply near-infrared spectroscopy (NIRS) to rapidly determine fungal concentration in intact garlic cloves, avoiding the laborious and time-consuming procedures of traditional assays. Preventive detection of infection before seeding is of great interest for farmers, because it could avoid serious losses of yield during harvesting and storage. Spectra were collected on 95 garlic cloves, divided in five classes of infection (from 1-healthy to 5-very highly infected) in the range of fungal concentration 0.34–7231.15 ppb. Calibration and cross validation models were developed with partial least squares regression (PLSR) on pretreated spectra (standard normal variate, SNV, and derivatives), providing good accuracy in prediction, with a coefficient of determination (R2) of 0.829 and 0.774, respectively, a standard error of calibration (SEC) of 615.17 ppb, and a standard error of cross validation (SECV) of 717.41 ppb. The calibration model was then used to predict fungal concentration in unknown samples, peeled and unpeeled. The results showed that NIRS could be used as a reliable tool to directly detect and quantify F. proliferatum infection in peeled intact garlic cloves, but the presence of the external peel strongly affected the prediction reliability. PMID:27428978

Development and validation of a habitat suitability model for ...

EPA Pesticide Factsheets

We developed a spatially-explicit, flexible 3-parameter habitat suitability model that can be used to identify and predict areas at higher risk for non-native dwarf eelgrass (Zostera japonica) invasion. The model uses simple environmental parameters (depth, nearshore slope, and salinity) to quantitatively describe habitat suitable for Z. japonica invasion based on ecology and physiology from the primary literature. Habitat suitability is defined with values ranging from zero to one, where one denotes areas most conducive to Z. japonica and zero denotes areas not likely to support Z. japonica growth. The model was applied to Yaquina Bay, Oregon, USA, an area that has well documented Z. japonica expansion over the last two decades. The highest suitability values for Z. japonica occurred in the mid to upper portions of the intertidal zone, with larger expanses occurring in the lower estuary. While the upper estuary did contain suitable habitat, most areas were not as large as in the lower estuary, due to inappropriate depth, a steeply sloping intertidal zone, and lower salinity. The lowest suitability values occurred below the lower intertidal zone, within the Yaquina River channel. The model was validated by comparison to a multi-year time series of Z. japonica maps, revealing a strong predictive capacity. Sensitivity analysis performed to evaluate the contribution of each parameter to the model prediction revealed that depth was the most important factor. Sh

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

PubMed

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

2012-04-01

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

Simulation of the effect of hydrogen bonds on water activity of glucose and dextran using the Veytsman model.

PubMed

De Vito, Francesca; Veytsman, Boris; Painter, Paul; Kokini, Jozef L

2015-03-06

Carbohydrates exhibit either van der Waals and ionic interactions or strong hydrogen bonding interactions. The prominence and large number of hydrogen bonds results in major contributions to phase behavior. A thermodynamic framework that accounts for hydrogen bonding interactions is therefore necessary. We have developed an extension of the thermodynamic model based on the Veytsman association theory to predict the contribution of hydrogen bonds to the behavior of glucose-water and dextran-water systems and we have calculated the free energy of mixing and its derivative leading to chemical potential and water activity. We compared our calculations with experimental data of water activity for glucose and dextran and found excellent agreement far superior to the Flory-Huggins theory. The validation of our calculations using experimental data demonstrated the validity of the Veytsman model in properly accounting for the hydrogen bonding interactions and successfully predicting water activity of glucose and dextran. Our calculations of the concentration of hydrogen bonds using the Veytsman model were instrumental in our ability to explain the difference between glucose and dextran and the role that hydrogen bonds play in contributing to these differences. The miscibility predictions showed that the Veytsman model is also able to correctly describe the phase behavior of glucose and dextran. Copyright © 2014 Elsevier Ltd. All rights reserved.

Development, test-retest reliability and validity of the Pharmacy Value-Added Services Questionnaire (PVASQ)

PubMed Central

Tan, Christine L.; Hassali, Mohamed A.; Saleem, Fahad; Shafie, Asrul A.; Aljadhey, Hisham; Gan, Vincent B.

2015-01-01

Objective: (i) To develop the Pharmacy Value-Added Services Questionnaire (PVASQ) using emerging themes generated from interviews. (ii) To establish reliability and validity of questionnaire instrument. Methods: Using an extended Theory of Planned Behavior as the theoretical model, face-to-face interviews generated salient beliefs of pharmacy value-added services. The PVASQ was constructed initially in English incorporating important themes and later translated into the Malay language with forward and backward translation. Intention (INT) to adopt pharmacy value-added services is predicted by attitudes (ATT), subjective norms (SN), perceived behavioral control (PBC), knowledge and expectations. Using a 7-point Likert-type scale and a dichotomous scale, test-retest reliability (N=25) was assessed by administrating the questionnaire instrument twice at an interval of one week apart. Internal consistency was measured by Cronbach’s alpha and construct validity between two administrations was assessed using the kappa statistic and the intraclass correlation coefficient (ICC). Confirmatory Factor Analysis, CFA (N=410) was conducted to assess construct validity of the PVASQ. Results: The kappa coefficients indicate a moderate to almost perfect strength of agreement between test and retest. The ICC for all scales tested for intra-rater (test-retest) reliability was good. The overall Cronbach’ s alpha (N=25) is 0.912 and 0.908 for the two time points. The result of CFA (N=410) showed most items loaded strongly and correctly into corresponding factors. Only one item was eliminated. Conclusions: This study is the first to develop and establish the reliability and validity of the Pharmacy Value-Added Services Questionnaire instrument using the Theory of Planned Behavior as the theoretical model. The translated Malay language version of PVASQ is reliable and valid to predict Malaysian patients’ intention to adopt pharmacy value-added services to collect partial medicine supply. PMID:26445622

Development and Validation of the Consumer Health Activation Index.

PubMed

Wolf, Michael S; Smith, Samuel G; Pandit, Anjali U; Condon, David M; Curtis, Laura M; Griffith, James; O'Conor, Rachel; Rush, Steven; Bailey, Stacy C; Kaplan, Gordon; Haufle, Vincent; Martin, David

2018-04-01

Although there has been increasing interest in patient engagement, few measures are publicly available and suitable for patients with limited health literacy. We sought to develop a Consumer Health Activation Index (CHAI) for use among diverse patients. Expert opinion, a systematic literature review, focus groups, and cognitive interviews with patients were used to create and revise a potential set of items. Psychometric testing guided by item response theory was then conducted among 301 English-speaking, community-dwelling adults. This included differential item functioning analyses to evaluate item performance across participant health literacy levels. To determine construct validity, CHAI scores were compared to scales measuring similar personality constructs. Associations between the CHAI and physical and mental health established predictive validity. A second study among 9,478 adults was used to confirm CHAI associations with health outcomes. Exploratory factor analyses revealed a single-factor solution with a 10-item scale. The CHAI showed good internal consistency (alpha = 0.81) and moderate test-retest reliability (ICC = 0.53). Reading grade level was found to be at the 6 th grade. Moderate to strong correlations were found with similar constructs (Multidimensional Health Locus of Control, r = 0.38, P < 0.001; Conscientiousness, r = 0.41, P < 0.001). Predictive validity was demonstrated through associations with functional health status measures (depression, r = -0.28, P < 0.001; anxiety, r = -0.22, P < 0.001; and physical functioning, r = 0.22, P < 0.001). In the validation sample, the CHAI was significantly associated with self-reported physical and mental health ( r = 0.31 and 0.32 respectively; both P < 0.001). The CHAI appears to be a valid, reliable, and easily administered tool that can be used to assess health activation among adults, including those with limited health literacy. Future studies should test the tool in actual use and explore further applications.

Validity and validation of expert (Q)SAR systems.

PubMed

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

2005-08-01

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

Validating Dimensions of Psychosis Symptomatology: Neural Correlates and 20-year Outcomes

PubMed Central

Kotov, Roman; Foti, Dan; Li, Kaiqiao; Bromet, Evelyn J.; Hajcak, Greg; Ruggero, Camilo J.

2016-01-01

Heterogeneity of psychosis presents significant challenges for classification. Between two and 12 symptom dimensions have been proposed, and consensus is lacking. The present study sought to identify uniquely informative models by comparing the validity of these alternatives. An epidemiologic cohort of 628 first-admission inpatients with psychosis was interviewed 6 times over two decades and completed an electrophysiological assessment of error processing at year 20. We first analyzed a comprehensive set of 49 symptoms rated by interviewers at baseline, progressively extracting from one to 12 factors. Next, we compared the ability of resulting factor solutions to (a) account for concurrent neural dysfunction and (b) predict 20-year role, social, residential, and global functioning, and life satisfaction. A four-factor model showed incremental validity with all outcomes, and more complex models did not improve explanatory power. The four dimensions—reality distortion, disorganization, inexpressivity, and apathy/asociality—were replicable in 5 follow-ups, internally consistent, stable across assessments, and showed strong discriminant validity. These results reaffirm the value of separating disorganization and reality distortion, are consistent with recent findings distinguishing inexpressivity and apathy/asociality, and suggest that these four dimensions are fundamental to understanding neural abnormalities and long-term outcomes in psychosis. PMID:27819471

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

PubMed

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

2017-09-01

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

Statistical Study of Interplanetary Coronal Mass Ejections with Strong Magnetic Fields

NASA Astrophysics Data System (ADS)

Murphy, Matthew E.

Coronal Mass Ejections (CMEs) with strong magnetic fields (B ) are typically associated with significant Solar Energetic Particle (SEP) events, high solar wind speed and solar flare events. Successful prediction of the arrival time of a CME at Earth is required to maximize the time available for satellite, infrastructure, and space travel programs to take protective action against the coming flux of high-energy particles. It is known that the magnetic field strength of a CME is linked to the strength of a geomagnetic storm on Earth. Unfortunately, the correlations between strong magnetic field CMEs from the entire sun (especially from the far side or non-Earth facing side of the sun) to SEP and flare events, solar source regions and other relevant solar variables are not well known. New correlation studies using an artificial intelligence engine (Eureqa) were performed to study CME events with magnetic field strength readings over 30 nanoteslas (nT) from January 2010 to October 17, 2014. This thesis presents the results of this study, validates Eureqa to obtain previously published results, and presents previously unknown functional relationships between solar source magnetic field data, CME initial speed and the CME magnetic field. These new results enable the development of more accurate CME magnetic field predictions and should help scientists develop better forecasts thereby helping to prevent damage to humanity's space and Earth assets.

Real-time assessment of perioperative behaviors in children and parents: development and validation of the perioperative adult child behavioral interaction scale.

PubMed

Sadhasivam, Senthilkumar; Cohen, Lindsey L; Hosu, Liana; Gorman, Kristin L; Wang, Yu; Nick, Todd G; Jou, Jing Fang; Samol, Nancy; Szabova, Alexandra; Hagerman, Nancy; Hein, Elizabeth; Boat, Anne; Varughese, Anna; Kurth, Charles Dean; Willging, J Paul; Gunter, Joel B

2010-04-01

Behavior in response to distressful events during outpatient pediatric surgery can contribute to postoperative maladaptive behaviors, such as temper tantrums, nightmares, bed-wetting, and attention seeking. Currently available perioperative behavioral assessment tools have limited utility in guiding interventions to ameliorate maladaptive behaviors because they cannot be used in real time, are only intended to be used during 1 phase of the experience (e.g., perioperative), or provide only a static assessment of the child (e.g., level of anxiety). A simple, reliable, real-time tool is needed to appropriately identify children and parents whose behaviors in response to distressful events at any point in the perioperative continuum could benefit from timely behavioral intervention. Our specific aims were to (1) refine the Perioperative Adult Child Behavioral Interaction Scale (PACBIS) to improve its reliability in identifying perioperative behaviors and (2) validate the refined PACBIS against several established instruments. The PACBIS was used to assess the perioperative behaviors of 89 children aged 3 to 12 years presenting for adenotonsillectomy and their parents. Assessments using the PACBIS were made during perioperative events likely to prove distressing to children and/or parents (perioperative measurement of blood pressure, induction of anesthesia, and removal of the IV catheter before discharge). Static measurements of perioperative anxiety and behavioral compliance during anesthetic induction were made using the modified Yale Preoperative Anxiety Scale and the Induction Compliance Checklist (ICC). Each event was videotaped for later scoring using the Child-Adult Medical Procedure Interaction Scale-Short Form (CAMPIS-SF) and Observational Scale of Behavioral Distress (OSBD). Interrater reliability using linear weighted kappa (kappa(w)) and multiple validations using Spearman correlation coefficients were analyzed. The PACBIS demonstrated good to excellent interrater reliability, with kappa(w) ranging from 0.62 to 0.94. The Child Coping and Child Distress subscores of the PACBIS demonstrated strong concurrent correlations with the modified Yale Preoperative Anxiety Scale, ICC, CAMPIS-SF, and OSBD. The Parent Positive subscore of the PACBIS correlated strongly with the CAMPIS-SF and OSBD, whereas the Parent Negative subscore showed significant correlation with the ICC. The PACBIS has strong construct and predictive validities. The PACBIS is a simple, easy to use, real-time instrument to evaluate perioperative behaviors of both children and parents. It has good to excellent interrater reliability and strong concurrent validity against currently accepted scales. The PACBIS offers a means to identify maladaptive child or parental behaviors in real time, making it possible to intervene to modify such behaviors in a timely fashion.

Procalcitonin decrease over 72 hours in US critical care units predicts fatal outcome in sepsis patients

PubMed Central

2013-01-01

Introduction Close monitoring and repeated risk assessment of sepsis patients in the intensive care unit (ICU) is important for decisions regarding care intensification or early discharge to the ward. We studied whether considering plasma kinetics of procalcitonin, a biomarker of systemic bacterial infection, over the first 72 critical care hours improved mortality prognostication of septic patients from two US settings. Methods This retrospective analysis included consecutively treated eligible adults with a diagnosis of sepsis from critical care units in two independent institutions in Clearwater, FL and Chicago, IL. Cohorts were used for derivation or validation to study the association between procalcitonin change over the first 72 critical care hours and mortality. Results ICU/in-hospital mortality rates were 29.2%/31.8% in the derivation cohort (n = 154) and 17.6%/29.4% in the validation cohort (n = 102). In logistic regression analysis of both cohorts, procalcitonin change was strongly associated with ICU and in-hospital mortality independent of clinical risk scores (Acute Physiology, Age and Chronic Health Evaluation IV or Simplified Acute Physiology Score II), with area under the curve (AUC) from 0.67 to 0.71. When procalcitonin decreased by at least 80%, the negative predictive value for ICU/in-hospital mortality was 90%/90% in the derivation cohort, and 91%/79% in the validation cohort. When procalcitonin showed no decrease or increased, the respective positive predictive values were 48%/48% and 36%/52%. Discussion In septic patients, procalcitonin kinetics over the first 72 critical care hours provide prognostic information beyond that available from clinical risk scores. If these observations are confirmed, procalcitonin monitoring may assist physician decision-making regarding care intensification or early transfer from the ICU to the floor. PMID:23787145

Automated Cervical Screening and Triage, Based on HPV Testing and Computer-Interpreted Cytology.

PubMed

Yu, Kai; Hyun, Noorie; Fetterman, Barbara; Lorey, Thomas; Raine-Bennett, Tina R; Zhang, Han; Stamps, Robin E; Poitras, Nancy E; Wheeler, William; Befano, Brian; Gage, Julia C; Castle, Philip E; Wentzensen, Nicolas; Schiffman, Mark

2018-04-11

State-of-the-art cervical cancer prevention includes human papillomavirus (HPV) vaccination among adolescents and screening/treatment of cervical precancer (CIN3/AIS and, less strictly, CIN2) among adults. HPV testing provides sensitive detection of precancer but, to reduce overtreatment, secondary "triage" is needed to predict women at highest risk. Those with the highest-risk HPV types or abnormal cytology are commonly referred to colposcopy; however, expert cytology services are critically lacking in many regions. To permit completely automatable cervical screening/triage, we designed and validated a novel triage method, a cytologic risk score algorithm based on computer-scanned liquid-based slide features (FocalPoint, BD, Burlington, NC). We compared it with abnormal cytology in predicting precancer among 1839 women testing HPV positive (HC2, Qiagen, Germantown, MD) in 2010 at Kaiser Permanente Northern California (KPNC). Precancer outcomes were ascertained by record linkage. As additional validation, we compared the algorithm prospectively with cytology results among 243 807 women screened at KPNC (2016-2017). All statistical tests were two-sided. Among HPV-positive women, the algorithm matched the triage performance of abnormal cytology. Combined with HPV16/18/45 typing (Onclarity, BD, Sparks, MD), the automatable strategy referred 91.7% of HPV-positive CIN3/AIS cases to immediate colposcopy while deferring 38.4% of all HPV-positive women to one-year retesting (compared with 89.1% and 37.4%, respectively, for typing and cytology triage). In the 2016-2017 validation, the predicted risk scores strongly correlated with cytology (P < .001). High-quality cervical screening and triage performance is achievable using this completely automated approach. Automated technology could permit extension of high-quality cervical screening/triage coverage to currently underserved regions.

The nature of youth care tasks in families experiencing chronic illness/disability: development of the Youth Activities of Caregiving Scale (YACS).

PubMed

Ireland, Michael James; Pakenham, Kenneth Ian

2010-07-01

The purpose of this study was to develop an empirically derived multi-item scale of care tasks performed by young people in the context of family illness/disability: the Youth Activities of Caregiving Scale (YACS). A total of 135 youngsters aged 10-24 years with an ill/disabled family member completed questionnaires. Factor analyses performed on the YACS yielded four factors, instrumental care, social/emotional care, personal/intimate care and domestic/household care, accounting for 57.78% of the variance. The internal reliabilities of all factors ranged from 0.74 to 0.92. Higher scores on the YACS related to higher youth age and several caregiving context variables (i.e. household type [single or dual-parent household], relationship with care-recipient and perceived choice in caregiving). Higher scores on the YACS also related to care-recipient illness/disability variables (onset, functional impairment, prognosis, predictability and illness/disability type). Strong positive correlations between the YACS and a conceptually related measure of young caregiving experiences provided good convergent validity data. Criterion validity was established with evidence that the YACS predicted youth adjustment in the domains of health and prosocial behaviour.

Overview of Recent DIII-D Experimental Results

NASA Astrophysics Data System (ADS)

Fenstermacher, Max; DIII-D Team

2017-10-01

Recent DIII-D experiments contributed to the ITER physics basis and to physics understanding for extrapolation to future devices. A predict-first analysis showed how shape can enhance access to RMP ELM suppression. 3D equilibrium changes from ELM control RMPs, were linked to density pumpout. Ion velocity imaging in the SOL showed 3D C2+flow perturbations near RMP induced n =1 islands. Correlation ECE reveals a 40% increase in Te turbulence during QH-mode and 70% during RMP ELM suppression vs. ELMing H-mode. A long-lived predator-prey oscillation replaces edge MHD in recent low-torque QH-mode plasmas. Spatio-temporally resolved runaway electron measurements validate the importance of synchrotron and collisional damping on RE dissipation. A new small angle slot divertor achieves strong plasma cooling and facilitates detachment access. Fast ion confinement was improved in high q_min scenarios using variable beam energy optimization. First reproducible, stable ITER baseline scenarios were established. Studies have validated a model for edge momentum transport that predicts the pedestal main-ion intrinsic velocity value and direction. Work supported by the US DOE under DE-FC02-04ER54698 and DE-AC52-07NA27344.

Eating styles in the morbidly obese: restraint eating, but not emotional and external eating, predicts dietary behaviour.

PubMed

Brogan, Amy; Hevey, David

2013-01-01

The research explored (1) the relationships between self-reported eating style (restraint, emotional and external eating) and dietary intake and (2) emotional eater status as a moderator of food intake when emotional, in a morbidly obese population. A sample of 57 obese participants (BMI: M = 51.84, SD = 8.66) completed a five-day food diary together with a reflective diary, which assessed eating style and positive and negative affect daily. A dietician-scored food pyramid analysis of intake. Restraint eating was the only predictor (negative) of overall food intake and the variable most strongly associated with the consumption of top-shelf foods. Emotional and external eating were unrelated to food intake. Emotional eater status did not moderate food intake in response to positive and negative mood states. The findings indicated largely analogous relationships between eating style and dietary intake in this obese sample compared with previous results from healthy populations. The lack of predictive validity for emotional eating scales (when emotional) raises questions over people's ability to adequately assess their eating style and consequently, the overall validity of emotional eater scales.

Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) predictors of police officer problem behavior.

PubMed

Tarescavage, Anthony M; Corey, David M; Ben-Porath, Yossef S

2015-02-01

The purpose of this study was to investigate the predictive validity of the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) in a sample of law enforcement officers. MMPI-2-RF scores were collected from preemployment psychological evaluations of 136 male police officers, and supervisor ratings of performance and problem behavior were subsequently obtained during the initial probationary period. The sample produced meaningfully lower and less variant substantive scale scores than the general population and the MMPI-2-RF Police Candidate comparison group, which significantly affected effect sizes for the zero-order correlations. After applying a correction for range restriction, MMPI-2-RF substantive scales demonstrated moderate to strong associations with criteria, particularly in the Emotional Dysfunction and Interpersonal Functioning domains. Relative risk ratio analyses showed that cutoffs of 45T and 50T maintained reasonable selection ratios because of the exceptionally low scores in this sample and were associated with significantly increased risk for problematic behavior. These results provide support for the predictive validity of the MMPI-2-RF substantive scales in this setting. Implications of these findings and limitations of these results are discussed. © The Author(s) 2014.

3D-Printed Tissue-Mimicking Phantoms for Medical Imaging and Computational Validation Applications

PubMed Central

Shahmirzadi, Danial; Li, Ronny X.; Doyle, Barry J.; Konofagou, Elisa E.; McGloughlin, Tim M.

2014-01-01

Abstract Abdominal aortic aneurysm (AAA) is a permanent, irreversible dilation of the distal region of the aorta. Recent efforts have focused on improved AAA screening and biomechanics-based failure prediction. Idealized and patient-specific AAA phantoms are often employed to validate numerical models and imaging modalities. To produce such phantoms, the investment casting process is frequently used, reconstructing the 3D vessel geometry from computed tomography patient scans. In this study the alternative use of 3D printing to produce phantoms is investigated. The mechanical properties of flexible 3D-printed materials are benchmarked against proven elastomers. We demonstrate the utility of this process with particular application to the emerging imaging modality of ultrasound-based pulse wave imaging, a noninvasive diagnostic methodology being developed to obtain regional vascular wall stiffness properties, differentiating normal and pathologic tissue in vivo. Phantom wall displacements under pulsatile loading conditions were observed, showing good correlation to fluid–structure interaction simulations and regions of peak wall stress predicted by finite element analysis. 3D-printed phantoms show a strong potential to improve medical imaging and computational analysis, potentially helping bridge the gap between experimental and clinical diagnostic tools. PMID:28804733

Models, validation, and applied geochemistry: Issues in science, communication, and philosophy

USGS Publications Warehouse

Nordstrom, D. Kirk

2012-01-01

Models have become so fashionable that many scientists and engineers cannot imagine working without them. The predominant use of computer codes to execute model calculations has blurred the distinction between code and model. The recent controversy regarding model validation has brought into question what we mean by a ‘model’ and by ‘validation.’ It has become apparent that the usual meaning of validation may be common in engineering practice and seems useful in legal practice but it is contrary to scientific practice and brings into question our understanding of science and how it can best be applied to such problems as hazardous waste characterization, remediation, and aqueous geochemistry in general. This review summarizes arguments against using the phrase model validation and examines efforts to validate models for high-level radioactive waste management and for permitting and monitoring open-pit mines. Part of the controversy comes from a misunderstanding of ‘prediction’ and the need to distinguish logical from temporal prediction. Another problem stems from the difference in the engineering approach contrasted with the scientific approach. The reductionist influence on the way we approach environmental investigations also limits our ability to model the interconnected nature of reality. Guidelines are proposed to improve our perceptions and proper utilization of models. Use of the word ‘validation’ is strongly discouraged when discussing model reliability.

Deorphaning the Macromolecular Targets of the Natural Anticancer Compound Doliculide.

PubMed

Schneider, Gisbert; Reker, Daniel; Chen, Tao; Hauenstein, Kurt; Schneider, Petra; Altmann, Karl-Heinz

2016-09-26

The cyclodepsipeptide doliculide is a marine natural product with strong actin-polymerizing and anticancer activities. Evidence for doliculide acting as a potent and subtype-selective antagonist of prostanoid E receptor 3 (EP3) is presented. Computational target prediction suggested that this membrane receptor is a likely macromolecular target and enabled immediate in vitro validation. This proof-of-concept study demonstrates the in silico deorphanization of phenotypic screening hits as a viable concept for future natural-product-inspired chemical biology and drug discovery efforts. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Molecular nonlinear dynamics and protein thermal uncertainty quantification

PubMed Central

Xia, Kelin; Wei, Guo-Wei

2014-01-01

This work introduces molecular nonlinear dynamics (MND) as a new approach for describing protein folding and aggregation. By using a mode system, we show that the MND of disordered proteins is chaotic while that of folded proteins exhibits intrinsically low dimensional manifolds (ILDMs). The stability of ILDMs is found to strongly correlate with protein energies. We propose a novel method for protein thermal uncertainty quantification based on persistently invariant ILDMs. Extensive comparison with experimental data and the state-of-the-art methods in the field validate the proposed new method for protein B-factor prediction. PMID:24697365

Parenting styles and child behavior in African American families of preschool children.

PubMed

Querido, Jane G; Warner, Tamara D; Eyberg, Sheila M

2002-06-01

Examined the relations between parenting styles and child behavior problems in African American preschool children. Participants were 108 African American female caregivers of 3- to 6-year-old children. Correlational analysis showed that parent-reported child behavior problems were associated with maternal education, family income, and parents' endorsement of authoritative parenting, authoritarian parenting, and permissive parenting. Hierarchical regression analysis showed that the authoritative parenting style was most predictive of fewer child behavior problems. These results are consistent with previous findings with European American families and provide strong support for the cross-cultural validity of the authoritative parenting style.

Development and Validation of the Questionnaire of Vaping Craving.

PubMed

Dowd, Ashley N; Motschman, Courtney A; Tiffany, Stephen T

2018-03-12

Craving may represent core motivational processes in tobacco dependence, but there is no psychometrically evaluated measure of craving for e-cigarettes (vaping craving). This research developed and validated a brief measure of vaping craving. The measure was evaluated in two studies. In Study 1, a 42-item questionnaire assessing a wide range of vaping craving content was administered to 209 current e-cigarette users. In Study 2, a 10-item questionnaire derived from Study 1 results was administered to 224 current e-cigarette users. Participants were recruited from Amazon's Mechanical Turk, an online labor market. Principal factor analysis identified the strongest loading items (.815 - .867) on the first extracted factor (77% of the factor variance) for inclusion in a 10-item Questionnaire of Vaping Craving (QVC). This item set, with an internal consistency (α) of .97, focused on desire and intent to vape, and anticipation of positive outcomes related to e-cigarette use. Confirmatory factor analysis revealed the items had strong factor loadings that were significantly predicted by the latent vaping craving construct (ps < .001). Higher vaping craving was significantly associated with the level of e-cigarette use, greater negative mood, and lower confidence in ability to quit vaping (ps < .01). Among participants who also smoked tobacco (87%), vaping craving was more strongly associated with e-cigarette dependence than tobacco dependence. The findings support the reliability and validity of the QVC and suggest it could be used in laboratory and clinical settings as a psychometrically sound measure of vaping craving.

Modeling breath-enhanced jet nebulizers to estimate pulmonary drug deposition.

PubMed

Wee, Wallace B; Leung, Kitty; Coates, Allan L

2013-12-01

Predictable delivery of aerosol medication for a given patient and drug-device combination is crucial, both for therapeutic effect and to avoid toxicity. The gold standard for measuring pulmonary drug deposition (PDD) is gamma scintigraphy. However, these techniques expose patients to radiation, are complicated, and are relevant for only one patient and drug-device combination, making them less available. Alternatively, in vitro experiments have been used as a surrogate to estimate in vivo performance, but this is time-consuming and has few "in vitro to in vivo" correlations for therapeutics delivered by inhalation. An alternative method for determining inhaled mass and PDD is proposed by deriving and validating a mathematical model, for the individual breathing patterns of normal subjects and drug-device operating parameters. This model was evaluated for patients with cystic fibrosis (CF). This study is comprised of three stages: mathematical model derivation, in vitro testing, and in vivo validation. The model was derived from an idealized patient's respiration cycle and the steady-state operating characteristics of a drug-device combination. The model was tested under in vitro dynamic conditions that varied tidal volume, inspiration-to-expiration time, and breaths per minute. This approach was then extended to incorporate additional physiological parameters (dead space, aerodynamic particle size distribution) and validated against in vivo nuclear medicine data in predicting PDD in both normal subjects and those with CF. The model shows strong agreement with in vitro testing. In vivo testing with normal subjects yielded good agreement, but less agreement for patients with chronic obstructive lung disease and bronchiectasis from CF. The mathematical model was successful in accommodating a wide range of breathing patterns and drug-device combinations. Furthermore, the model has demonstrated its effectiveness in predicting the amount of aerosol delivered to "normal" subjects. However, challenges remain in predicting deposition in obstructive lung disease.

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

PubMed

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

2018-01-01

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

Network-based de-noising improves prediction from microarray data.

PubMed

Kato, Tsuyoshi; Murata, Yukio; Miura, Koh; Asai, Kiyoshi; Horton, Paul B; Koji, Tsuda; Fujibuchi, Wataru

2006-03-20

Prediction of human cell response to anti-cancer drugs (compounds) from microarray data is a challenging problem, due to the noise properties of microarrays as well as the high variance of living cell responses to drugs. Hence there is a strong need for more practical and robust methods than standard methods for real-value prediction. We devised an extended version of the off-subspace noise-reduction (de-noising) method to incorporate heterogeneous network data such as sequence similarity or protein-protein interactions into a single framework. Using that method, we first de-noise the gene expression data for training and test data and also the drug-response data for training data. Then we predict the unknown responses of each drug from the de-noised input data. For ascertaining whether de-noising improves prediction or not, we carry out 12-fold cross-validation for assessment of the prediction performance. We use the Pearson's correlation coefficient between the true and predicted response values as the prediction performance. De-noising improves the prediction performance for 65% of drugs. Furthermore, we found that this noise reduction method is robust and effective even when a large amount of artificial noise is added to the input data. We found that our extended off-subspace noise-reduction method combining heterogeneous biological data is successful and quite useful to improve prediction of human cell cancer drug responses from microarray data.

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

PubMed

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

2018-04-01

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

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

ERIC Educational Resources Information Center

Brown, James M.; Chang, Gerald

1982-01-01

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

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

ERIC Educational Resources Information Center

Golmon, Melton E.; Berry, Charles A.

1981-01-01

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

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

PubMed

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

2011-12-01

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

Enhancement of seasonal prediction of East Asian summer rainfall related to western tropical Pacific convection

NASA Astrophysics Data System (ADS)

Lee, Doo Young; Ahn, Joong-Bae; Yoo, Jin-Ho

2015-08-01

The prediction skills of climate model simulations in the western tropical Pacific (WTP) and East Asian region are assessed using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers (June-August) during the period 1983-2005, along with corresponding observed and reanalyzed data. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP Indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index or each MPI. Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by hybrid dynamical-statistical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using a hybrid dynamical-statistical approach compared to the dynamical forecast alone.

Seasonal prediction of East Asian summer rainfall using a multi-model ensemble system

NASA Astrophysics Data System (ADS)

Ahn, Joong-Bae; Lee, Doo-Young; Yoo, Jin‑Ho

2015-04-01

Using the retrospective forecasts of seven state-of-the-art coupled models and their multi-model ensemble (MME) for boreal summers, the prediction skills of climate models in the western tropical Pacific (WTP) and East Asian region are assessed. The prediction of summer rainfall anomalies in East Asia is difficult, while the WTP has a strong correlation between model prediction and observation. We focus on developing a new approach to further enhance the seasonal prediction skill for summer rainfall in East Asia and investigate the influence of convective activity in the WTP on East Asian summer rainfall. By analyzing the characteristics of the WTP convection, two distinct patterns associated with El Niño-Southern Oscillation developing and decaying modes are identified. Based on the multiple linear regression method, the East Asia Rainfall Index (EARI) is developed by using the interannual variability of the normalized Maritime continent-WTP Indices (MPIs), as potentially useful predictors for rainfall prediction over East Asia, obtained from the above two main patterns. For East Asian summer rainfall, the EARI has superior performance to the East Asia summer monsoon index or each MPI. Therefore, the regressed rainfall from EARI also shows a strong relationship with the observed East Asian summer rainfall pattern. In addition, we evaluate the prediction skill of the East Asia reconstructed rainfall obtained by hybrid dynamical-statistical approach using the cross-validated EARI from the individual models and their MME. The results show that the rainfalls reconstructed from simulations capture the general features of observed precipitation in East Asia quite well. This study convincingly demonstrates that rainfall prediction skill is considerably improved by using a hybrid dynamical-statistical approach compared to the dynamical forecast alone. Acknowledgements This work was carried out with the support of Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under grant project PJ009353 and Korea Meteorological Administration Research and Development Program under grant CATER 2012-3100, Republic of Korea.

Predictive validity of behavioural animal models for chronic pain

PubMed Central

Berge, Odd-Geir

2011-01-01

Rodent models of chronic pain may elucidate pathophysiological mechanisms and identify potential drug targets, but whether they predict clinical efficacy of novel compounds is controversial. Several potential analgesics have failed in clinical trials, in spite of strong animal modelling support for efficacy, but there are also examples of successful modelling. Significant differences in how methods are implemented and results are reported means that a literature-based comparison between preclinical data and clinical trials will not reveal whether a particular model is generally predictive. Limited reports on negative outcomes prevents reliable estimate of specificity of any model. Animal models tend to be validated with standard analgesics and may be biased towards tractable pain mechanisms. But preclinical publications rarely contain drug exposure data, and drugs are usually given in high doses and as a single administration, which may lead to drug distribution and exposure deviating significantly from clinical conditions. The greatest challenge for predictive modelling is, however, the heterogeneity of the target patient populations, in terms of both symptoms and pharmacology, probably reflecting differences in pathophysiology. In well-controlled clinical trials, a majority of patients shows less than 50% reduction in pain. A model that responds well to current analgesics should therefore predict efficacy only in a subset of patients within a diagnostic group. It follows that successful translation requires several models for each indication, reflecting critical pathophysiological processes, combined with data linking exposure levels with effect on target. LINKED ARTICLES This article is part of a themed issue on Translational Neuropharmacology. To view the other articles in this issue visit http://dx.doi.org/10.1111/bph.2011.164.issue-4 PMID:21371010

Single-Nucleotide Polymorphisms Within the Thrombomodulin Gene (THBD) Predict Mortality in Patients With Graft-Versus-Host Disease.

PubMed

Rachakonda, Sivaramakrishna P; Penack, Olaf; Dietrich, Sascha; Blau, Olga; Blau, Igor Wolfgang; Radujkovic, Aleksandar; Isermann, Berend; Ho, Anthony D; Uharek, Lutz; Dreger, Peter; Kumar, Rajiv; Luft, Thomas

2014-10-20

Steroid-refractory graft-versus-host disease (GVHD) is a major and often fatal complication after allogeneic stem-cell transplantation (alloSCT). Although the pathophysiology of steroid refractoriness is not fully understood, evidence is accumulating that endothelial cell stress is involved, and endothelial thrombomodulin (THBD) plays a role in this process. Here we assess whether single-nucleotide polymorphisms (SNPs) within the THBD gene predict outcome after alloSCT. Seven SNPs within the THBD gene were studied (rs1962, rs1042579, rs1042580, rs3176123, rs3176124, rs3176126, and rs3176134) in a training cohort of 306 patients. The relevant genotypes were then validated in an independent cohort (n = 321). In the training cohort, an increased risk of nonrelapse mortality (NRM) was associated with three of seven SNPs tested: rs1962, rs1042579 (in linkage disequilibrium with rs3176123), and rs1042580. When patients were divided into risk groups (one v no high-risk SNP), a strong correlation with NRM was observed (hazard ratio [HR], 2.31; 95% CI, 1.36 to 3.95; P = .002). More specifically, NRM was predicted by THBD SNPs in patients who later developed GVHD (HR, 3.03; 95% CI, 1.61 to 5.68; P < .001) but not in patients without GVHD. In contrast, THBD SNPs did not predict incidence of acute GVHD. Multivariable analyses adjusting for clinical variables confirmed the independent effect of THBD SNPs on NRM. All findings could be reproduced in the validation cohort. THBD SNPs predict mortality of manifest GVHD but not the risk of acquiring GVHD, supporting the hypothesis that endothelial vulnerability contributes to GVHD refractoriness. © 2014 by American Society of Clinical Oncology.

Systematic elucidation and in vivo validation of sequences enriched in hindbrain transcriptional control

PubMed Central

Burzynski, Grzegorz M.; Reed, Xylena; Taher, Leila; Stine, Zachary E.; Matsui, Takeshi; Ovcharenko, Ivan; McCallion, Andrew S.

2012-01-01

Illuminating the primary sequence encryption of enhancers is central to understanding the regulatory architecture of genomes. We have developed a machine learning approach to decipher motif patterns of hindbrain enhancers and identify 40,000 sequences in the human genome that we predict display regulatory control that includes the hindbrain. Consistent with their roles in hindbrain patterning, MEIS1, NKX6-1, as well as HOX and POU family binding motifs contributed strongly to this enhancer model. Predicted hindbrain enhancers are overrepresented at genes expressed in hindbrain and associated with nervous system development, and primarily reside in the areas of open chromatin. In addition, 77 (0.2%) of these predictions are identified as hindbrain enhancers on the VISTA Enhancer Browser, and 26,000 (60%) overlap enhancer marks (H3K4me1 or H3K27ac). To validate these putative hindbrain enhancers, we selected 55 elements distributed throughout our predictions and six low scoring controls for evaluation in a zebrafish transgenic assay. When assayed in mosaic transgenic embryos, 51/55 elements directed expression in the central nervous system. Furthermore, 30/34 (88%) predicted enhancers analyzed in stable zebrafish transgenic lines directed expression in the larval zebrafish hindbrain. Subsequent analysis of sequence fragments selected based upon motif clustering further confirmed the critical role of the motifs contributing to the classifier. Our results demonstrate the existence of a primary sequence code characteristic to hindbrain enhancers. This code can be accurately extracted using machine-learning approaches and applied successfully for de novo identification of hindbrain enhancers. This study represents a critical step toward the dissection of regulatory control in specific neuronal subtypes. PMID:22759862

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

PubMed Central

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

2009-01-01

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

Development of Modeling Capabilities for Launch Pad Acoustics and Ignition Transient Environment Prediction

NASA Technical Reports Server (NTRS)

West, Jeff; Strutzenberg, Louise L.; Putnam, Gabriel C.; Liever, Peter A.; Williams, Brandon R.

2012-01-01

This paper presents development efforts to establish modeling capabilities for launch vehicle liftoff acoustics and ignition transient environment predictions. Peak acoustic loads experienced by the launch vehicle occur during liftoff with strong interaction between the vehicle and the launch facility. Acoustic prediction engineering tools based on empirical models are of limited value in efforts to proactively design and optimize launch vehicles and launch facility configurations for liftoff acoustics. Modeling approaches are needed that capture the important details of the plume flow environment including the ignition transient, identify the noise generation sources, and allow assessment of the effects of launch pad geometric details and acoustic mitigation measures such as water injection. This paper presents a status of the CFD tools developed by the MSFC Fluid Dynamics Branch featuring advanced multi-physics modeling capabilities developed towards this goal. Validation and application examples are presented along with an overview of application in the prediction of liftoff environments and the design of targeted mitigation measures such as launch pad configuration and sound suppression water placement.

Predicting Changes in Depressive Symptoms from Pregnancy to Postpartum: The Role of Brooding Rumination and Negative Inferential Styles

PubMed Central

Barnum, Sarah E.; Woody, Mary L.; Gibb, Brandon E.

2014-01-01

The current study examined the role of cognitive factors in the development and maintenance of depressive symptoms from pregnancy into the postpartum period. One hundred and one women were assessed for levels of rumination (brooding and reflection), negative inferential styles, and depressive symptoms in their third trimester of pregnancy and depressive symptom levels again at four and eight weeks postpartum. We found that, although none of the three cognitive variables predicted women’s initial depressive reactions following childbirth (from pregnancy to one month postpartum), brooding rumination and negative inferential styles predicted longer-term depressive symptom changes (from pregnancy to two months postpartum). However, the predictive validity of women’s negative inferential styles was limited to women already exhibiting relatively high depressive symptom levels during pregnancy, suggesting that it was more strongly related to the maintenance of depressive symptoms into the postpartum period rather than increases in depressive symptoms following childbirth. Modifying cognitive risk factors, therefore, may be an important focus of intervention for depression during pregnancy. PMID:25401383

ProTox: a web server for the in silico prediction of rodent oral toxicity

PubMed Central

Drwal, Malgorzata N.; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R.; Preissner, Robert

2014-01-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein–ligand-based pharmacophore models (‘toxicophores’) for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. PMID:24838562

Assessing a Top-Down Modeling Approach for Seasonal Scale Snow Sensitivity

NASA Astrophysics Data System (ADS)

Luce, C. H.; Lute, A.

2017-12-01

Mechanistic snow models are commonly applied to assess changes to snowpacks in a warming climate. Such assessments involve a number of assumptions about details of weather at daily to sub-seasonal time scales. Models of season-scale behavior can provide contrast for evaluating behavior at time scales more in concordance with climate warming projections. Such top-down models, however, involve a degree of empiricism, with attendant caveats about the potential of a changing climate to affect calibrated relationships. We estimated the sensitivity of snowpacks from 497 Snowpack Telemetry (SNOTEL) stations in the western U.S. based on differences in climate between stations (spatial analog). We examined the sensitivity of April 1 snow water equivalent (SWE) and mean snow residence time (SRT) to variations in Nov-Mar precipitation and average Nov-Mar temperature using multivariate local-fit regressions. We tested the modeling approach using a leave-one-out cross-validation as well as targeted two-fold non-random cross-validations contrasting, for example, warm vs. cold years, dry vs. wet years, and north vs. south stations. Nash-Sutcliffe Efficiency (NSE) values for the validations were strong for April 1 SWE, ranging from 0.71 to 0.90, and still reasonable, but weaker, for SRT, in the range of 0.64 to 0.81. From these ranges, we exclude validations where the training data do not represent the range of target data. A likely reason for differences in validation between the two metrics is that the SWE model reflects the influence of conservation of mass while using temperature as an indicator of the season-scale energy balance; in contrast, SRT depends more strongly on the energy balance aspects of the problem. Model forms with lower numbers of parameters generally validated better than more complex model forms, with the caveat that pseudoreplication could encourage selection of more complex models when validation contrasts were weak. Overall, the split sample validations confirm transferability of the relationships in space and time contingent upon full representation of validation conditions in the calibration data set. The ability of the top-down space-for-time models to predict in new time periods and locations lends confidence to their application for assessments and for improving finer time scale models.

Comparison of Model Prediction with Measurements of Galactic Background Noise at L-Band

NASA Technical Reports Server (NTRS)

LeVine, David M.; Abraham, Saji; Kerr, Yann H.; Wilson, Willam J.; Skou, Niels; Sobjaerg, S.

2004-01-01

The spectral window at L-band (1.413 GHz) is important for passive remote sensing of surface parameters such as soil moisture and sea surface salinity that are needed to understand the hydrological cycle and ocean circulation. Radiation from celestial (mostly galactic) sources is strong in this window and an accurate accounting for this background radiation is often needed for calibration. Modem radio astronomy measurements in this spectral window have been converted into a brightness temperature map of the celestial sky at L-band suitable for use in correcting passive measurements. This paper presents a comparison of the background radiation predicted by this map with measurements made with several modem L-band remote sensing radiometers. The agreement validates the map and the procedure for locating the source of down-welling radiation.

Improved pump turbine transient behaviour prediction using a Thoma number-dependent hillchart model

NASA Astrophysics Data System (ADS)

Manderla, M.; Kiniger, K.; Koutnik, J.

2014-03-01

Water hammer phenomena are important issues for high head hydro power plants. Especially, if several reversible pump-turbines are connected to the same waterways there may be strong interactions between the hydraulic machines. The prediction and coverage of all relevant load cases is challenging and difficult using classical simulation models. On the basis of a recent pump-storage project, dynamic measurements motivate an improved modeling approach making use of the Thoma number dependency of the actual turbine behaviour. The proposed approach is validated for several transient scenarios and turns out to increase correlation between measurement and simulation results significantly. By applying a fully automated simulation procedure broad operating ranges can be covered which provides a consistent insight into critical load case scenarios. This finally allows the optimization of the closing strategy and hence the overall power plant performance.

Generic Raman-based calibration models enabling real-time monitoring of cell culture bioreactors.

PubMed

Mehdizadeh, Hamidreza; Lauri, David; Karry, Krizia M; Moshgbar, Mojgan; Procopio-Melino, Renee; Drapeau, Denis

2015-01-01

Raman-based multivariate calibration models have been developed for real-time in situ monitoring of multiple process parameters within cell culture bioreactors. Developed models are generic, in the sense that they are applicable to various products, media, and cell lines based on Chinese Hamster Ovarian (CHO) host cells, and are scalable to large pilot and manufacturing scales. Several batches using different CHO-based cell lines and corresponding proprietary media and process conditions have been used to generate calibration datasets, and models have been validated using independent datasets from separate batch runs. All models have been validated to be generic and capable of predicting process parameters with acceptable accuracy. The developed models allow monitoring multiple key bioprocess metabolic variables, and hence can be utilized as an important enabling tool for Quality by Design approaches which are strongly supported by the U.S. Food and Drug Administration. © 2015 American Institute of Chemical Engineers.

An Aquatic Decomposition Scoring Method to Potentially Predict the Postmortem Submersion Interval of Bodies Recovered from the North Sea.

PubMed

van Daalen, Marjolijn A; de Kat, Dorothée S; Oude Grotebevelsborg, Bernice F L; de Leeuwe, Roosje; Warnaar, Jeroen; Oostra, Roelof Jan; M Duijst-Heesters, Wilma L J

2017-03-01

This study aimed to develop an aquatic decomposition scoring (ADS) method and investigated the predictive value of this method in estimating the postmortem submersion interval (PMSI) of bodies recovered from the North Sea. This method, consisting of an ADS item list and a pictorial reference atlas, showed a high interobserver agreement (Krippendorff's alpha ≥ 0.93) and hence proved to be valid. This scoring method was applied to data, collected from closed cases-cases in which the postmortal submersion interval (PMSI) was known-concerning bodies recovered from the North Sea from 1990 to 2013. Thirty-eight cases met the inclusion criteria and were scored by quantifying the observed total aquatic decomposition score (TADS). Statistical analysis demonstrated that TADS accurately predicts the PMSI (p < 0.001), confirming that the decomposition process in the North Sea is strongly correlated to time. © 2017 American Academy of Forensic Sciences.

Hidden Criticality of Counterion Condensation Near a Charged Cylinder.

PubMed

Cha, Minryeong; Yi, Juyeon; Kim, Yong Woon

2017-09-05

Counterion condensation onto a charged cylinder, known as the Manning transition, has received a great deal of attention since it is essential to understand the properties of polyelectrolytes in ionic solutions. However, the current understanding is still far from complete and poses a puzzling question: While the strong-coupling theory valid at large ionic correlations suggests a discontinuous nature of the counterion condensation, the mean-field theory always predicts a continuous transition at the same critical point. This naturally leads to a question how one can reconcile the mean-field theory with the strong-coupling prediction. Here, we study the counterion condensation transition on a charged cylinder via Monte Carlo simulations. Varying the cylinder radius systematically in relation to the system size, we find that in addition to the Manning transition, there exists a novel transition where all counterions are bound to the cylinder and the heat capacity shows a drop at a finite Manning parameter. A finite-size scaling analysis is carried out to confirm the criticality of the complete condensation transition, yielding the same critical exponents with the Manning transition. We show that the existence of the complete condensation is essential to explain how the condensation nature alters from continuous to discontinuous transition.

Depletion sensitivity predicts unhealthy snack purchases.

PubMed

Salmon, Stefanie J; Adriaanse, Marieke A; Fennis, Bob M; De Vet, Emely; De Ridder, Denise T D

2016-01-01

The aim of the present research is to examine the relation between depletion sensitivity - a novel construct referring to the speed or ease by which one's self-control resources are drained - and snack purchase behavior. In addition, interactions between depletion sensitivity and the goal to lose weight on snack purchase behavior were explored. Participants included in the study were instructed to report every snack they bought over the course of one week. The dependent variables were the number of healthy and unhealthy snacks purchased. The results of the present study demonstrate that depletion sensitivity predicts the amount of unhealthy (but not healthy) snacks bought. The more sensitive people are to depletion, the more unhealthy snacks they buy. Moreover, there was some tentative evidence that this relation is more pronounced for people with a weak as opposed to a strong goal to lose weight, suggesting that a strong goal to lose weight may function as a motivational buffer against self-control failures. All in all, these findings provide evidence for the external validity of depletion sensitivity and the relevance of this construct in the domain of eating behavior. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multicentre validation of a sepsis prediction algorithm using only vital sign data in the emergency department, general ward and ICU

PubMed Central

Mao, Qingqing; Jay, Melissa; Calvert, Jacob; Barton, Christopher; Shimabukuro, David; Shieh, Lisa; Chettipally, Uli; Fletcher, Grant; Kerem, Yaniv; Zhou, Yifan; Das, Ritankar

2018-01-01

Objectives We validate a machine learning-based sepsis-prediction algorithm (InSight) for the detection and prediction of three sepsis-related gold standards, using only six vital signs. We evaluate robustness to missing data, customisation to site-specific data using transfer learning and generalisability to new settings. Design A machine-learning algorithm with gradient tree boosting. Features for prediction were created from combinations of six vital sign measurements and their changes over time. Setting A mixed-ward retrospective dataset from the University of California, San Francisco (UCSF) Medical Center (San Francisco, California, USA) as the primary source, an intensive care unit dataset from the Beth Israel Deaconess Medical Center (Boston, Massachusetts, USA) as a transfer-learning source and four additional institutions’ datasets to evaluate generalisability. Participants 684 443 total encounters, with 90 353 encounters from June 2011 to March 2016 at UCSF. Interventions None. Primary and secondary outcome measures Area under the receiver operating characteristic (AUROC) curve for detection and prediction of sepsis, severe sepsis and septic shock. Results For detection of sepsis and severe sepsis, InSight achieves an AUROC curve of 0.92 (95% CI 0.90 to 0.93) and 0.87 (95% CI 0.86 to 0.88), respectively. Four hours before onset, InSight predicts septic shock with an AUROC of 0.96 (95% CI 0.94 to 0.98) and severe sepsis with an AUROC of 0.85 (95% CI 0.79 to 0.91). Conclusions InSight outperforms existing sepsis scoring systems in identifying and predicting sepsis, severe sepsis and septic shock. This is the first sepsis screening system to exceed an AUROC of 0.90 using only vital sign inputs. InSight is robust to missing data, can be customised to novel hospital data using a small fraction of site data and retains strong discrimination across all institutions. PMID:29374661

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

ERIC Educational Resources Information Center

Thorsen, Cecilia; Cliffordson, Christina

2012-01-01

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

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

PubMed

Leslie, William D; Lix, Lisa M

2011-03-01

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

Strong ground motion prediction applying dynamic rupture simulations for Beppu-Haneyama Active Fault Zone, southwestern Japan

NASA Astrophysics Data System (ADS)

Yoshimi, M.; Matsushima, S.; Ando, R.; Miyake, H.; Imanishi, K.; Hayashida, T.; Takenaka, H.; Suzuki, H.; Matsuyama, H.

2017-12-01

We conducted strong ground motion prediction for the active Beppu-Haneyama Fault zone (BHFZ), Kyushu island, southwestern Japan. Since the BHFZ runs through Oita and Beppy cities, strong ground motion as well as fault displacement may affect much to the cities.We constructed a 3-dimensional velocity structure of a sedimentary basin, Beppu bay basin, where the fault zone runs through and Oita and Beppu cities are located. Minimum shear wave velocity of the 3d model is 500 m/s. Additional 1-d structure is modeled for sites with softer sediment: holocene plain area. We observed, collected, and compiled data obtained from microtremor surveys, ground motion observations, boreholes etc. phase velocity and H/V ratio. Finer structure of the Oita Plain is modeled, as 250m-mesh model, with empirical relation among N-value, lithology, depth and Vs, using borehole data, then validated with the phase velocity data obtained by the dense microtremor array observation (Yoshimi et al., 2016).Synthetic ground motion has been calculated with a hybrid technique composed of a stochastic Green's function method (for HF wave), a 3D finite difference (LF wave) and 1D amplification calculation. Fault geometry has been determined based on reflection surveys and active fault map. The rake angles are calculated with a dynamic rupture simulation considering three fault segments under a stress filed estimated from source mechanism of earthquakes around the faults (Ando et al., JpGU-AGU2017). Fault parameters such as the average stress drop, a size of asperity etc. are determined based on an empirical relation proposed by Irikura and Miyake (2001). As a result, strong ground motion stronger than 100 cm/s is predicted in the hanging wall side of the Oita plain.This work is supported by the Comprehensive Research on the Beppu-Haneyama Fault Zone funded by the Ministry of Education, Culture, Sports, Science, and Technology (MEXT), Japan.

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

The predictive validity of the MCAT exam in relation to academic performance through medical school: a national cohort study of 2001-2004 matriculants.

PubMed

Dunleavy, Dana M; Kroopnick, Marc H; Dowd, Keith W; Searcy, Cynthia A; Zhao, Xiaohui

2013-05-01

Most research examining the predictive validity of the Medical College Admission Test (MCAT) has focused on the relationship between MCAT scores and scores on the United States Medical Licensing Examination Step exams. This study examined whether MCAT scores predict students' unimpeded progress toward graduation (UP), which the authors defined as not withdrawing or being dismissed for academic reasons, graduating within five years of matriculation, and passing the Step 1, Step 2 Clinical Knowledge, and Step 2 Clinical Skills exams on the first attempt. Students who matriculated during 2001-2004 at 119 U.S. medical schools were included in the analyses. Logistic regression analyses were used to estimate the relationships between UP and MCAT total scores alone, undergraduate grade point averages (UGPAs) alone, and UGPAs and MCAT total scores together. All analyses were conducted at the school level and were considered together to evaluate relationships across schools. The majority of matriculants experienced UP. Together, UGPAs and MCAT total scores predicted UP well. MCAT total scores alone were a better predictor than UGPAs alone. Relationships were similar across schools; however, there was more variability across schools in the relationship between UP and UGPAs than between UP and MCAT total scores. The combination of UGPAs and MCAT total scores performs well as a predictor of UP. Both UGPAs and MCAT total scores are strong predictors of academic performance in medical school through graduation, not just the first two years. Further, these relationships generalize across medical schools.

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.

A scale on beliefs about children's adjustment in same-sex families: reliability and validity.

PubMed

Frias-Navarro, Dolores; Monterde-I-Bort, Hector

2012-01-01

In this study, we developed a new instrument named Scale Beliefs about Children's Adjustment on Same-Sex Families (SBCASSF). The scale was developed to assess of the adults' beliefs about negative impacts on children who are raised by same-sex parents. An initial pool of 95 items was generated by the authors based on a review of the literature on homophobia and feedback from several focus groups. Research findings, based on a sample of 212 university students (mean age 22 years, SD = 8.28), supported the reliability and validity of the scale. The final versions of the SBCASSF included items reflecting the following two factors: individual opposition (α = .87) and normative opposition (α = .88). Convergent validity of the scale is demonstrated by predictable correlations with beliefs about the cause of same-sex sexual orientation and the support for gay and lesbian rights. Our study reveals a strong positive association between high scores on SBCASSF and beliefs that the origin of same-sex sexual orientation is learned and opposition to gay and lesbian rights.

Indirect Validation of Probe Speed Data on Arterial Corridors

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

Eshragh, Sepideh; Young, Stanley E.; Sharifi, Elham

This study aimed to estimate the accuracy of probe speed data on arterial corridors on the basis of roadway geometric attributes and functional classification. It was assumed that functional class (medium and low) along with other road characteristics (such as weighted average of the annual average daily traffic, average signal density, average access point density, and average speed) were available as correlation factors to estimate the accuracy of probe traffic data. This study tested these factors as predictors of the fidelity of probe traffic data by using the results of an extensive validation exercise. This study showed strong correlations betweenmore » these geometric attributes and the accuracy of probe data when they were assessed by using average absolute speed error. Linear models were regressed to existing data to estimate appropriate models for medium- and low-type arterial corridors. The proposed models for medium- and low-type arterials were validated further on the basis of the results of a slowdown analysis. These models can be used to predict the accuracy of probe data indirectly in medium and low types of arterial corridors.« less

Mutations in gp41 are correlated with coreceptor tropism but do not improve prediction methods substantially.

PubMed

Thielen, Alexander; Lengauer, Thomas; Swenson, Luke C; Dong, Winnie W Y; McGovern, Rachel A; Lewis, Marilyn; James, Ian; Heera, Jayvant; Valdez, Hernan; Harrigan, P Richard

2011-01-01

The main determinants of HIV-1 coreceptor usage are located in the V3-loop of gp120, although mutations in V2 and gp41 are also known. Incorporation of V2 is known to improve prediction algorithms; however, this has not been confirmed for gp41 mutations. Samples with V3 and gp41 genotypes and Trofile assay (Monogram Biosciences, South San Francisco, CA, USA) results were taken from the HOMER cohort (n=444) and from patients screened for the MOTIVATE studies (n=1,916; 859 with maraviroc outcome data). Correlations of mutations with tropism were assessed using Fisher's exact test and prediction models trained using support vector machines. Models were validated by cross-validation, by testing models from one dataset on the other, and by analysing virological outcome. Several mutations within gp41 were highly significant for CXCR4 usage; most strikingly an insertion occurring in 7.7% of HOMER-R5 and 46.3% of HOMER-X4 samples (MOTIVATE 5.7% and 25.2%, respectively). Models trained on gp41 sequence alone achieved relatively high areas under the receiver-operating characteristic curve (AUCs; HOMER 0.713 and MOTIVATE 0.736) that were almost as good as V3 models (0.773 and 0.884, respectively). However, combining the two regions improved predictions only marginally (0.813 and 0.902, respectively). Similar results were found when models were trained on HOMER and validated on MOTIVATE or vice versa. The difference in median log viral load decrease at week 24 between patients with R5 and X4 virus was 1.65 (HOMER 2.45 and MOTIVATE 0.79) for V3 models, 1.59 for gp41-models (2.42 and 0.83, respectively) and 1.58 for the combined predictor (2.44 and 0.86, respectively). Several mutations within gp41 showed strong correlation with tropism in two independent datasets. However, incorporating gp41 mutations into prediction models is not mandatory because they do not improve substantially on models trained on V3 sequences alone.

The stroke impairment assessment set: its internal consistency and predictive validity.

PubMed

Tsuji, T; Liu, M; Sonoda, S; Domen, K; Chino, N

2000-07-01

To study the scale quality and predictive validity of the Stroke Impairment Assessment Set (SIAS) developed for stroke outcome research. Rasch analysis of the SIAS; stepwise multiple regression analysis to predict discharge functional independence measure (FIM) raw scores from demographic data, the SIAS scores, and the admission FIM scores; cross-validation of the prediction rule. Tertiary rehabilitation center in Japan. One hundred ninety stroke inpatients for the study of the scale quality and the predictive validity; a second sample of 116 stroke inpatients for the cross-validation study. Mean square fit statistics to study the degree of fit to the unidimensional model; logits to express item difficulties; discharge FIM scores for the study of predictive validity. The degree of misfit was acceptable except for the shoulder range of motion (ROM), pain, visuospatial function, and speech items; and the SIAS items could be arranged on a common unidimensional scale. The difficulty patterns were identical at admission and at discharge except for the deep tendon reflexes, ROM, and pain items. They were also similar for the right- and left-sided brain lesion groups except for the speech and visuospatial items. For the prediction of the discharge FIM scores, the independent variables selected were age, the SIAS total scores, and the admission FIM scores; and the adjusted R2 was .64 (p < .0001). Stability of the predictive equation was confirmed in the cross-validation sample (R2 = .68, p < .001). The unidimensionality of the SIAS was confirmed, and the SIAS total scores proved useful for stroke outcome prediction.

Peak ground motion predictions with empirical site factors using Taiwan Strong Motion Network recordings

NASA Astrophysics Data System (ADS)

Chung, Jen-Kuang

2013-09-01

A stochastic method called the random vibration theory (Boore, 1983) has been used to estimate the peak ground motions caused by shallow moderate-to-large earthquakes in the Taiwan area. Adopting Brune's ω-square source spectrum, attenuation models for PGA and PGV were derived from path-dependent parameters which were empirically modeled from about one thousand accelerograms recorded at reference sites mostly located in a mountain area and which have been recognized as rock sites without soil amplification. Consequently, the predicted horizontal peak ground motions at the reference sites, are generally comparable to these observed. A total number of 11,915 accelerograms recorded from 735 free-field stations of the Taiwan Strong Motion Network (TSMN) were used to estimate the site factors by taking the motions from the predictive models as references. Results from soil sites reveal site amplification factors of approximately 2.0 ~ 3.5 for PGA and about 1.3 ~ 2.6 for PGV. Finally, as a result of amplitude corrections with those empirical site factors, about 75% of analyzed earthquakes are well constrained in ground motion predictions, having average misfits ranging from 0.30 to 0.50. In addition, two simple indices, R 0.57 and R 0.38, are proposed in this study to evaluate the validity of intensity map prediction for public information reports. The average percentages of qualified stations for peak acceleration residuals less than R 0.57 and R 0.38 can reach 75% and 54%, respectively, for most earthquakes. Such a performance would be good enough to produce a faithful intensity map for a moderate scenario event in the Taiwan region.

Prediction of winter precipitation over northwest India using ocean heat fluxes

NASA Astrophysics Data System (ADS)

Nageswararao, M. M.; Mohanty, U. C.; Osuri, Krishna K.; Ramakrishna, S. S. V. S.

2016-10-01

The winter precipitation (December-February) over northwest India (NWI) is highly variable in terms of time and space. The maximum precipitation occurs over the Himalaya region and decreases towards south of NWI. The winter precipitation is important for water resources and agriculture sectors over the region and for the economy of the country. It is an exigent task to the scientific community to provide a seasonal outlook for the regional scale precipitation. The oceanic heat fluxes are known to have a strong linkage with the ocean and atmosphere. Henceforth, in this study, we obtained the relationship of NWI winter precipitation with total downward ocean heat fluxes at the global ocean surface, 15 regions with significant correlations are identified from August to November at 90 % confidence level. These strong relations encourage developing an empirical model for predicting winter precipitation over NWI. The multiple linear regression (MLR) and principal component regression (PCR) models are developed and evaluated using leave-one-out cross-validation. The developed regression models are able to predict the winter precipitation patterns over NWI with significant (99 % confidence level) index of agreement and correlations. Moreover, these models capture the signals of extremes, but could not reach the peaks (excess and deficit) of the observations. PCR performs better than MLR for predicting winter precipitation over NWI. Therefore, the total downward ocean heat fluxes at surface from August to November are having a significant impact on seasonal winter precipitation over the NWI. It concludes that these interrelationships are more useful for the development of empirical models and feasible to predict the winter precipitation over NWI with sufficient lead-time (in advance) for various risk management sectors.

Multiway analysis methods applied to the fluorescence excitation-emission dataset for the simultaneous quantification of valsartan and amlodipine in tablets

NASA Astrophysics Data System (ADS)

Dinç, Erdal; Ertekin, Zehra Ceren; Büker, Eda

2017-09-01

In this study, excitation-emission matrix datasets, which have strong overlapping bands, were processed by using four different chemometric calibration algorithms consisting of parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares for the simultaneous quantitative estimation of valsartan and amlodipine besylate in tablets. In analyses, preliminary separation step was not used before the application of parallel factor analysis Tucker3, three-way partial least squares and unfolded partial least squares approaches for the analysis of the related drug substances in samples. Three-way excitation-emission matrix data array was obtained by concatenating excitation-emission matrices of the calibration set, validation set, and commercial tablet samples. The excitation-emission matrix data array was used to get parallel factor analysis, Tucker3, three-way partial least squares and unfolded partial least squares calibrations and to predict the amounts of valsartan and amlodipine besylate in samples. For all the methods, calibration and prediction of valsartan and amlodipine besylate were performed in the working concentration ranges of 0.25-4.50 μg/mL. The validity and the performance of all the proposed methods were checked by using the validation parameters. From the analysis results, it was concluded that the described two-way and three-way algorithmic methods were very useful for the simultaneous quantitative resolution and routine analysis of the related drug substances in marketed samples.

Impact of correlation of predictors on discrimination of risk models in development and external populations.

PubMed

Kundu, Suman; Mazumdar, Madhu; Ferket, Bart

2017-04-19

The area under the ROC curve (AUC) of risk models is known to be influenced by differences in case-mix and effect size of predictors. The impact of heterogeneity in correlation among predictors has however been under investigated. We sought to evaluate how correlation among predictors affects the AUC in development and external populations. We simulated hypothetical populations using two different methods based on means, standard deviations, and correlation of two continuous predictors. In the first approach, the distribution and correlation of predictors were assumed for the total population. In the second approach, these parameters were modeled conditional on disease status. In both approaches, multivariable logistic regression models were fitted to predict disease risk in individuals. Each risk model developed in a population was validated in the remaining populations to investigate external validity. For both approaches, we observed that the magnitude of the AUC in the development and external populations depends on the correlation among predictors. Lower AUCs were estimated in scenarios of both strong positive and negative correlation, depending on the direction of predictor effects and the simulation method. However, when adjusted effect sizes of predictors were specified in the opposite directions, increasingly negative correlation consistently improved the AUC. AUCs in external validation populations were higher or lower than in the derivation cohort, even in the presence of similar predictor effects. Discrimination of risk prediction models should be assessed in various external populations with different correlation structures to make better inferences about model generalizability.

Deep learning of quasar spectra to discover and characterize damped Lyα systems

NASA Astrophysics Data System (ADS)

Parks, David; Prochaska, J. Xavier; Dong, Shawfeng; Cai, Zheng

2018-05-01

We have designed, developed, and applied a convolutional neural network (CNN) architecture using multi-task learning to search for and characterize strong H I Lyα absorption in quasar spectra. Without any explicit modelling of the quasar continuum or application of the predicted line profile for Lyα from quantum mechanics, our algorithm predicts the presence of strong H I absorption and estimates the corresponding redshift zabs and H I column density N_{H I}, with emphasis on damped Lyα systems (DLAs, absorbers with N_{H I}≥ 2 × 10^{20} cm^{-2}). We tuned the CNN model using a custom training set of DLAs injected into DLA-free quasar spectra from the Sloan Digital Sky Survey (SDSS), data release 5 (DR5). Testing on a held-back validation set demonstrates a high incidence of DLAs recovered by the algorithm (97.4 per cent as DLAs and 99 per cent as an H I absorber with N_{H I}> 10^{19.5} cm^{-2}) and excellent estimates for zabs and N_{H I}. Similar results are obtained against a human-generated survey of the SDSS DR5 data set. The algorithm yields a low incidence of false positives and negatives but is challenged by overlapping DLAs and/or very high N_{H I} systems. We have applied this CNN model to the quasar spectra of SDSS DR7 and the Baryon Oscillation Spectroscopic Survey (data release 12) and provide catalogues of 4913 and 50 969 DLAs, respectively (including 1659 and 9230 high-confidence DLAs that were previously unpublished). This work validates the application of deep learning techniques to astronomical spectra for both classification and quantitative measurements.

Network-based analysis of oligodendrogliomas predicts novel cancer gene candidates within the region of the 1p/19q co-deletion.

PubMed

Gladitz, Josef; Klink, Barbara; Seifert, Michael

2018-06-11

Oligodendrogliomas are primary human brain tumors with a characteristic 1p/19q co-deletion of important prognostic relevance, but little is known about the pathology of this chromosomal mutation. We developed a network-based approach to identify novel cancer gene candidates in the region of the 1p/19q co-deletion. Gene regulatory networks were learned from gene expression and copy number data of 178 oligodendrogliomas and further used to quantify putative impacts of differentially expressed genes of the 1p/19q region on cancer-relevant pathways. We predicted 8 genes with strong impact on signaling pathways and 14 genes with strong impact on metabolic pathways widespread across the region of the 1p/19 co-deletion. Many of these candidates (e.g. ELTD1, SDHB, SEPW1, SLC17A7, SZRD1, THAP3, ZBTB17) are likely to push, whereas others (e.g. CAP1, HBXIP, KLK6, PARK7, PTAFR) might counteract oligodendroglioma development. For example, ELTD1, a functionally validated glioblastoma oncogene located on 1p, was overexpressed. Further, the known glioblastoma tumor suppressor SLC17A7 located on 19q was underexpressed. Moreover, known epigenetic alterations triggered by mutated SDHB in paragangliomas suggest that underexpressed SDHB in oligodendrogliomas may support and possibly enhance the epigenetic reprogramming induced by the IDH-mutation. We further analyzed rarely observed deletions and duplications of chromosomal arms within oligodendroglioma subcohorts identifying putative oncogenes and tumor suppressors that possibly influence the development of oligodendroglioma subgroups. Our in-depth computational study contributes to a better understanding of the pathology of the 1p/19q co-deletion and other chromosomal arm mutations. This might open opportunities for functional validations and new therapeutic strategies.

Integrated fusion simulation with self-consistent core-pedestal coupling

DOE PAGES

Meneghini, O.; Snyder, P. B.; Smith, S. P.; ...

2016-04-20

In this study, accurate prediction of fusion performance in present and future tokamaks requires taking into account the strong interplay between core transport, pedestal structure, current profile and plasma equilibrium. An integrated modeling workflow capable of calculating the steady-state self- consistent solution to this strongly-coupled problem has been developed. The workflow leverages state-of-the-art components for collisional and turbulent core transport, equilibrium and pedestal stability. Validation against DIII-D discharges shows that the workflow is capable of robustly pre- dicting the kinetic profiles (electron and ion temperature and electron density) from the axis to the separatrix in good agreement with the experiments.more » An example application is presented, showing self-consistent optimization for the fusion performance of the 15 MA D-T ITER baseline scenario as functions of the pedestal density and ion effective charge Z eff.« less

Intoxication-Related AmED (Alcohol Mixed with Energy Drink) Expectancies Scale: Initial Development and Validation

PubMed Central

Miller, Kathleen E.; Dermen, Kurt H.; Lucke, Joseph F.

2017-01-01

BACKGROUND Young adult use of alcohol mixed with energy drinks (AmEDs) has been linked with elevated risks for a constellation of problem behaviors. These risks may be conditioned by expectancies regarding the effects of caffeine in conjunction with alcohol consumption. The aim of this study was to describe the construction and psychometric evaluation of the Intoxication-Related AmED Expectancies Scale (AmED_EXPI), 15 self-report items measuring beliefs about how the experience of AmED intoxication differs from the experience of noncaffeinated alcohol (NCA) intoxication. METHODS Scale development and testing were conducted using data from a U.S. national sample of 3,105 adolescents and emerging adults aged 13–25. Exploratory and confirmatory factor analyses were conducted to evaluate the factor structure and establish factor invariance across gender, age, and prior experience with AmED use. Cross-sectional and longitudinal analyses examining correlates of AmED use were used to assess construct and predictive validity. RESULTS In confirmatory factor analyses, fit indices for the hypothesized four-factor structure (i.e., Intoxication Management [IM], Alertness [AL], Sociability [SO], and Jitters [JT]) revealed a moderately good fit to the data. Together, these factors accounted for 75.3% of total variance. The factor structure was stable across male/female, teen/young adult, and AmED experience/no experience subgroups. The resultant unit-weighted subscales showed strong internal consistency and satisfactory convergent validity. Baseline scores on the IM, SO, and JT subscales predicted changes in AmED use over a subsequent three-month period. CONCLUSIONS The AmED_EXPI appears to be a reliable and valid tool for measuring expectancies about the effects of caffeine during alcohol intoxication. PMID:28421613

Dual energy X-ray absorptiometry spine scans to determine abdominal fat in post-menopausal women

PubMed Central

Bea, J. W.; Blew, R. M.; Going, S. B.; Hsu, C-H; Lee, M. C.; Lee, V. R.; Caan, B.J.; Kwan, M.L.; Lohman, T. G.

2016-01-01

Body composition may be a better predictor of chronic disease risk than body mass index (BMI) in older populations. Objectives We sought to validate spine fat fraction (%) from dual energy X-ray absorptiometry (DXA) spine scans as a proxy for total abdominal fat. Methods Total body DXA scan abdominal fat regions of interest (ROI) that have been previously validated by magnetic resonance imaging were assessed among healthy, postmenopausal women who also had antero-posterior spine scans (n=103). ROIs were 1) lumbar vertebrae L2-L4 and 2) L2-Iliac Crest (L2-IC), manually selected by two independent raters, and 3) trunk, auto-selected by DXA software. Intra-class correlation coefficients evaluated intra and inter-rater reliability on a random subset (N=25). Linear regression models, validated by bootstrapping, assessed the relationship between spine fat fraction (%) and total abdominal fat (%) ROIs. Results Mean age, BMI and total body fat were: 66.1 ± 4.8y, 25.8 ± 3.8kg/m2 and 40.0 ± 6.6%, respectively. There were no significant differences within or between raters. Linear regression models adjusted for several participant and scan characteristics were equivalent to using only BMI and spine fat fraction. The model predicted L2-L4 (Adj. R2: 0.83) and L2-IC (Adj.R2:0.84) abdominal fat (%) well; the adjusted R2 for trunk fat (%) was 0.78. Model validation demonstrated minimal over-fitting (Adj. R2: 0.82, 0.83, and 0.77 for L2-L4, L2-IC, and trunk fat respectively). Conclusions The strong correlation between spine fat fraction and DXA abdominal fat measures make it suitable for further development in post-menopausal chronic disease risk prediction models. PMID:27416964

Brief comprehensive quality of life assessment after stroke: the assessment of quality of life instrument in the north East melbourne stroke incidence study (NEMESIS).

PubMed

Sturm, Jonathan W; Osborne, Richard H; Dewey, Helen M; Donnan, Geoffrey A; Macdonell, Richard A L; Thrift, Amanda G

2002-12-01

Generic utility health-related quality of life instruments are useful in assessing stroke outcome because they facilitate a broader description of the disease and outcomes, allow comparisons between diseases, and can be used in cost-benefit analysis. The aim of this study was to validate the Assessment of Quality of Life (AQoL) instrument in a stroke population. Ninety-three patients recruited from the community-based North East Melbourne Stroke Incidence Study between July 13, 1996, and April 30, 1997, were interviewed 3 months after stroke. Validity of the AQoL was assessed by examining associations between the AQoL and comparator instruments: the Medical Outcomes Short-Form Health Survey (SF-36); London Handicap Scale; Barthel Index; National Institutes of Health Stroke Scale; and Irritability, Depression, Anxiety scale. Sensitivity of the AQoL was assessed by comparing AQoL scores from groups of patients categorized by severity of impairment and disability and with total anterior circulation syndrome (TACS) versus non-TACS. Predictive validity was assessed by examining the association between 3-month AQoL scores and outcomes of death or institutionalization 12 months after stroke. Overall AQoL utility scores and individual dimension scores were most highly correlated with relevant scales on the comparator instruments. AQoL scores clearly differentiated between patients in categories of severity of impairment and disability and between patients with TACS and non-TACS. AQoL scores at 3 months after stroke predicted death and institutionalization at 12 months. The AQoL demonstrated strong psychometric properties and appears to be a valid and sensitive measure of health-related QoL after stroke.

Intoxication-Related Alcohol Mixed with Energy Drink Expectancies Scale: Initial Development and Validation.

PubMed

Miller, Kathleen E; Dermen, Kurt H; Lucke, Joseph F

2017-06-01

Young adult use of alcohol mixed with energy drinks (AmEDs) has been linked with elevated risks of a constellation of problem behaviors. These risks may be conditioned by expectancies regarding the effects of caffeine in conjunction with alcohol consumption. The aim of this study was to describe the construction and psychometric evaluation of the Intoxication-Related AmED Expectancies Scale (AmED_EXPI), 15 self-report items measuring beliefs about how the experience of AmED intoxication differs from the experience of noncaffeinated alcohol (NCA) intoxication. Scale development and testing were conducted using data from a U.S. national sample of 3,105 adolescents and emerging adults aged 13 to 25. Exploratory and confirmatory factor analyses were conducted to evaluate the factor structure and establish factor invariance across gender, age, and prior experience with AmED use. Cross-sectional and longitudinal analyses examining correlates of AmED use were used to assess construct and predictive validity. In confirmatory factor analyses, fit indices for the hypothesized 4-factor structure (i.e., Intoxication Management [IM], Alertness [AL], Sociability [SO], and Jitters [JT]) revealed a moderately good fit to the data. Together, these factors accounted for 75.3% of total variance. The factor structure was stable across male/female, teen/young adult, and AmED experience/no experience subgroups. The resultant unit-weighted subscales showed strong internal consistency and satisfactory convergent validity. Baseline scores on the IM, SO, and JT subscales predicted changes in AmED use over a subsequent 3-month period. The AmED_EXPI appears to be a reliable and valid tool for measuring expectancies about the effects of caffeine during alcohol intoxication. Copyright © 2017 by the Research Society on Alcoholism.

Predicting Blunt Cerebrovascular Injury in Pediatric Trauma: Validation of the “Utah Score”

PubMed Central

Ravindra, Vijay M.; Bollo, Robert J.; Sivakumar, Walavan; Akbari, Hassan; Naftel, Robert P.; Limbrick, David D.; Jea, Andrew; Gannon, Stephen; Shannon, Chevis; Birkas, Yekaterina; Yang, George L.; Prather, Colin T.; Kestle, John R.

2017-01-01

Abstract Risk factors for blunt cerebrovascular injury (BCVI) may differ between children and adults, suggesting that children at low risk for BCVI after trauma receive unnecessary computed tomography angiography (CTA) and high-dose radiation. We previously developed a score for predicting pediatric BCVI based on retrospective cohort analysis. Our objective is to externally validate this prediction score with a retrospective multi-institutional cohort. We included patients who underwent CTA for traumatic cranial injury at four pediatric Level I trauma centers. Each patient in the validation cohort was scored using the “Utah Score” and classified as high or low risk. Before analysis, we defined a misclassification rate <25% as validating the Utah Score. Six hundred forty-five patients (mean age 8.6 ± 5.4 years; 63.4% males) underwent screening for BCVI via CTA. The validation cohort was 411 patients from three sites compared with the training cohort of 234 patients. Twenty-two BCVIs (5.4%) were identified in the validation cohort. The Utah Score was significantly associated with BCVIs in the validation cohort (odds ratio 8.1 [3.3, 19.8], p < 0.001) and discriminated well in the validation cohort (area under the curve 72%). When the Utah Score was applied to the validation cohort, the sensitivity was 59%, specificity was 85%, positive predictive value was 18%, and negative predictive value was 97%. The Utah Score misclassified 16.6% of patients in the validation cohort. The Utah Score for predicting BCVI in pediatric trauma patients was validated with a low misclassification rate using a large, independent, multicenter cohort. Its implementation in the clinical setting may reduce the use of CTA in low-risk patients. PMID:27297774

The Predictive Validity of Teacher Candidate Letters of Reference

ERIC Educational Resources Information Center

Mason, Richard W.; Schroeder, Mark P.

2014-01-01

Letters of reference are widely used as an essential part of the hiring process of newly licensed teachers. While the predictive validity of these letters of reference has been called into question it has never been empirically studied. The current study examined the predictive validity of the quality of letters of reference for forty-one student…

Predictive Validity of a Student Self-Report Screener of Behavioral and Emotional Risk in an Urban High School

ERIC Educational Resources Information Center

Dowdy, Erin; Harrell-Williams, Leigh; Dever, Bridget V.; Furlong, Michael J.; Moore, Stephanie; Raines, Tara; Kamphaus, Randy W.

2016-01-01

Increasingly, schools are implementing school-based screening for risk of behavioral and emotional problems; hence, foundational evidence supporting the predictive validity of screening instruments is important to assess. This study examined the predictive validity of the Behavior Assessment System for Children-2 Behavioral and Emotional Screening…

Predictive Validity of Curriculum-Based Measures for English Learners at Varying English Proficiency Levels

ERIC Educational Resources Information Center

Kim, Jennifer Sun; Vanderwood, Michael L.; Lee, Catherine Y.

2016-01-01

This study examined the predictive validity of curriculum-based measures in reading for Spanish-speaking English learners (ELs) at various levels of English proficiency. Third-grade Spanish-speaking EL students were screened during the fall using DIBELS Oral Reading Fluency (DORF) and Daze. Predictive validity was examined in relation to spring…

Prediction of endoplasmic reticulum resident proteins using fragmented amino acid composition and support vector machine.

PubMed

Kumar, Ravindra; Kumari, Bandana; Kumar, Manish

2017-01-01

The endoplasmic reticulum plays an important role in many cellular processes, which includes protein synthesis, folding and post-translational processing of newly synthesized proteins. It is also the site for quality control of misfolded proteins and entry point of extracellular proteins to the secretory pathway. Hence at any given point of time, endoplasmic reticulum contains two different cohorts of proteins, (i) proteins involved in endoplasmic reticulum-specific function, which reside in the lumen of the endoplasmic reticulum, called as endoplasmic reticulum resident proteins and (ii) proteins which are in process of moving to the extracellular space. Thus, endoplasmic reticulum resident proteins must somehow be distinguished from newly synthesized secretory proteins, which pass through the endoplasmic reticulum on their way out of the cell. Approximately only 50% of the proteins used in this study as training data had endoplasmic reticulum retention signal, which shows that these signals are not essentially present in all endoplasmic reticulum resident proteins. This also strongly indicates the role of additional factors in retention of endoplasmic reticulum-specific proteins inside the endoplasmic reticulum. This is a support vector machine based method, where we had used different forms of protein features as inputs for support vector machine to develop the prediction models. During training leave-one-out approach of cross-validation was used. Maximum performance was obtained with a combination of amino acid compositions of different part of proteins. In this study, we have reported a novel support vector machine based method for predicting endoplasmic reticulum resident proteins, named as ERPred. During training we achieved a maximum accuracy of 81.42% with leave-one-out approach of cross-validation. When evaluated on independent dataset, ERPred did prediction with sensitivity of 72.31% and specificity of 83.69%. We have also annotated six different proteomes to predict the candidate endoplasmic reticulum resident proteins in them. A webserver, ERPred, was developed to make the method available to the scientific community, which can be accessed at http://proteininformatics.org/mkumar/erpred/index.html. We found that out of 124 proteins of the training dataset, only 66 proteins had endoplasmic reticulum retention signals, which shows that these signals are not an absolute necessity for endoplasmic reticulum resident proteins to remain inside the endoplasmic reticulum. This observation also strongly indicates the role of additional factors in retention of proteins inside the endoplasmic reticulum. Our proposed predictor, ERPred, is a signal independent tool. It is tuned for the prediction of endoplasmic reticulum resident proteins, even if the query protein does not contain specific ER-retention signal.

Propeller aircraft interior noise model utilization study and validation

NASA Technical Reports Server (NTRS)

Pope, L. D.

1984-01-01

Utilization and validation of a computer program designed for aircraft interior noise prediction is considered. The program, entitled PAIN (an acronym for Propeller Aircraft Interior Noise), permits (in theory) predictions of sound levels inside propeller driven aircraft arising from sidewall transmission. The objective of the work reported was to determine the practicality of making predictions for various airplanes and the extent of the program's capabilities. The ultimate purpose was to discern the quality of predictions for tonal levels inside an aircraft occurring at the propeller blade passage frequency and its harmonics. The effort involved three tasks: (1) program validation through comparisons of predictions with scale-model test results; (2) development of utilization schemes for large (full scale) fuselages; and (3) validation through comparisons of predictions with measurements taken in flight tests on a turboprop aircraft. Findings should enable future users of the program to efficiently undertake and correctly interpret predictions.

A simplified approach to the pooled analysis of calibration of clinical prediction rules for systematic reviews of validation studies

PubMed Central

Dimitrov, Borislav D; Motterlini, Nicola; Fahey, Tom

2015-01-01

Objective Estimating calibration performance of clinical prediction rules (CPRs) in systematic reviews of validation studies is not possible when predicted values are neither published nor accessible or sufficient or no individual participant or patient data are available. Our aims were to describe a simplified approach for outcomes prediction and calibration assessment and evaluate its functionality and validity. Study design and methods: Methodological study of systematic reviews of validation studies of CPRs: a) ABCD2 rule for prediction of 7 day stroke; and b) CRB-65 rule for prediction of 30 day mortality. Predicted outcomes in a sample validation study were computed by CPR distribution patterns (“derivation model”). As confirmation, a logistic regression model (with derivation study coefficients) was applied to CPR-based dummy variables in the validation study. Meta-analysis of validation studies provided pooled estimates of “predicted:observed” risk ratios (RRs), 95% confidence intervals (CIs), and indexes of heterogeneity (I2) on forest plots (fixed and random effects models), with and without adjustment of intercepts. The above approach was also applied to the CRB-65 rule. Results Our simplified method, applied to ABCD2 rule in three risk strata (low, 0–3; intermediate, 4–5; high, 6–7 points), indicated that predictions are identical to those computed by univariate, CPR-based logistic regression model. Discrimination was good (c-statistics =0.61–0.82), however, calibration in some studies was low. In such cases with miscalibration, the under-prediction (RRs =0.73–0.91, 95% CIs 0.41–1.48) could be further corrected by intercept adjustment to account for incidence differences. An improvement of both heterogeneities and P-values (Hosmer-Lemeshow goodness-of-fit test) was observed. Better calibration and improved pooled RRs (0.90–1.06), with narrower 95% CIs (0.57–1.41) were achieved. Conclusion Our results have an immediate clinical implication in situations when predicted outcomes in CPR validation studies are lacking or deficient by describing how such predictions can be obtained by everyone using the derivation study alone, without any need for highly specialized knowledge or sophisticated statistics. PMID:25931829

A modified artificial neural network based prediction technique for tropospheric radio refractivity

PubMed Central

Javeed, Shumaila; Javed, Wajahat; Atif, M.; Uddin, Mueen

2018-01-01

Radio refractivity plays a significant role in the development and design of radio systems for attaining the best level of performance. Refractivity in the troposphere is one of the features affecting electromagnetic waves, and hence the communication system interrupts. In this work, a modified artificial neural network (ANN) based model is applied to predict the refractivity. The suggested ANN model comprises three modules: the data preparation module, the feature selection module, and the forecast module. The first module applies pre-processing to make the data compatible for the feature selection module. The second module discards irrelevant and redundant data from the input set. The third module uses ANN for prediction. The ANN model applies a sigmoid activation function and a multi-variate auto regressive model to update the weights during the training process. In this work, the refractivity is predicted and estimated based on ten years (2002–2011) of meteorological data, such as the temperature, pressure, and humidity, obtained from the Pakistan Meteorological Department (PMD), Islamabad. The refractivity is estimated using the method suggested by the International Telecommunication Union (ITU). The refractivity is predicted for the year 2012 using the database of the previous ten years, with the help of ANN. The ANN model is implemented in MATLAB. Next, the estimated and predicted refractivity levels are validated against each other. The predicted and actual values (PMD data) of the atmospheric parameters agree with each other well, and demonstrate the accuracy of the proposed ANN method. It was further found that all parameters have a strong relationship with refractivity, in particular the temperature and humidity. The refractivity values are higher during the rainy season owing to a strong association with the relative humidity. Therefore, it is important to properly cater the signal communication system during hot and humid weather. Based on the results, the proposed ANN method can be used to develop a refractivity database, which is highly important in a radio communication system. PMID:29494609

Spatial Attention, Motor Intention, and Bayesian Cue Predictability in the Human Brain.

PubMed

Kuhns, Anna B; Dombert, Pascasie L; Mengotti, Paola; Fink, Gereon R; Vossel, Simone

2017-05-24

Predictions about upcoming events influence how we perceive and respond to our environment. There is increasing evidence that predictions may be generated based upon previous observations following Bayesian principles, but little is known about the underlying cortical mechanisms and their specificity for different cognitive subsystems. The present study aimed at identifying common and distinct neural signatures of predictive processing in the spatial attentional and motor intentional system. Twenty-three female and male healthy human volunteers performed two probabilistic cueing tasks with either spatial or motor cues while lying in the fMRI scanner. In these tasks, the percentage of cue validity changed unpredictably over time. Trialwise estimates of cue predictability were derived from a Bayesian observer model of behavioral responses. These estimates were included as parametric regressors for analyzing the BOLD time series. Parametric effects of cue predictability in valid and invalid trials were considered to reflect belief updating by precision-weighted prediction errors. The brain areas exhibiting predictability-dependent effects dissociated between the spatial attention and motor intention task, with the right temporoparietal cortex being involved during spatial attention and the left angular gyrus and anterior cingulate cortex during motor intention. Connectivity analyses revealed that all three areas showed predictability-dependent coupling with the right hippocampus. These results suggest that precision-weighted prediction errors of stimulus locations and motor responses are encoded in distinct brain regions, but that crosstalk with the hippocampus may be necessary to integrate new trialwise outcomes in both cognitive systems. SIGNIFICANCE STATEMENT The brain is able to infer the environments' statistical structure and responds strongly to expectancy violations. In the spatial attentional domain, it has been shown that parts of the attentional networks are sensitive to the predictability of stimuli. It remains unknown, however, whether these effects are ubiquitous or if they are specific for different cognitive systems. The present study compared the influence of model-derived cue predictability on brain activity in the spatial attentional and motor intentional system. We identified areas with distinct predictability-dependent activation for spatial attention and motor intention, but also common connectivity changes of these regions with the hippocampus. These findings provide novel insights into the generality and specificity of predictive processing signatures in the human brain. Copyright © 2017 the authors 0270-6474/17/375334-11$15.00/0.

The predictive validity of three versions of the MCAT in relation to performance in medical school, residency, and licensing examinations: a longitudinal study of 36 classes of Jefferson Medical College.

PubMed

Callahan, Clara A; Hojat, Mohammadreza; Veloski, Jon; Erdmann, James B; Gonnella, Joseph S

2010-06-01

The Medical College Admission Test (MCAT) has undergone several revisions for content and validity since its inception. With another comprehensive review pending, this study examines changes in the predictive validity of the MCAT's three recent versions. Study participants were 7,859 matriculants in 36 classes entering Jefferson Medical College between 1970 and 2005; 1,728 took the pre-1978 version of the MCAT; 3,032 took the 1978-1991 version, and 3,099 took the post-1991 version. MCAT subtest scores were the predictors, and performance in medical school, attrition, scores on the medical licensing examinations, and ratings of clinical competence in the first year of residency were the criterion measures. No significant improvement in validity coefficients was observed for performance in medical school or residency. Validity coefficients for all three versions of the MCAT in predicting Part I/Step 1 remained stable (in the mid-0.40s, P < .01). A systematic decline was observed in the validity coefficients of the MCAT versions in predicting Part II/Step 2. It started at 0.47 for the pre-1978 version, decreased to between 0.42 and 0.40 for the 1978-1991 versions, and to 0.37 for the post-1991 version. Validity coefficients for the MCAT versions in predicting Part III/Step 3 remained near 0.30. These were generally larger for women than men. Although the findings support the short- and long-term predictive validity of the MCAT, opportunities to strengthen it remain. Subsequent revisions should increase the test's ability to predict performance on United States Medical Licensing Examination Step 2 and must minimize the differential validity for gender.

Thermodynamics of enzyme-catalyzed esterifications: II. Levulinic acid esterification with short-chain alcohols.

PubMed

Altuntepe, Emrah; Emel'yanenko, Vladimir N; Forster-Rotgers, Maximilian; Sadowski, Gabriele; Verevkin, Sergey P; Held, Christoph

2017-10-01

Levulinic acid was esterified with methanol, ethanol, and 1-butanol with the final goal to predict the maximum yield of these equilibrium-limited reactions as function of medium composition. In a first step, standard reaction data (standard Gibbs energy of reaction Δ R g 0 ) were determined from experimental formation properties. Unexpectedly, these Δ R g 0 values strongly deviated from data obtained with classical group contribution methods that are typically used if experimental standard data is not available. In a second step, reaction equilibrium concentrations obtained from esterification catalyzed by Novozym 435 at 323.15 K were measured, and the corresponding activity coefficients of the reacting agents were predicted with perturbed-chain statistical associating fluid theory (PC-SAFT). The so-obtained thermodynamic activities were used to determine Δ R g 0 at 323.15 K. These results could be used to cross-validate Δ R g 0 from experimental formation data. In a third step, reaction-equilibrium experiments showed that equilibrium position of the reactions under consideration depends strongly on the concentration of water and on the ratio of levulinic acid: alcohol in the initial reaction mixtures. The maximum yield of the esters was calculated using Δ R g 0 data from this work and activity coefficients of the reacting agents predicted with PC-SAFT for varying feed composition of the reaction mixtures. The use of the new Δ R g 0 data combined with PC-SAFT allowed good agreement to the measured yields, while predictions based on Δ R g 0 values obtained with group contribution methods showed high deviations to experimental yields.

A Random Forest approach to predict the spatial distribution of sediment pollution in an estuarine system

PubMed Central

Kreakie, Betty J.; Cantwell, Mark G.; Nacci, Diane

2017-01-01

Modeling the magnitude and distribution of sediment-bound pollutants in estuaries is often limited by incomplete knowledge of the site and inadequate sample density. To address these modeling limitations, a decision-support tool framework was conceived that predicts sediment contamination from the sub-estuary to broader estuary extent. For this study, a Random Forest (RF) model was implemented to predict the distribution of a model contaminant, triclosan (5-chloro-2-(2,4-dichlorophenoxy)phenol) (TCS), in Narragansett Bay, Rhode Island, USA. TCS is an unregulated contaminant used in many personal care products. The RF explanatory variables were associated with TCS transport and fate (proxies) and direct and indirect environmental entry. The continuous RF TCS concentration predictions were discretized into three levels of contamination (low, medium, and high) for three different quantile thresholds. The RF model explained 63% of the variance with a minimum number of variables. Total organic carbon (TOC) (transport and fate proxy) was a strong predictor of TCS contamination causing a mean squared error increase of 59% when compared to permutations of randomized values of TOC. Additionally, combined sewer overflow discharge (environmental entry) and sand (transport and fate proxy) were strong predictors. The discretization models identified a TCS area of greatest concern in the northern reach of Narragansett Bay (Providence River sub-estuary), which was validated with independent test samples. This decision-support tool performed well at the sub-estuary extent and provided the means to identify areas of concern and prioritize bay-wide sampling. PMID:28738089

Analysis of subarachnoid hemorrhage using the Nationwide Inpatient Sample: the NIS-SAH Severity Score and Outcome Measure.

PubMed

Washington, Chad W; Derdeyn, Colin P; Dacey, Ralph G; Dhar, Rajat; Zipfel, Gregory J

2014-08-01

Studies using the Nationwide Inpatient Sample (NIS), a large ICD-9-based (International Classification of Diseases, Ninth Revision) administrative database, to analyze aneurysmal subarachnoid hemorrhage (SAH) have been limited by an inability to control for SAH severity and the use of unverified outcome measures. To address these limitations, the authors developed and validated a surrogate marker for SAH severity, the NIS-SAH Severity Score (NIS-SSS; akin to Hunt and Hess [HH] grade), and a dichotomous measure of SAH outcome, the NIS-SAH Outcome Measure (NIS-SOM; akin to modified Rankin Scale [mRS] score). Three separate and distinct patient cohorts were used to define and then validate the NIS-SSS and NIS-SOM. A cohort (n = 148,958, the "model population") derived from the 1998-2009 NIS was used for developing the NIS-SSS and NIS-SOM models. Diagnoses most likely reflective of SAH severity were entered into a regression model predicting poor outcome; model coefficients of significant factors were used to generate the NIS-SSS. Nationwide Inpatient Sample codes most likely to reflect a poor outcome (for example, discharge disposition, tracheostomy) were used to create the NIS-SOM. Data from 716 patients with SAH (the "validation population") treated at the authors' institution were used to validate the NIS-SSS and NIS-SOM against HH grade and mRS score, respectively. Lastly, 147,395 patients (the "assessment population") from the 1998-2009 NIS, independent of the model population, were used to assess performance of the NIS-SSS in predicting outcome. The ability of the NIS-SSS to predict outcome was compared with other common measures of disease severity (All Patient Refined Diagnosis Related Group [APR-DRG], All Payer Severity-adjusted DRG [APS-DRG], and DRG). RESULTS The NIS-SSS significantly correlated with HH grade, and there was no statistical difference between the abilities of the NIS-SSS and HH grade to predict mRS-based outcomes. As compared with the APR-DRG, APSDRG, and DRG, the NIS-SSS was more accurate in predicting SAH outcome (area under the curve [AUC] = 0.69, 0.71, 0.71, and 0.79, respectively). A strong correlation between NIS-SOM and mRS was found, with an agreement and kappa statistic of 85% and 0.63, respectively, when poor outcome was defined by an mRS score > 2 and 95% and 0.84 when poor outcome was defined by an mRS score > 3. Data in this study indicate that in the analysis of NIS data sets, the NIS-SSS is a valid measure of SAH severity that outperforms previous measures of disease severity and that the NIS-SOM is a valid measure of SAH outcome. It is critically important that outcomes research in SAH using administrative data sets incorporate the NIS-SSS and NIS-SOM to adjust for neurology-specific disease severity.

Performance of genomic prediction within and across generations in maritime pine.

PubMed

Bartholomé, Jérôme; Van Heerwaarden, Joost; Isik, Fikret; Boury, Christophe; Vidal, Marjorie; Plomion, Christophe; Bouffier, Laurent

2016-08-11

Genomic selection (GS) is a promising approach for decreasing breeding cycle length in forest trees. Assessment of progeny performance and of the prediction accuracy of GS models over generations is therefore a key issue. A reference population of maritime pine (Pinus pinaster) with an estimated effective inbreeding population size (status number) of 25 was first selected with simulated data. This reference population (n = 818) covered three generations (G0, G1 and G2) and was genotyped with 4436 single-nucleotide polymorphism (SNP) markers. We evaluated the effects on prediction accuracy of both the relatedness between the calibration and validation sets and validation on the basis of progeny performance. Pedigree-based (best linear unbiased prediction, ABLUP) and marker-based (genomic BLUP and Bayesian LASSO) models were used to predict breeding values for three different traits: circumference, height and stem straightness. On average, the ABLUP model outperformed genomic prediction models, with a maximum difference in prediction accuracies of 0.12, depending on the trait and the validation method. A mean difference in prediction accuracy of 0.17 was found between validation methods differing in terms of relatedness. Including the progenitors in the calibration set reduced this difference in prediction accuracy to 0.03. When only genotypes from the G0 and G1 generations were used in the calibration set and genotypes from G2 were used in the validation set (progeny validation), prediction accuracies ranged from 0.70 to 0.85. This study suggests that the training of prediction models on parental populations can predict the genetic merit of the progeny with high accuracy: an encouraging result for the implementation of GS in the maritime pine breeding program.

Prediction of parenteral nutrition osmolarity by digital refractometry.

PubMed

Chang, Wei-Kuo; Yeh, Ming-Kung

2011-05-01

Infusion of high-osmolarity parenteral nutrition (PN) formulations into a peripheral vein will damage the vessel. In this study, the authors developed a refractometric method to predict PN formulation osmolarity for patients receiving PN. Nutrients in PN formulations were prepared for Brix value and osmolality measurement. Brix value and osmolality measurement of the dextrose, amino acids, and electrolytes were used to evaluate the limiting factor of PN osmolarity prediction. A best-fit equation was generated to predict PN osmolarity (mOsm/L): 81.05 × Brix value--116.33 (R(2) > 0.99). To validate the PN osmolarity prediction by these 4 equations, a total of 500 PN admixtures were tested. The authors found strong linear relationships between the Brix values and the osmolality measurement of dextrose (R(2) = 0.97), amino acids (R(2) = 0.99), and electrolytes (R(2) > 0.96). When PN-measured osmolality was between 600 and 900 mOsm/kg, approximately 43%, 29%, 43%, and 0% of the predicted osmolarity obtained by equations 1, 2, 3, and 4 were outside the acceptable 90% to 110% confidence interval range, respectively. When measured osmolality was between 900 and 1,500 mOsm/kg, 31%, 100%, 85%, and 15% of the predicted osmolarity by equations 1, 2, 3, and 4 were outside the acceptable 90% to 110% confidence interval range, respectively. The refractive method permits accurate PN osmolarity prediction and reasonable quality assurance before PN formulation administration.

Comparison of total body water estimates from O-18 and bioelectrical response prediction equations

NASA Technical Reports Server (NTRS)

Barrows, Linda H.; Inners, L. Daniel; Stricklin, Marcella D.; Klein, Peter D.; Wong, William W.; Siconolfi, Steven F.

1993-01-01

Identification of an indirect, rapid means to measure total body water (TBW) during space flight may aid in quantifying hydration status and assist in countermeasure development. Bioelectrical response testing and hydrostatic weighing were performed on 27 subjects who ingested O-18, a naturally occurring isotope of oxygen, to measure true TBW. TBW estimates from three bioelectrical response prediction equations and fat-free mass (FFM) were compared to TBW measured from O-18. A repeated measures MANOVA with post-hoc Dunnett's Test indicated a significant (p less than 0.05) difference between TBW estimates from two of the three bioelectrical response prediction equations and O-18. TBW estimates from FFM and the Kushner & Schoeller (1986) equation yielded results that were similar to those given by O-18. Strong correlations existed between each prediction method and O-18; however, standard errors, identified through regression analyses, were higher for the bioelectrical response prediction equations compared to those derived from FFM. These findings suggest (1) the Kushner & Schoeller (1986) equation may provide a valid measure of TBW, (2) other TBW prediction equations need to be identified that have variability similar to that of FFM, and (3) bioelectrical estimates of TBW may prove valuable in quantifying hydration status during space flight.

A simple risk scoring system for prediction of relapse after inpatient alcohol treatment.

PubMed

Pedersen, Mads Uffe; Hesse, Morten

2009-01-01

Predicting relapse after alcoholism treatment can be useful in targeting patients for aftercare services. However, a valid and practical instrument for predicting relapse risk does not exist. Based on a prospective study of alcoholism treatment, we developed the Risk of Alcoholic Relapse Scale (RARS) using items taken from the Addiction Severity Index and some basic demographic information. The RARS was cross-validated using two non-overlapping samples, and tested for its ability to predict relapse across different models of treatment. The RARS predicted relapse to drinking within 6 months after alcoholism treatment in both the original and the validation sample, and in a second validation sample it predicted admission to new treatment 3 years after treatment. The RARS can identify patients at high risk of relapse who need extra aftercare and support after treatment.

Criterion for evaluating the predictive ability of nonlinear regression models without cross-validation.

PubMed

Kaneko, Hiromasa; Funatsu, Kimito

2013-09-23

We propose predictive performance criteria for nonlinear regression models without cross-validation. The proposed criteria are the determination coefficient and the root-mean-square error for the midpoints between k-nearest-neighbor data points. These criteria can be used to evaluate predictive ability after the regression models are updated, whereas cross-validation cannot be performed in such a situation. The proposed method is effective and helpful in handling big data when cross-validation cannot be applied. By analyzing data from numerical simulations and quantitative structural relationships, we confirm that the proposed criteria enable the predictive ability of the nonlinear regression models to be appropriately quantified.

Family-Based Benchmarking of Copy Number Variation Detection Software.

PubMed

Nutsua, Marcel Elie; Fischer, Annegret; Nebel, Almut; Hofmann, Sylvia; Schreiber, Stefan; Krawczak, Michael; Nothnagel, Michael

2015-01-01

The analysis of structural variants, in particular of copy-number variations (CNVs), has proven valuable in unraveling the genetic basis of human diseases. Hence, a large number of algorithms have been developed for the detection of CNVs in SNP array signal intensity data. Using the European and African HapMap trio data, we undertook a comparative evaluation of six commonly used CNV detection software tools, namely Affymetrix Power Tools (APT), QuantiSNP, PennCNV, GLAD, R-gada and VEGA, and assessed their level of pair-wise prediction concordance. The tool-specific CNV prediction accuracy was assessed in silico by way of intra-familial validation. Software tools differed greatly in terms of the number and length of the CNVs predicted as well as the number of markers included in a CNV. All software tools predicted substantially more deletions than duplications. Intra-familial validation revealed consistently low levels of prediction accuracy as measured by the proportion of validated CNVs (34-60%). Moreover, up to 20% of apparent family-based validations were found to be due to chance alone. Software using Hidden Markov models (HMM) showed a trend to predict fewer CNVs than segmentation-based algorithms albeit with greater validity. PennCNV yielded the highest prediction accuracy (60.9%). Finally, the pairwise concordance of CNV prediction was found to vary widely with the software tools involved. We recommend HMM-based software, in particular PennCNV, rather than segmentation-based algorithms when validity is the primary concern of CNV detection. QuantiSNP may be used as an additional tool to detect sets of CNVs not detectable by the other tools. Our study also reemphasizes the need for laboratory-based validation, such as qPCR, of CNVs predicted in silico.

A Public-Private Partnership Develops and Externally Validates a 30-Day Hospital Readmission Risk Prediction Model

PubMed Central

Choudhry, Shahid A.; Li, Jing; Davis, Darcy; Erdmann, Cole; Sikka, Rishi; Sutariya, Bharat

2013-01-01

Introduction: Preventing the occurrence of hospital readmissions is needed to improve quality of care and foster population health across the care continuum. Hospitals are being held accountable for improving transitions of care to avert unnecessary readmissions. Advocate Health Care in Chicago and Cerner (ACC) collaborated to develop all-cause, 30-day hospital readmission risk prediction models to identify patients that need interventional resources. Ideally, prediction models should encompass several qualities: they should have high predictive ability; use reliable and clinically relevant data; use vigorous performance metrics to assess the models; be validated in populations where they are applied; and be scalable in heterogeneous populations. However, a systematic review of prediction models for hospital readmission risk determined that most performed poorly (average C-statistic of 0.66) and efforts to improve their performance are needed for widespread usage. Methods: The ACC team incorporated electronic health record data, utilized a mixed-method approach to evaluate risk factors, and externally validated their prediction models for generalizability. Inclusion and exclusion criteria were applied on the patient cohort and then split for derivation and internal validation. Stepwise logistic regression was performed to develop two predictive models: one for admission and one for discharge. The prediction models were assessed for discrimination ability, calibration, overall performance, and then externally validated. Results: The ACC Admission and Discharge Models demonstrated modest discrimination ability during derivation, internal and external validation post-recalibration (C-statistic of 0.76 and 0.78, respectively), and reasonable model fit during external validation for utility in heterogeneous populations. Conclusions: The ACC Admission and Discharge Models embody the design qualities of ideal prediction models. The ACC plans to continue its partnership to further improve and develop valuable clinical models. PMID:24224068

Prediction models for successful external cephalic version: a systematic review.

PubMed

Velzel, Joost; de Hundt, Marcella; Mulder, Frederique M; Molkenboer, Jan F M; Van der Post, Joris A M; Mol, Ben W; Kok, Marjolein

2015-12-01

To provide an overview of existing prediction models for successful ECV, and to assess their quality, development and performance. We searched MEDLINE, EMBASE and the Cochrane Library to identify all articles reporting on prediction models for successful ECV published from inception to January 2015. We extracted information on study design, sample size, model-building strategies and validation. We evaluated the phases of model development and summarized their performance in terms of discrimination, calibration and clinical usefulness. We collected different predictor variables together with their defined significance, in order to identify important predictor variables for successful ECV. We identified eight articles reporting on seven prediction models. All models were subjected to internal validation. Only one model was also validated in an external cohort. Two prediction models had a low overall risk of bias, of which only one showed promising predictive performance at internal validation. This model also completed the phase of external validation. For none of the models their impact on clinical practice was evaluated. The most important predictor variables for successful ECV described in the selected articles were parity, placental location, breech engagement and the fetal head being palpable. One model was assessed using discrimination and calibration using internal (AUC 0.71) and external validation (AUC 0.64), while two other models were assessed with discrimination and calibration, respectively. We found one prediction model for breech presentation that was validated in an external cohort and had acceptable predictive performance. This model should be used to council women considering ECV. Copyright © 2015. Published by Elsevier Ireland Ltd.

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.

A three-step approach for the derivation and validation of high-performing predictive models using an operational dataset: congestive heart failure readmission case study.

PubMed

AbdelRahman, Samir E; Zhang, Mingyuan; Bray, Bruce E; Kawamoto, Kensaku

2014-05-27

The aim of this study was to propose an analytical approach to develop high-performing predictive models for congestive heart failure (CHF) readmission using an operational dataset with incomplete records and changing data over time. Our analytical approach involves three steps: pre-processing, systematic model development, and risk factor analysis. For pre-processing, variables that were absent in >50% of records were removed. Moreover, the dataset was divided into a validation dataset and derivation datasets which were separated into three temporal subsets based on changes to the data over time. For systematic model development, using the different temporal datasets and the remaining explanatory variables, the models were developed by combining the use of various (i) statistical analyses to explore the relationships between the validation and the derivation datasets; (ii) adjustment methods for handling missing values; (iii) classifiers; (iv) feature selection methods; and (iv) discretization methods. We then selected the best derivation dataset and the models with the highest predictive performance. For risk factor analysis, factors in the highest-performing predictive models were analyzed and ranked using (i) statistical analyses of the best derivation dataset, (ii) feature rankers, and (iii) a newly developed algorithm to categorize risk factors as being strong, regular, or weak. The analysis dataset consisted of 2,787 CHF hospitalizations at University of Utah Health Care from January 2003 to June 2013. In this study, we used the complete-case analysis and mean-based imputation adjustment methods; the wrapper subset feature selection method; and four ranking strategies based on information gain, gain ratio, symmetrical uncertainty, and wrapper subset feature evaluators. The best-performing models resulted from the use of a complete-case analysis derivation dataset combined with the Class-Attribute Contingency Coefficient discretization method and a voting classifier which averaged the results of multi-nominal logistic regression and voting feature intervals classifiers. Of 42 final model risk factors, discharge disposition, discretized age, and indicators of anemia were the most significant. This model achieved a c-statistic of 86.8%. The proposed three-step analytical approach enhanced predictive model performance for CHF readmissions. It could potentially be leveraged to improve predictive model performance in other areas of clinical medicine.

Therapeutic Misconception in Research Subjects: Development and Validation of a Measure

PubMed Central

Appelbaum, Paul S.; Anatchkova, Milena; Albert, Karen; Dunn, Laura B.; Lidz, Charles W.

2013-01-01

Background Therapeutic misconception (TM), which occurs when research subjects fail to appreciate the distinction between the imperatives of clinical research and ordinary treatment, may undercut the process of obtaining meaningful consent to clinical research participation. Previous studies have found TM is widespread, but progress in addressing TM has been stymied by the absence of a validated method for assessing its presence. Purpose The goal of this study was to develop and validate a theoretically grounded measure of TM, assess its diagnostic accuracy, and test previous findings regarding its prevalence. Methods 220 participants were recruited from clinical trials at 4 academic medical centers in the U.S. Participants completed a 28-item Likert-type questionnaire to assess the presence of beliefs associated with TM, and a semi-structured TM interview designed to elicit their perceptions of the nature of the clinical trial in which they were participating. Data from the questionnaires were subjected to factor analysis and items with poor factor loadings were excluded. This resulted in a 10-item scale, with 3 strongly correlated factors and excellent internal consistency; the fit indices of the model across 10 training sets were consistent with the original results, suggesting a stable factor solution. Results The scale was validated against the TM interview, with significantly higher scores among subjects coded as displaying evidence of TM. ROC analysis based on a 10-fold internal cross-validation yielded AUC=.682 for any evidence of TM. When sensitivity (0.72) and specificity (0.61) were both optimized, Positive Predictive Value was 0.65 and Negative Predictive Value was 0.68, with a Positive Likelihood Ratio of 1.89, and a Negative Likelihood Ratio of 0.47. 50.5% (n=101) of participants manifested evidence of TM on the TM interview, a somewhat lower rate than in most previous studies. Limitations The predictive value of the scale compared with the “gold standard” clinical interview is modest, although similar to other instruments based on self-report assessing states of mind rather than discrete symptoms. Thus, although the scale can offer evidence of which subjects are at risk for distortions in their decisions and to what degree, it will not allow researchers to conclude definitively that TM is present in a given subject. Conclusions The development of a reliable and valid TM scale, even with modest predictive power, should permit investigators in clinical trials to identify subjects with tendencies to misinterpret the nature of the situation and to provide additional information to them. It should also stimulate research on how best to decrease TM and facilitate meaningful informed consent to clinical research. PMID:22942217

Risk assessment for juvenile justice: a meta-analysis.

PubMed

Schwalbe, Craig S

2007-10-01

Risk assessment instruments are increasingly employed by juvenile justice settings to estimate the likelihood of recidivism among delinquent juveniles. In concert with their increased use, validation studies documenting their predictive validity have increased in number. The purpose of this study was to assess the average predictive validity of juvenile justice risk assessment instruments and to identify risk assessment characteristics that are associated with higher predictive validity. A search of the published and grey literature yielded 28 studies that estimated the predictive validity of 28 risk assessment instruments. Findings of the meta-analysis were consistent with effect sizes obtained in larger meta-analyses of criminal justice risk assessment instruments and showed that brief risk assessment instruments had smaller effect sizes than other types of instruments. However, this finding is tentative owing to limitations of the literature.

Biomarkers and Surrogate Endpoints: Lessons Learned From Glaucoma

PubMed Central

Medeiros, Felipe A.

2017-01-01

With the recent progress in imaging technologies for assessment of structural damage in glaucoma, a debate has emerged on whether these measurements can be used as valid surrogate endpoints in clinical trials evaluating new therapies for the disease. A discussion of surrogates should be grounded on knowledge acquired from their use in other areas of medicine as well as regulatory requirements. This article reviews the conditions for valid surrogacy in the context of glaucoma clinical trials and critically evaluates the role of biomarkers such as IOP and imaging measurements as potential surrogates for clinically relevant outcomes. Valid surrogate endpoints must be able to predict a clinically relevant endpoint, such as loss of vision or decrease in quality of life. In addition, the effect of a proposed treatment on the surrogate must capture the effect of the treatment on the clinically relevant endpoint. Despite its widespread use in clinical trials, no proper validation of IOP as a surrogate endpoint has yet been conducted for any class of IOP-lowering treatments. Although strong evidence has accumulated about imaging measurements as predictors of relevant functional outcomes in glaucoma, there is still insufficient evidence to support their use as valid surrogate endpoints. However, imaging biomarkers could potentially be used as part of composite endpoints in glaucoma trials, overcoming weaknesses of the use of structural or functional endpoints in isolation. Efforts should be taken to properly design and conduct studies that can provide proper validation of potential biomarkers in glaucoma clinical trials. PMID:28475699

Biomarkers and Surrogate Endpoints: Lessons Learned From Glaucoma.

PubMed

Medeiros, Felipe A

2017-05-01

With the recent progress in imaging technologies for assessment of structural damage in glaucoma, a debate has emerged on whether these measurements can be used as valid surrogate endpoints in clinical trials evaluating new therapies for the disease. A discussion of surrogates should be grounded on knowledge acquired from their use in other areas of medicine as well as regulatory requirements. This article reviews the conditions for valid surrogacy in the context of glaucoma clinical trials and critically evaluates the role of biomarkers such as IOP and imaging measurements as potential surrogates for clinically relevant outcomes. Valid surrogate endpoints must be able to predict a clinically relevant endpoint, such as loss of vision or decrease in quality of life. In addition, the effect of a proposed treatment on the surrogate must capture the effect of the treatment on the clinically relevant endpoint. Despite its widespread use in clinical trials, no proper validation of IOP as a surrogate endpoint has yet been conducted for any class of IOP-lowering treatments. Although strong evidence has accumulated about imaging measurements as predictors of relevant functional outcomes in glaucoma, there is still insufficient evidence to support their use as valid surrogate endpoints. However, imaging biomarkers could potentially be used as part of composite endpoints in glaucoma trials, overcoming weaknesses of the use of structural or functional endpoints in isolation. Efforts should be taken to properly design and conduct studies that can provide proper validation of potential biomarkers in glaucoma clinical trials.

Theory-Based Cartographic Risk Model Development and Application for Home Fire Safety.

PubMed

Furmanek, Stephen; Lehna, Carlee; Hanchette, Carol

There is a gap in the use of predictive risk models to identify areas at risk for home fires and burn injury. The purpose of this study was to describe the creation, validation, and application of such a model using a sample from an intervention study with parents of newborns in Jefferson County, KY, as an example. Performed was a literature search to identify risk factors for home fires and burn injury in the target population. Obtained from the American Community Survey at the census tract level and synthesized to create a predictive cartographic risk model was risk factor data. Model validation was performed through correlation, regression, and Moran's I with fire incidence data from open records. Independent samples t-tests were used to examine the model in relation to geocoded participant addresses. Participant risk level for fire rate was determined and proximity to fire station service areas and hospitals. The model showed high and severe risk clustering in the northwest section of the county. Strongly correlated with fire rate was modeled risk; the best predictive model for fire risk contained home value (low), race (black), and non high school graduates. Applying the model to the intervention sample, the majority of participants were at lower risk and mostly within service areas closest to a fire department and hospital. Cartographic risk models were useful in identifying areas at risk and analyzing participant risk level. The methods outlined in this study are generalizable to other public health issues.

Determinants of Scanpath Regularity in Reading.

PubMed

von der Malsburg, Titus; Kliegl, Reinhold; Vasishth, Shravan

2015-09-01

Scanpaths have played an important role in classic research on reading behavior. Nevertheless, they have largely been neglected in later research perhaps due to a lack of suitable analytical tools. Recently, von der Malsburg and Vasishth (2011) proposed a new measure for quantifying differences between scanpaths and demonstrated that this measure can recover effects that were missed with the traditional eyetracking measures. However, the sentences used in that study were difficult to process and scanpath effects accordingly strong. The purpose of the present study was to test the validity, sensitivity, and scope of applicability of the scanpath measure, using simple sentences that are typically read from left to right. We derived predictions for the regularity of scanpaths from the literature on oculomotor control, sentence processing, and cognitive aging and tested these predictions using the scanpath measure and a large database of eye movements. All predictions were confirmed: Sentences with short words and syntactically more difficult sentences elicited more irregular scanpaths. Also, older readers produced more irregular scanpaths than younger readers. In addition, we found an effect that was not reported earlier: Syntax had a smaller influence on the eye movements of older readers than on those of young readers. We discuss this interaction of syntactic parsing cost with age in terms of shifts in processing strategies and a decline of executive control as readers age. Overall, our results demonstrate the validity and sensitivity of the scanpath measure and thus establish it as a productive and versatile tool for reading research. Copyright © 2014 Cognitive Science Society, Inc.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

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

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

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

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Quality appraisal of generic self-reported instruments measuring health-related productivity changes: a systematic review

PubMed Central

2014-01-01

Background Health impairments can result in disability and changed work productivity imposing considerable costs for the employee, employer and society as a whole. A large number of instruments exist to measure health-related productivity changes; however their methodological quality remains unclear. This systematic review critically appraised the measurement properties in generic self-reported instruments that measure health-related productivity changes to recommend appropriate instruments for use in occupational and economic health practice. Methods PubMed, PsycINFO, Econlit and Embase were systematically searched for studies whereof: (i) instruments measured health-related productivity changes; (ii) the aim was to evaluate instrument measurement properties; (iii) instruments were generic; (iv) ratings were self-reported; (v) full-texts were available. Next, methodological quality appraisal was based on COSMIN elements: (i) internal consistency; (ii) reliability; (iii) measurement error; (iv) content validity; (v) structural validity; (vi) hypotheses testing; (vii) cross-cultural validity; (viii) criterion validity; and (ix) responsiveness. Recommendations are based on evidence syntheses. Results This review included 25 articles assessing the reliability, validity and responsiveness of 15 different generic self-reported instruments measuring health-related productivity changes. Most studies evaluated criterion validity, none evaluated cross-cultural validity and information on measurement error is lacking. The Work Limitation Questionnaire (WLQ) was most frequently evaluated with moderate respectively strong positive evidence for content and structural validity and negative evidence for reliability, hypothesis testing and responsiveness. Less frequently evaluated, the Stanford Presenteeism Scale (SPS) showed strong positive evidence for internal consistency and structural validity, and moderate positive evidence for hypotheses testing and criterion validity. The Productivity and Disease Questionnaire (PRODISQ) yielded strong positive evidence for content validity, evidence for other properties is lacking. The other instruments resulted in mostly fair-to-poor quality ratings with limited evidence. Conclusions Decisions based on the content of the instrument, usage purpose, target country and population, and available evidence are recommended. Until high-quality studies are in place to accurately assess the measurement properties of the currently available instruments, the WLQ and, in a Dutch context, the PRODISQ are cautiously preferred based on its strong positive evidence for content validity. Based on its strong positive evidence for internal consistency and structural validity, the SPS is cautiously recommended. PMID:24495301

Strongly nonlinear dynamics of electrolytes in large ac voltages.

PubMed

Højgaard Olesen, Laurits; Bazant, Martin Z; Bruus, Henrik

2010-07-01

We study the response of a model microelectrochemical cell to a large ac voltage of frequency comparable to the inverse cell relaxation time. To bring out the basic physics, we consider the simplest possible model of a symmetric binary electrolyte confined between parallel-plate blocking electrodes, ignoring any transverse instability or fluid flow. We analyze the resulting one-dimensional problem by matched asymptotic expansions in the limit of thin double layers and extend previous work into the strongly nonlinear regime, which is characterized by two features--significant salt depletion in the electrolyte near the electrodes and, at very large voltage, the breakdown of the quasiequilibrium structure of the double layers. The former leads to the prediction of "ac capacitive desalination" since there is a time-averaged transfer of salt from the bulk to the double layers, via oscillating diffusion layers. The latter is associated with transient diffusion limitation, which drives the formation and collapse of space-charge layers, even in the absence of any net Faradaic current through the cell. We also predict that steric effects of finite ion sizes (going beyond dilute-solution theory) act to suppress the strongly nonlinear regime in the limit of concentrated electrolytes, ionic liquids, and molten salts. Beyond the model problem, our reduced equations for thin double layers, based on uniformly valid matched asymptotic expansions, provide a useful mathematical framework to describe additional nonlinear responses to large ac voltages, such as Faradaic reactions, electro-osmotic instabilities, and induced-charge electrokinetic phenomena.

Psychometric properties of Frustration Discomfort Scale in a Turkish sample.

PubMed

Ozer, Bilge Uzun; Demir, Ayhan; Harrington, Neil

2012-08-01

The present study assessed the psychometric properties of the Frustration Discomfort Scale for Turkish college students. The Frustration Discomfort Scale (FDS), Procrastination Assessment Scale-Student, and Rosenberg Self-Esteem Scale were administered to a sample of 171 (98 women, 73 men) Turkish college students. The results of the confirmatory factor analysis yielded fit index values demonstrating viability of the four-dimensional solution as in the original. Findings also revealed that, as predicted, the Discomfort Intolerance subscale of Turkish FDS was most strongly correlated with procrastination. Overall results provided evidence for the factor validity and reliability of the Turkish version of the scale for use in a Turkish population.

The virial coefficients of hard hypersphere binary mixtures

NASA Astrophysics Data System (ADS)

Enciso, E.; Almarza, N. G.; Gonzalez, M. A.; Bermejo, F. J.

The third, fourth and fifth virial coefficients of hard hypersphere binary mixtures with dimensionality d = 4, 5 have been calculated for size ratios R ≥0.1, R ı σ22 / σ11 , where σ ii is the diameter of component i . The composition independent partial virial coefficients have been evaluated by Monte Carlo integration of the corresponding Mayer modified star diagrams. The results are compared with the predictions of Santos, S., Yuste, S. B., and Lopez de Haro, M., 1999, Molec. Phys ., 96 , 1 of the equation of state of a multicomponent mixture of hard hyperspheres, and the good agreement gives strong support to the validity of that recipe.

Prediction model to estimate presence of coronary artery disease: retrospective pooled analysis of existing cohorts

PubMed Central

Genders, Tessa S S; Steyerberg, Ewout W; Nieman, Koen; Galema, Tjebbe W; Mollet, Nico R; de Feyter, Pim J; Krestin, Gabriel P; Alkadhi, Hatem; Leschka, Sebastian; Desbiolles, Lotus; Meijs, Matthijs F L; Cramer, Maarten J; Knuuti, Juhani; Kajander, Sami; Bogaert, Jan; Goetschalckx, Kaatje; Cademartiri, Filippo; Maffei, Erica; Martini, Chiara; Seitun, Sara; Aldrovandi, Annachiara; Wildermuth, Simon; Stinn, Björn; Fornaro, Jürgen; Feuchtner, Gudrun; De Zordo, Tobias; Auer, Thomas; Plank, Fabian; Friedrich, Guy; Pugliese, Francesca; Petersen, Steffen E; Davies, L Ceri; Schoepf, U Joseph; Rowe, Garrett W; van Mieghem, Carlos A G; van Driessche, Luc; Sinitsyn, Valentin; Gopalan, Deepa; Nikolaou, Konstantin; Bamberg, Fabian; Cury, Ricardo C; Battle, Juan; Maurovich-Horvat, Pál; Bartykowszki, Andrea; Merkely, Bela; Becker, Dávid; Hadamitzky, Martin; Hausleiter, Jörg; Dewey, Marc; Zimmermann, Elke; Laule, Michael

2012-01-01

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations. Design Retrospective pooled analysis of individual patient data. Setting 18 hospitals in Europe and the United States. Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory. Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates. PMID:22692650

Pneumococcal vaccine targeting strategy for older adults: customized risk profiling.

PubMed

Balicer, Ran D; Cohen, Chandra J; Leibowitz, Morton; Feldman, Becca S; Brufman, Ilan; Roberts, Craig; Hoshen, Moshe

2014-02-12

Current pneumococcal vaccine campaigns take a broad, primarily age-based approach to immunization targeting, overlooking many clinical and administrative considerations necessary in disease prevention and resource planning for specific patient populations. We aim to demonstrate the utility of a population-specific predictive model for hospital-treated pneumonia to direct effective vaccine targeting. Data was extracted for 1,053,435 members of an Israeli HMO, age 50 and older, during the study period 2008-2010. We developed and validated a logistic regression model to predict hospital-treated pneumonia using training and test samples, including a set of standard and population-specific risk factors. The model's predictive value was tested for prospectively identifying cases of pneumonia and invasive pneumococcal disease (IPD), and was compared to the existing international paradigm for patient immunization targeting. In a multivariate regression, age, co-morbidity burden and previous pneumonia events were most strongly positively associated with hospital-treated pneumonia. The model predicting hospital-treated pneumonia yielded a c-statistic of 0.80. Utilizing the predictive model, the top 17% highest-risk within the study validation population were targeted to detect 54% of those members who were subsequently treated for hospitalized pneumonia in the follow up period. The high-risk population identified through this model included 46% of the follow-up year's IPD cases, and 27% of community-treated pneumonia cases. These outcomes were compared with international guidelines for risk for pneumococcal diseases that accurately identified only 35% of hospitalized pneumonia, 41% of IPD cases and 21% of community-treated pneumonia. We demonstrate that a customized model for vaccine targeting performs better than international guidelines, and therefore, risk modeling may allow for more precise vaccine targeting and resource allocation than current national and international guidelines. Health care managers and policy-makers may consider the strategic potential of utilizing clinical and administrative databases for creating population-specific risk prediction models to inform vaccination campaigns. Copyright © 2013 Elsevier Ltd. All rights reserved.

Differential encoding of factors influencing predicted reward value in monkey rostral anterior cingulate cortex.

PubMed

Toda, Koji; Sugase-Miyamoto, Yasuko; Mizuhiki, Takashi; Inaba, Kiyonori; Richmond, Barry J; Shidara, Munetaka

2012-01-01

The value of a predicted reward can be estimated based on the conjunction of both the intrinsic reward value and the length of time to obtain it. The question we addressed is how the two aspects, reward size and proximity to reward, influence the responses of neurons in rostral anterior cingulate cortex (rACC), a brain region thought to play an important role in reward processing. We recorded from single neurons while two monkeys performed a multi-trial reward schedule task. The monkeys performed 1-4 sequential color discrimination trials to obtain a reward of 1-3 liquid drops. There were two task conditions, a valid cue condition, where the number of trials and reward amount were associated with visual cues, and a random cue condition, where the cue was picked from the cue set at random. In the valid cue condition, the neuronal firing is strongly modulated by the predicted reward proximity during the trials. Information about the predicted reward amount is almost absent at those times. In substantial subpopulations, the neuronal responses decreased or increased gradually through schedule progress to the predicted outcome. These two gradually modulating signals could be used to calculate the effect of time on the perception of reward value. In the random cue condition, little information about the reward proximity or reward amount is encoded during the course of the trial before reward delivery, but when the reward is actually delivered the responses reflect both the reward proximity and reward amount. Our results suggest that the rACC neurons encode information about reward proximity and amount in a manner that is dependent on utility of reward information. The manner in which the information is represented could be used in the moment-to-moment calculation of the effect of time and amount on predicted outcome value.

Predicting RNA pseudoknot folding thermodynamics

PubMed Central

Cao, Song; Chen, Shi-Jie

2006-01-01

Based on the experimentally determined atomic coordinates for RNA helices and the self-avoiding walks of the P (phosphate) and C4 (carbon) atoms in the diamond lattice for the polynucleotide loop conformations, we derive a set of conformational entropy parameters for RNA pseudoknots. Based on the entropy parameters, we develop a folding thermodynamics model that enables us to compute the sequence-specific RNA pseudoknot folding free energy landscape and thermodynamics. The model is validated through extensive experimental tests both for the native structures and for the folding thermodynamics. The model predicts strong sequence-dependent helix-loop competitions in the pseudoknot stability and the resultant conformational switches between different hairpin and pseudoknot structures. For instance, for the pseudoknot domain of human telomerase RNA, a native-like and a misfolded hairpin intermediates are found to coexist on the (equilibrium) folding pathways, and the interplay between the stabilities of these intermediates causes the conformational switch that may underlie a human telomerase disease. PMID:16709732

Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

PubMed Central

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-01-01

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers. PMID:25551518

Identifying environmental risk factors of cholera in a coastal area with geospatial technologies.

PubMed

Xu, Min; Cao, Chunxiang; Wang, Duochun; Kan, Biao

2014-12-29

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis

PubMed Central

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-01-01

Abstract. Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens. PMID:26057029

Discrimination of healthy and osteoarthritic articular cartilages by Fourier transform infrared imaging and partial least squares-discriminant analysis.

PubMed

Zhang, Xue-Xi; Yin, Jian-Hua; Mao, Zhi-Hua; Xia, Yang

2015-06-01

Fourier transform infrared imaging (FTIRI) combined with chemometrics algorithm has strong potential to obtain complex chemical information from biology tissues. FTIRI and partial least squares-discriminant analysis (PLS-DA) were used to differentiate healthy and osteoarthritic (OA) cartilages for the first time. A PLS model was built on the calibration matrix of spectra that was randomly selected from the FTIRI spectral datasets of healthy and lesioned cartilage. Leave-one-out cross-validation was performed in the PLS model, and the fitting coefficient between actual and predicted categorical values of the calibration matrix reached 0.95. In the calibration and prediction matrices, the successful identifying percentages of healthy and lesioned cartilage spectra were 100% and 90.24%, respectively. These results demonstrated that FTIRI combined with PLS-DA could provide a promising approach for the categorical identification of healthy and OA cartilage specimens.

Friction behavior of a multi-interface system and improved performance by AlMgB 14–TiB 2–C and diamond-like-carbon coatings

DOE PAGES

Qu, Jun; Blau, Peter J.; Higdon, Clifton; ...

2016-03-29

We investigated friction behavior of a bearing system with two interfaces involved: a roller component experiencing rolling–sliding interaction against twin cylinders under point contacts while simultaneously undergoing pure sliding interaction against a socket under a conformal contact. Lubrication modeling predicted a strong correlation between the roller's rolling condition and the system's friction behavior. Experimental observations first validated the analytical predictions using steel and iron components. Diamond-like-carbon (DLC) coating and AlMgB 14–TiB 2 coating with a carbon topcoat (BAMC) were then applied to the roller and twin cylinders, respectively. In conclusion, testing and analysis results suggest that the coatings effectively decreasedmore » the slip ratio for the roller–cylinder contact and the sliding friction at both bearing interfaces and, as a result, significantly reduced the system frictional torque.« less

Modeling of the reactant conversion rate in a turbulent shear flow

NASA Technical Reports Server (NTRS)

Frankel, S. H.; Madnia, C. K.; Givi, P.

1992-01-01

Results are presented of direct numerical simulations (DNS) of spatially developing shear flows under the influence of infinitely fast chemical reactions of the type A + B yields Products. The simulation results are used to construct the compositional structure of the scalar field in a statistical manner. The results of this statistical analysis indicate that the use of a Beta density for the probability density function (PDF) of an appropriate Shvab-Zeldovich mixture fraction provides a very good estimate of the limiting bounds of the reactant conversion rate within the shear layer. This provides a strong justification for the implementation of this density in practical modeling of non-homogeneous turbulent reacting flows. However, the validity of the model cannot be generalized for predictions of higher order statistical quantities. A closed form analytical expression is presented for predicting the maximum rate of reactant conversion in non-homogeneous reacting turbulence.

Corrosion fatigue crack propagation in metals

NASA Technical Reports Server (NTRS)

Gangloff, Richard P.

1990-01-01

This review assesses fracture mechanics data and mechanistic models for corrosion fatigue crack propagation in structural alloys exposed to ambient temperature gases and electrolytes. Extensive stress intensity-crack growth rate data exist for ferrous, aluminum and nickel based alloys in a variety of environments. Interactive variables (viz., stress intensity range, mean stress, alloy composition and microstructure, loading frequency, temperature, gas pressure and electrode potential) strongly affect crack growth kinetics and complicate fatigue control. Mechanistic models to predict crack growth rates were formulated by coupling crack tip mechanics with occluded crack chemistry, and from both the hydrogen embrittlement and anodic dissolution/film rupture perspectives. Research is required to better define: (1) environmental effects near threshold and on crack closure; (2) damage tolerant life prediction codes and the validity of similitude; (3) the behavior of microcrack; (4) probes and improved models of crack tip damage; and (5) the cracking performance of advanced alloys and composites.

Visualizing In Situ Microstructure Dependent Crack Tip Stress Distribution in IN-617 Using Nano-mechanical Raman Spectroscopy

NASA Astrophysics Data System (ADS)

Zhang, Yang; Mohanty, Debapriya P.; Tomar, Vikas

2016-11-01

Inconel 617 (IN-617) is a solid solution alloy, which is widely used in applications that require high-temperature component operation due to its high-temperature stability and strength as well as strong resistance to oxidation and carburization. The current work focuses on in situ measurements of stress distribution under 3-point bending at elevated temperature in IN-617. A nanomechanical Raman spectroscopy measurement platform was designed and built based on a combination of a customized open Raman spectroscopy (NMRS) system incorporating a motorized scanning and imaging system with a nanomechanical loading platform. Based on the scanning of the crack tip notch area using the NMRS notch tip, stress distribution under applied load with micron-scale resolution for analyzed microstructures is predicted. A finite element method-based formulation to predict crack tip stresses is presented and validated using the presented experimental data.

miRTarBase update 2018: a resource for experimentally validated microRNA-target interactions.

PubMed

Chou, Chih-Hung; Shrestha, Sirjana; Yang, Chi-Dung; Chang, Nai-Wen; Lin, Yu-Ling; Liao, Kuang-Wen; Huang, Wei-Chi; Sun, Ting-Hsuan; Tu, Siang-Jyun; Lee, Wei-Hsiang; Chiew, Men-Yee; Tai, Chun-San; Wei, Ting-Yen; Tsai, Tzi-Ren; Huang, Hsin-Tzu; Wang, Chung-Yu; Wu, Hsin-Yi; Ho, Shu-Yi; Chen, Pin-Rong; Chuang, Cheng-Hsun; Hsieh, Pei-Jung; Wu, Yi-Shin; Chen, Wen-Liang; Li, Meng-Ju; Wu, Yu-Chun; Huang, Xin-Yi; Ng, Fung Ling; Buddhakosai, Waradee; Huang, Pei-Chun; Lan, Kuan-Chun; Huang, Chia-Yen; Weng, Shun-Long; Cheng, Yeong-Nan; Liang, Chao; Hsu, Wen-Lian; Huang, Hsien-Da

2018-01-04

MicroRNAs (miRNAs) are small non-coding RNAs of ∼ 22 nucleotides that are involved in negative regulation of mRNA at the post-transcriptional level. Previously, we developed miRTarBase which provides information about experimentally validated miRNA-target interactions (MTIs). Here, we describe an updated database containing 422 517 curated MTIs from 4076 miRNAs and 23 054 target genes collected from over 8500 articles. The number of MTIs curated by strong evidence has increased ∼1.4-fold since the last update in 2016. In this updated version, target sites validated by reporter assay that are available in the literature can be downloaded. The target site sequence can extract new features for analysis via a machine learning approach which can help to evaluate the performance of miRNA-target prediction tools. Furthermore, different ways of browsing enhance user browsing specific MTIs. With these improvements, miRTarBase serves as more comprehensively annotated, experimentally validated miRNA-target interactions databases in the field of miRNA related research. miRTarBase is available at http://miRTarBase.mbc.nctu.edu.tw/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

An improved stable isotope N-terminal labeling approach with light/heavy TMPP to automate proteogenomics data validation: dN-TOP.

PubMed

Bertaccini, Diego; Vaca, Sebastian; Carapito, Christine; Arsène-Ploetze, Florence; Van Dorsselaer, Alain; Schaeffer-Reiss, Christine

2013-06-07

In silico gene prediction has proven to be prone to errors, especially regarding precise localization of start codons that spread in subsequent biological studies. Therefore, the high throughput characterization of protein N-termini is becoming an emerging challenge in the proteomics and especially proteogenomics fields. The trimethoxyphenyl phosphonium (TMPP) labeling approach (N-TOP) is an efficient N-terminomic approach that allows the characterization of both N-terminal and internal peptides in a single experiment. Due to its permanent positive charge, TMPP labeling strongly affects MS/MS fragmentation resulting in unadapted scoring of TMPP-derivatized peptide spectra by classical search engines. This behavior has led to difficulties in validating TMPP-derivatized peptide identifications with usual score filtering and thus to low/underestimated numbers of identified N-termini. We present herein a new strategy (dN-TOP) that overwhelmed the previous limitation allowing a confident and automated N-terminal peptide validation thanks to a combined labeling with light and heavy TMPP reagents. We show how this double labeling allows increasing the number of validated N-terminal peptides. This strategy represents a considerable improvement to the well-established N-TOP method with an enhanced and accelerated data processing making it now fully compatible with high-throughput proteogenomics studies.

Validating dimensions of psychosis symptomatology: Neural correlates and 20-year outcomes.

PubMed

Kotov, Roman; Foti, Dan; Li, Kaiqiao; Bromet, Evelyn J; Hajcak, Greg; Ruggero, Camilo J

2016-11-01

Heterogeneity of psychosis presents significant challenges for classification. Between 2 and 12 symptom dimensions have been proposed, and consensus is lacking. The present study sought to identify uniquely informative models by comparing the validity of these alternatives. An epidemiologic cohort of 628 first-admission inpatients with psychosis was interviewed 6 times over 2 decades and completed an electrophysiological assessment of error processing at year 20. We first analyzed a comprehensive set of 49 symptoms rated by interviewers at baseline, progressively extracting from 1 to 12 factors. Next, we compared the ability of resulting factor solutions to (a) account for concurrent neural dysfunction and (b) predict 20-year role, social, residential, and global functioning, and life satisfaction. A four-factor model showed incremental validity with all outcomes, and more complex models did not improve explanatory power. The 4 dimensions-reality distortion, disorganization, inexpressivity, and apathy/asociality-were replicable in 5 follow-ups, internally consistent, stable across assessments, and showed strong discriminant validity. These results reaffirm the value of separating disorganization and reality distortion, are consistent with recent findings distinguishing inexpressivity and apathy/asociality, and suggest that these 4 dimensions are fundamental to understanding neural abnormalities and long-term outcomes in psychosis. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Predictive Validity of the Tilburg Frailty Indicator: Disability, Health Care Utilization, and Quality of Life in a Population at Risk

ERIC Educational Resources Information Center

Gobbens, Robbert J. J.; van Assen, Marcel A. L. M.; Luijkx, Katrien G.; Schols, Jos M. G. A.

2012-01-01

Purpose: To assess the predictive validity of frailty and its domains (physical, psychological, and social), as measured by the Tilburg Frailty Indicator (TFI), for the adverse outcomes disability, health care utilization, and quality of life. Design and Methods: The predictive validity of the TFI was tested in a representative sample of 484…

VALIDATION OF BENEFIT-TRANSFER FUNCTIONS

EPA Science Inventory

1. Identification of benefit-transfer functions that are the most credible. 2. Identification of benefit-transfer issues that are related to transfer method and those related to data limitations. 3. Clarification of issues t...

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.

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.

The importance of molecular structures, endpoints' values, and predictivity parameters in QSAR research: QSAR analysis of a series of estrogen receptor binders.

PubMed

Li, Jiazhong; Gramatica, Paola

2010-11-01

Quantitative structure-activity relationship (QSAR) methodology aims to explore the relationship between molecular structures and experimental endpoints, producing a model for the prediction of new data; the predictive performance of the model must be checked by external validation. Clearly, the qualities of chemical structure information and experimental endpoints, as well as the statistical parameters used to verify the external predictivity have a strong influence on QSAR model reliability. Here, we emphasize the importance of these three aspects by analyzing our models on estrogen receptor binders (Endocrine disruptor knowledge base (EDKB) database). Endocrine disrupting chemicals, which mimic or antagonize the endogenous hormones such as estrogens, are a hot topic in environmental and toxicological sciences. QSAR shows great values in predicting the estrogenic activity and exploring the interactions between the estrogen receptor and ligands. We have verified our previously published model for additional external validation on new EDKB chemicals. Having found some errors in the used 3D molecular conformations, we redevelop a new model using the same data set with corrected structures, the same method (ordinary least-square regression, OLS) and DRAGON descriptors. The new model, based on some different descriptors, is more predictive on external prediction sets. Three different formulas to calculate correlation coefficient for the external prediction set (Q2 EXT) were compared, and the results indicated that the new proposal of Consonni et al. had more reasonable results, consistent with the conclusions from regression line, Williams plot and root mean square error (RMSE) values. Finally, the importance of reliable endpoints values has been highlighted by comparing the classification assignments of EDKB with those of another estrogen receptor binders database (METI): we found that 16.1% assignments of the common compounds were opposite (20 among 124 common compounds). In order to verify the real assignments for these inconsistent compounds, we predicted these samples, as a blind external set, by our regression models and compared the results with the two databases. The results indicated that most of the predictions were consistent with METI. Furthermore, we built a kNN classification model using the 104 consistent compounds to predict those inconsistent ones, and most of the predictions were also in agreement with METI database.

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.

Risk prediction models for graft failure in kidney transplantation: a systematic review.

PubMed

Kaboré, Rémi; Haller, Maria C; Harambat, Jérôme; Heinze, Georg; Leffondré, Karen

2017-04-01

Risk prediction models are useful for identifying kidney recipients at high risk of graft failure, thus optimizing clinical care. Our objective was to systematically review the models that have been recently developed and validated to predict graft failure in kidney transplantation recipients. We used PubMed and Scopus to search for English, German and French language articles published in 2005-15. We selected studies that developed and validated a new risk prediction model for graft failure after kidney transplantation, or validated an existing model with or without updating the model. Data on recipient characteristics and predictors, as well as modelling and validation methods were extracted. In total, 39 articles met the inclusion criteria. Of these, 34 developed and validated a new risk prediction model and 5 validated an existing one with or without updating the model. The most frequently predicted outcome was graft failure, defined as dialysis, re-transplantation or death with functioning graft. Most studies used the Cox model. There was substantial variability in predictors used. In total, 25 studies used predictors measured at transplantation only, and 14 studies used predictors also measured after transplantation. Discrimination performance was reported in 87% of studies, while calibration was reported in 56%. Performance indicators were estimated using both internal and external validation in 13 studies, and using external validation only in 6 studies. Several prediction models for kidney graft failure in adults have been published. Our study highlights the need to better account for competing risks when applicable in such studies, and to adequately account for post-transplant measures of predictors in studies aiming at improving monitoring of kidney transplant recipients. © The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

NASA Astrophysics Data System (ADS)

Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen

2016-07-01

Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.

Tumour gene expression predicts response to cetuximab in patients with KRAS wild-type metastatic colorectal cancer.

PubMed

Baker, J B; Dutta, D; Watson, D; Maddala, T; Munneke, B M; Shak, S; Rowinsky, E K; Xu, L-A; Harbison, C T; Clark, E A; Mauro, D J; Khambata-Ford, S

2011-02-01

Although it is accepted that metastatic colorectal cancers (mCRCs) that carry activating mutations in KRAS are unresponsive to anti-epidermal growth factor receptor (EGFR) monoclonal antibodies, a significant fraction of KRAS wild-type (wt) mCRCs are also unresponsive to anti-EGFR therapy. Genes encoding EGFR ligands amphiregulin (AREG) and epiregulin (EREG) are promising gene expression-based markers but have not been incorporated into a test to dichotomise KRAS wt mCRC patients with respect to sensitivity to anti-EGFR treatment. We used RT-PCR to test 110 candidate gene expression markers in primary tumours from 144 KRAS wt mCRC patients who received monotherapy with the anti-EGFR antibody cetuximab. Results were correlated with multiple clinical endpoints: disease control, objective response, and progression-free survival (PFS). Expression of many of the tested candidate genes, including EREG and AREG, strongly associate with all clinical endpoints. Using multivariate analysis with two-layer five-fold cross-validation, we constructed a four-gene predictive classifier. Strikingly, patients below the classifier cutpoint had PFS and disease control rates similar to those of patients with KRAS mutant mCRC. Gene expression appears to identify KRAS wt mCRC patients who receive little benefit from cetuximab. It will be important to test this model in an independent validation study.

Quantitative models for predicting adsorption of oxytetracycline, ciprofloxacin and sulfamerazine to swine manures with contrasting properties.

PubMed

Cheng, Dengmiao; Feng, Yao; Liu, Yuanwang; Li, Jinpeng; Xue, Jianming; Li, Zhaojun

2018-09-01

Understanding antibiotic adsorption in livestock manures is crucial to assess the fate and risk of antibiotics in the environment. In this study, three quantitative models developed with swine manure-water distribution coefficients (LgK d ) for oxytetracycline (OTC), ciprofloxacin (CIP) and sulfamerazine (SM1) in swine manures. Physicochemical parameters (n=12) of the swine manure were used as independent variables using partial least-squares (PLSs) analysis. The cumulative cross-validated regression coefficients (Q 2 cum ) values, standard deviations (SDs) and external validation coefficient (Q 2 ext ) ranged from 0.761 to 0.868, 0.027 to 0.064, and 0.743 to 0.827 for the three models; as such, internal and external predictability of the models were strong. The pH, soluble organic carbon (SOC) and nitrogen (SON), and Ca were important explanatory variables for the OTC-Model, pH, SOC, and SON for the CIP-model, and pH, total organic nitrogen (TON), and SOC for the SM1-model. The high VIPs (variable importance in the projections) of pH (1.178-1.396), SOC (0.968-1.034), and SON (0.822 and 0.865) established these physicochemical parameters as likely being dominant (associatively) in affecting transport of antibiotics in swine manures. Copyright © 2018 Elsevier B.V. All rights reserved.

Characteristics of Mild Cognitive Impairment Using the Thai Version of the Consortium to Establish a Registry for Alzheimer's Disease Tests: A Multivariate and Machine Learning Study.

PubMed

Tunvirachaisakul, Chavit; Supasitthumrong, Thitiporn; Tangwongchai, Sookjareon; Hemrunroj, Solaphat; Chuchuen, Phenphichcha; Tawankanjanachot, Itthipol; Likitchareon, Yuthachai; Phanthumchinda, Kamman; Sriswasdi, Sira; Maes, Michael

2018-04-04

The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) developed a neuropsychological battery (CERAD-NP) to screen patients with Alzheimer's dementia. Mild cognitive impairment (MCI) has received attention as a pre-dementia stage. To delineate the CERAD-NP features of MCI and their clinical utility to externally validate MCI diagnosis. The study included 60 patients with MCI, diagnosed using the Clinical Dementia Rating, and 63 normal controls. Data were analysed employing receiver operating characteristic analysis, Linear Support Vector Machine, Random Forest, Adaptive Boosting, Neural Network models, and t-distributed stochastic neighbour embedding (t-SNE). MCI patients were best discriminated from normal controls using a combination of Wordlist Recall, Wordlist Memory, and Verbal Fluency Test. Machine learning showed that the CERAD features learned from MCI patients and controls were not strongly predictive of the diagnosis (maximal cross-validation 77.2%), whilst t-SNE showed that there is a considerable overlap between MCI and controls. The most important features of the CERAD-NP differentiating MCI from normal controls indicate impairments in episodic and semantic memory and recall. While these features significantly discriminate MCI patients from normal controls, the tests are not predictive of MCI. © 2018 S. Karger AG, Basel.

PDCD1 (PD-1) promoter methylation predicts outcome in head and neck squamous cell carcinoma patients.

PubMed

Goltz, Diane; Gevensleben, Heidrun; Dietrich, Joern; Schroeck, Friederike; de Vos, Luka; Droege, Freya; Kristiansen, Glen; Schroeck, Andreas; Landsberg, Jennifer; Bootz, Friedrich; Dietrich, Dimo

2017-06-20

Biomarkers that facilitate the prediction of disease recurrence in head and neck squamous cell carcinoma (HNSCC) may enable physicians to personalize treatment. In the current study, DNA promoter methylation of programmed cell death 1 (PDCD1, PD-1) was evaluated as a prognostic biomarker in HNSCC patients. High PDCD1 methylation (mPDCD1) was associated with a significantly shorter overall survival after surgical resection in both the discovery (HR = 2.24 [95%CI: 1.08-4.64], p = 0.029) and the validation cohort (HR = 1.54 [95%CI: 1.08-2.21], p = 0.017). In multivariate Cox proportional hazards analysis, PDCD1 methylation remained a significant prognostic factor for HNSCC (HR = 2.14 [95%CI: 1.19-3.84], p = 0.011). Further, mPDCD1 was strongly associated with the human papilloma virus (HPV) status. mPDCD1 was assessed retrospectively in a discovery cohort of 120 HNSCC patients treated at the University Hospital of Bonn and a validation cohort of 527 HNSCC cases analyzed by The Cancer Genome Atlas Research Network. PDCD1 methylation might aid the identification of HNSCC patients potentially benefitting from a radical or alternative treatment, particularly in the context of immunotherapies targeting PD-1/PD-L1.

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1)

PubMed Central

Lingner, Thomas; Kataya, Amr R. A.; Reumann, Sigrun

2012-01-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences.1 As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity.” Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals. PMID:22415050

Experimental and statistical post-validation of positive example EST sequences carrying peroxisome targeting signals type 1 (PTS1).

PubMed

Lingner, Thomas; Kataya, Amr R A; Reumann, Sigrun

2012-02-01

We recently developed the first algorithms specifically for plants to predict proteins carrying peroxisome targeting signals type 1 (PTS1) from genome sequences. As validated experimentally, the prediction methods are able to correctly predict unknown peroxisomal Arabidopsis proteins and to infer novel PTS1 tripeptides. The high prediction performance is primarily determined by the large number and sequence diversity of the underlying positive example sequences, which mainly derived from EST databases. However, a few constructs remained cytosolic in experimental validation studies, indicating sequencing errors in some ESTs. To identify erroneous sequences, we validated subcellular targeting of additional positive example sequences in the present study. Moreover, we analyzed the distribution of prediction scores separately for each orthologous group of PTS1 proteins, which generally resembled normal distributions with group-specific mean values. The cytosolic sequences commonly represented outliers of low prediction scores and were located at the very tail of a fitted normal distribution. Three statistical methods for identifying outliers were compared in terms of sensitivity and specificity." Their combined application allows elimination of erroneous ESTs from positive example data sets. This new post-validation method will further improve the prediction accuracy of both PTS1 and PTS2 protein prediction models for plants, fungi, and mammals.

Genomic selection across multiple breeding cycles in applied bread wheat breeding.

PubMed

Michel, Sebastian; Ametz, Christian; Gungor, Huseyin; Epure, Doru; Grausgruber, Heinrich; Löschenberger, Franziska; Buerstmayr, Hermann

2016-06-01

We evaluated genomic selection across five breeding cycles of bread wheat breeding. Bias of within-cycle cross-validation and methods for improving the prediction accuracy were assessed. The prospect of genomic selection has been frequently shown by cross-validation studies using the same genetic material across multiple environments, but studies investigating genomic selection across multiple breeding cycles in applied bread wheat breeding are lacking. We estimated the prediction accuracy of grain yield, protein content and protein yield of 659 inbred lines across five independent breeding cycles and assessed the bias of within-cycle cross-validation. We investigated the influence of outliers on the prediction accuracy and predicted protein yield by its components traits. A high average heritability was estimated for protein content, followed by grain yield and protein yield. The bias of the prediction accuracy using populations from individual cycles using fivefold cross-validation was accordingly substantial for protein yield (17-712 %) and less pronounced for protein content (8-86 %). Cross-validation using the cycles as folds aimed to avoid this bias and reached a maximum prediction accuracy of [Formula: see text] = 0.51 for protein content, [Formula: see text] = 0.38 for grain yield and [Formula: see text] = 0.16 for protein yield. Dropping outlier cycles increased the prediction accuracy of grain yield to [Formula: see text] = 0.41 as estimated by cross-validation, while dropping outlier environments did not have a significant effect on the prediction accuracy. Independent validation suggests, on the other hand, that careful consideration is necessary before an outlier correction is undertaken, which removes lines from the training population. Predicting protein yield by multiplying genomic estimated breeding values of grain yield and protein content raised the prediction accuracy to [Formula: see text] = 0.19 for this derived trait.

Performance and robustness of penalized and unpenalized methods for genetic prediction of complex human disease.

PubMed

Abraham, Gad; Kowalczyk, Adam; Zobel, Justin; Inouye, Michael

2013-02-01

A central goal of medical genetics is to accurately predict complex disease from genotypes. Here, we present a comprehensive analysis of simulated and real data using lasso and elastic-net penalized support-vector machine models, a mixed-effects linear model, a polygenic score, and unpenalized logistic regression. In simulation, the sparse penalized models achieved lower false-positive rates and higher precision than the other methods for detecting causal SNPs. The common practice of prefiltering SNP lists for subsequent penalized modeling was examined and shown to substantially reduce the ability to recover the causal SNPs. Using genome-wide SNP profiles across eight complex diseases within cross-validation, lasso and elastic-net models achieved substantially better predictive ability in celiac disease, type 1 diabetes, and Crohn's disease, and had equivalent predictive ability in the rest, with the results in celiac disease strongly replicating between independent datasets. We investigated the effect of linkage disequilibrium on the predictive models, showing that the penalized methods leverage this information to their advantage, compared with methods that assume SNP independence. Our findings show that sparse penalized approaches are robust across different disease architectures, producing as good as or better phenotype predictions and variance explained. This has fundamental ramifications for the selection and future development of methods to genetically predict human disease. © 2012 WILEY PERIODICALS, INC.

ProTox: a web server for the in silico prediction of rodent oral toxicity.

PubMed

Drwal, Malgorzata N; Banerjee, Priyanka; Dunkel, Mathias; Wettig, Martin R; Preissner, Robert

2014-07-01

Animal trials are currently the major method for determining the possible toxic effects of drug candidates and cosmetics. In silico prediction methods represent an alternative approach and aim to rationalize the preclinical drug development, thus enabling the reduction of the associated time, costs and animal experiments. Here, we present ProTox, a web server for the prediction of rodent oral toxicity. The prediction method is based on the analysis of the similarity of compounds with known median lethal doses (LD50) and incorporates the identification of toxic fragments, therefore representing a novel approach in toxicity prediction. In addition, the web server includes an indication of possible toxicity targets which is based on an in-house collection of protein-ligand-based pharmacophore models ('toxicophores') for targets associated with adverse drug reactions. The ProTox web server is open to all users and can be accessed without registration at: http://tox.charite.de/tox. The only requirement for the prediction is the two-dimensional structure of the input compounds. All ProTox methods have been evaluated based on a diverse external validation set and displayed strong performance (sensitivity, specificity and precision of 76, 95 and 75%, respectively) and superiority over other toxicity prediction tools, indicating their possible applicability for other compound classes. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Evaluating the Predictive Validity of the Computerized Comprehension Task: Comprehension Predicts Production

PubMed Central

Friend, Margaret; Schmitt, Sara A.; Simpson, Adrianne M.

2017-01-01

Until recently, the challenges inherent in measuring comprehension have impeded our ability to predict the course of language acquisition. The present research reports on a longitudinal assessment of the convergent and predictive validity of the CDI: Words and Gestures and the Computerized Comprehension Task (CCT). The CDI: WG and the CCT evinced good convergent validity however the CCT better predicted subsequent parent reports of language production. Language sample data in the third year confirm this finding: the CCT accounted for 24% of the variance in unique word use. These studies provide evidence for the utility of a behavior-based approach to predicting the course of language acquisition into production. PMID:21928878

Broad-scale predictability of carbohydrates and exopolymers in Antarctic and Arctic sea ice

PubMed Central

Underwood, Graham J. C.; Aslam, Shazia N.; Michel, Christine; Niemi, Andrea; Norman, Louiza; Meiners, Klaus M.; Laybourn-Parry, Johanna; Paterson, Harriet; Thomas, David N.

2013-01-01

Sea ice can contain high concentrations of dissolved organic carbon (DOC), much of which is carbohydrate-rich extracellular polymeric substances (EPS) produced by microalgae and bacteria inhabiting the ice. Here we report the concentrations of dissolved carbohydrates (dCHO) and dissolved EPS (dEPS) in relation to algal standing stock [estimated by chlorophyll (Chl) a concentrations] in sea ice from six locations in the Southern and Arctic Oceans. Concentrations varied substantially within and between sampling sites, reflecting local ice conditions and biological content. However, combining all data revealed robust statistical relationships between dCHO concentrations and the concentrations of different dEPS fractions, Chl a, and DOC. These relationships were true for whole ice cores, bottom ice (biomass rich) sections, and colder surface ice. The distribution of dEPS was strongly correlated to algal biomass, with the highest concentrations of both dEPS and non-EPS carbohydrates in the bottom horizons of the ice. Complex EPS was more prevalent in colder surface sea ice horizons. Predictive models (validated against independent data) were derived to enable the estimation of dCHO concentrations from data on ice thickness, salinity, and vertical position in core. When Chl a data were included a higher level of prediction was obtained. The consistent patterns reflected in these relationships provide a strong basis for including estimates of regional and seasonal carbohydrate and dEPS carbon budgets in coupled physical-biogeochemical models, across different types of sea ice from both polar regions. PMID:24019487

Broad-scale predictability of carbohydrates and exopolymers in Antarctic and Arctic sea ice.

PubMed

Underwood, Graham J C; Aslam, Shazia N; Michel, Christine; Niemi, Andrea; Norman, Louiza; Meiners, Klaus M; Laybourn-Parry, Johanna; Paterson, Harriet; Thomas, David N

2013-09-24

Sea ice can contain high concentrations of dissolved organic carbon (DOC), much of which is carbohydrate-rich extracellular polymeric substances (EPS) produced by microalgae and bacteria inhabiting the ice. Here we report the concentrations of dissolved carbohydrates (dCHO) and dissolved EPS (dEPS) in relation to algal standing stock [estimated by chlorophyll (Chl) a concentrations] in sea ice from six locations in the Southern and Arctic Oceans. Concentrations varied substantially within and between sampling sites, reflecting local ice conditions and biological content. However, combining all data revealed robust statistical relationships between dCHO concentrations and the concentrations of different dEPS fractions, Chl a, and DOC. These relationships were true for whole ice cores, bottom ice (biomass rich) sections, and colder surface ice. The distribution of dEPS was strongly correlated to algal biomass, with the highest concentrations of both dEPS and non-EPS carbohydrates in the bottom horizons of the ice. Complex EPS was more prevalent in colder surface sea ice horizons. Predictive models (validated against independent data) were derived to enable the estimation of dCHO concentrations from data on ice thickness, salinity, and vertical position in core. When Chl a data were included a higher level of prediction was obtained. The consistent patterns reflected in these relationships provide a strong basis for including estimates of regional and seasonal carbohydrate and dEPS carbon budgets in coupled physical-biogeochemical models, across different types of sea ice from both polar regions.

Analysis of model development strategies: predicting ventral hernia recurrence.

PubMed

Holihan, Julie L; Li, Linda T; Askenasy, Erik P; Greenberg, Jacob A; Keith, Jerrod N; Martindale, Robert G; Roth, J Scott; Liang, Mike K

2016-11-01

There have been many attempts to identify variables associated with ventral hernia recurrence; however, it is unclear which statistical modeling approach results in models with greatest internal and external validity. We aim to assess the predictive accuracy of models developed using five common variable selection strategies to determine variables associated with hernia recurrence. Two multicenter ventral hernia databases were used. Database 1 was randomly split into "development" and "internal validation" cohorts. Database 2 was designated "external validation". The dependent variable for model development was hernia recurrence. Five variable selection strategies were used: (1) "clinical"-variables considered clinically relevant, (2) "selective stepwise"-all variables with a P value <0.20 were assessed in a step-backward model, (3) "liberal stepwise"-all variables were included and step-backward regression was performed, (4) "restrictive internal resampling," and (5) "liberal internal resampling." Variables were included with P < 0.05 for the Restrictive model and P < 0.10 for the Liberal model. A time-to-event analysis using Cox regression was performed using these strategies. The predictive accuracy of the developed models was tested on the internal and external validation cohorts using Harrell's C-statistic where C > 0.70 was considered "reasonable". The recurrence rate was 32.9% (n = 173/526; median/range follow-up, 20/1-58 mo) for the development cohort, 36.0% (n = 95/264, median/range follow-up 20/1-61 mo) for the internal validation cohort, and 12.7% (n = 155/1224, median/range follow-up 9/1-50 mo) for the external validation cohort. Internal validation demonstrated reasonable predictive accuracy (C-statistics = 0.772, 0.760, 0.767, 0.757, 0.763), while on external validation, predictive accuracy dipped precipitously (C-statistic = 0.561, 0.557, 0.562, 0.553, 0.560). Predictive accuracy was equally adequate on internal validation among models; however, on external validation, all five models failed to demonstrate utility. Future studies should report multiple variable selection techniques and demonstrate predictive accuracy on external data sets for model validation. Copyright © 2016 Elsevier Inc. All rights reserved.

Validation of the Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM).

PubMed

Willis, Michael; Johansen, Pierre; Nilsson, Andreas; Asseburg, Christian

2017-03-01

The Economic and Health Outcomes Model of Type 2 Diabetes Mellitus (ECHO-T2DM) was developed to address study questions pertaining to the cost-effectiveness of treatment alternatives in the care of patients with type 2 diabetes mellitus (T2DM). Naturally, the usefulness of a model is determined by the accuracy of its predictions. A previous version of ECHO-T2DM was validated against actual trial outcomes and the model predictions were generally accurate. However, there have been recent upgrades to the model, which modify model predictions and necessitate an update of the validation exercises. The objectives of this study were to extend the methods available for evaluating model validity, to conduct a formal model validation of ECHO-T2DM (version 2.3.0) in accordance with the principles espoused by the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) and the Society for Medical Decision Making (SMDM), and secondarily to evaluate the relative accuracy of four sets of macrovascular risk equations included in ECHO-T2DM. We followed the ISPOR/SMDM guidelines on model validation, evaluating face validity, verification, cross-validation, and external validation. Model verification involved 297 'stress tests', in which specific model inputs were modified systematically to ascertain correct model implementation. Cross-validation consisted of a comparison between ECHO-T2DM predictions and those of the seminal National Institutes of Health model. In external validation, study characteristics were entered into ECHO-T2DM to replicate the clinical results of 12 studies (including 17 patient populations), and model predictions were compared to observed values using established statistical techniques as well as measures of average prediction error, separately for the four sets of macrovascular risk equations supported in ECHO-T2DM. Sub-group analyses were conducted for dependent vs. independent outcomes and for microvascular vs. macrovascular vs. mortality endpoints. All stress tests were passed. ECHO-T2DM replicated the National Institutes of Health cost-effectiveness application with numerically similar results. In external validation of ECHO-T2DM, model predictions agreed well with observed clinical outcomes. For all sets of macrovascular risk equations, the results were close to the intercept and slope coefficients corresponding to a perfect match, resulting in high R 2 and failure to reject concordance using an F test. The results were similar for sub-groups of dependent and independent validation, with some degree of under-prediction of macrovascular events. ECHO-T2DM continues to match health outcomes in clinical trials in T2DM, with prediction accuracy similar to other leading models of T2DM.

Evaluation of limited sampling models for prediction of oral midazolam AUC for CYP3A phenotyping and drug interaction studies.

PubMed

Mueller, Silke C; Drewelow, Bernd

2013-05-01

The area under the concentration-time curve (AUC) after oral midazolam administration is commonly used for cytochrome P450 (CYP) 3A phenotyping studies. The aim of this investigation was to evaluate a limited sampling strategy for the prediction of AUC with oral midazolam. A total of 288 concentration-time profiles from 123 healthy volunteers who participated in four previously performed drug interaction studies with intense sampling after a single oral dose of 7.5 mg midazolam were available for evaluation. Of these, 45 profiles served for model building, which was performed by stepwise multiple linear regression, and the remaining 243 datasets served for validation. Mean prediction error (MPE), mean absolute error (MAE) and root mean squared error (RMSE) were calculated to determine bias and precision The one- to four-sampling point models with the best coefficient of correlation were the one-sampling point model (8 h; r (2) = 0.84), the two-sampling point model (0.5 and 8 h; r (2) = 0.93), the three-sampling point model (0.5, 2, and 8 h; r (2) = 0.96), and the four-sampling point model (0.5,1, 2, and 8 h; r (2) = 0.97). However, the one- and two-sampling point models were unable to predict the midazolam AUC due to unacceptable bias and precision. Only the four-sampling point model predicted the very low and very high midazolam AUC of the validation dataset with acceptable precision and bias. The four-sampling point model was also able to predict the geometric mean ratio of the treatment phase over the baseline (with 90 % confidence interval) results of three drug interaction studies in the categories of strong, moderate, and mild induction, as well as no interaction. A four-sampling point limited sampling strategy to predict the oral midazolam AUC for CYP3A phenotyping is proposed. The one-, two- and three-sampling point models were not able to predict midazolam AUC accurately.

Atom and receptor based 3D QSAR models for generating new conformations from pyrazolopyrimidine as IL-2 inducible tyrosine kinase inhibitors.

PubMed

Ul-Haq, Zaheer; Effendi, Juweria Shahrukh; Ashraf, Sajda; Bkhaitan, Majdi M

2017-06-01

In the current study, quantitative three-dimensional structure-activity-relationship (3D-QSAR) method was performed to design a model for new chemical entities by utilizing pyrazolopyrimidines. Their inhibiting activity on receptor IL-2 Itk correlates descriptors based on topology and hydrophobicity. The best model developed by ligand-based (atom-based) approach has correlation-coefficient of r 2 : 0.987 and cross-validated squared correlation-coefficient of q 2 : 0.541 with an external prediction capability of r 2 : 0.944. Whereas the best selected model developed by structured-based (receptor-based) approach has correlation-coefficient of r 2 : 0.987, cross-validated squared correlation-coefficient of q 2 : 0.637 with an external predictive ability of r 2 : 0.941. The statistical parameters prove that structure-based gave a better model to design new chemical scaffolds. The results achieved indicated that hydrophobicity at R 1 location play a vital role in the inhibitory activity and introduction of appropriately bulky and strongly hydrophobic-groups at position 3 of the terminal phenyl-group which is highly significant to enhance the activity. Six new pyrazolopyrimidine derivatives were designed. Docking simulation study was carried out and their inhibitory activity was predicted by the best structure based model with predictive activity of ranging from 8.43 to 8.85 log unit. The interacting residues PHE435, ASP500, LYS391, GLU436, MET438, CYS442, ILE369, VAL377 of PDB 4HCT were studied with respect to type of bonding with the new compounds. This study was aimed to search out more potent inhibitors of IL-2 Itk. Copyright © 2017 Elsevier Inc. All rights reserved.

Validation of a coupled core-transport, pedestal-structure, current-profile and equilibrium model

NASA Astrophysics Data System (ADS)

Meneghini, O.

2015-11-01

The first workflow capable of predicting the self-consistent solution to the coupled core-transport, pedestal structure, and equilibrium problems from first-principles and its experimental tests are presented. Validation with DIII-D discharges in high confinement regimes shows that the workflow is capable of robustly predicting the kinetic profiles from on axis to the separatrix and matching the experimental measurements to within their uncertainty, with no prior knowledge of the pedestal height nor of any measurement of the temperature or pressure. Self-consistent coupling has proven to be essential to match the experimental results, and capture the non-linear physics that governs the core and pedestal solutions. In particular, clear stabilization of the pedestal peeling ballooning instabilities by the global Shafranov shift and destabilization by additional edge bootstrap current, and subsequent effect on the core plasma profiles, have been clearly observed and documented. In our model, self-consistency is achieved by iterating between the TGYRO core transport solver (with NEO and TGLF for neoclassical and turbulent flux), and the pedestal structure predicted by the EPED model. A self-consistent equilibrium is calculated by EFIT, while the ONETWO transport package evolves the current profile and calculates the particle and energy sources. The capabilities of such workflow are shown to be critical for the design of future experiments such as ITER and FNSF, which operate in a regime where the equilibrium, the pedestal, and the core transport problems are strongly coupled, and for which none of these quantities can be assumed to be known. Self-consistent core-pedestal predictions for ITER, as well as initial optimizations, will be presented. Supported by the US Department of Energy under DE-FC02-04ER54698, DE-SC0012652.

Simulating flame lift-off characteristics of diesel and biodiesel fuels using detailed chemical-kinetic mechanisms and LES turbulence model.

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

Som, S; Longman, D. E.; Luo, Z

2012-01-01

Combustion in direct-injection diesel engines occurs in a lifted, turbulent diffusion flame mode. Numerous studies indicate that the combustion and emissions in such engines are strongly influenced by the lifted flame characteristics, which are in turn determined by fuel and air mixing in the upstream region of the lifted flame, and consequently by the liquid breakup and spray development processes. From a numerical standpoint, these spray combustion processes depend heavily on the choice of underlying spray, combustion, and turbulence models. The present numerical study investigates the influence of different chemical kinetic mechanisms for diesel and biodiesel fuels, as well asmore » Reynolds-averaged Navier-Stokes (RANS) and large eddy simulation (LES) turbulence models on predicting flame lift-off lengths (LOLs) and ignition delays. Specifically, two chemical kinetic mechanisms for n-heptane (NHPT) and three for biodiesel surrogates are investigated. In addition, the RNG k-{epsilon} (RANS) model is compared to the Smagorinsky based LES turbulence model. Using adaptive grid resolution, minimum grid sizes of 250 {micro}m and 125 {micro}m were obtained for the RANS and LES cases respectively. Validations of these models were performed against experimental data from Sandia National Laboratories in a constant volume combustion chamber. Ignition delay and flame lift-off validations were performed at different ambient temperature conditions. The LES model predicts lower ignition delays and qualitatively better flame structures compared to the RNG k-{epsilon} model. The use of realistic chemistry and a ternary surrogate mixture, which consists of methyl decanoate, methyl 9-decenoate, and NHPT, results in better predicted LOLs and ignition delays. For diesel fuel though, only marginal improvements are observed by using larger size mechanisms. However, these improved predictions come at a significant increase in computational cost.« less

Prediction of Outcome From Adult Bacterial Meningitis in a High-HIV-Seroprevalence, Resource-Poor Setting Using the Malawi Adult Meningitis Score (MAMS).

PubMed

Wall, Emma C; Mukaka, Mavuto; Scarborough, Matthew; Ajdukiewicz, Katherine M A; Cartwright, Katharine E; Nyirenda, Mulinda; Denis, Brigitte; Allain, Theresa J; Faragher, Brian; Lalloo, David G; Heyderman, Robert S

2017-02-15

Acute bacterial meningitis (ABM) in adults residing in resource-poor countries is associated with mortality rates >50%. To improve outcome, interventional trials and standardized clinical algorithms are urgently required. To optimize these processes, we developed and validated an outcome prediction tool to identify ABM patients at greatest risk of death. We derived a nomogram using mortality predictors derived from a logistic regression model of a discovery database of adult Malawian patients with ABM (n = 523 [65%] cerebrospinal fluid [CSF] culture positive). We validated the nomogram internally using a bootstrap procedure and subsequently used the nomogram scores to further interpret the effects of adjunctive dexamethasone and glycerol using clinical trial data from Malawi. ABM mortality at 6-week follow-up was 54%. Five of 15 variables tested were strongly associated with poor outcome (CSF culture positivity, CSF white blood cell count, hemoglobin, Glasgow Coma Scale, and pulse rate), and were used in the derivation of the Malawi Adult Meningitis Score (MAMS) nomogram. The C-index (area under the curve) was 0.76 (95% confidence interval, .71-.80) and calibration was good (Hosmer-Lemeshow C-statistic = 5.48, df = 8, P = .705). Harmful effects of adjunctive glycerol were observed in groups with relatively low predicted risk of poor outcome (25%-50% risk): Case Fatality Rate of 21% in the placebo group and 52% in the glycerol group (P < .001). This effect was not seen with adjunctive dexamethasone. MAMS provides a novel tool for predicting prognosis and improving interpretation of ABM clinical trials by risk stratification in resource-poor settings. Whether MAMS can be applied to non-HIV-endemic countries requires further evaluation. © The Author 2016. Published by Oxford University Press for the Infectious Diseases Society of America.

A Multi-institutional Comparison of Adrenal Venous Sampling in Patients with Primary Aldosteronism: Caution Advised if Successful Bilateral Adrenal Vein Sampling is Not Achieved.

PubMed

Wang, Tracy S; Kline, Greg; Yen, Tina W; Yin, Ziyan; Liu, Ying; Rilling, William; So, Benny; Findling, James W; Evans, Douglas B; Pasieka, Janice L

2018-02-01

In patients with primary aldosteronism (PA), adrenal venous sampling (AVS) is recommended to differentiate between unilateral (UNI) or bilateral (BIL) adrenal disease. A recent study suggested that lateralization could be predicted, based on the ratio of aldosterone/cortisol levels (A/C) between the left adrenal vein (LAV) and inferior vena cava (IVC), with a 100% positive predictive value (PPV). This study aimed to validate those findings utilizing a larger, multi-institutional cohort. A retrospective review was performed of patients with PA who underwent AVS from 2 tertiary-care institutions. Laterality was predicted by an A/C ratio of >3:1 between the dominant and non-dominant adrenal. AVS results were compared to LAV/IVC ratios utilizing the published criteria (Lt ≥ 5.5; Rt ≤ 0.5). Of 222 patients, 124 (57%) had UNI and 98 (43%) had BIL disease based on AVS. AVS and LAV/IVC findings were concordant for laterality in 141 (64%) patients (69 UNI, 72 BIL). Using only the LAV/IVC ratio, 54 (24%) patients with UNI disease on AVS who underwent successful surgery would have been assumed to have BAH unless AVS was repeated, and 24 (11%) patients with BIL disease on AVS may have been incorrectly offered surgery (PPV 70%). Based on median LAV/IVC ratios (left 5.26; right 0.31; BIL 2.84), no LAV/IVC ratio accurately predicted laterality. This multi-institutional study of patients with both UNI and BIL PA failed to validate the previously reported PPV of LAV/IVC ratio for lateralization. Caution should be used in interpreting incomplete AVS data to differentiate between UNI versus BIL disease and strong consideration given to repeat AVS prior to adrenalectomy.

Evaluation of Psychometric Properties of Voice Activity and Participation Profile (VAPP): A Spanish Version.

PubMed

Bermúdez-de-Alvear, Rosa M; Gálvez-Ruiz, Pablo; Martínez-Arquero, A Ginés; Rando-Márquez, Sara; Fernández-Contreras, Elena

2018-06-11

This study aimed to analyze the psychometric properties of the Spanish version of the Voice Activity and Participation Profile (SVAPP) questionnaire. A randomized, cross-sectional sampling strategy with controls was used. Two samples with a total of 169 participants were analyzed, specifically 61 men (mean age 37.02) and 108 women (mean age 37.78). Of these participants, 112 were patients and 57 were controls. The instrument was submitted to reliability (internal consistency and corrected item-total correlations) and reproducibility analyses. Validation assessment was based on the construct validity, convergent validity, discriminant validity, and concurrent validity. The global internal consistency was excellent (Cronbach's α = 0.976), corrected item-total correlations were satisfactory and ranged 0.63-0.89, and factor loadings were above 0.50. The different subscales showed good internal consistency (alpha coefficients ranged 0.830-0.956) and test-retest values were consistently associated. The exploratory factor analysis evidenced a strongly defined five factors internal structure, with factors loadings ranging 0.51-0.86. Convergent validity demonstrated that all subscales and scores were very strongly correlated (Pearson r above 0.735) and significantly associated. The discriminant validity analysis showed that SVAPP had good specificity to distinguish dysphonic from healthy voice subjects. Concurrent validity with Voice Handicap Index Spanish version (SVHI) showed very strong correlations between total scores, and between SVHI total score and SVAPP Daily and Social Communication subscales; correlations between both tests subscales were strong; only between SVAPP Work and SVHI Physical sections correlations were moderate. The findings of the present study demonstrated evidence for the SVAPP questionnaire reliability and validity, and provided insightful implications of voice disorders on Spanish patients' quality of life. However, further investigations are required. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

The diagnosis of urinary tract infections in young children (DUTY): protocol for a diagnostic and prospective observational study to derive and validate a clinical algorithm for the diagnosis of UTI in children presenting to primary care with an acute illness.

PubMed

Downing, Harriet; Thomas-Jones, Emma; Gal, Micaela; Waldron, Cherry-Ann; Sterne, Jonathan; Hollingworth, William; Hood, Kerenza; Delaney, Brendan; Little, Paul; Howe, Robin; Wootton, Mandy; Macgowan, Alastair; Butler, Christopher C; Hay, Alastair D

2012-07-19

Urinary tract infection (UTI) is common in children, and may cause serious illness and recurrent symptoms. However, obtaining a urine sample from young children in primary care is challenging and not feasible for large numbers. Evidence regarding the predictive value of symptoms, signs and urinalysis for UTI in young children is urgently needed to help primary care clinicians better identify children who should be investigated for UTI. This paper describes the protocol for the Diagnosis of Urinary Tract infection in Young children (DUTY) study. The overall study aim is to derive and validate a cost-effective clinical algorithm for the diagnosis of UTI in children presenting to primary care acutely unwell. DUTY is a multicentre, diagnostic and prospective observational study aiming to recruit at least 7,000 children aged before their fifth birthday, being assessed in primary care for any acute, non-traumatic, illness of ≤ 28 days duration. Urine samples will be obtained from eligible consented children, and data collected on medical history and presenting symptoms and signs. Urine samples will be dipstick tested in general practice and sent for microbiological analysis. All children with culture positive urines and a random sample of children with urine culture results in other, non-positive categories will be followed up to record symptom duration and healthcare resource use. A diagnostic algorithm will be constructed and validated and an economic evaluation conducted.The primary outcome will be a validated diagnostic algorithm using a reference standard of a pure/predominant growth of at least >103, but usually >105 CFU/mL of one, but no more than two uropathogens.We will use logistic regression to identify the clinical predictors (i.e. demographic, medical history, presenting signs and symptoms and urine dipstick analysis results) most strongly associated with a positive urine culture result. We will then use economic evaluation to compare the cost effectiveness of the candidate prediction rules. This study will provide novel, clinically important information on the diagnostic features of childhood UTI and the cost effectiveness of a validated prediction rule, to help primary care clinicians improve the efficiency of their diagnostic strategy for UTI in young children.

The diagnosis of urinary tract infections in young children (DUTY): protocol for a diagnostic and prospective observational study to derive and validate a clinical algorithm for the diagnosis of UTI in children presenting to primary care with an acute illness

PubMed Central

2012-01-01

Background Urinary tract infection (UTI) is common in children, and may cause serious illness and recurrent symptoms. However, obtaining a urine sample from young children in primary care is challenging and not feasible for large numbers. Evidence regarding the predictive value of symptoms, signs and urinalysis for UTI in young children is urgently needed to help primary care clinicians better identify children who should be investigated for UTI. This paper describes the protocol for the Diagnosis of Urinary Tract infection in Young children (DUTY) study. The overall study aim is to derive and validate a cost-effective clinical algorithm for the diagnosis of UTI in children presenting to primary care acutely unwell. Methods/design DUTY is a multicentre, diagnostic and prospective observational study aiming to recruit at least 7,000 children aged before their fifth birthday, being assessed in primary care for any acute, non-traumatic, illness of ≤ 28 days duration. Urine samples will be obtained from eligible consented children, and data collected on medical history and presenting symptoms and signs. Urine samples will be dipstick tested in general practice and sent for microbiological analysis. All children with culture positive urines and a random sample of children with urine culture results in other, non-positive categories will be followed up to record symptom duration and healthcare resource use. A diagnostic algorithm will be constructed and validated and an economic evaluation conducted. The primary outcome will be a validated diagnostic algorithm using a reference standard of a pure/predominant growth of at least >103, but usually >105 CFU/mL of one, but no more than two uropathogens. We will use logistic regression to identify the clinical predictors (i.e. demographic, medical history, presenting signs and symptoms and urine dipstick analysis results) most strongly associated with a positive urine culture result. We will then use economic evaluation to compare the cost effectiveness of the candidate prediction rules. Discussion This study will provide novel, clinically important information on the diagnostic features of childhood UTI and the cost effectiveness of a validated prediction rule, to help primary care clinicians improve the efficiency of their diagnostic strategy for UTI in young children. PMID:22812651

Prediction and validation of residual feed intake and dry matter intake in Danish lactating dairy cows using mid-infrared spectroscopy of milk.

PubMed

Shetty, N; Løvendahl, P; Lund, M S; Buitenhuis, A J

2017-01-01

The present study explored the effectiveness of Fourier transform mid-infrared (FT-IR) spectral profiles as a predictor for dry matter intake (DMI) and residual feed intake (RFI). The partial least squares regression method was used to develop the prediction models. The models were validated using different external test sets, one randomly leaving out 20% of the records (validation A), the second randomly leaving out 20% of cows (validation B), and a third (for DMI prediction models) randomly leaving out one cow (validation C). The data included 1,044 records from 140 cows; 97 were Danish Holstein and 43 Danish Jersey. Results showed better accuracies for validation A compared with other validation methods. Milk yield (MY) contributed largely to DMI prediction; MY explained 59% of the variation and the validated model error root mean square error of prediction (RMSEP) was 2.24kg. The model was improved by adding live weight (LW) as an additional predictor trait, where the accuracy R 2 increased from 0.59 to 0.72 and error RMSEP decreased from 2.24 to 1.83kg. When only the milk FT-IR spectral profile was used in DMI prediction, a lower prediction ability was obtained, with R 2 =0.30 and RMSEP=2.91kg. However, once the spectral information was added, along with MY and LW as predictors, model accuracy improved and R 2 increased to 0.81 and RMSEP decreased to 1.49kg. Prediction accuracies of RFI changed throughout lactation. The RFI prediction model for the early-lactation stage was better compared with across lactation or mid- and late-lactation stages, with R 2 =0.46 and RMSEP=1.70. The most important spectral wavenumbers that contributed to DMI and RFI prediction models included fat, protein, and lactose peaks. Comparable prediction results were obtained when using infrared-predicted fat, protein, and lactose instead of full spectra, indicating that FT-IR spectral data do not add significant new information to improve DMI and RFI prediction models. Therefore, in practice, if full FT-IR spectral data are not stored, it is possible to achieve similar DMI or RFI prediction results based on standard milk control data. For DMI, the milk fat region was responsible for the major variation in milk spectra; for RFI, the major variation in milk spectra was within the milk protein region. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

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

PubMed

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

2013-01-01

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

Dynamic Assessment of Reading Difficulties: Predictive and Incremental Validity on Attitude toward Reading and the Use of Dialogue/Participation Strategies in Classroom Activities.

PubMed

Navarro, Juan-José; Lara, Laura

2017-01-01

Dynamic Assessment (DA) has been shown to have more predictive value than conventional tests for academic performance. However, in relation to reading difficulties, further research is needed to determine the predictive validity of DA for specific aspects of the different processes involved in reading and the differential validity of DA for different subgroups of students with an academic disadvantage. This paper analyzes the implementation of a DA device that evaluates processes involved in reading (EDPL) among 60 students with reading comprehension difficulties between 9 and 16 years of age, of whom 20 have intellectual disabilities, 24 have reading-related learning disabilities, and 16 have socio-cultural disadvantages. We specifically analyze the predictive validity of the EDPL device over attitude toward reading, and the use of dialogue/participation strategies in reading activities in the classroom during the implementation stage. We also analyze if the EDPL device provides additional information to that obtained with a conventionally applied personal-social adjustment scale (APSL). Results showed that dynamic scores, obtained from the implementation of the EDPL device, significantly predict the studied variables. Moreover, dynamic scores showed a significant incremental validity in relation to predictions based on an APSL scale. In relation to differential validity, the results indicated the superior predictive validity for DA for students with intellectual disabilities and reading disabilities than for students with socio-cultural disadvantages. Furthermore, the role of metacognition and its relation to the processes of personal-social adjustment in explaining the results is discussed.

Dynamic Assessment of Reading Difficulties: Predictive and Incremental Validity on Attitude toward Reading and the Use of Dialogue/Participation Strategies in Classroom Activities

PubMed Central

Navarro, Juan-José; Lara, Laura

2017-01-01

Dynamic Assessment (DA) has been shown to have more predictive value than conventional tests for academic performance. However, in relation to reading difficulties, further research is needed to determine the predictive validity of DA for specific aspects of the different processes involved in reading and the differential validity of DA for different subgroups of students with an academic disadvantage. This paper analyzes the implementation of a DA device that evaluates processes involved in reading (EDPL) among 60 students with reading comprehension difficulties between 9 and 16 years of age, of whom 20 have intellectual disabilities, 24 have reading-related learning disabilities, and 16 have socio-cultural disadvantages. We specifically analyze the predictive validity of the EDPL device over attitude toward reading, and the use of dialogue/participation strategies in reading activities in the classroom during the implementation stage. We also analyze if the EDPL device provides additional information to that obtained with a conventionally applied personal-social adjustment scale (APSL). Results showed that dynamic scores, obtained from the implementation of the EDPL device, significantly predict the studied variables. Moreover, dynamic scores showed a significant incremental validity in relation to predictions based on an APSL scale. In relation to differential validity, the results indicated the superior predictive validity for DA for students with intellectual disabilities and reading disabilities than for students with socio-cultural disadvantages. Furthermore, the role of metacognition and its relation to the processes of personal-social adjustment in explaining the results is discussed. PMID:28243215

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.

Tuning Glass Transition in Polymer Nanocomposites with Functionalized Cellulose Nanocrystals through Nanoconfinement.

PubMed

Qin, Xin; Xia, Wenjie; Sinko, Robert; Keten, Sinan

2015-10-14

Cellulose nanocrystals (CNCs) exhibit impressive interfacial and mechanical properties that make them promising candidates to be used as fillers within nanocomposites. While glass-transition temperature (Tg) is a common metric for describing thermomechanical properties, its prediction is extremely difficult as it depends on filler surface chemistry, volume fraction, and size. Here, taking CNC-reinforced poly(methyl-methacrylate) (PMMA) nanocomposites as a relevant model system, we present a multiscale analysis that combines atomistic molecular dynamics (MD) surface energy calculations with coarse-grained (CG) simulations of relaxation dynamics near filler-polymer interfaces to predict composite properties. We discover that increasing the volume fraction of CNCs results in nanoconfinement effects that lead to an appreciation of the composite Tg provided that strong interfacial interactions are achieved, as in the case of TEMPO-mediated surface modifications that promote hydrogen bonding. The upper and lower bounds of shifts in Tg are predicted by fully accounting for nanoconfinement and interfacial properties, providing new insight into tuning these aspects in nanocomposite design. Our multiscale, materials-by-design framework is validated by recent experiments and breaks new ground in predicting, without any empirical parameters, key structure-property relationships for nanocomposites.

Observational evidence of European summer weather patterns predictable from spring

NASA Astrophysics Data System (ADS)

Ossó, Albert; Sutton, Rowan; Shaffrey, Len; Dong, Buwen

2018-01-01

Forecasts of summer weather patterns months in advance would be of great value for a wide range of applications. However, seasonal dynamical model forecasts for European summers have very little skill, particularly for rainfall. It has not been clear whether this low skill reflects inherent unpredictability of summer weather or, alternatively, is a consequence of weaknesses in current forecast systems. Here we analyze atmosphere and ocean observations and identify evidence that a specific pattern of summertime atmospheric circulation––the summer East Atlantic (SEA) pattern––is predictable from the previous spring. An index of North Atlantic sea-surface temperatures in March–April can predict the SEA pattern in July–August with a cross-validated correlation skill above 0.6. Our analyses show that the sea-surface temperatures influence atmospheric circulation and the position of the jet stream over the North Atlantic. The SEA pattern has a particularly strong influence on rainfall in the British Isles, which we find can also be predicted months ahead with a significant skill of 0.56. Our results have immediate application to empirical forecasts of summer rainfall for the United Kingdom, Ireland, and northern France and also suggest that current dynamical model forecast systems have large potential for improvement.

Geographic and temporal validity of prediction models: Different approaches were useful to examine model performance

PubMed Central

Austin, Peter C.; van Klaveren, David; Vergouwe, Yvonne; Nieboer, Daan; Lee, Douglas S.; Steyerberg, Ewout W.

2017-01-01

Objective Validation of clinical prediction models traditionally refers to the assessment of model performance in new patients. We studied different approaches to geographic and temporal validation in the setting of multicenter data from two time periods. Study Design and Setting We illustrated different analytic methods for validation using a sample of 14,857 patients hospitalized with heart failure at 90 hospitals in two distinct time periods. Bootstrap resampling was used to assess internal validity. Meta-analytic methods were used to assess geographic transportability. Each hospital was used once as a validation sample, with the remaining hospitals used for model derivation. Hospital-specific estimates of discrimination (c-statistic) and calibration (calibration intercepts and slopes) were pooled using random effects meta-analysis methods. I2 statistics and prediction interval width quantified geographic transportability. Temporal transportability was assessed using patients from the earlier period for model derivation and patients from the later period for model validation. Results Estimates of reproducibility, pooled hospital-specific performance, and temporal transportability were on average very similar, with c-statistics of 0.75. Between-hospital variation was moderate according to I2 statistics and prediction intervals for c-statistics. Conclusion This study illustrates how performance of prediction models can be assessed in settings with multicenter data at different time periods. PMID:27262237

Parent- and Self-Reported Dimensions of Oppositionality in Youth: Construct Validity, Concurrent Validity, and the Prediction of Criminal Outcomes in Adulthood

ERIC Educational Resources Information Center

Aebi, Marcel; Plattner, Belinda; Metzke, Christa Winkler; Bessler, Cornelia; Steinhausen, Hans-Christoph

2013-01-01

Background: Different dimensions of oppositional defiant disorder (ODD) have been found as valid predictors of further mental health problems and antisocial behaviors in youth. The present study aimed at testing the construct, concurrent, and predictive validity of ODD dimensions derived from parent- and self-report measures. Method: Confirmatory…

External validity of two nomograms for predicting distant brain failure after radiosurgery for brain metastases in a bi-institutional independent patient cohort.

PubMed

Prabhu, Roshan S; Press, Robert H; Boselli, Danielle M; Miller, Katherine R; Lankford, Scott P; McCammon, Robert J; Moeller, Benjamin J; Heinzerling, John H; Fasola, Carolina E; Patel, Kirtesh R; Asher, Anthony L; Sumrall, Ashley L; Curran, Walter J; Shu, Hui-Kuo G; Burri, Stuart H

2018-03-01

Patients treated with stereotactic radiosurgery (SRS) for brain metastases (BM) are at increased risk of distant brain failure (DBF). Two nomograms have been recently published to predict individualized risk of DBF after SRS. The goal of this study was to assess the external validity of these nomograms in an independent patient cohort. The records of consecutive patients with BM treated with SRS at Levine Cancer Institute and Emory University between 2005 and 2013 were reviewed. Three validation cohorts were generated based on the specific nomogram or recursive partitioning analysis (RPA) entry criteria: Wake Forest nomogram (n = 281), Canadian nomogram (n = 282), and Canadian RPA (n = 303) validation cohorts. Freedom from DBF at 1-year in the Wake Forest study was 30% compared with 50% in the validation cohort. The validation c-index for both the 6-month and 9-month freedom from DBF Wake Forest nomograms was 0.55, indicating poor discrimination ability, and the goodness-of-fit test for both nomograms was highly significant (p < 0.001), indicating poor calibration. The 1-year actuarial DBF in the Canadian nomogram study was 43.9% compared with 50.9% in the validation cohort. The validation c-index for the Canadian 1-year DBF nomogram was 0.56, and the goodness-of-fit test was also highly significant (p < 0.001). The validation accuracy and c-index of the Canadian RPA classification was 53% and 0.61, respectively. The Wake Forest and Canadian nomograms for predicting risk of DBF after SRS were found to have limited predictive ability in an independent bi-institutional validation cohort. These results reinforce the importance of validating predictive models in independent patient cohorts.

Validity and reliability of sleep time questionnaires in children and adolescents: A systematic review and meta-analysis.

PubMed

Nascimento-Ferreira, Marcus V; Collese, Tatiana S; de Moraes, Augusto César F; Rendo-Urteaga, Tara; Moreno, Luis A; Carvalho, Heráclito B

2016-12-01

Sleep duration has been associated with several health outcomes in children and adolescents. As an extensive number of questionnaires are currently used to investigate sleep schedule or sleep time, we performed a systematic review of criterion validation of sleep time questionnaires for children and adolescents, considering accelerometers as the reference method. We found a strong correlation between questionnaires and accelerometers for weeknights and a moderate correlation for weekend nights. When considering only studies performing a reliability assessment of the used questionnaires, a significant increase in the correlations for both weeknights and weekend nights was observed. In conclusion, moderate to strong criterion validity of sleep time questionnaires was observed; however, the reliability assessment of the questionnaires showed strong validation performance. Copyright © 2015 Elsevier Ltd. All rights reserved.

French version of the Family Attitude Scale: psychometric properties and relation of attitudes to the respondent's psychiatric status.

PubMed

Vandeleur, Caroline L; Kavanagh, David J; Favez, Nicolas; Castelao, Enrique; Preisig, Martin

2013-12-15

The Family Attitude Scale (FAS) is a self-report measure of critical or hostile attitudes and behaviors towards another family member, and demonstrates an ability to predict relapse in psychoses. Data are not currently available on a French version of the scale. The present study developed a French version of the FAS, using a large general population sample to test its internal structure, criterion validity and relationships with the respondents' symptoms and psychiatric diagnoses, and examined the reciprocity of FAS ratings by respondents and their partners. A total of 2072 adults from an urban population undertook a diagnostic interview and completed self-report measures, including an FAS about their partner. A subset of participants had partners who also completed the FAS. Confirmatory factor analyses revealed an excellent fit by a single-factor model, and the FAS demonstrated a strong association with dyadic adjustment. FAS scores of respondents were affected by their anxiety levels and mood, alcohol and anxiety diagnoses, and moderate reciprocity of attitudes and behaviors between the partners was seen. The French version of the FAS has similarly strong psychometric properties to the original English version. Future research should assess the ability of the French FAS to predict relapse of psychiatric disorders. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Do Implicit Attitudes Predict Actual Voting Behavior Particularly for Undecided Voters?

PubMed Central

Friese, Malte; Smith, Colin Tucker; Plischke, Thomas; Bluemke, Matthias; Nosek, Brian A.

2012-01-01

The prediction of voting behavior of undecided voters poses a challenge to psychologists and pollsters. Recently, researchers argued that implicit attitudes would predict voting behavior particularly for undecided voters whereas explicit attitudes would predict voting behavior particularly for decided voters. We tested this assumption in two studies in two countries with distinct political systems in the context of real political elections. Results revealed that (a) explicit attitudes predicted voting behavior better than implicit attitudes for both decided and undecided voters, and (b) implicit attitudes predicted voting behavior better for decided than undecided voters. We propose that greater elaboration of attitudes produces stronger convergence between implicit and explicit attitudes resulting in better predictive validity of both, and less incremental validity of implicit over explicit attitudes for the prediction of voting behavior. However, greater incremental predictive validity of implicit over explicit attitudes may be associated with less elaboration. PMID:22952898

RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction.

PubMed

Chen, Xing; Wu, Qiao-Feng; Yan, Gui-Ying

2017-07-03

Cumulative verified experimental studies have demonstrated that microRNAs (miRNAs) could be closely related with the development and progression of human complex diseases. Based on the assumption that functional similar miRNAs may have a strong correlation with phenotypically similar diseases and vice versa, researchers developed various effective computational models which combine heterogeneous biologic data sets including disease similarity network, miRNA similarity network, and known disease-miRNA association network to identify potential relationships between miRNAs and diseases in biomedical research. Considering the limitations in previous computational study, we introduced a novel computational method of Ranking-based KNN for miRNA-Disease Association prediction (RKNNMDA) to predict potential related miRNAs for diseases, and our method obtained an AUC of 0.8221 based on leave-one-out cross validation. In addition, RKNNMDA was applied to 3 kinds of important human cancers for further performance evaluation. The results showed that 96%, 80% and 94% of predicted top 50 potential related miRNAs for Colon Neoplasms, Esophageal Neoplasms, and Prostate Neoplasms have been confirmed by experimental literatures, respectively. Moreover, RKNNMDA could be used to predict potential miRNAs for diseases without any known miRNAs, and it is anticipated that RKNNMDA would be of great use for novel miRNA-disease association identification.

RKNNMDA: Ranking-based KNN for MiRNA-Disease Association prediction

PubMed Central

Chen, Xing; Yan, Gui-Ying

2017-01-01

ABSTRACT Cumulative verified experimental studies have demonstrated that microRNAs (miRNAs) could be closely related with the development and progression of human complex diseases. Based on the assumption that functional similar miRNAs may have a strong correlation with phenotypically similar diseases and vice versa, researchers developed various effective computational models which combine heterogeneous biologic data sets including disease similarity network, miRNA similarity network, and known disease-miRNA association network to identify potential relationships between miRNAs and diseases in biomedical research. Considering the limitations in previous computational study, we introduced a novel computational method of Ranking-based KNN for miRNA-Disease Association prediction (RKNNMDA) to predict potential related miRNAs for diseases, and our method obtained an AUC of 0.8221 based on leave-one-out cross validation. In addition, RKNNMDA was applied to 3 kinds of important human cancers for further performance evaluation. The results showed that 96%, 80% and 94% of predicted top 50 potential related miRNAs for Colon Neoplasms, Esophageal Neoplasms, and Prostate Neoplasms have been confirmed by experimental literatures, respectively. Moreover, RKNNMDA could be used to predict potential miRNAs for diseases without any known miRNAs, and it is anticipated that RKNNMDA would be of great use for novel miRNA-disease association identification. PMID:28421868

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning

NASA Astrophysics Data System (ADS)

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-01

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

Predicting Protein–protein Association Rates using Coarse-grained Simulation and Machine Learning

PubMed Central

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-01-01

Protein–protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate. PMID:28418043

Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

PubMed

Xie, Zhong-Ru; Chen, Jiawen; Wu, Yinghao

2017-04-18

Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large benchmark set of 49 protein complexes. The predicted rate was overestimated in the benchmark test compared to the experimental results for a group of protein complexes. We hypothesized that this resulted from molecular flexibility at the interface regions of the interacting proteins. After applying a machine learning algorithm with input variables that accounted for both the conformational flexibility and the energetic factor of binding, we successfully identified most of the protein complexes with overestimated association rates and improved our final prediction by using a cross-validation test. This method was then applied to a new independent test set and resulted in a similar prediction accuracy to that obtained using the training set. It has been thought that diffusion-limited protein association is dominated by long-range interactions. Our results provide strong evidence that the conformational flexibility also plays an important role in regulating protein association. Our studies provide new insights into the mechanism of protein association and offer a computationally efficient tool for predicting its rate.

A validity and reliability study of the coping self-efficacy scale

PubMed Central

Chesney, Margaret A.; Neilands, Torsten B.; Chambers, Donald B.; Taylor, Jonelle M.; Folkman, Susan

2006-01-01

Objectives Investigate the psychometric characteristics of the coping self-efficacy (CSE) scale, a 26-item measure of one’s confidence in performing coping behaviors when faced with life challenges. Design Data came from two randomized clinical trials (N1 = 149, N2 = 199) evaluating a theory-based Coping Effectiveness Training (CET) intervention in reducing psychological distress and increasing positive mood in persons coping with chronic illness. Methods The 348 participants were HIV-seropositive men with depressed mood who have sex with men. Participants were randomly assigned to intervention and comparison conditions and assessed pre- and post-intervention. Outcome variables included the CSE scale, ways of coping, and measures of social support and psychological distress and well-being. Results Exploratory (EFA) and confirmatory factor analyses (CFA) revealed a 13-item reduced form of the CSE scale with three factors: Use problem-focused coping (6 items, α = .91), stop unpleasant emotions and thoughts (4 items, α = .91), and get support from friends and family (3 items, α = .80). Internal consistency and test–retest reliability are strong for all three factors. Concurrent validity analyses showed these factors assess self-efficacy for different types of coping. Predictive validity analyses showed that residualized change scores in using problem- and emotion-focused coping skills were predictive of reduced psychological distress and increased psychological well-being over time. Conclusions The CSE scale provides a measure of a person’s perceived ability to cope effectively with life challenges, as well as a way to assess changes in CSE over time in intervention research. PMID:16870053

Genome-based prediction of test cross performance in two subsequent breeding cycles.

PubMed

Hofheinz, Nina; Borchardt, Dietrich; Weissleder, Knuth; Frisch, Matthias

2012-12-01

Genome-based prediction of genetic values is expected to overcome shortcomings that limit the application of QTL mapping and marker-assisted selection in plant breeding. Our goal was to study the genome-based prediction of test cross performance with genetic effects that were estimated using genotypes from the preceding breeding cycle. In particular, our objectives were to employ a ridge regression approach that approximates best linear unbiased prediction of genetic effects, compare cross validation with validation using genetic material of the subsequent breeding cycle, and investigate the prospects of genome-based prediction in sugar beet breeding. We focused on the traits sugar content and standard molasses loss (ML) and used a set of 310 sugar beet lines to estimate genetic effects at 384 SNP markers. In cross validation, correlations >0.8 between observed and predicted test cross performance were observed for both traits. However, in validation with 56 lines from the next breeding cycle, a correlation of 0.8 could only be observed for sugar content, for standard ML the correlation reduced to 0.4. We found that ridge regression based on preliminary estimates of the heritability provided a very good approximation of best linear unbiased prediction and was not accompanied with a loss in prediction accuracy. We conclude that prediction accuracy assessed with cross validation within one cycle of a breeding program can not be used as an indicator for the accuracy of predicting lines of the next cycle. Prediction of lines of the next cycle seems promising for traits with high heritabilities.

Development of estrogen receptor beta binding prediction model using large sets of chemicals.

PubMed

Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

2017-11-03

We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

Predictive validity of the Braden Scale, Norton Scale, and Waterlow Scale in the Czech Republic.

PubMed

Šateková, Lenka; Žiaková, Katarína; Zeleníková, Renáta

2017-02-01

The aim of this study was to determine the predictive validity of the Braden, Norton, and Waterlow scales in 2 long-term care departments in the Czech Republic. Assessing the risk for developing pressure ulcers is the first step in their prevention. At present, many scales are used in clinical practice, but most of them have not been properly validated yet (for example, the Modified Norton Scale in the Czech Republic). In the Czech Republic, only the Braden Scale has been validated so far. This is a prospective comparative instrument testing study. A random sample of 123 patients was recruited. The predictive validity of the pressure ulcer risk assessment scales was evaluated based on sensitivity, specificity, positive and negative predictive values, and the area under the receiver operating characteristic curve. The data were collected from April to August 2014. In the present study, the best predictive validity values were observed for the Norton Scale, followed by the Braden Scale and the Waterlow Scale, in that order. We recommended that the above 3 pressure ulcer risk assessment scales continue to be evaluated in the Czech clinical setting. © 2016 John Wiley & Sons Australia, Ltd.

Systems analysis identifies miR-29b regulation of invasiveness in melanoma.

PubMed

Andrews, Miles C; Cursons, Joseph; Hurley, Daniel G; Anaka, Matthew; Cebon, Jonathan S; Behren, Andreas; Crampin, Edmund J

2016-11-16

In many cancers, microRNAs (miRs) contribute to metastatic progression by modulating phenotypic reprogramming processes such as epithelial-mesenchymal plasticity. This can be driven by miRs targeting multiple mRNA transcripts, inducing regulated changes across large sets of genes. The miR-target databases TargetScan and DIANA-microT predict putative relationships by examining sequence complementarity between miRs and mRNAs. However, it remains a challenge to identify which miR-mRNA interactions are active at endogenous expression levels, and of biological consequence. We developed a workflow to integrate TargetScan and DIANA-microT predictions into the analysis of data-driven associations calculated from transcript abundance (RNASeq) data, specifically the mutual information and Pearson's correlation metrics. We use this workflow to identify putative relationships of miR-mediated mRNA repression with strong support from both lines of evidence. Applying this approach systematically to a large, published collection of unique melanoma cell lines - the Ludwig Melbourne melanoma (LM-MEL) cell line panel - we identified putative miR-mRNA interactions that may contribute to invasiveness. This guided the selection of interactions of interest for further in vitro validation studies. Several miR-mRNA regulatory relationships supported by TargetScan and DIANA-microT demonstrated differential activity across cell lines of varying matrigel invasiveness. Strong negative statistical associations for these putative regulatory relationships were consistent with target mRNA inhibition by the miR, and suggest that differential activity of such miR-mRNA relationships contribute to differences in melanoma invasiveness. Many of these relationships were reflected across the skin cutaneous melanoma TCGA dataset, indicating that these observations also show graded activity across clinical samples. Several of these miRs are implicated in cancer progression (miR-211, -340, -125b, -221, and -29b). The specific role for miR-29b-3p in melanoma has not been well studied. We experimentally validated the predicted miR-29b-3p regulation of LAMC1 and PPIC and LASP1, and show that dysregulation of miR-29b-3p or these mRNA targets can influence cellular invasiveness in vitro. This analytic strategy provides a comprehensive, systems-level approach to identify miR-mRNA regulation in high-throughput cancer data, identifies novel putative interactions with functional phenotypic relevance, and can be used to direct experimental resources for subsequent experimental validation. Computational scripts are available: http://github.com/uomsystemsbiology/LMMEL-miR-miner.

Validity of Integrity Tests for Predicting Drug and Alcohol Abuse

DTIC Science & Technology

1993-08-31

Wiinkler and Sheridan (1989) found that employees who entered employee assistance programs for treating drug addiction were more likely be absent...August 31, 1993 Final 4. TITLE AND SUBTITLE S. FUNDING NUMBERS Validity of Integrity Tests for Predicting Drug and Alcohol Abuse C No. N00014-92-J...words) This research used psychometric meta-analysis (Hunter & Schmidt, 1990b) to examine the validity of integrity tests for predicting drug and

Validated Questionnaire of Maternal Attitude and Knowledge for Predicting Caries Risk in Children: Epidemiological Study in North Jakarta, Indonesia.

PubMed

Laksmiastuti, Sri Ratna; Budiardjo, Sarworini Bagio; Sutadi, Heriandi

2017-06-01

Predicting caries risk in children can be done by identifying caries risk factors. It is an important measure which contributes to best understanding of the cariogenic profile of the patient. Identification could be done by clinical examination and answering the questionnaire. We arrange the study to verify the questionnaire validation for predicting caries risk in children. The study was conducted on 62 pairs of mothers and their children, aged between 3 and 5 years. The questionnaire consists of 10 questions concerning mothers' attitude and knowledge about oral health. The reliability and validity test is based on Cronbach's alpha and correlation coefficient value. All question are reliable (Cronbach's alpha = 0.873) and valid (Corrected item-total item correlation >0.4). Five questionnaires of mother's attitude about oral health and five questionnaires of mother's knowledge about oral health are reliable and valid for predicting caries risk in children.

Predicting Individual Differences in Placebo Analgesia: Contributions of Brain Activity during Anticipation and Pain Experience

PubMed Central

Wager, Tor D.; Atlas, Lauren Y.; Leotti, Lauren A.; Rilling, James K.

2012-01-01

Recent studies have identified brain correlates of placebo analgesia, but none have assessed how accurately patterns of brain activity can predict individual differences in placebo responses. We reanalyzed data from two fMRI studies of placebo analgesia (N = 47), using patterns of fMRI activity during the anticipation and experience of pain to predict new subjects’ scores on placebo analgesia and placebo-induced changes in pain processing. We used a cross-validated regression procedure, LASSO-PCR, which provided both unbiased estimates of predictive accuracy and interpretable maps of which regions are most important for prediction. Increased anticipatory activity in a frontoparietal network and decreases in a posterior insular/temporal network predicted placebo analgesia. Patterns of anticipatory activity across the cortex predicted a moderate amount of variance in the placebo response (~12% overall, ~40% for study 2 alone), which is substantial considering the multiple likely contributing factors. The most predictive regions were those associated with emotional appraisal, rather than cognitive control or pain processing. During pain, decreases in limbic and paralimbic regions most strongly predicted placebo analgesia. Responses within canonical pain-processing regions explained significant variance in placebo analgesia, but the pattern of effects was inconsistent with widespread decreases in nociceptive processing. Together, the findings suggest that engagement of emotional appraisal circuits drives individual variation in placebo analgesia, rather than early suppression of nociceptive processing. This approach provides a framework that will allow prediction accuracy to increase as new studies provide more precise information for future predictive models. PMID:21228154

A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities

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

Valencia, Antoni; Prous, Josep; Mora, Oscar

As indicated in ICH M7 draft guidance, in silico predictive tools including statistically-based QSARs and expert analysis may be used as a computational assessment for bacterial mutagenicity for the qualification of impurities in pharmaceuticals. To address this need, we developed and validated a QSAR model to predict Salmonella t. mutagenicity (Ames assay outcome) of pharmaceutical impurities using Prous Institute's Symmetry℠, a new in silico solution for drug discovery and toxicity screening, and the Mold2 molecular descriptor package (FDA/NCTR). Data was sourced from public benchmark databases with known Ames assay mutagenicity outcomes for 7300 chemicals (57% mutagens). Of these data, 90%more » was used to train the model and the remaining 10% was set aside as a holdout set for validation. The model's applicability to drug impurities was tested using a FDA/CDER database of 951 structures, of which 94% were found within the model's applicability domain. The predictive performance of the model is acceptable for supporting regulatory decision-making with 84 ± 1% sensitivity, 81 ± 1% specificity, 83 ± 1% concordance and 79 ± 1% negative predictivity based on internal cross-validation, while the holdout dataset yielded 83% sensitivity, 77% specificity, 80% concordance and 78% negative predictivity. Given the importance of having confidence in negative predictions, an additional external validation of the model was also carried out, using marketed drugs known to be Ames-negative, and obtained 98% coverage and 81% specificity. Additionally, Ames mutagenicity data from FDA/CFSAN was used to create another data set of 1535 chemicals for external validation of the model, yielding 98% coverage, 73% sensitivity, 86% specificity, 81% concordance and 84% negative predictivity. - Highlights: • A new in silico QSAR model to predict Ames mutagenicity is described. • The model is extensively validated with chemicals from the FDA and the public domain. • Validation tests show desirable high sensitivity and high negative predictivity. • The model predicted 14 reportedly difficult to predict drug impurities with accuracy. • The model is suitable to support risk evaluation of potentially mutagenic compounds.« less